Handbook for J1+ Preparation

Contents
1. Flowcharts
2. Graphs
3. Pareto Diagram
4. Check-sheet
5. Histogram
6. Cause and Effect Diagram
7. Stratification
8. Scatter Diagram
9. Control Charts
10. Brainstorming
11. Arrow Diagram
12. Affinity Diagram
13. Tree Diagram
14. Relations Diagram
15. Matrix Diagram
16. Matrix Data Analysis
17. Process Decision Program Chart (PDPC)
18. Basic Statistics
19. Improvement Fundamentals
 Flowcharts
Introduction
Flow Diagram is a graphical or pictorial way to depict process.
With help of a flow diagram we can show process sequence.
Flowcharts were introduced by Frank Gilbrethand Lillian Gilbrethin 1921, and they were
called Flow Process Charts at the beginning.
In 1947, ASME (American Society of Mechanical Engineers) adopted a symbol set derived
from Gilbreths original work as the ASME Standard: Operation and Flow Process Charts.
Douglas Hartree in 1949 explained that Herman Goldstine and John von Neumann had
developed a flowchart (originally, diagram) to plan computer programs.

About the Inventor

Frank Bunker Gilbreth Sr. (July 7, 1868 June 14, 1924) was an American engineer,
consultant and author, known as early advocate of scientific management and a pioneer
of time and motion study, and is perhaps best known as the father and central figure
of Cheaper by the Dozen.
Both he and his wife Lillian Moller Gilbreth were industrial engineers and efficiency experts
who contributed to the study of industrial engineering in fields such as motion study and
human factors.

Purpose and Applicability

For defining the process flow
For defining the problem
For identifying the root causes
For devising the solution
For implementing the solution
For Data Management
For planning a new project
For managing workflow
At the time of review / follow up
 Symbols used in Flow Diagrams

Symbol Name Description

The terminator or rounded rectangle symbol
marks the starting or ending point of the
Start/End Symbol system. It usually contains the word "Start" or
"End."

Action or Process A box can represent a single step ("add two

cups of flour"), and entire sub-process
Symbol ("make bread") within a larger process.

Document Symbol A printed document or report.

Multiple
Represents multiple documents in the
Documents process.
Symbol

A decision or branching point. Lines

representing different decisions emerge from
Decision Symbol different points of the diamond.

Input/Output Represents material or information entering

or leaving the system, such as customer
Symbol order (input) or a product (output).

Manual Input Represents a step where a user is prompted

Symbol to enter information manually.

Preparation Represents a set-up to another step in the

Symbol process.

Connector Indicates that the flow continues where a

Symbol matching symbol (containing the same letter)
has been placed.
 Or Symbol Indicates that the process flow continues in
more than two branches.

Summoning Indicates a point in the flowchart where

Junction Symbol multiple branches converge back into a
single process.

Merge Symbol Indicates a step where two or more sub-lists

or sub-processes become one.

Collate Symbol Indicates a step that orders information into a

standard format.

Indicates a step that organizes a list of items

Sort Symbol into a sequence or sets based on some pre-
determined criteria.

Indicates a sequence of actions that perform

Subroutine a specific task embedded within a larger
Symbol process. This sequence of actions could be
described in more detail on a separate
flowchart.

Manual Loop Indicates a sequence of commands that will

Symbol continue to repeat until stopped manually.

Loop Limit Indicates the point at which a loop should

Symbol stop.

Delay Symbol Indicates a delay in the process.

Data Storage or
Stored Data Indicates a step where data gets stored.
Symbol
 Indicates a list of information with a standard
Database Symbol structure that allows for searching and
sorting.

Internal Storage Indicates that information was stored in

Symbol memory during a program, used in software
design flowcharts.

Display Symbol Indicates a step that displays information.

Off Page Indicates that the process continues off

page.

Steps of drawing a Flowchart

Discuss the purpose of it
Decide the boundaries
Put each process in writing from the beginning
When you come to a decision area follow one till completion
Ensure every branch is completed

Example from the plant

 Graphs
Introduction
Graph is a pictorial representation of data which is easily understandable and helps
represent large amount of information comprehensively and in a compact manner for better
interpretation.
William Playfair, a Scottish engineer, economist is considered to be the founder of graphs;
started use of line graph, bar chart in 1786 for economic data, and the pie chart in 1801 to
show part-whole relations.
Florence Nightingale (1820-1910), an English social reformer and statistician, popularized
charting techniques by using them to improve quality of medical care. She used graphs to
record and present temperatures trends of patients.

About the Inventor

William Playfair (22 September 1759 11 February 1823) was a Scottish engineer andpolitical
economist, the founder of graphical methods of statistics.Playfair, who argued that charts
communicated better than tables of data, has been credited with inventing the line, bar, area,
and pie charts. His time-series plots are still presented as models of clarity.Playfair first
published The Commercial and Political Atlas in London in 1786. It contained 43 time-series
plots and one bar chart, a form apparently introduced in this work. It has been described as the
first major work to contain statistical graphs. Playfair's Statistical Breviary, published in London
in 1801, contains what is generally credited as the first pie chart.

Purpose and applicability of the tool

Graphs of various types are used for pictorial representation of data. Pictorial representation
enables the user or viewer to quickly grasp the meaning of the data.
Converting raw data into insights by providing trends, solutions.
Analysis of unorganized data.
Generally used for:
Explanation and understanding
Recording data
Process control
Elementary data analysis

Types of Graphs
Commonly used graphs:
1.Line graph
2.Bar Chart/Graph
3.Pie Chart or Circle Graph
Special Purpose Graphs:
1.Belt Graph
2.Radar Graph
3.Compound Graph
4.Strata Graph
5.Float Graph
6.Zee Graph
7.Pyramid graph

Type Name Used For(Examples)

Display and compare the number, frequency or other

Bar chart
measure for different discrete categories of data

Usually for tracking something over time, time series

Line chart
data

Area chart Comparisons, relative contribution over time

Relative contribution of different categories to an overall

Pie chart
total

Displaying multivariate data on different axes starting

Radar chart
from the same point

Scatter plot
Show the relationship between two or more sets of data
 Commonly Used Graphs
1. Line Graphs
What is a Line Graph?
It is a type of graph that displays information as a series of data points called markers
connected by straight line segments. A basic graph common in many fields.
It is used for observing quantity changes over time or trends. Line graphs are used
when one variable (independent) affects another, which is the dependent variable.

Where to use Line graph?

To display comparison between two or more different series
When data defines more meaningful patterns.

Standard Instructions:
Only standard colours- BLACK and BLUE to be used in case two graphs need to be
shown.
X and Y axes should be defined by units.
If X-axis is timeline then always use line graph.
Title must be at bottom of the graph.
Indicate the direction of good performance on the performance indicator, placed at
extreme top right side of the graph.
Use RED colour to show benchmark.

Steps of Construction
Steps to Running a Line Graph in Excel:
1. Collect the data for X and Y variables. X is an independent variable and Y dependent
variable of X
2. Insert the data into two adjacent columns/rows of the Excel Sheet
3. Select the X and Y complete data
4. Now select the Insert tab button and in that select the Chart option
5. From the Chart option select the Line Graph

Steps to Running a Line Graph in Minitab:

Timeplots usually show a large amount of variation. In order to see underlying trends,
sometimes a technique called smoothing is used to create a line graph.
1. Open Minitab andtype or copy your data into the Minitab worksheet.
2. Click Graph and then click Time Series Plot.
3. Click Simple and then Click OK.
4. Click the variable names you want to graph from the left window and then click
select to move the variables over to the Variables window.
5. Click Index.
 Example from the plant

65
IOF Fe & SiO2 65
66 65 8
63 63 63 7
64 63 63 63
7.4
61 62 61 6
62
60 60 60
59 5
60 58 5.335 5.47 59
4.68 4.205 4
58 3.98 4.135
3
56 2.83 57 2.7 3.01
2.58 2.41 2.73 2
2.42 2.4 2.44 2.52 2.35
54 2.05 1
52 0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Fe(T) SiO2

2. Bar Chart
What is a Bar Graph?
A bar graph is a chart that uses either horizontal or vertical bars to show comparisons
among categories.
One axis of the chart shows the specific categories being compared, and the other axis
represents a discrete value.
Where to use a Bar Graph?
To compare things between different groups or to track changes over time.
Steps of Construction
Steps to Running a Bar Graph in Excel:
1. Collect the Data
2. Type the Data in Excel sheet
3. Select the Data
4. Now select the Insert tab button and in that select the Chart option
5. From the Chart option select the Bar Graph
Steps to Running a Bar Chart in Minitab:
1. Type your Data in columns in a Minitab worksheet
2. Click Graph, then click Bar chart
3. Select your variable type from Bar Represents drop down menu
4. Click OK
5. Select a variable from the left windowand then click the Select button to move
your variable over to the Variables window.
6. Click OK
 Example from the plant

Production Plan Act

300000

250000

200000

150000
259250
100000 184716

111800
102102
94630
94087
91667

87500

55800
54285

55800
48447

51840
46057
50000

0
BP 2 PP1 PP2 SP 1 SP 2 SP 3 SP 4
Plan Act

3. Pie Chart
What is a Pie Chart?
A pie chart (or a circle chart) is a circular statistical graphic which is divided into slices to
illustrate numerical proportion.
The arc length of each slice (and consequently its central angle and area),
is proportional to the quantity it represents. Pie charts are very widely used in the
business world and the mass media.
Where to use a Pie Chart?
Pie charts are used to convey approximate relative value.
Pie charts are generally used to show percentage or proportional data and usually the
percentage represented by each category is provided next to the corresponding slice of
pie.
Pie charts are good for displaying data for around 6 categories or fewer.
Steps of construction
Steps to Running a Pie Chart in Excel:
Collect the Data
Type or copy the Data in Excel sheet
Select the Data
Now select the Insert tab button and in that select the Chart option
From the Chart option select the Pie Chart
Steps to Running a Pie Chart in Minitab:
Type your Data in columns in a Minitab worksheet
Select Graph, then select Pie chart from the pull down menu
Select Chart values from a table.
 Click in the Categorical variable box, click on C1 in the left hand box and then click on
the Select button.
Click in the Summary variables box, click on C2 in the left hand box and then click the
Select button again.
To enter labels for the pie slices, click Labels and enter a title in the appropriate place.
While still in the Labels menu, click on the Slice Labels tab and under Label pie slices
with select Category name.
Click OK. Minitab now has the data, the title, and the labels it needs to create the desired
pie chart.
Click OK and Minitab will create the pie chart.

Example from the plant

BF 2 Production Loss
590 , 1%
2643 , 6% 25 , 0%

9481 , 21%

33395 , 72%

Raw Material Quality & Shortage

Internal Delays
SMS
External Delays

Special Purpose Graphs

1. Belt Graphs
These are like a pie chart but use bars and are suitable for showing comparative levels.
Can be made on % basis, as well as quantitative basis.
Can be made as vertical or horizontal bars.
A sub-divided bar graph is also called as component or proportional bar graph.
 Example from the plant

BF 4 Productivity and Silicon

4.00

3.50

3.00 0.57 0.57

0.57
2.50

2.00

1.50 2.79 2.82 2.60

1.00

0.50

0.00
Aug-17 Sep-17 Oct-17
Si Productivity

2. Radar Graphs

When the circular graph outline is combined with a grid system that has radial and
concentric lines originating at a centre pole, the result is a polar graph.
Because of the radial grid, the polar graph readily displays information such as certain
types of mathematical equations and more commonly variations in physical
measurements either around the 360 degrees of a circle (or compass) or through-out a
time period.
Example from the plant

SiO2 and
1
Al2O3
15 8 2

14 6 3
4
13 4
2

0
12 5

11 6

10 7
9 8
Al2O3 SiO2
3. Compound Graphs
A compound graph is a combination of bar and line graph.
These graphs are based on Pareto Analysis.
Example from the plant

BF 3 Production Loss
100%
10000 98% 100% 100% 90%
93% 80%
86%
8000 70%
60%
6000 50%
40%
4000
30%
2000 20%
10%
0 0%
Internal Raw Material External SMS Others
Delays Quality & Delays
Shortage

Prod Loss Cumulative percentage

4. Strata Graph/Area Graph

An area chart or area graph displays graphically quantitative data. It is based on the line
chart.
The area between axis and line are commonly emphasized with colours, textures and
hatchings.
This type of graph is used to show the trend in the total and the components in the
total.
Example from the plant

Fuel Rate at BF 2
600
400
200
0
Apr-17 May-17
Jun-17
Jul-17
Aug-17
Sep-17

Coke Nut Coke CDI

5. Float Graphs
This is an ideal graph for comparison of two distinct aspects.
This helps to find out total problem in relation to the entire aspect.
It shows the whole process at a glance.
Example

110
90
70
50
30
10
-10
1 2 3 4 5 6 7 8 9 10 11 12
-30
-50
-70
-90
Series2 Series1

6. Z Graphs
This graph has three values. Monthly, cumulative and comparison with the last twelve
months.
This is an ideal graph to find out the result of a particular month, what is the trend and
cumulative value; complex situation with a minimum number of charts or graphs.
Z chart can reduce at least three different charts into one simple chart.

Example from the plant

BF 4 Production Trend
4000000
3500000
3000000
2500000
2000000
1500000
1000000
500000
0

Month Prod Cumm Prod Prod Last 12 months

 7. Pyramid Graph or Side by Side Graph
It is used to show contrasting trends between levels of an independent variable.
It is used for displaying of more than two independent variables and comparison
between individual pair of value is very important.
This type of graph is used for representation of population in particular state or country.

Questionnaire - 1
1. Flowcharts were introduced by-
(a) Frank Gilbreth
(b) Lillian Gilbreth
(c) Both of the above
(d) None of the above
2. One of the purposes of Flowchart is identifying the root causes.
(a) True
(b) False
3. The Diamond shape in Flowcharts indicates-
(a) Decision point
(b) Starting of the process
(c) Continuity of the process
(d) Brief description of activity involved in that step
4. A Rounded Rectangle symbol indicates printed document or report which pertains to the
process.
(a) True
(b) False
5. Douglas Hartree in _______ explained that Herman Goldstine and John von Neumann had
developed a flowchart (originally, diagram) to plan computer programs.
(a) 1947
(b) 1849
(c) 1949
(d) 1847
6. Who is considered to be the founder of Graphs?
(a) William Rankine
(b) Florence Nightingale
(c) Alan Stevenson
(d) William Playfair
7. Playfair's Statistical Breviary, published in London in 1801, contains what is generally
credited as the first __________.
(a) Bar graph
(b) Scatter Plot
(c) Pie Chart
(d) Line Graph
8. One of the purposes of Graph is converting processed data into insights by providing trends,
solutions.
(a) True
(b) False
9. Strata graph is a special purpose graph.
(a) True
(b) False

10. Line graph is a basic graph in many fields.

(a) True
(b) False
11. Both the variables in Line graph are independent of one another.
(a) True
(b) False
12. Only standard colours: _________ to be used in case two graphs need to be shown.
(a) Black and Blue
(b) Black and Red
(c) Red and Blue
(d) Red, Black and Blue
13. According to the standard instructions, title of Line Graph must be at extreme top right of
the graph.
(a) True
(b) False
14. Which colour should be used to show benchmark in Line Graph?
(a) Black
(b) Blue
(c) Red
(d) None of the above
15. In Minitab which technique is used to create a Line Graph?
(a) Smoothing
(b) Blending
(c) Roughing
(d) Merging
16. A bar graph is a chart that uses only vertical bars to show comparisons among categories.
(a) True
(b) False
17. Pie charts are good for displaying data for around 6 categories or more.
(a) True
(b) False
18. Belt Graphs are like a pie chart but use lines and are suitable for showing comparative levels.
(a) True
(b) False
19. Compound Graphs are based on Pareto Analysis.
(a) True
(b) False
 20. Area Graph is based on ____________.
(a) Bar Chart
(b) Pie Chart
(c) Line chart
(d) Stock Chart
21. Float Graph is an ideal graph for comparison of ______ distinct aspects.
(a) Three
(b) Two
(c) Four
(d) Five
22. Z Graph has three values. Monthly, cumulative and comparison with the last _______
months.
(a) Six
(b) Two
(c) Four
(d) Twelve
23. Pyramid graph is used to show contrasting trends between levels of a dependent variable.
(a) True
(b) False

Answer key:
1. (c) 13.(b)
2. (a) 14.(c)
3. (a) 15.(a)
4. (b) 16.(b)
5. (c) 17.(b)
6. (d) 18.(b)
7. (c) 19.(a)
8. (b) 20.(c)
9. (a) 21.(b)
10.(a) 22.(d)
11.(b) 23.(b)
12.(a)
 Pareto Diagram
Introduction

Pareto chart is a bar graph that depicts which situations are more significant
It is developed by Vilfredo Pareto, an Italian economist
He observed that 80 % of Italys wealth lay in the hands of 20 % of the population
This tool is used for prioritization by the Pareto Principle (80-20 rule) and
differentiates Vital Few from Useful Many
The Pareto Principle (also known as 80-20 rule) states that for many events, roughly
80% of the effects come from 20% of the causes. This principle was developed by
Joseph Juran, based on the work of Vilfredo Pareto
Left vertical axis depicts actual frequency of items while the right vertical axis
denotes cumulative percentage

What is Pareto Principle?

Inputs
Causes 20%
Effort

Outputs

80% Effects

Results
 About the inventor

Vilfredo Federico Damaso Pareto (Italian: [vilfredopareto]; born Wilfried Fritz Pareto,
15 July 1848 19 August 1923) was an Italian engineer, sociologist, economist, political
scientist, and philosopher, now also known for the 80/20 rule, named after him as the Pareto
principle. He made several important contributions to economics, particularly in the study
of income distribution and in the analysis of individuals' choices. He was also responsible for
popularising the use of the term "elite" in social analysis.

Role of Pareto Principle in TQM

The Pareto principle has many applications in quality control.It is the basis for the Pareto
chart, one of the key tools used in total quality control and Six Sigma techniques. The Pareto
principle serves as a baseline for ABC-analysis and XYZ-analysis, widely used
in logistics and procurement for the purpose of optimizing stock of goods, as well as costs of
keeping and replenishing that stock.

There are two ways to analyze Pareto data depending on what you want to know:

Counts Pareto: Use this type of Pareto analysis to learn which category occurs most often,
you will need to do a counts Pareto diagram. To create a counts Pareto, you will need to
know the categories and how often each occurred.

Cost Pareto: Use this type of Pareto analysis if you want to know which category of problem
is the most expensive in terms of some cost. A cost Pareto provides more details about the
impact of a specific category, than a count Pareto can. For example, suppose you have 50
occurrences of one problem and 3 occurrences of another. Based on a count Pareto, you
would be likely to tackle the problem that occurred 50 times first. However, suppose the
problem that occurred 50 times costs only $.50 per occurrence ($25 total) and the problem
that occurs 3 times costs $50 each time ($150 total). Based on the cost Pareto, you may want
to tackle the more expensive problem first. To create a cost Pareto, you will need to know the
categories, how often each occurred, and a cost for each category.

Steps in making Pareto Chart:

These charts can be generated by simple spreadsheet programs, such as Apache
OpenOffice/LibreOffice Calc and Microsoft Excel, visualization tools such as Tableau
Software, specialized statistical software tools, and online quality charts generators.
Steps to Running a Pareto Chart in Excel
Select the Problem
Collect data
Sort data & calculate cumulative frequency
Construct the axes
Construct the bars
Draw the cumulative percentage line
Title and label the chart
Interpret the chart
 Steps to Running a Pareto Chart in Minitab

Open Minitab and type or copy your data into the Minitab worksheet.
Click on Stat Quality Tools Pareto Chart.
A new window with the title Pareto Chart pops up.
Select Category into the Defects or attribute data in box. ...
Click OK

Purpose & applicability of the tool

Useful in analyzing data about the frequency of problems or causes in a process

Useful in establishing priorities
Comparing Pareto charts of a given situation over time determines whether an
implemented solution reduced the relative frequency or cost of that problem or cause
Applicable to all functions
Use a Pareto diagram when you can answer "yes" to both these questions:

1. Can data be arranged into categories?

2. Is the rank of each category important?

Getting the most

Despite its simplicity, Pareto analysis is one of the most powerful of the problem-solving
tools for system improvement. Getting the most from Pareto analysis includes making
subdivisions, multi-perspective analyses, and repeat analyses.

Subdivisions are useful when data has been first recorded at a very general level, but
problem solving needs to occur at a more specific level. A retail chain manager might create
a Pareto diagram for all the customer returns of furniture by store in his district. Once he or
she has identified the store which contributes most returns to the total, the next step might be
to analyze that store's returns by furniture type. If "chairs" turned up as the biggest category
of furniture returns for the store in question, yet another Pareto of chair returns might help to
discover whether dining room chairs, occasional chairs, wooden chairs, or upholstered chairs
were being returned more frequently. Because the Pareto principle holds for sub groupings of
data, such successive analyses can be performed to help teams target small elements of a
large problem.

Multi-perspective analyses are useful when data can be stratified or subdivided in several
different ways. The retail manager might study customer returns of furniture by number of
units and again by cost. A store might discover that chairs have accounted for the majority of
items returned over a period of time, but that fine dining sets accounted for the majority of
cost. Depending on priority, the problem could be attacked to reduce either the highest
frequency or the highest cost item. The district retail manager might study his or her district-
wide furniture returns by store, by lot number, by furniture type, by cause for return, by
frequency, by cost, by salesperson, by delivery carrier, or by any other set of categories he or
she thinks may reveal opportunities for improvement. Multi-perspective Pareto analysis helps
assure that a set of data is reviewed from all angles and that many explanations for variability
are considered.

Repeat analyses are useful when improvement activity is underway and performance data is
changing over time. If the retail manager worked with the store's delivery staff to reduce the
number of fine dining sets being damaged and subsequently returned, it would be useful to
repeat an earlier Pareto analysis using more recent data to see if the target category has
shrunk. Depending on the cycle of data collectionhourly, daily, weekly, monthly, quarterly,
or otherrepeated Pareto analyses help to monitor the improvements made to the system
producing the data.

Caution is in order for users of Pareto analysis who have not monitored the systems they are
studying for stability. A wildly fluctuating system will produce inconsistent Pareto rankings
that can lead to misjudgments. If, for example, the retail manager failed to note that customer
furniture returns varied greatly from month to month, the ranking of categories may be
entirely different in a month with high returns from those of a month in which returns were
unusually low. Repeated Pareto analyses can help to confirm rankings, but the most effective
protection against being misled is to first use a control chart to tell if the system is stable and
predictable.

Pareto Analysis - Risks and how to avoid them:

Risks Steps to avoid them

Selecting the wrong items, such Take care to start with the right
as jumping to conclusions rather problem
than using proven facts
Using measures which lead tothe Remember that the focus is to find
highest bar on the chart the most important item, so get the
indicating something that is not measurements right
the most appropriate item to
address
Assuming the people who doing Educate the people who are doing
the measurement are motivated the measurements and check with
and able to do this their managers that they can do this
extra work
Ending up with things that are too Carefully consider the efforts you
big to address will need to address the selected
items. If this will be too much, then
take another step to find a lower
level focus.
 Example from the Plant:

H1 Hot Metal Short fall 2017-18

96% 99% 100%

89% 100%
140000
90%
120000 80%
100000 57% 70%
60%
80000
50%
60000 40%
40000 30%
20%
20000 10%
0 0%
Internal Delays Raw Material SMS External Delays Others
Quality &
Shortage
Prod Loss Cumulative percentage

Questionnaire
1) Pareto Chart is based on which rule?
a) 70/30
b) 80/20
c) 60/40
d) 50/50

2) Pareto Chart is a scatter plot that depicts which situations are less significant.
a) True
b) False

3) Who developed Pareto chart?

a) MaffeoPantaleoni
b) Joseph Juran
c) Alfred Pareto
d) Vilfredo Pareto

4) Left vertical axis in Pareto chart depicts actual frequency of items.

a) True
b) False
5) Pareto Chart differentiates Vital Few from __________.
a) Useful Few
b) Useful Many
c) Vital Many
d) Insignificant Few
6) Pareto Chart is used in which of the following techniques?
a) Six Sigma
b) Three Sigma
c) Six Delta
d) Six Beta

7) To learn which category occurs most often, you will need to do a cost Pareto diagram.
a) True
b) False
8) A cost Pareto provides more details about the impact of a specific category.
a) True
b) False
9) Pareto Chart is useful in establishing inferiorities.
a) True
b) False

10) Pareto charts can be generated by visualization tools such as ________ Software.
a) Fusion Charts
b) Timeline JS.
c) D3.js.
d) Tableau
11) Subdivisions are useful when data has been first recorded at a very specific level, but
problem solving needs to occur at a more general level.
a) True
b) False
12) Multi-perspective Pareto analysis helps assure that a set of data is reviewed from
____________ and that many explanations for variability are considered.
a) Only one angle
b) All angles
c) A specific angle
d) Both angles
13) Repeat analyses are useful when improvement activity is over.
a) True
b) False

14) Repeated Pareto analyses help to monitor the _____________ made to the system
producing the data.
a) Deteriorations
b) Changes
c) Alterations
d) Improvements
15) A wildly fluctuating system will produce consistent Pareto rankings that can lead to
misjudgements.
a) True
b) False

16) Repeated Pareto analyses can help to confirm rankings, but the most effective protection
against being misled is to first use a ____________ to tell if the system is stable and
predictable.
a) Scatter Chart
b) Column Histogram Chart
c) Bar Graph
d) Control Chart
17) One of the risks of Pareto Analysis is to end up with things that are too big to address.
a) True
b) False
18) Vilfredo Pareto observed that _____ of Italys wealth lay in the hands of 20 % of the
population.
a) 20%
b) 70%
c) 80%
d) 30%

19) The Pareto Principle (also known as 80-20 rule) states that for many events, roughly 80%
of the effects come from 20% of the causes. This principle was developed by
a) Vilfredo Pareto
b) Joseph Juran
c) Kaoru Ishikawa
d) Deming

20) A Pareto Diagram can be used

a) When the data can be arranged into categories.
b) When the rank of each category is important.
c) Both of the above
d) None of the Above

Answer Key
1. b 11. b
2. b 12. b
3. a 13. d
4. b 14. b
5. a 15. d
6. b 16. a
7. a 17. c
8. b 18. b
9. d 19. c
10. b 20. c
 Check-sheet
Introduction
As one of Ishikawas basic quality tools, Check Sheets are an effective means of
gathering data in a helpful, meaningful way.
Used for gathering facts, rather than opinion about a process.
It is used to collect data in real time at the source of data generation.
Provides an easy, structured and standardized way of recording data.
The data captured may be quantitative or qualitative. When the information is
quantitative, the check sheet is sometimes called a Tally Sheet.
Usually involves making tally-marks / check-marks on a sheet to count the number of
times something happens as it happens.Data is read by observing the location and
number of marks on the sheet.

Objectives
The main objectives of the check lists are:
Clearly identify what is being observed.
Keep the data collection process as easy as possible.
Group the data. Collected data should be grouped in a way that makes the data
valuable and reliable. Similar problems must be in similar groups.
Create a format that will give the most information with the least amount of effort.

Purpose and applicability of the tool

When observing a process and recording information over time.
When measuring and visualizing the effect of a problem on a process.
When checking a solution to see the improvement.

Types of Check-sheets
1. Defective item Check-sheet
To investigate total number of different types of defects occurring.
Can give clue to where improvements needed.
Incorporate stratification into check sheet design, e.g. morning shift, evening shift,
lines, machine etc.
Must understand how to record defects. Can have two or more defects in one
defective part.
2. Defect cause Check-sheet
Need stratification of data to find possible causes of defects
Understand type of defects and possible causes
Which machine?
Which worker?

Can take countermeasures immediately

3. Production Process distribution Check-sheet

To find the variations of measured item.
Similar to a histogram
Simple way to classify data exactly at the time of collection.
Prepared in advance. Symbols (e.g. X) placed in the box each time measurement
made.
When stratification required on single sheet-use different colour or symbol/mark

4. Defect Location check-sheet

Need to know location occurrence
Defect location sketch or expanded view of product.
Mark location to find pattern of defect occurrence.
Once location known-finding causes of defects is easier, e.g. casting blowhole
positions, paint chipping, dents, etc.

Benefits of the tool

Effective way of displaying data
Easy to use
Can identify the root cause of a problem
A first step in the construction of other graphical tools
Provides a structure for uniform data collection
Can be used to substantiate or refute allegations
 Steps of Check-sheet construction

Decide what event or problem will be observed.

Decide Data Collection Plan-time-period and frequency

Design the check-sheet template

Trial run of the check-sheet

Record data on the check Sheet

 Histogram
Discrete and Continuous Data
Discrete Data

A set of data is said to be discrete if the values / observations belonging to it are distinct and
separate, i.e. they can be counted. It is also a set of data that cannot take decimal values.
Example:
Number of good or bad parts in a lot, number of students in a class etc.

Continuous Data

A set of data is said to be continuous if the values / observations belonging to it may take on
any value within a finite or infinite interval. You can count, order and measure continuous
data.
So continuous data can take decimal values and still make a sense.
Example:
Height, weight, temperature, the amount of carbon percentage in hot metal, the time
required to complete one heat.

Introduction
Histogram is a tool similar to a bar chart in structure, for graphically portraying a frequency
distribution. It enables the user to obtain useful information about the shape and dispersion
(spread) of a set of data.
The Histogram enables a very concise portrayal of a KPI data / other data / information in a
bar chart format and help understand / characterise data.

Difference between Histogram and Pareto Diagram

Histogram Pareto Diagram

Histogram is a tool that
illustrates the frequency of Paretodiagram is a tool for
Purpose
occurrence of an event, using prioritizingdata
height of bar as indicator
Used for both continuous and
Type of data Used only continuous data
discrete data
Used to analyse Location Used for identify vital few
(Mean),Spread (variation or causes that contribute to
Application
Std. Deviation) and Shape majority of effects by using
(distribution) of Data the Pareto 80/20 rule
 Thehistogram condenses
dataseriesintoaneasilyinterpretedvisualbytakingmanydatapointsandgroupingthemintologica
lrangesorbins.
DerivedfromtheGreekwords-HistosAnythingsetupright,Gamma-Drawingrecordwriting.

alDiagram.

Histogram Overview
Histogram speaks about:
Location The mean or average value, of a set of data.

Shape The type of data distribution.

Spread The total amount of variation or deviation from the mean value.
 Types of Histogram
Typical Histogram Shapes and What They Mean

1. Normal:
A common pattern is the bell-shaped curve known as the Normal distribution.
Here, points are as likely to occur on one side of the average similar to the other side.

2. Skewed:
The skewed distribution is asymmetrical a natural prevents the outcomes on one side. The
distributions peak is off centre towards the limit and a tail stretches away from it.

3. Comb:
In a comb distribution, the bars are alternately tall and short. This distribution often results
from rounded-off data and / or an incorrectly constructed data.

4. Dog Food:
The Dog Food distribution is missing something- results near the average.
5. Double-peaked or Bimodal:
The outcomes of two processes with different distributions are combined in one set of data.

6. Plateau:
The Plateau might be called a Multimodal distribution. Several processes with normal
distributions are combined.

7. Edge peak:
The edge peak distribution looks like the normal distribution except that it has a large peak
at one tail. Usually this is caused by the faulty construction of the histogram with data
lumped together into a group labelled greater than

8. Truncated or heart-cut:
The Truncated distribution looks like a normal distribution with the tails cut off.

Steps of Histogram construction

Steps of a Histogram construction in Excel:
1. Collect data, minimum hundred data points
2. Insert the data collected in Excel sheet
3. Select Sort & Filter, select Sort Largest to Smallest
4. Identify maximum value, identify minimum value
5. Calculate Range
Range=MaximumvalueMinimumvalue
 6. Determine width of class interval (W)
W= Range/Total number of classes

7. Construct Frequency Distribution Table

8. Select two columns Class Interval, Frequency
9. Select Insert option, select Column, select 2D Column
10. The bar chart will appear
11. Right click on bar chart, select Format Data Series
12. Reduce Gap to 0%. Increase Separated to Overlapped
13. Select Border Colour option, select solid line option
14. Change the border colour to Black
15. Add Data Labels

Steps of a Histogram construction in Minitab:

1. Type your data into columns in Minitab. In most histogram cases, youll have two
sets of variables in two columns.
2. Click Graph and then click Histogram.
3. Choose the type of histogram you want to make. In most cases for elementary
statistics, a Simple histogram is usually the best option.
4. Click OK.
5. Click the name of the variable you want to make a histogram for and then click the
Select button to move that variable name to the Graph Variables box.
6. Click OK to create the histogram in Minitab.
7. (Optional)Change the number of bins (category widths) by clicking on one of the bin
headings (numbers) at the base of a bar. This opens the Edit Scale box. Click
Binning and then click the Number of intervals radio button. Change the number
of bins and click OK.
 Example from the plant

Histogram of PP-2 Con. Moisture

Normal
30 Mean 1 0.59
StDev 0.4864
N 1 50
25

20
Frequency

15

10

0
9.6 1 0.0 1 0.4 1 0.8 1 1 .2 1 1 .6
PP-2 Con. Moisture

Where to use Histograms

Whenyouwanttoseetheshapeofthedatas distribution-
determiningwhethertheoutputofaprocessisdistributedapproximatelynormallyornot?
When analysing whetheraprocesscanmeetthecustomersrequirements.
When analysing whattheoutputfromasuppliersprocesslookslike.
Whenseeingwhetheraprocesschangehasoccurredfromonetimeperiodtoanother
Analysingtheimpactofanimprovementaction
checkingwhethertheshiftinMeanorVariationhashappenedornot?
Whencomparingoutputsoftwoprocessesfortheircurrentlevelofprocesscapability(Mean,Varia
nce)
Whenyouwishtocommunicatethedistributionofdataquicklyandeasilytoothers.
 Questionnaire
1. As one of Ishikawas basic quantity tools, Check Sheets are an effective means of gathering data
in a helpful, meaningful way.
(a) True Answer key: (b)
(b) False
2. Check-sheet provides an easy, structured and standardized way of processing data.
(a) True Answer key: (b)
(b) False
3. When the information is quantitative, the Check-sheet is sometimes called a
(a) Spread sheet
(b) Work sheet Answer key: (d)
(c) Data sheet
(d) Tally sheet
4. One of the objectives of Check-sheet is to clearly identify what is being observed.
(a) True Answer key: (a)
(b) False
5. Defective item Check-sheet incorporate stratification into Check-sheet design.
(a) True Answer key: (a)
(b) False
6. Which type of Check-sheet is similar to Histogram?
(a) Defective item Check-sheet
(b) Defect cause Check-sheet Answer key: (c)
(c) Production Process distribution Check-sheet
(d) Defect Location Check-sheet
7. Defect Location Check-sheet marks location to find pattern of defect occurrence.
(a) True Answer key: (a)
(b) False
8. Check-sheet is the ________ step in the construction of other graphical tools.
(a) Last
(b) Middle Answer key: (c)
(c) First
(d) Fifth
9. A set of data is said to be discrete if the values / observations belonging to it are
indistinct and attached.
(a)True Answer key: (b)
(b)False
10. A set of data is said to be continuous if the values / observations belonging to it may
take on any value within a finite or infinite interval.
(a) True Answer key: (a)
(b) False
11. Histogram is a tool similar to a ______ chart in structure, for graphically portraying a
frequency distribution.
(a) Line
(b) Pie Answer key: (d)
(c) Bubble
(d) Bar
12. Histogram uses only continuous data.
(a) True Answer key: (b)
(b) False
13. Histogram groups the data points into logical ranges or bins.
(a) True Answer key: (a)
(b) False
14. Who introduced the term Histogram?
(a) Isaac Milner
(b) Ronald Fisher Answer key: (c)
(c) Karl Pearson
(d) Karl Landsteiner
15. A common Histogram pattern is ___________ curve known as Normal Distribution.
(a) Oval-shaped
(b) Rectangle-shaped Answer key: (d)
(c) Triangle-shaped
(d) Bell-shaped
16. The Skewed Histogram is asymmetrical.
(a) True Answer key: (a)
(b) False
17. In a Comb Histogram, the bars are tall and short, respectively.
(a) True Answer key: (b)
(b) False
18. The Plateau Histogram might be called Bimodal distribution.
(a) True Answer key: (b)
(b) False
19. The edge peak distribution looks like a normal distribution except that it has a large
peak at one tail.
(a) True Answer key: (a)
(b) False
20. Minimum data points required to construct a Histogram-
(a) 90
(b) 50 Answer key: (c)
(c) 100
(d) 150
 Cause and Effect Diagram
Introduction
Cause and effect diagram is a graphical technique to examine why something happened or
might happen by organizing potential causes into smaller categories. It can be used in teams
to identify and arrange all the possible causes of an event / problem / outcome.
One of the Seven Basic Tools of Quality, it isalso known as Fish-bone Diagramfor its fish
bone kind of construction. It is also known as Ishikawa Diagram.
Invented by Prof. Kaoru Ishikawa in 1943. He first used it to explain at Kawasaki Steel Works.
There are three types of Cause and effect Diagram. They are:
Cause-Enumeration Type
Dispersion-Analysis Type
Product-Classification Type
The commontype used is called Cause-Enumeration Type.

Type What is it? Advantages

Cause- Generic type, can be used
1 Enumeration Conventional C&E; follows all 7 steps for any cause-effect
Type situation
Good for analysing
Instead of brainstorming, first major causes
repetitive problems, when
(Major Bones) to be analysed are decided.
major causes are known.
Once the major causes are decided, the
Is advantageous when the
Dispersion- spine is drawn and probable causes are
2 team building the cause-
Analysis Type attached directly.
effect diagram has
After the diagram is ready, the team
expertise in the process /
analyse the diagram to determine the major
function they debating
causes.
about.
Used for manufacturing / production units as Easier to construct and
they have a set of sequential operations. understand.
Production-
Each stage in the production process leading Those involved in making
3 Classification
to the effect being examined is shown along C&E diagram are already
Type
the main arrow or backbone of the diagram. familiar with each of the
Possible causes are then shown as branches. production steps identified.

About the Inventor

Kaoru Ishikawa was a Japanese organizational theorist, Professor at the Faculty of
Engineering at The University of Tokyo, noted for his quality management innovations.
According to Ishikawa, quality improvement is a continuous process, and it can always be
taken one step further.
 With his cause and effect diagram (also called the "Ishikawa" or "fishbone" diagram) this
management leader made significant and specific advancements in quality improvement.
With the use of this new diagram, the user can see all possible causes of a result, and
hopefully find the root of process imperfections. By pinpointing root problems, this diagram
provides quality improvement from the "bottom up."
Dr. W. Edwards Deming --one of Ishikawa's colleagues -- adopted this diagram and used it to
teach Total Quality Control in Japan as early as World War II. Both Ishikawa and Deming use
this diagram as one the first tools in the quality management process.
Ishikawa also showed the importance of the seven quality tools: control chart, run chart,
histogram, scatter diagram, Pareto chart, and flowchart. Additionally, Ishikawa explored the
concept of quality circles.

Where is C&E diagram used?

Use Cause and Effect Diagram Use Failure Mode and Effect Analysis

Problem has occurred Potential / Future Problem

Cause Effect Cause Effect

Reasons that Symptoms that Reasons that Symptoms that
led to the evidenced from the could led to the would result from
problem problemproblem the problem

Uses / Applications:-
For defining the problem.
For visualization of cause-effect linkages.
For listing probable causes of a problem.
For arriving at the possible causes of the problem.
Especially when a teams thinking tends to fall into ruts.
Developing objectives for solutions.

Benefits:-
Helps generate a structured lists of potential causes of problems, stimulates and aids the
thinking process.
Helps systematic idea generation through visual representation of cause-effect
relationship.
Helps prioritisation of reasons (creation of a Pareto for vital few causes)
Helps data collection tools.
 Role in TQM
In the total quality management (TQM) fishbone diagram (Ishikawa diagram, Herringbone
diagram, cause-and-effect diagram, Fishbone diagram) represents factors (reasons) which
influence on quality coefficient of the final result of the concerned process. The main factors
are 4M:

Men
Methods
Materials
Machines

These main factors are subdivided into smaller. The degree of the detailed elaboration is
defined only by factors significance and planners tasks. With the help of Ishikawa
diagram it is possible to show visually all factors which influence on the quality
coefficient, sort them out and show their interrelation.

Steps in making Cause and Effect diagram

Define key effect

Brainstorm

Fill in the box and draw the spine

Identify Main Bones

Add lower level causes

Identify increasingly more detailed levels of causes(Secondary Causes)

Analyze the diagram

 Define key effect
Identify and clearly define the outcome or effect to be analysed.
Decide on the effects to be examined. Effects are stated as particular quality
characteristics, problem resulting from work, planning objectives.
Remember, an effect maybe positive (an objective) or negative (a problem), depending
upon the issue that is being discussed.

Positive effect
Focuses on a desired outcome.
Tends to foster pride and ownership over productive areas.

Negative effect
Can side-track the team into justifying why the problem occurred and placing blame.
However, it is sometimes easier for a team to focus on what causes a problem than
what causes an excellent outcome.

Brainstorm
Conduct a brainstorm to determine all the possible causes of the effect.
General guidelines for conducting Brainstorming:
Have a mixed team from different parts of the process.
Get a fresh pair of eyes from someone who is not too close to the process.
Have a facilitator an impartial referee.
Everyone is an equal contributor.
Fast and furious go for quantity rather than quality (of ideas) at first.
Know when to stop.
Write each idea on a post to make it easy to transfer them onto fishbone diagram later.
Be careful not to muddle causes and solutions on this stage.
It is important to brainstorm before identifying cause categories otherwise you can
constrain the range of ideas.

Fill in the Effect Box and draw the Spine

Draw a horizontal arrow pointing to the right. This is the spine.
To the right of the arrow, write a brief description of the effect or outcome which results
from the process.
Draw a box around the description of the effect.
 Identify Main Bones
Establish main causes or categories under which other possible causes will be listed.
There are a whole set of common causes categories, some of which are listed below:
Nomenclature Details Applicable to
Methods, Materials, Machineries and
4Ms Manufacturing Industry
Man
Machine, Method, Materials,
6Ms Measurement, Man and Mother Nature Manufacturing Industry
(Environment)
Service Industry,
4Ps Policies, Procedures, People and Plant
Administration Functions
Price, Promotion, People, Processes, Place Service Industry, Marketing
8Ps / Plant, Policies, Procedures, Products (or Function, Administration
Service) Function
4Ss Surroundings, Suppliers, Systems, Skills Service Industry
Selectively used under
Equipment, Process, People, Materials,
Others various industries and
Environment and Management
functions

Write the main categories your team has selected to the left of the effect box. Draw
some above and below the spine.
Draw a box around each category label and use a diagonal line to form a branch from the
box to the spine.

Add lower level causes (Primary causes)

Transfer the potential causes from brainstorming outcomes to the diagram, placing each
cases under the appropriate category.
If causes seem to fit more than one category then it is acceptable to duplicate them.
Identify as many causes or factors as possible and attach them as sub-branches of the
major branches.
Fill in detail for each cause. If a minor cause applies to more than one major cause, list it
under both.

Identify secondary causes

Identify increasingly more detailed levels of causes and continue organizing them under
related causes and categories.
We can do this by asking a series of why questions.
Branches and twigs can be further developed by asking questions.
This avoids using broad statements that may in themselves be effects.
Repeat the process for all other major branches.
 Analyze the diagram

Balance Check the 'balance' of C&E diagram

Thick cluster A thick cluster of sub-causes around one major cause / area may
indicate that there is scope of further study.
Skeletal cluster A main category having few specific causes may indicate a need
for further identification of sub-causes.
Repetitive Identify the causes that appear repeatedly under different
categories. This may represent root causes.
Quantification Look for what you can measure in each cause so you can quantify
the effects of any changes you make.
Classification Classify the identified causes into measurable and non-
measurable category for studying the extent of contribution.
Action items Most importantly identify and circle the causes that you can action
on.

Steps to Running Cause and Effect Diagram in Minitab

1. First, start by using the drop-down lists on the left side to tell Minitab that our
information is in Constants (meaning we will type the information into this dialog box,
versus having the data already typed into the worksheet). As we work through this, we
can always click OK to see our progress.To go back to the last dialog to keep entering
information, press (Ctrl+E) on the keyboard.

2. Enter the causes in the empty column in the middle.Note that any individual cause that
includes multiple words (for example, Day of Week) must be included in double-quotes:
Day of Week. Without the double-quotes, Minitab will assign each individual word as
a cause. Multiple causes for the same branch are entered with a space between the
causes. For example, to enter Ambient Temperature and Ambient Moisture as causes,
enter: Ambient Temperature Ambient Moisture
After completing the dialog, click OK again to see progress.

3. As a final step, add sub-branches to some of causes. To add sub-branches, click

the Sub button for that particular branch. This will bring up the Sub-Branches dialog.
Here the names of each of causes are automatically listed in the Labels column.
Choose Constants from the drop-down list and type in the sub-branch labels. Note that
the same double-quote rule for sub-braches with multiple words applies here.
 Example from the plant

Jamming of
Charging plate chain scrapper
Man vibration Machine Lump coal

Poor
Improper operating skill Unskilled
training operator Chain scrapper not
working efficiently

Improper Charging car

operation by mechanism not
Unskilled charging car Cake stamping working properly
operator operator not effective

Side wall cylinders

Miscommunication not opening
Improper uniformly
Malfunction of
training Coal
limit switches
accumulation
on operating
Coal moisture Conditions not safe platform
not optimum High fatigue when working on
operating platform
Hammer mill
Space constraint for
hammer worn
out cleaning Coal lifting
High temperature procedure not
Coal crushing followed
not optimum Coal cake Insufficient training
charging
Less width of
Coal procedure
operating
not
processing system
followed
not
Sticking of coals
sufficient Insufficient training Improper speed
to side walls
of charging plate

Material Environment Method

Encoder program
problem

Coal Spillage at operating platform

 Stratification
Introduction
Stratificationistheprocessofdividingmembersofadatapopulationintohomogeneoussubgro
upsbeforesamplingaccordingtocommonfactorsortendencies.
It is a technique used to segregate the data from variety of sources to obtain the trends.
Stratification is basically a technique to solve the sampling error and is used mostly in the
define stage of a six sigma project.
It can be used to great effect in combination with other techniques, including histogram
and scatter diagram. If, for example, three shift teams are responsible for a certain
product output stratifying the data into shift groups might produce histograms that
indicate process adjustments were taking place at shift changeovers.
Subgroupsformedbystratification Strata
Strata are defined based on
Product
Process
Suppliers
Equipment
Operator
Time
Raw material
Type of defect
Cause of defect
Strata are mutually exclusive and collectively depict the whole theme.

Where to use Stratification

Before collecting data.
When data come from several sources or conditions, such as shifts, days of the week,
suppliers or population groups.
When data analysis may require separating different sources or conditions.

Stratification considerations
Here are examples of different sources that might require data to be stratified:
Equipment
Shifts
Departments
Materials
Suppliers
Day of the week
Time of day
Products
Survey data usually benefit from stratification.
 Always consider before collecting data whether stratification might be needed during
analysis. Plan to collect stratification information. After the data are collected it might be
too late.
On your graph or chart, include a legend that identifies the marks or colours used.

Steps of Stratification

Select the stratification variables

Establish factors that are to be used for

each stratification variable

Sort observations into the factors of one

of the stratification variables

Display the results on a graph - bar chart

Prepare and display results for other

stratification variables

Questionnaire
1. Cause & effect diagram is used for potential/future problem.
a. True
b. False
2. Cause and Effect diagram is also known as Herringbone Diagram.
a. True
b. False
3. The Common type of Cause and Effect diagram is
a. Dispersion Analysis type
b. Production Classification type
c. Cause Enumeration type
d. None of the above
4. According to Ishikawa, quality improvement is a dis-continuous process.
a. True
b. False

5. Ishikawa explored the concept of ____________ circles.

 a. Quantity
b. Quality
c. Bothe of the above
d. None of the above
6. The main factors, which influence onquality coefficient of the final result of the
concerned process, are 4Ms:
a. Machine, Method, Materials, Measurement
b. Men, Machine, Method, Materials
c. Machine, Method, Materials, Mother Nature (Environment)
d. None of the above
7. A thick cluster of sub-causes around one major cause / area may indicate that there
is scope of further study.
a. True
b. False
8. Dispersion Analysis Type of Cause and Effect Diagram does not follow all the steps
of construction.
a. True
b. False
9. Prof. Kaoru Ishikawa invented Cause and Effect Diagram in
a. 1945
b. 1947
c. 1943
d. 1843
10. The common cause category 4S (Surroundings, Suppliers, Systems, Skills) is
applicable to
a. Manufacturing Industry
b. Service Industry
c. Marketing Function
d. Administration Function
11. Brainstorming is an important step in making Dispersion Analysis type of Cause and
Effect diagram.
a. True
b. False
12. Stratificationistheprocessofdividingmembersofadatapopulationinto
heterogeneoussubgroupsbeforesampling.
a. True
b. False

13. Stratification is basically a technique to solve the sampling error and is used mostly
in the ___________ stage of a six sigma project.
 a. Analyze
b. Control
c. Define
d. Improve
14. Strata are mutually inclusive and collectively depict the whole theme.
a. True
b. False
15. Raw material is one of the bases on which Strata are defined.
a. True
b. False

Answer key:

1. b
2. a
3. c
4. b
5. b
6. b
7. a
8. a
9. c
10. b
11. b
12. b
13. c
14. b
15. a
 Scatter Diagram
Introduction
The Scatter Diagram (also called Scatter Plot) is the graphical technique can be used in
teams to establish correlation between two interdependent variables. The chart on which the
dots are plotted is also called as a Dotogram.
First used by Prof. Kaoru Ishikawa in 1943.
It is used as one of the basic problem solving tools mainly for defining relationship between
two variables; especially when there is a suspicion on two parameters to be correlated.
The values for each pair of a variable are plotted on a graph in the form of dots thereby
obtaining as many points as the number of observations. Then by looking at the scatter of
several points, the degree of correlation is ascertained.
The degree to which the variables are related to each other depends on the manner in which
the points are scattered over the chart. The more the points plotted are scattered over the
chart, the lesser is the degree of correlation between the variables. The more the points
plotted are closer to the line, the higher is the degree of correlation. The degree of correlation
is denoted by r.
For more than 2 variables, multivariate analysis / hypothesis testing is used.

What is correlation?
Correlation is the measure of amount of linear relationship between two variables.
A positive correlation indicates the extent to which variables increase or decrease in parallel;
a negative correlation indicates the extent to which one variable increases as the other
decreases.
It is represented by Correlation coefficient (r) which is a pure number ranging between -1 and
+1. -1 means totally negative correlation and +1 means totally positive correlation.
 Correlation coefficient r between two variables X and Y is calculated as per the Pearsons
formula
N( ) ( ) ( )
=
[ ( ) ] [ ( ) ]
Where,
N = number of pairs of values
x = sum of x values
y = sum of y values
xy= product of paired values
x2 = sum of squares of x values
y2 = sum of squares of y values

Types of Scatter Diagram

Differentiation of Scatter Plots can be made on the basis of:
1. Type of Correlation Positive, Negative, Curvi-linear
2. Extent of Correlation None, Low, High, Perfect

Types of correlation
1. No Correlation
2. Positive Correlation
3. Negative Correlation
4. Curvilinear Correlation
5. Partial Correlation

Extent of correlation
1. No Correlation
2. Weak Correlation
3. Strong Correlation
Perfect Correlation
 Uses and benefits of Scatter Diagram
Uses:
Used for studying the relationship between dependent (x) and independent (y).
Benefits:
Helps understand type of correlation (positive, negative)
Helps understand degree of correlation (none, weak, strong, perfect)
Helps establish countermeasures on basis of the relationship
Also, help establish cause & effect relationship

Steps in making Scatter Diagram

Discuss the purpose (Suspicion statement)

Decide the paired variables (x, y)

Collect pairs data for x &y (desirable > 30 pairs)

Plot the data on an x-y graph

Interpret from the plot (Graph)

Calculate the Correlation Coefficient r

Infer from the value of r

Steps in making a Scatter Diagram in Excel

1. Enter data for x and yinto the Excel worksheet
2. Click on Insert and then click on Scatter.A scatter plot appears.
3. Right click on scatter data points and select Add trendline. A trendline appears.
4. Select Graph, then go to Layout on the horizontal bar, then to Axis Titles and then to Primary
Horizontal Axis Title. Enter the name of the horizontal Axis.
5. Select the Graph, then go to Layout on the horizontal bar, then to Axis Titles and then to
Primary Vertical Axis Title. Then choose the type.Enter the name of the Vertical Axis.
6. Type CORRREL in a cell and then select Array1 for data range of x and Array 2 for data range of y.
The value of r will be returned by the formula.
 Steps in making a Scatter Diagram in Minitab
1. Enter your data into two columns. One column should be the x-variable (the independent
variable) and the second column should be the y-variable (the dependent variable).
2. Click Graph on the toolbar and then click Scatter plot.
3. Click Simple Scatter plot. You can choose one of the others (such as the scatter plot with lines).
4. Click your y-variable name in the left window, then click Select to move that y-variable into the
y-variable box.
5. Click your x-variable name in the left window, then click Select to move that x-variable into the
x-variable box.
6. Click OK to create the scatter plot in Minitab. The graph will appear in a separate window.

Example from the plant

Hot Metal Production vs Slag Rate

420
415
410
405
Slag Rate

400
395
390
385
380
375
370
9200 9300 9400 9500 9600 9700 9800 9900 10000
Hot Metal (Actual)

Slag Rate kg/thm Linear (Slag Rate kg/thm)

Questionnaire
1. Scatter diagram is used for
(a) Relation between two inter-related data variables
(b) Type of correlation
(c) Degree of correlation
(d) All the above
2. Scatter Diagram was first used by
(a) W. Edwards Deming
(b) Walter A. Shewhart
(c) Kaoru Ishikawa
(d) None of the above
3. The Chart on which the dots of the Scatter Plot are plotted is called
(a) Datagram
(b) Dotogram
(c) Dotagram
(d) None of the above
4. Scatter Diagram is used to show correlation between two interdependent variables.For
more than 2 variables, multivariate analysis / hypothesis testing is used.
(a) True
(b) False
5. Correlation is the measure of amount of non-linear relationship between two variables.
(a) True
(b) False
6. After drawing a scatter diagram, the company realizes that the pollution level is coming
down with time by incorporating advanced technology. The type of correlation exhibited by
scatter diagram is
(a) Positive correlation
(b) Negative correlation
(c) Curvi-linear correlation
(d) None of the above
7. In scatter diagram, 'r' denotes
(a) Correlation coefficient
(b) Correlation
(c) Radius
(d) Degree
8. In scatter diagram, which among the following denotes a strong positive correlation?
(a) r=2.223
(b) r=0
(c) r=0.998
(d) r=0.3
9. Value of 'r' in scatter diagram lies between
(a) 0 to 1
(b) -1 to +1
(c) -1 to 0
(d) 1 to 2
10. Basappa drew a scatter diagram to study correlation between Hot metal Silica and
temperature. He observed that hot metal silica is reducing with increase in temperature
and 'r' value is 0.78. The correlation exhibited is
(a) Strong negative correlation
(b) Moderate negative correlation
(c) Strong positive correlation
(d) No correlation
11. The following scatter diagram is an example of which type of scatter diagram?

(a)Negative correlation
(b)Curvi-linear correlation
(c) Positive correlation
(d)No correlation
12. Hanumantha is one of the intelligent and hard-working employees of Hot-Strip Mill and
is very enthusiastic to participate in J1+ test. He has registered for the test and
successfully scored 82 marks in his first attempt. Eager for scoring high marks, he
recalled the errors in his previous attempt and the areas which could not fetch him
complete marks. In one of his practical questions, he was supposed to construct a
scatter diagram out of the given data set. While he was successful in constructing the
scatter diagram using Insert -> Scatter Diagram option in MS-Excel, he was unable to
 calculate the "r" value for the relation which depicts the strength of the relation among
the variables. Help Hanumantha to choose the right syntax for calculating the "r" value:
(a) =CALCULATE(r, array1, array2), where array1 and array2 denote the two data sets
(b)=CORREL(array1, array2), where arra1 and array2 denote the two data sets
(c) =RVALUE(array1,array2), where arra1 and array2 denote the two data sets
(d)=COEFF(array1,array2), where arra1 and array2 denote the two data sets
13. Scatter diagrams A, B, C, D are arranged in the form of

(a) Negative correlation; Positive correlation; Perfect correlation; Partial correlation

(b) Positive correlation; Partial correlation; Negative correlation; Perfect correlation
(c) Positive correlation; Partial correlation; Perfect correlation; Negative correlation
(d) Negative correlation; Partial correlation; Perfect correlation; Positive correlation
14. Correlation coefficient r between two variables is calculated as per the
(a)Shewharts Formula
(b)Demings Formula
(c) Pearsons Formula
(d)None of the above

15. Rinish drew the following scatter diagram to study correlation between Slag rate and
Fuel rate whose r is 0.083733.
Scatterplot of Slag Rate vs Fuel Rate
542.5

540.0

537.5
Slag Rate

535.0

532.5

530.0

527.5

525.0
370 380 390 400 41 0 420
Fuel Rate
 Which type of Scatter Diagram is this?
(a) Strong Positive Correlation
(b) Strong Negative Correlation
(c) ModeratePositive Correlation
(d) No Correlation

Answer Key:

1. d
2. c
3. b
4. a
5. b
6. b
7. a
8. c
9. b
10. b
11. b
12. b
13. c
14. c
15. c
 Control Charts
Introduction
Control chart is the basic tool of SPC (Statistical Process Control is an industry-standard
methodology for measuring and controlling quality during the manufacturing process.
Quality data in the form of Product orProcess measurements are obtained in real-time
during manufacturing.)
The control chart is a graph used to study how a process changes over time. Data are
plotted in time order.
A control chart always has a central line for the average, an upper line for the
upper control limit and a lower line for the lower control limit.
These lines are determined from historical data. By comparing current data to these lines,
you can draw conclusions about whether the process variation is consistent (in control) or is
unpredictable (out of control, affected by special causes of variation).
The control chart was invented by Walter A. Shewhart at Bell Labs in the 1920s while
seeking to improve the reliability of telephony transmission systems.
He analysed different processes and concluded that all manufacturing processes display
variation. He identified two components of variation:
A Steady component which appears to be inherent to the process and called as
Chance causes / Common causeand which cannot be economically removed until
basic changes are made to the process.
An Intermittent component, called as Assignable cause / Special cause, which can
be predicted and economically removed.

About the Inventor

Walter Andrew Shewhart was an American physicist, engineer and statistician, sometimes
known as the father of statistical quality control and also related to the Shewhart cycle.
One of W. Edwards Deming's teachers, he preached the importance of adapting
management processes to create profitable situations for both businesses and consumers,
promoting the utilization of his own creation - the SPC control chart.Many of the modern
ideas regarding quality owe their inspiration to Dr. Shewhart.
He also developed the Shewhart Cycle Learning and Improvement cycle, combining both
creative management thinking with statistical analysis. This cycle contains four continuous
steps: Plan, Do, Study and Act. These steps (commonly referred to as the PDSA cycle),
Shewhart believed, ultimately lead to total quality improvement. The cycle draws its
structure from the notion that constant evaluation of management practices- as well as the
willingness of management to adopt and disregard unsupported ideas- is keys to the
evolution of a successful enterprise.
 Common causes and Special causes variations
Even in the best designed production processes, certain amount of variability exists. Also
known as background noise, variability is a cumulative effect of many small and
unavoidable causes.
When variation is relatively small, it is considered acceptable. In SPC, this natural variability
is often called Chance causes or Common causes. A process that is operating with only
chance causes of variation (inherent part of process) is said to be in control.
Other kinds of variability may arise from three major sources incorrect operation,
incorrect design or defective inputs. Such variability is generally large and it usually
represents an unacceptable level of process performance. These are called Assignable
causes or Special causes. A process that is operating in the presence of assignable causes is
said to be out of control.
Purpose of SPC is to quickly detect occurrence of assignable / special causes or process
shifts so that investigation and corrective action may be undertaken before non-conformity
occurs. The control chart is an online process-monitoring technique widely used for this
purpose.

Common causes / Chance Assignable causes / Special

Comparison criteria
causes causes
Poor design, Poor Machine malfunction,
maintenance, Lack of clearly Operator error, Defective raw
Generic types of variations
defined SOPs, Vibration in material, Power surges,
industrial processes etc. Automation failure etc.

Nature / source System deficiencies Process failure

Scattered, unstable and

Process behavior Stable and predictable
unpredictable

Type of improvement actions Requires fundamental changes In-process corrections and ROI
required and ROI is low is high

Responsibility of action Management Operator / supervisor

Approx. % in total 85%-95% are of this type 5%-15% are of this type
 Control Charts: Control Limits
Control limits, also known as natural process limits, are horizontal lines drawn on a
statistical process control chart, usually at a distance of 3 standard deviations of the
plotted statistic from the statistic's mean.
The fundamental relationships in developing control charts are as follows:-
The center (or the central) line is the mean of the process.
The Upper control limit (UCL) is the mean plus 3 times standard deviations.
The Lower control limit (LCL) is the mean minus 3 times standard deviations.
So, the limits are: Mean
The reason for using 3 standard deviations is based on the assumption that the process
output follows a Normal Distribution.
If the process is in control, there is a very small probability of an observation falling outside
of the control limits. This probability increases as the process deviates from the in-Control
state.

Types of Control Charts

Control Charts

Attribute Control
Variable Control Charts
Charts

No. of measurements in Defects- Total Defectives-

each sub-group Defects in individual contain single /
/ all items multiple defects
More
One 4 to 8
than 8 Sub-group Sub-group Sub-group Sub-group
sample size sample size sample size sample size
Individual Average & Average & constant different constant different
and Range Standard
moving chart (X- Deviation Defects
range Defects per Proportion
Bar, R chart (X- per sub- No. of
chart (I- unit of
chart) Bar, S) group Defectives
MR) C Chart Defectives
U chart In P chart
P chart
 Individuals and Moving Range Chart

The individuals and moving range (I-MR) chart is one of the most commonly used control
charts for continuous data; it is applicable when one data point is collected at each point in
time.

The I-MR control chart is actually two charts used in tandem. Together they monitor the
process average as well as process variation. With x-axes that are time based, the chart
shows a history of the process.

The I chart is used to detect trends and shifts in the data, and thus in the process. The
individuals chart must have the data time-ordered; that is, the data must be entered in the
sequence in which it was generated. If data is not correctly tracked, trends or shifts in the
process may not be detected and may be incorrectly attributed to random (common cause)
variation. There are advanced control chart analysis techniques that forego the detection of
shifts and trends, but before applying these advanced methods, the data should be plotted
and analysed in time sequence.

The MR chart shows short-term variability in a process an assessment of the stability of

process variation. The moving range is the difference between consecutive observations. It
is expected that the difference between consecutive points is predictable. Points outside
the control limits indicate instability. If there are any out of control points, the special
causes must be eliminated.

The I-MR chart is best used when:

1. The natural subgroup size is unknown.
2. The integrity of the data prevents a clear picture of a logical subgroup.
3. The data is scarce (therefore subgrouping is not yet practical).
4. The natural subgroup needing to be assessed is not yet defined.

Xbar-Range Chart
Another commonly used control chart for continuous data is the X-bar and range (Xbar-R)
chart.
Like the I-MR chart, it is comprised of two charts used in tandem.
The Xbar-R chart is used when you can rationally collect measurements in subgroups of
between two and 10 observations. Each subgroup is a snapshot of the process at a given
point in time.
The charts x-axes are time based, so that the chart shows a history of the process. For this
reason, it is important that the data is in time-order.
The X-bar chart is used to evaluate consistency of process averages by plotting the average
of each subgroup. It is efficient at detecting relatively large shifts (typically plus or minus 1.5
or larger) in the process average.
The R chart, on the other hand, plots the ranges of each subgroup. The R chart is used to
evaluate the consistency of process variation. Look at the R chart first; if the R chart is out of
control, then the control limits on the Xbar chart are meaningless.
 Xbar-Sigma Chart
An Xbar-S chart is a combination of control charts used to monitor the process variability (as
the standard deviation) and average (as the mean) when measuring subgroups at regular
intervals from a process.
An Xbar-chart is a type of control chart used to monitor the process mean when measuring
subgroups at regular intervals from a process. An S-chart is a type of control chart used to
monitor the process variability (as the standard deviation) when measuring subgroups (n
5) at regular intervals from a process.
X-bar & Sigma charts are used when you can rationally collect measurements in groups
(subgroups).Each subgroup represents a "snapshot" of the process at a given point in time.
The x-axes are time based, so that the charts show a history of the process. For this reason,
you must have data that is time-ordered. If this is not the case, then trends or shifts in the
process may not be detected, but instead attributed to random (common cause) variation.
For subgroup sizes greater than ten, always use Xbar-S charts, since the range statistic is a
poor estimator of process sigma for large subgroups. In fact, the subgroup sigma is always a
better estimate of subgroup variation than subgroup range.The larger the subgroup, the
more sensitive the Xbar-S charts will be to shifts, providing a rational subgroup can be
formed.

c-Chart
Used when identifying the total count of defects per unit (c) that occurred during the
sampling period, the c-chart allows the practitioner to assign each sample more than one
defect. This chart is used when the number of samples of each sampling period is essentially
the same.

u-Chart
Similar to a c-chart, the u-chart is used to track the total count of defects per unit (u) that
occur during the sampling period and can track a sample having more than one defect.
However, unlike a c-chart, a u-chart is used when the number of samples of each sampling
period may vary significantly.

np-Chart
Use an np-chart when identifying the total count of defective units (the unit may have one
or more defects) with a constant sampling size.

p-Chart
Used when each unit can be considered pass or fail no matter the number of defects a p-
chart shows the number of tracked failures (np) divided by the number of total units (n).
 Benefits of Control Charts
When properly used, Control Charts can:
Be used by operator for on-going control of the process
Help the process perform consistently and predictably
Allow the process to achieve
Higher quality
Lower unit cost
Higher effective capability
Provide a common language for discussing the performance of the process
Distinguish special from common cause variation
Acts as a guide for deciding, whether to take local action or action on the system

Steps of making a Control Chart

Identifying parameter to be studied for variation

Data collection

Determine type of Control Chart to be used

Calculate Control Limits

Putting sample limits and data on chart

Find and address special causes

Recalculate Control Limits

Extend the control limits to on-going process

Identify the parameter to be studied for variation

Decide the process characteristics / parameters which you want to study for variation.
Example: Si content in Hot Metal, Hot Metal temperature, Coil thickness, Defects in each
coil etc.
Data collection
As per standards laid out by AIAG (Automotive Industry Action Group), minimum number
of data points required to analyse a process for variation is 100.
 The data related to process parameter is collected in the form of Sub-groups which
contain one or more samples.
Subgroup size- Size of the sub-group depends on the process under study. If variation in
the process is relatively small, then large sub-group size (sample size more than 8 in
each sub-group) needed to detect the process shift. If process has a large variation then
small sub-group sample size (sample size less than 8 in each sub-group) is sufficient to
detect the process shift.
Sub-group frequency- The sub-groups are taken sequentially in time, i.e. once in hour /
shift / day etc. Frequency of sub-group has to be decided in such a way that it can
reflect the potential opportunity for a process change.

Calculate the control statistics and sample control limits

The control statistics are to be calculated for the collected data set, such as:
Mean
Range
Standard deviation
Using these control characteristics and control chart formulae, calculate sample limits
such as:
Central line (CL)
Upper control limit (UCL)
Lower control limit (LCL)

1. Calculate average of each sub-group ( )

2. Calculate the range (R) of each sub-group, Range= Max. value in sub-group Min.
value in sub-group
3. Calculate grand average ( )
4. Calculate average of ranges ( )
5. Calculate Upper Control Limit, UCL= + A2
6. Calculate Central Line ( )
7. Calculate Lower Control Limit, LCL= - A2
[Where A2 is statistical constant taken from standard table]

Plotting sample limits and data on chart

Plot the calculated sample limits on chart, plot the sub-group data, connect the points and
visualize the patterns and trends.

Find and address the special causes

Look for out of control points, i.e. points outside the control limits, those variations are
due to special causes.
Conduct a process analysis to determine the root causes, with the help of process log.
Improve the process by taking suitable corrective actions on special causes.
 Sometimes it may be required to take some major steps, as well as to correct the special
causes.

Recalculate the control limits

While conducting initial process study, the control limits should be recalculated to
exclude the effects of special causes.
For this either we can eliminate the special cause from the process by taking actions or
exclude all sub-group data that are affected from special cause. Confirm all the data
points are fully within control limits, if not repeat the above process.

Extend the control limits to on-going process

When all data points are falling within control limits (no special cause in the process),
plot these calculated control limits on the blank chart and use them to detect the
occurrence of special cause.
Provide these blank charts to the Operator / Supervisor, who will record the online data
and plot them on these charts, and he can respond to signs out-of-control (special cause)
conditions.
Apply below rules of Special cause detection for Control chart interpretation-
1. One point outside the control limit
2. 2 out of 3 consecutive points more than 2 away from the mean on one side.
3. 4 out of 5 consecutive points more than 1 away from the mean on one side
4. 7 consecutive points on one side of mean
5. 6 consecutive points trending up or down
6. 14 consecutive points alternating up or down

If Rule no. 1 is violated, immediately analyze the cause of variation and if necessary stop
the process.
Violation of above Rule no. 2 to 6, indicates the presence of special cause in the
process, with the help of process log, identify the root cause/s, due to which the out-of-
control variation occurred in the process.
Take Corrective and Preventive actions to eliminate those special causes.

Steps to running Control Chart in Excel

1. Open a blank Excel worksheet. Type the name you want to use for your data in cell B1and
then enter the data for your chart in that column.
2. Select a blank cell below your data in column B. Click the Formula tab and then click the
small Arrow beside the AutoSum button. Select Average from the drop-down menu.
Highlight the cells containing the data and press Enter.
3. Select the blank cell beneath the cell used to calculate the data average. Click the
small Arrow beside the AutoSum button again. This time select More Functions.
 Click STDEV in the window that opens, highlight the cells containing the data and
press Enter.
4. Type Average in cell C1 and then click cell C2. Type = and then click the cell containing the
average. Insert a $ between the column letter and row number and then press Enter.
5. Select cell C2 and press Ctrl-C to copy it. Drag the cursor over the blank cells in column C
that have a value beside them and then press Ctrl-V to fill each cell with the average. When
you plot the control chart, having these cells filled with the same number gives you a
straight average line.
6. Type UCL in cell D1 to specify the Upper Control Limit. The UCL is calculated by adding the
average to 3 times the standard deviation.
7. Insert a $ between the cell and row for each cell and then press Enter.
8. Type LCL in cell E1 for the Lower Control Limit. The LCL subtracts 3 times the standard
deviation from the average.
9. Insert a $ between the cell and row for each cell and press Enter.
10. Copy the cells containing the UCL and LCL values and paste them into the cells below them.
This will give you straight lines for both the UCL and LCL values in the control chart.
11. Highlight the cells containing the Average, UCL and LCL data.
12. Click the Insert tab and click the Line Chart icon. From the drop-down menu, select the Line
with markers.

Click the Chart Title at the top of the line chart and replace it with Control Chart.

Questionnaire
1. Control Chart can be made for-
a. Variable Data
b. Attribute Data
c. a & b
d. None
2. Time order is not important for data to make control charts.
a. True
b. False
3. Control Chart was invented by-
a. JezyNeyman
b. Gertrude Mary Cox
c. Walter A. Shewhart
d. Walter Lewin
4. For Monitoring Yield strength of HR coil with subgroup size of five which type of control
charts should be used?
a. I-MR Chart
b. P Chart
c. Xbar-R Chart
 d. C Chart
5. The chart used to monitor variable data is-
a. I-MR Chart
b. P Chart
c. C Chart
d. All of the above
6. Central tendency of a process is monitored through-
a. Range Chart
b. Mean Chart
c. P Chart
d. C Chart
7. What is the term for the variation due to the inherent variability of an operation?
a. total variation
b. explainable variation
c. special causes of variation
d. common causes of variation
8. An Intermittent component, called as Assignable cause / Special cause, which can be
predicted and economically removed.
a. True
b. False
9. Shewhart cycle is commonly referred to as PSDA cycle.
a. True
b. False
10. In SPC, natural variability is often called-
a. Assignable Causes
b. Chance Causes
c. Both of the above
d. None of the above
11. 2 out of 3 points occur out of 2 sigma Lines is considered as abnormal.
a. True
b. False
12. The approx. % of Assignable causes is-
a. 85%-95%
b. 60%-70%
c. 45%-65%
d. 5%-15%
13. The nature of the depicted control chart is :
 a. Unstable, Conforming
b. Unstable, Non-conforming
c. Stable, Non-conforming
d. Stable, conforming
14. The nature of the depicted control chart is:

a. Stable and Conforming

b. Stable and non-conforming
c. Unstable and conforming
d. Unstable and non-conforming
15. The reason for using 3 standard deviations is based on the assumption that the process
output follows a Normal Distribution.
a. True
b. False
16. What % of values lies between +3 and -3 when the process is under normal distribution?
a. 99.67
b. 99.23
c. 99.73
d. 99.99
17. Read the following conversation between Ratnakar and Vinayak. Based on your
understanding, suggest the type of control chart Ratnakar should prefer. Ratnakar: Hey
Vinayak I want to monitor and control the number of defects in Pens in my unit. Vinayak: Oh
thats great Ratnakar! You may use Control Chart for the same. Ratnakar: Yes! But I am
unable to figure out which type of Control Chart should I use? Vinayak: Ok! Tell me is your
sub-group sample size constant? Ratnakar: Yes it is constant and I want to see the defects
per pen.
a. Defects per Unit i.e. C-Chart
b. Defects per sub-group i.e. U-Chart
c. X-MR Chart
d. X-Bar, S Chart
18. UmeshNaik wants to use control chart at filtration area to monitor moisture %. Per shift he
is getting 8 samples. Please suggest what type of control chart to be used by UmeshNaik.
a. I-MR Chart
b. Xbar-R Chart
c. P Chart
d. C Chart
19. I-MR is applicable when one data point is collected at each point in time.
a. True
b. False
20. Control Charts allow the process to achieve higher quality, higher unit cost, higher effective
capability.
a. True
b. False
21. One of the most important tools among the 7 QC tools is Control Chart. Control Chart helps
in identifying the Common Causes and Assignable Causes. Common Causes are those causes
which lie:
a. Between UCL and LCL
b. Outside UCL and LCL
c. On the mean
d. Outside UCL
22. While analyzing a control chart, an employee generally gets two types of causes namely
Common Causes & Assignable Causes. Choose the incorrect statement:
a. Common Causes are those causes which lie between UCL&LCL
b. Assignable Causes can be identified very easily
c. Assignable Causes are fewer in number
d. Common Causes are easy to solve

Answer key:
1. c 12. d
2. b 13. a
3. c 14. d
4. c 15. a
5. a 16. c
6. b 17. a
7. d 18. b
8. a 19. a
9. b 20. a
10. b 21. a
11. b 22. d
 Brainstorming
Introduction
Brainstorming is a group creativity technique by which efforts are made to find a
conclusion for a specific problem by gathering a list of ideas spontaneously
contributed by its members.
Every participant is encouraged to think aloud and suggest as many ideas as
possible, no matter seemingly how outlandish or bizarre. Analysis, discussion, or
criticism of the aired ideas is allowed only when the brainstorming session is over
and evaluation session begins.
The common principle of brainstorming is to set aside the restrictive thinking
processes so that many ideas can be generated.
The term was popularized byadvertising executive Alex Faickney Osborn in the
1953 book Applied Imagination. Alex F. Osborn began developing methods
for creative problem-solvingin 1939. He was frustrated by employees inability to
develop creative ideas individually for ad campaigns. In response, he began hosting
group-thinking sessions and discovered a significant improvement in the quality
and quantity of ideas produced by employees. Osborn outlined his method in the
1948 book Your Creative Power, "How to Organize a Squad to Create Ideas".
Brainstorming can be used to identify alternatives, obtain a complete list of items
and to solve problems.
There are a variety of brainstorming techniques.

About the inventor

Alex Faickney Osborn (May 24, 1888 May 5, 1966) was an advertising executive
and the author of the creativity technique named brainstorming.
In 1941 Alex Osborn found that conventional business meetings were inhibiting the
creation of new ideas and proposed some rules designed to help stimulate them.
He was looking for rules which would give people the freedom of mind and action
to spark off and reveal new ideas. To "think up" was originally the term he used to
describe the process he developed, and that in turn came to be known as
"brainstorming". He described brainstorming as "a conference technique by which
a group attempts to find a solution for a specific problem by amassing all the ideas
spontaneously by its members".
The rules he came up with are the following:
No criticism of ideas
Go for large quantities of ideas
Build on each others ideas
Encourage wild and exaggerated ideas
 He found that when these rules were followed, a lot more ideas were created and
that a greater quantity of original ideas gave rise to a greater quantity of useful
ideas. Quantity produced quality.
Using these new rules, people's natural inhibitions were reduced, inhibitions which
prevented them putting forward ideas which they felt might be considered "wrong"
or "stupid". Osborn also found that generating "silly" ideas could spark off very
useful ideas because they changed the way people thought.

Uses of Brainstorming

What to use for:

Identification of the problem(s)
Finding out the possible causes to the problem
Generating ideas for arriving at a solution
Predicting the possible resistance to the solution
Finding out the process to overcome the resistance

When to use:
Brainstorming can be used to develop the following
Advertising campaigns
Marketing strategy and methods
Research and Development procedures
Research techniques
Patents
Physical products
Written documents and articles
Services
Processes
Engineering components
Government policies
Consumer research
Factories
Management methods
Company structure and policy
Investment decisions
New industries
Better insurance policies
 How to use:

Focus on quantity If lots of ideas are generated it will be easy to produce a radical
and effective solution.
Reserve criticism Dont comment on any ideas. First accept all, at a large stage
judge.
Welcome unusual ideas to get a good and long list of ideas, unusual ideas are
welcomed.
Combine and improve ideas Good ideas may be combined to form a single better
idea.

Steps to Conduct Brainstorming session

Guidelines
Make sure that all team members fully understand the objective of the
brainstorming session.
Encourage active participation of all members.
Develop a high energy, enthusiastic climate.
Avoid discussing ideas as they are presented, including criticizing and
complimenting.
Encourage creative thinking, including far-out ideas.
Build and expand on the ideas of others.
Record all ideas exactly as presented on a flipchart, possibly using two recorders.
Avoid stopping when the ideas slow down. Rather, try to generate as long a list as
possible.
 Modes / Types of Brainstorming

Nominal Technique
Participants are asked to write their ideas anonymously. Then the facilitator
collects the ideas and the group votes on each idea. The vote can be as simple as a
show of hands in favour of a given idea. This process is called distillation.
After distillation, the top ranked ideas may be sent back to the group or to
subgroups for further brainstorming.
It is important that the facilitator be trained in this process before attempting to
facilitate this technique. The group should be primed and encouraged to embrace
the process.
This technique is commonly termed as silent brainstorming.

Group Passing Technique

Each person in a circular group writes down one idea, and then passes the piece of
paper to the next person, who adds some thoughts.
This continues until everybody gets his or her original piece of paper back. By this
time, it is likely that the group will have extensively elaborated on each idea.
The group may also create an "idea book" and post a distribution list or routing slip
to the front of the book. On the first page is a description of the problem. The first
person to receive the book lists his or her ideas and then routes the book to the
next person on the distribution list. The second person can log new ideas or add to
the ideas of the previous person. This continues until the distribution list is
exhausted.
A follow-up "read out" meeting is then held to discuss the ideas logged in the book.
This technique takes longer, but it allows individuals time to think deeply about the
problem.

Question brainstorming
This process involves brainstorming the questions, rather than trying to come up
with immediate answers and short term solutions.
Theoretically, this technique should not inhibit participation as there is no need to
provide solutions. The answers to the questions form the framework for
constructing future action plans. Once the list of questions is set, it may be
necessary to prioritize them to reach to the best solution in an orderly way.
Questorming is another term for this mode of inquiry.
Team Idea Mapping Method

This method of brainstorming works by the method of association. It may improve

collaboration and increase the quantity of ideas, and is designed so that all
attendees participate and no ideas are rejected.
The process begins with a well-defined topic. Each participant brainstorms
individually, then all the ideas are merged onto one large idea map.
During this consolidation phase, participants may discover a common
understanding of the issues as they share the meanings behind their ideas. During
this sharing, new ideas may arise by the association, and they are added to the map
as well.
Once all the ideas are captured, the group can prioritize and/or take action.

Free Writing

When you free write you write whatever comes into your mind. On finish, read
back over the text and decide the solution.

Individual Brainstorming

Individual brainstorming is the use of brainstorming in solitary situations.

It typically includes such techniques as free writing, free speaking, word
association, and drawing a mind map, which is a visual note taking technique in
which people diagram their thoughts.
Individual brainstorming is a useful method in creative writing and has been shown
to be superior to traditional group brainstorming.

Conventional Brainstorming

Free flowing idea generation

Conducted on definition of the problem
Continues till all thoughts are exhaustively captured
No in process evaluation
Segregate on themes later

Affinity Analysis

Everyone sticks their post it notes on the wall near a similar idea; then clusters of
post it notes representing similar ideas are created
Ideas reviewed by clusters, then variants are clubbed under one head to develop
solutions.
 Idea sheet (Brainwriting)

Writing on slips, post its for issues / KPIs

Avoids dominating effect of individuals
Avoids effects of recency factors during discussions
Takes care of shyness on individuals

KPI based brainstorming

1. Issue / KPI based brainstorming:

Ideas generated along pre-decided KPI branch or issues.
Bucketing / Categorisation done along with.
2. Reverse brainstorming:
Ideas around how to make the issue / KPI worse
After evaluation, focus on how to make it better
This technique can be used as a final evaluation of a short-list of previously team-
generated ideas in the conventional brainstorming session.

Directed Brainstorming

1. Osborns / Scamper Method:

A series of idea provoking ideas like Substitute?, Combine?, Adapt?, Modify?, Put
to other uses?, Eliminate?, Reverse or rearrange?
2. Idea Box:
Specify opportunity and parameters thereof.
Then identify possible variations in them, different combinations to arrive at the
solution(s).

Advantages and Disadvantages of Brainstorming

Advantages Disadvantages
Requires an experienced and sensitive
Many ideas can be generated in a short
facilitator who understands the social
time.
psychology of small groups.
Requires a dedication to quantity rather
Requires few material resources.
than quality.
The results can be used immediately or Shy people can have difficulties in
for possible use in other projects. participating.
May not be appropriate for some
Is a democratic way of generating ideas.
business or international cultures.
The concept of brainstorming is easy to
understand.
 Example from the plant
 Arrow Diagram
Introduction
Arrow Diagram is a network diagramming technique in which activities are represented
by arrows.
This is also termed as activity network diagram, activity chart, node diagram, CPM
(critical path method) chart.
The arrow diagram shows the required order of tasks in a project or process, the best
schedule for the entire project, and potential scheduling and resource problems and their
solutions. The arrow diagram lets you calculate the critical path of the project. This is
the flow of critical steps where delays will affect the timing of the entire project and
where addition of resources can speed up the project.
Precedence relationships between activities are represented by circles (node) connected
by one or more arrows. The length of the arrow represents the duration of the relevant
activity.Sometimes a "dummy task" is added, to represent a dependency between tasks,
which does not represent any actual activity.

Uses and Applicability of Arrow Diagram

When to use:

To understand and manage a complex project or task.

To understand and manage a project that is of major importance to the organization,
where the consequences of late completion are severe.
To understand and manage a project in which multiple activities must take place and be
managed simultaneously.
To explain the project status to others.
Implement plans for new product development and its follow up.
Develop product improvement plans and follow up activities.
Establish daily plans for experimental trials and follow up activities.
Establish daily plans for increases in production and their follow up activities.
Synchronize the preceding plans for QC activities.
Develop plans for a facility move and for monitoring follow up.
Implement a periodic facility maintenance plan and its follow up.
Analyse a manufacturing process and draw up plans for improved efficiency.
Plan and follow up QC inspections and diagnostic tests.
Plan and follow up QC conferences and QC circle conferences.

Purpose and Applicability:

It leads to discovery of possible improvements.

It makes easy to monitor progress of work.
 Deals promptly with changes to plan.
Improves communication among team.
Promotes understanding and agreement among group.

Symbols used in Arrow Diagram

Event / Node / Junction points:

A node is a specific, definable achievement in the project.
1 Corresponds to event in the diagram & number.
It has zero duration and consumes nil resources.

Activity A Job / Task / Operation: Represents that activity required time.

Dummies: Represents only a relationship between

Dummy Activity
operations, with no time required

Steps in Constructing Arrow Diagram

Indicate the order of operation. Start from left, considering what

precedes, what follows and what is in parallel

Indicate the Junction Points / events

Draw lines and arrows. Solid lines for operations essential to plans,
dotted lines for dummy operations.

Insert Junction Point number

Indicate operation names

Indicate days required for each operation

Shows the Critical Path (path taking the most days) with a bold line
and arrow
 Example from the plant

Questionnaire
1. Arrow Diagram is also known as
a. CPM Chart
b. Node Diagram
c. Both of the above
d. None of the above
2. Dummy task represent actual activity.
a. True
b. False
3. Match the following:

a. i 2, ii 3, iii 1
b. i 1, ii 3, iii 2
c. i 2, ii 1, iii 3
d. i 1, ii 2, iii - 3
4. The arrow diagram lets you calculate the critical path of the project.
a. True
b. False
5. Arrow Diagram makes difficult to monitor progress of work.
a. True
b. False
6. Which statement/s is/are true about Brainstorming
a. Means of generating ideas
b. A tool which can be used to identify alternatives
c. A democratic way of generating ideas
d. All of the above
7. Which of the statement/s is/are wrong?Brainstorming is used for
a. Identifying the problem
b. Finding an immediate solution
c. Finding out the process to overcome resistance
d. All of the above
8. Which of the following is correct regarding Brainstorming?
a. Focus on quantity
b. Reserve Criticism
c. Welcome unusual ideas
d. All of the above
9. Brainstorming term was popularised by
a. William Playfair
b. Walter A Shewhart
c. Alex F. Osborn
d. JiroKawakita
10. Which of the below is/are not Brainstorming technique/s?
a. Free writing
b. Nominal Group technique
c. Group passing technique
d. Linear technique
11. Reverse Brainstorming is
a. An approach from bottom to top across an hierarchy
b. To do brainstorming after an idea fails
c. Generating ideas how to make an issue worse
d. None of the above
12. Moderator/Facilitator presence is required in Affinity analysis.
a. True
b. False
13. Brainstorming is an useful tool in problem solving because
a. It is applicable to all types of business
b. Requires few material resources
c. Many ideas can be generated in short time
d. b & c
14. Brainstorming requires experienced facilitator.
a. True
b. False
15. Physical presence of participant is required in Brainwriting technique.
a. True
b. False
16. Anonymity of participant is seen in
a. Group passing technique
b. Free writing
c. Nominal group technique
d. Individual Brainstorming technique
17. Who can participate in Brainstorming?
a. All persons in the team relevant to the issue
b. Only shop floor employees
c. Supervising employees
d. Only area in-charge of all disciplines

18. The role/s of a Moderator in Brainstorming is/are

a. Briefing about the Topic/issue
b. Creating a lively and informal atmosphere
c. Training
d. a&b
19. KPI based brainstorming is used when idea not known.
a. True
b. False
20. Sticky notes which type of Brainstorming?
a. Nominal Group Technique
b. Group passing Technique
c. Affinity Analysis
d. Reverse Osborne
21. Which type of brainstorming is beneficial when peer leaders have exaggerated effect
over group decisions and often tend to dominate a discussion? It is a constructive
way of problem solving as it involves a process of distillation of ideas by voting and is
commonly termed as silent brainstorming.
a. Nominal Group Technique
b. Question Brainstorming
 c. Team Idea Mapping
d. Group Passing Technique
Answer Key:

1. c 12. b
2. b 13. d
3. c 14. a
4. a 15. b
5. b 16. c
6. d 17. a
7. b 18. d
8. d 19. b
9. c 20. c
10. d 21. a
11. c
 Affinity Diagram
Introduction
Affinity diagram is a tool that gathers large amounts of language data (ideas, opinions,
issues) and organizes them into groupings based on their natural relationships.
The Affinity process is often used to group ideas generated by Brainstorming.
It is also frequently used in contextual inquiryas a way to organize notes and insights
from field interviews. It can also be used for organizing other freeform comments, such
as open-ended survey responses, support call logs, or other qualitative data.
It is one of the Seven Management and Planning Tools.
This method taps a teams creativity and intuition.
The term affinity diagram was devised by JiroKawakita in the 1960s and is sometimes
referred to as the KJ Method.

About the inventor

JiroKawakita was a pioneer in participation of remote Nepalese villagers in researching
their problems, resulting in practical benefits of portable water supplies and rapid rope-
way transport across mountain gorges.
He was awarded the Ramon Magsaysay Award in 1984.

Uses
Exploring into unknown areas.
When you are confronted with many facts or ideas in apparent chaos.
When issues seem too large and complex to grasp.
When group consensus is necessary.

Purpose and Applicability of the tool

For gathering large amount of disorganized, confused and intertwined verbal data.
For organizing the verbal data into groups based on natural relationship.
It discovers the previously unseen connections between various ideas or information.
Encourages new pattern of thinking.
 Steps to construct Affinity Diagram

Define the issue:Define the issue for discussion between relevant

parties
What are the difficulties / opportunities?
What are the critical points to overcome?

Brainstorming or Brainwriting:
Organize the brainstorming session on the issue, collecting free
opinions from all members.

Put them down on Post-its:

Use one Post-it per fact or idea
The desirable total no. of Post-its is about 20. Give 3-4 per
member in a 6 member session.

Check the understanding of the members

Group ideas together by affinity:

Look for similar ideas and group them together
The maximum number of Post-its per group is about 5
You can have ones that do not belong to any group (loners)

Choose a title for each group:

Write the title on the Post-its above each group
Encircle the Post-its for loners

Further groupings

Example from the plant

 Tree Diagram
Introduction

It is a graphic tool which starts with a central item and then branches into two or more and
keeps branching until the line of inquiry begun with central item is exhausted. It looks like
a tree, with a trunk and multiple branches.
It is also known as systematic diagram, tree analysis, analytical tree, or hierarchy diagram.
It is used to break down broad categories into finer and finer levels of detail. Developing
the tree diagram helps you move your thinking step by step from generalities to specifics.
The purpose of the tree diagram is to explore ways and means to achieve an objective,
develop a list of alternate means to reach the desired situation in a sequential order and to
present them in a visual form.
A Tree Diagram can be used to break down a project into tasks that can then be prioritized
or used to compile a schedule of deadlines for the project.
Tree diagrams can also be helpful in analyzing seemingly simple projects that have not
been smoothly implemented in the past. By breaking the job down into its components, it
becomes clear where the problematic step was omitted or mishandled.

Uses

When planning to define the necessary activities.

When understanding a construction of a product.
When analysing a process splitting it into sub-processes.
When probing for the root cause of a problem.
When evaluating implementation issues for several potential solutions.
As a communication tool, to explain details to others.
 How to create a Tree Diagram

Title Procedure Guidelines

Defining the subject in a clear It will not be clear, at the outset,

Define the and simple statement. what the final shape will look like so
subject Reduce the statement down to a use card on a flipchart or board
short verb - object form. that can be rearranged.

Consistently use simple questions

Identify the next level down
such as:
components for example ideas
What must be done to achieve
Identify subject on how to achieve an objective,
this?
components major causes of a problem, key
What are the physical parts of
components of a product or sub-
this?
processes of a process.
Why does this happen?

Consider each successive layer as

Clarify the components when the
parent and child relationships.
level has been completed.
Ensure that each child has a
Clarify Ensure everyone understands
direct relationship to its parent. If
components each component.
not rephrase the card.
Reduce each statement down to
Each parent will typically have 2 to
a simple verb-object form.
4 children.

Starting from the left hand side

of the Tree Diagram, look for
Look for gaps gaps in the logic. Does each Ask the question do the children
top down parent relate down to its children represent their parent well?
i.e. are they at the right level. If
not, rearrange the cards.

Ask the questions:

Starting from the lowest level,
If these are done, will the next
Look for gaps challenge each level to ensure
level up be achieved?
bottom up that there are no gaps,
Are these actions really
duplication or redundancy.
necessary?
 Example

One example of Tree Diagram is KPI Drill Down.

What is Key Performance Indicator (KPI)?

KPIs or Key Performance Indicators are set of quantifiable measuresthat an industry, a
company, a department, a group or an individual uses to gauge or measure performanceor
improving compliance to strategic and operational goals.

Scope of KPI Drill Down

The scope of any Quality Management is P, Q, C, D, S, M,E.
Hence the KPI Drill Down should be done for all of them.

Description Examples of this type of KPI that can be benchmarked

Productivity Throughput, Yield (%), Tap-to-tap time (Mins), Casting Speed (M/min) etc.
Quality Skin Panel Strike Rate (%), RDI of Sinter, HM Silicon, Yield (%)
BF Coke Rate (Kg/t), Solid Fuel Rate of Sinter Plant (Kg/t), Total Charge
Cost
(Kg/tcs)
Delivery Logistics Cost (Rs/t), Turnaround Time (Hrs)
Safety LTIFR, Million Injury Free Man Days
Morale Employee Satisfaction Index
Environment Specific Energy Consumption, Emission Parameters
Each of these heads of P,Q,C,D,S,M,E may have both Strategic and operational KPIs.
 More about KPIs
KPIs are useful because

KPIs can be applied in Business Analysisto gauge trends / advise strategic direction.
KPIs can be broken down and set as targets for achievement by departments, groups /
individuals.
KPIs help create visualisation of the Business / Operating Process by converting business
objectives into specific Strategies and then into specific & measurable Means. Means are
generally KPIs that can be controlled and acted on.
Then translating them into ideas / project.
KPIs can be tracked & reviewedat regular intervals for non-achievement / issues /
interventions.

KPIs should be

Specific, Measurableclear and focused, no ambiguity, can be quantified/measured and

may be either quantitative or qualitative
Relevantand consistent with the specific companies vision, strategy and objectives,
focusedon outcomes
Understood, Agreedindividuals, groups know how their activities contribute to overall
goals, all contributors agree / share responsibility
Governedaccountability and responsibility is defined and understood
Reportedregular reports are made available to all stakeholders and contributors
Assessedregular assessment to ensure that they remain relevant

KPI Drill Down Generic Format

 KPI Drill Down (Objective Strategy Means)

Steps of KPI Drill Down

Esatblish KPI Establish the Objective Strategy Means relationship

Realtions and Establish relationship between KPIs
make Tree Tie them up
Diagram Drill down up to controllable and measurable KPI level

Validate From all Angles -

Validate the Should be tactically connected
Tree Should be mutually exclusive
Should be cumulatively exhaustive

Map the following:

Map required Current Value
values Benchmark Value
Target
 What is done after KPI Drill Down?
After completing the KPI Tree and populating the numbers (Current Value, Benchmark,
Target Value) proceed to do the following:
Analyse Performance Gaps / potential
Carry out brainstorming sessions on the KPIs that you want to improve
Map improvement Projects against each KPI

Example from the plant

Planned shut
Billet Caster Example down
Equipment
Availability
breakdown

Set up time

Heats per Waiting for steel

day

Throughput Yield Speed Speed

Heat
Quality Product Mix
weight
 Relations Diagram
Introduction
Also called interrelationship diagram or digraph, network diagram.
The Interrelationship diagram shows cause-and-effect relationships.
Used to analyze natural links between different aspects of a complex situation and
guide team members to think in multiple direction.
The output of the tool is a list of root causes for the problem with some indication of
their relative importance.

Uses of Relations Diagram

When trying to understand the links between ideas or cause-and-effect.
When a complex issue is being analyzed for causes.
When a complex solution is being implemented.
After generating an affinity diagram, causeandeffect diagram or tree diagram, for
explore the relations of ideas more comprehensively.
It is also useful in building consensus within groups.

Procedure

Write a statement defining the issue the relation diagram will explore

Brainstorm ideas about the issue and write them on cards

Place one idea at a time on the work surface and ask is this idea related to any
others? place ideas that are related near the first. Leave space between cards to
allow for drawing arrows later. Repeat until all cards are on the work surface.

For each idea ask,Does this idea cause or influence any other idea? Draw arrows
from each idea to the ones it causes or influences. Repeat the question for every idea.
 Structure of Relation Diagram
The structure of relations diagram is not very rigid.
It is quite flexible. Only thing fixed about the diagram is
aboldborderedrectangle/roundedrectangleinwhich the effect iswritten.
Thecausesareenteredinlight bordered
rectangles/roundedrectanglesandlinesaredrawntoshowrelationbetweentherectangles.
Thelineshavearrowsatoneendshowingwhichisthecauseandwhich istheeffect.
Thearrowalwaysleadingfromthecausetotheeffect.
The most common shape the diagram takes has the effect at the centre, with
immediate causes surrounding it and secondary and tertiary causes as outer layers.
The most common structure of the relations diagram is as seen in diagram 1, where the
effect is placed in the centre and the causes surround it, is called focused counterpoint
type.
When the interrelations between the immediate causes are more widespread, it may
be difficult to connect the rectangles located on either side of the effect. In such cases
the effect may be placed on the top or the left hand side of the diagram and causes
below or to the right of the effect.
Arrows in such a diagram is in only one direction bottom to top or left to right.
Diagram 2 shows a unidirectional type of structure.
These two diagrams have shown how the structures of relations diagram are extremely
flexible.
The shape depends on the nature and extent on interrelations between various causes.
The team is free to arrange the rectangles with causes in any convenient shape. If
needed, the shape is recast with rearrangement of the causes for ease of connecting
the rectangles.
 How to analyze Relations Diagram
Count the arrows in and out for each idea. Write the counts at the bottom of each box.
Note which ideas have more outgoing (from) arrows. These are root causes.
Note which ideas have primarily incoming (to) arrows. These are final effects that also
may be critical to address.
Be sure to check whether ideas with fewer arrows also are key ideas. The number of
arrows is only an indicator, not an absolute rule.
A cause with multiple arrows flowing into it indicates a bottleneck. This can be difficult
to eliminate, due to multiple contributory causes.
A key cause is one which is selected to be addressed by future action. Key causes may
be highlighted in some way, such as double circling etc.
 Example from the plant

Relationships among causes of low customer satisfaction

Analysis of the above Relations Diagram

Type of Relations Diagram Unidirectional Structure Type

Root Cause Unskilled employees

Bottleneck Low Quality Product

A Key Cause Poor Support

 Questionnaire
1. Affinity diagram is a tool that gathers large amounts of language data (ideas,
opinions, issues) and organizes them into groupings based on their natural
relationships.
a. True
b. False
2. When do we use Affinity Diagram?
a. While unifying thinking of diverse group of people on a single problem
b. To show the flow of the process
c. When group consensus is necessary
d. None of these
3. The term Affinity Diagram was devised by
a. Kaoru Ishikawa
b. JiroKawakita
c. Walter A. Shewhart
d. None of these
4. JiroKawakita was awarded the ________________ in 1984.
a. Ramon Magsaysay Award
b. Malcolm Baldrige National Quality Award
c. Philippine Quality Award
d. None of these
5. Affinity Diagram is often referred to as
a. Network Diagram
b. Ishikawa Diagram
c. KJ Method
d. None of these
6. Affinity Diagram encourages new pattern of thinking and taps a teams creativity.
a. True
b. False
7. While constructing Affinity Diagram, ideas generated in Brainstorming session
are put down on Postits. One Postit is used per fact or idea. What is the
desirable total number of Postits?
a. 10
b. 15
c. 25
d. 20
8. Tree Diagram is also known as
a. Systematic Diagram
b. Hierarchy Diagram
c. Both of the above
d. None of these
9. Developing the tree diagram helps you move your thinking step by step from
specifics to generalities.
a. True
b. False
10. When do we use Tree Diagram?
a. To find out the possible causes of the problem(s)
b. When planning to define the necessary activities
c. When checking a solution to see the improvement
d. None of these
11. One example of Tree Diagram is KPI Drill Down.
a. True
b. False
12. KPI is
a. Key Profit Indicator
b. Key Performance Indicator
c. Both of the above
d. None of the above
13. Match the following:

a. i 1, ii 3, iii 2, iv 4
b. i 3, ii 2, iii 1, iv 4
c. i 4, ii 3, iii 2, iv 1
d. i 1, ii 2, iii 3, iv - 4
14. Means are generally KPIs that cannot be controlled and acted on.
a. True
b. False
15. KPIs are useful because KPIs can be applied in Business Analysisto gauge trends /
advise strategic direction.
a. True
b. False
16. KPIs should be
a. Specific, Measurable
b. Understood, Agreed
c. Both of the above
d. None of the above
17. What is done after KPI Drill Down?
a. Carry out brainstorming sessions on the KPIs that you want to improve
b. Map improvement Projects against each KPI

c. Both of the above

d. None of the above
18. Relations Diagram is also called
a. Interrelationship diagram or diagraph
b. Network diagram
c. Both of the above
d. None of these
19. Relations Diagram is used to guide team members to think in one direction.
a. True
b. False
20. Relations diagram can explore the ideas more comprehensively after generating -
a. Affinity Diagram
b. Cause and Effect / Tree Diagram
c. Histogram
d. Both a & b
21. The arrow in the Relations Diagram always lead from
a. Cause to effect
b. Effect to cause
c. Its bi-directional
d. None of these
22. _________________ is the type of Relation Diagram where the effect is placed at
the centre and causes around it.
a. Unidirectional type
b. Focused counterpoint type
c. Randomly oriented type
d. None of these
23. When should one prefer the Unidirectional type Relation Diagram?
a. When there is narrow connection between the causes
b. When there is not much interrelation between the causes and it is easy to
connect them
c. When the interrelation between the immediate causes is widespread and it
becomes difficult to connect them on either side of effect
d. None of these
24. The structure of Relations Diagram is very rigid.
a. True
b. False
 25. In Relations Diagram, a cause with multiple arrows flowing into it indicates a
bottleneck.
a. True
b. False

Answer Key:

1. a 10. b 19. b
2. c 11. a 20. d
3. b 12. b 21. a
4. a 13. c 22. b
5. c 14. b 23. c
6. a 15. a 24. b
7. d 16. c 25. a
8. c 17. c
9. b 18. c
 Matrix Diagram
Introduction
A Matrix Diagram (MD) is a tool that allows a team to identify the presence and
strengths of relationships between two or more lists of items. It provides a compact
way of representing many-to-many relationships of varying strengths.
Thematrixdiagramdepictstherelationshipbetweentwo,threeorfourgroupsofinformation.I
tenlightensinformationabouttherelationship,suchasitsstrength,therolesplayedbyvariousi
ndividualsormeasurements.
TheMatrixDiagramisasimpletoolthatallowsrelativelycomplexsituationstobeanalysedinasi
mplestraightforwardway.
The contents of the lists being related in a matrix diagram can be: Data, Information,
Functions, Concepts, Actions, People, Materials, Equipment etc.

Shapes of Matrix

Matrix Type Group Mapping Relation

L shaped 2 groups A B (or A A)
T shaped 3 groups A C but not B C
Y shaped 3 groups ABCA
C shaped 3 groups All three simultaneously (3D)
X shaped 4 groups A B C D A but not A C or B D
Roof shaped 1 group A A when also A B in L or T
 Steps of Construction

Identify the purpose for drawing matrix diagram

Select the suitable matrix type

Identify the factors / lists for plotting in matrix diagram

Score or rate the relationships between factors under matrix

diagram

Interpret the matrix diagram and take suitable actions

S. M. A. R. T. Matrix Diagram
S. M. A. R. T. Plan Matrix:
A SMART Matrix is a communication and planning tool used to identify the specifics of
actions or tasks.
Technique for structuring the task details when planning the implementation of a
project.
For each implementable task SMART stands for:
Specific (activity or task)
Measurable (outcome or process)
Assignment (who will perform)
Resources (what is needed)
Time (anticipated duration)
Predecessors (what must be done first)
It is an L-shaped matrix designed to capture the key points of teams project objectives.
It provides a process to review how actions are being implemented around various
attributes.
 Uses:

To analyze planned activities are on track.

To understand the resource requirement for a plan.
To understand sequence and relation of various tasks.

Steps:

Consensus among
Define S. M. A. R. T.
all parties in matrix

Example:

Correlation Matrix Diagram

A matrix that depicts the gauge of relationship between two sets of parameters plotted.
The correlation matrix, often referred to as the Roof, is used to aid in developing
relationships between customer requirements and product requirements and identifies
where these units might work together.

Uses:
Shows the relationship between one list of variables and another. Relationships are
usually based on experience.
Such a matrix forms the body of a house of quality.
 Example:

Construct Correlation Matrix relating problem solving tools and steps

Flow Check- Control
Graphs Histogram Pareto C&E Stratification Scatter
Chart sheets Chart
Identification of
1
problem
Definition of
2
problem
Recording of
3
facts
Detecting
4 causes of
problems
Developing
5 solutions to
problems
6 Implementation
Evaluation of
7
results
Standardization
8
of process

Frequently

Used
Rarely Used

Applications
A matrix diagram can be used where we wish to identify and assess the strength of
relationships between two or more lists of items.
It is particularly useful for examining the relationships between:
A set of vague and un-measurable items with a set of precise and measurable items
(such as relating customer requirements to technical requirements).
Two sets of items that are physically different (such as design solutions to a set of
technical requirements).
Establish strategies to find out market view on product mix.
Analyze non-conformance in manufacturing process.
Show the relations between required quality level and control functions established.
Prioritize among the many tasks given by comparison.
 Matrix Data Analysis
Introduction
When comparing large set of items, the complexity of the situation can make it difficult
to determine how different factors relate to one another. In particular, it can be useful
to find groups of items that behave in similar ways.
In Matrix Data Analysis, the data is arranged for easy visualization and comparisons.
Relationships between data variables shown on both axes are identified using symbols
for importance or numerical values for evaluations.
It is one of the second seven tools according to Mizuno, although others replace it with
the Prioritization Matrix. It is often abbreviated as MDAC.
Applications:
It is used to identify the clusters of related items within a large group.
To identify the strength of relationships among variables.
To perform market research.

Step-by-step procedure
Step 1 The team first determines what characteristics need to be analyzed. This
process may be influenced by some product or service concern, loss of market share or
unfavourable benchmarking results.
Step 2 A research and data collection process is performed to acquire the data to be
charted on matrix data analysis chart. Data may come from surveys, interviews, focus
groups, historical records, benchmarks or published sources. Ensure that appropriate
scales are used to position or calculate data.
Step 3 Plot the comparison data on the chart. Care must be taken to ensure unbiased
positioning of the organizations data.
Step 4 The completed chart is discussed all relationships are reviewed and a summary
statement is prepared. Finally, the chart is dated and presented to the process owners.

Typical Uses
The Matrix Data Analysis Chart (or MDAC) helps classify items by identifying two major
characteristics common to all items and then plotting each item as a point on a standard
X-Y chart. This makes it easier to see how the individual items relate both to the
characteristics and to one another, thus:
Measured Characteristic Characteristic
item A B
Item 1 10 8
Item 2 5 -4
Item 3 -8 -5
Item 4 -5 3
Item 5 7 -5
Item 6 8 9
 Example

Typically Used By
Research / statistics
Creativity / innovation
Engineering
Project Management
Manufacturing
Marketing / sales
Administration / documentation
Servicing / support
Customer / quality metrics
 Process Decision Program Chart (PDPC)
Introduction
The Process Decision Program Chart (often called as just PDPC) is a simple tool, derived
from the Japanese name.
Also called as one of the Advanced Quality Tools or Management Tools.
PDPC is a method to overcome problems when a goal to be achieved is not familiar.
The Process Decision Program Chart (PDPC) systematically identifies what might go
wrong in a plan under development.
With the help of PDPC we can map out all the conceivable events or contingencies that
can occur in the implementation stage and find out feasible countermeasures to
overcome.
This tool helps one to prepare a contingency plan to achieve the objective if adverse
events occur.
Process diagrams and planning tree diagrams are extended by a couple of levels when
the PDPC is applied to the bottom level tasks on those diagrams.

Purpose of PDPC
To prepare for abnormal occurrences with low probability which may otherwise be
overlooked.
To present the occurrences as well as the countermeasures to guard against such
occurrences in the form of a visual chart.
The tool forces one to think all the possible obstacles in the smooth progress of a
process.
Find ways and means to surmount obstacles to ensure successful and timely completion
of the process or the project.
By using PDPC, one can either revise the plan to avoid the problems or be ready with
the best response when a problem occurs.
For producing the desired result from many possible outcomes.
Used for getting activities back on track.
Steers events in required direction if unanticipated problems occur.
Finds feasible countermeasures to overcome problems.
 When to use PDPC
Before implementing a plan, especially when the plan is large and complex.
When the plan must be completed on schedule.
When the price of failure is high or the impact of any abnormal occurrence is more.
Used to plan contingencies.

Steps in Construction of PDPC

First level:Indicate the purpose of the plan

Second level: Mention the activities to be undertaken. These are main activities

Third level: Mention the steps in the above activities. These are broadly defined
tasks to accomplish the main activities.

Fourth level:Indicate the contingencies that can occur in the implementation

stage.

Fifth level:Mention the feasible countermeasures (contingency plan) to overcome

above contingencies.

Construction of Process Decision Program Chart (PDPC)

Counter
Possible measure 1
Problem 1
Activity 1
Step 1
Activity 1

Counter
Possible measure 2
Problem 2

Activity 1
Plan
Step 2
(Objective) Counter
measure 1

Possible
Activity 2 Problem 1 Counter
measure 1
Step 1
Possible
Problem 1 Counter
measure 1
 Procedure for construction of PDPC
1. Develop a Tree Diagram of the proposed plan. This should be a high-level diagram
showing the objective, a second level of main activities and a third level of broadly
defined tasks to accomplish the main activities.
2. For each task on the third level, brainstorm what could go wrong.
3. Review all the potential problems and eliminate any that are improbable or whose
consequences would be insignificant. Show the problems as a fourth level linked to the
tasks.
4. For each potential problem, brainstorm possible countermeasures. These might be
actions or changes to the plan that would prevent the problem, or actions that would
remedy it once it occurred. Show the countermeasures as a fifth level.
5. Decide how practical each countermeasure is. Use criteria such as cost, time required,
ease of implementation and effectiveness.

Some Questions that can be used to identify problems

What inputs must be present? Are there any undesirable inputs linked to the good
inputs?
What outputs are we expecting? Might others happen as well?
What is this supposed to do? Is there something else that it might do instead or in
addition?
Does this depend on actions, conditions or events? Are these controllable or
uncontrollable?
What cannot be changed or is inflexible?
Have we allowed any margin for error?
What assumptions are we making that could turn out to be wrong?
What has been our experience in similar situations in the past?
How is this different from before?
If we wanted this to fail, how could we accomplish that?
 Example from the plant
Installation of Combined Stirring and Oxygen Blowing Process at SMS 1

Plan Activity Step Risk Countermeasure

(Task)
Plan to shift
away from ARS
Space area
constraint near
Con-2
Plan to locate
Seconadry Steel near LHF
Installation of Installation
making unit at
CASOB near BOF-2
SMS 1 Possibility of
Plan to shift
heavy fume
away from ARS
generation near
area
ARS

Applications of PDPC
Used to prevent problems by identifying opportunities for error and devising measures
to avoid failure.
Used during the implementation of solutions for predicting resistance and for planning
measures to overcome the resistance.

Advantages of PDPC
Facilitates forecasting
Enables problem to pinpointed
Illustrates how events will be directed to successful conclusion.
Enables those involved to understand decision-makers intensions
Fosters co-operation and communication in group
Easily modified and easily understood

Disadvantage of PDPC
Only identifies and addresses transparent problems.
 Questionnaire
1. The Matrix Diagram is a simple tool that allows relatively complex situations to be
analysed in a simple straightforward way.
a. True
b. False
2. A Matrix Diagram (MD) is a tool that allows a team to identify the presence and
strengths of relationships between two or more lists of items. Identify the matrix
diagram shown below

a. T shaped
b. Y shaped
c. C shaped
d. Roof shaped
3. Match the following:

a. i 1, ii 3, iii 4, iv 2
b. i 4, ii 1, iii 2, iv 3
c. i 2, ii 3, iii 1, iv 4
d. None of these
4. SMART Matrix is a communication and planning tool used to identify the specifics of
actions or tasks.For each implementable task SMART stands for: Specific,
_____________ , Assignment, Resources, Time.
a. Matrix
b. Management
c. Measurement
d. None of these
5. SMART Matrix is a T- shaped matrix designed to capture the key points of teams
project objectives.
a. True
b. False
6. The correlation matrix is often referred to as
a. X shaped
b. Y shaped
c. Roof shaped
d. None of these
7. One of the applications of Matrix Diagram is to establish strategies to find out market
view on product mix.
a. True
b. False
8. Full form of MDAC is
a. Matrix Diagram Analysis Chart
b. Matrix Data Analysis Chart
c. Matrix Data Analog Chart
d. None of these
9. Using MDAC, strength of relationships among variables cannot be identified.
a. True
b. False
10. The data, to be charted on MDAC, may come from historical records.
a. True
b. False
11. Full form of PDPC
a. Provisional Development Plan Consent
b. Phase Dynamical Probability Change
c. Process Decision Program Chart
d. None of these
12. Process diagrams and planning ______________ are extended by a couple of levels
when the PDPC is applied to the bottom level tasks on those diagrams.
a. Relations Diagram
b. Matrix Diagram
c. Affinity Diagram
d. Tree Diagram
13. PDPC is used to plan contingencies.
a. True
b. False
14. What is the sequence of making PDPC?
a. Decide plan-mention activities-mention steps in activities-identify contingencies-
find countermeasures.
 b. Mention activities-decide plan- mention steps in activities-identify contingencies-
find countermeasures.
c. Decide plan-mention activities-identify contingencies-mention steps in activities-
find countermeasures.
d. Decide plan-identify contingencies-find countermeasures-mention activities-
mention steps in activities.
15. What is the final level of PDPC?
a. List of problems which might occur in process.
b. Contingency or countermeasure plan
c. List of critical equipment
d. Probable causes of problems which might occur in process.
16. Brainstorming is involved in construction of PDPC.
a. True
b. False

Answer key: 8. b
9. b
1. a
10. a
2. c
11. c
3. b
12. d
4. c
13. a
5. b
14. a
6. c
15. b
7. a
16. a
 Basic Statistics
Definition of Statistics
Statistics is the science of learning from data and of measuring, controlling and
communicating uncertainty from the data collected in a systematic manner for a pre-
determined purpose and placed in relation to each other.
It is methodology which scientists and mathematicians have developed for interpreting
and drawing conclusions from collected data.
Statistics is the science of dealing with uncertain phenomenon and events, providing
crucial guidance in determining what information are reliable and which predictions can
be trusted.

Functions of statistics
1. Condensation: Condensation is mainly applied at embracing the understanding of a
huge mass of data by providing only few observations. Dealing with large number of
data is cumbersome thus, statistical methods help us to understand the complexity of
huge data.
2. Comparison: Comparison of an entity with other entity is easy to do with the help of
statistics through tools like graphs, diagrams, coefficient of correlation etc.
3. Forecasting: In business, predicting the future trends, forecasting the future problems
and opportunities is always the concern of management. Statistical tools like time series
analysis, regression tools etc. enable us to do the same.
4. Estimation: Statistics helps to estimate about the population by drawing inferences
from samples; tools like estimation theory etc. enable us to do the same.
5. Optimization: Business tends to optimize its productivity, profits, cost. Statistical tools
like DOE, Linear programming, Simulations etc. help us to generate and evaluate
strategies to optimize business interests.

Descriptive and Inferential Statistics

 Branches of statistics
Branch of Measuring
Meaning What does it entail
statistics (of)
Describing the whole set of data with
Central a single value that represents middle
Tendency or centre of distribution.
Involve summarizing, tabulating, Mean, Median, Mode
organizing and graphing data in Describing how spread out a data
order to summarize a data set for set is.
the entire population of subjects. When a data set has a large number
No attempt is made to infer or Dispersion
Descriptive of values.
predict the characteristics of Range, Standard deviation,
Statistics subject that have not been Variance
observed or measured.
Techniques used to divide a set of
Tell us what the data shows and
Position data into equal groups.
help to present quantitative
Percentile, Quartile, Z Score
descriptions in a sensible way.
Shows shape and distribution of
Shape data.
Skewness, Kurtosis
Quantitatively describing the main
features of a population based on
sample under study. Hypothesis
Helps take inference on a testing
population based on results of a
Inferential
sample under study which
Statistics represents whole population.
Is valuable when it is not Estimation
convenient or possible to examine of
each member of an entire parameters
population.

Introduction to Data
Types of data

Data

Qualitative Quantitative

Nominal: Data Ordinal: Has Binary: Place Discrete: It is a Variable: Could Interval Ratio
which has no items assigned data in one of count that cant be divided E.g. Temp. E.g. Body
implicit or to categories two mutually be made more reduced to finer range Mass
natural order that do have exclusive precise; involves levels and can index
or rank some kind of categories integers and take any value. (BMI)
between the implicit or right/wrong, cant take E.g. If I use a
categories. E.g. natural order. true/false or decimal values. weighing scale
colour of E.g. Height type accept/reject. E.g. If I tally the to measure the
candies etc. short, tall or E.g. Good no. of candies, it weight of
medium. Candy and bad would be candies, it would
candy discrete data. be continuous
data.
 Measure of Central tendency

Mean
Definition:For data set, the terms arithmetic mean, average are used synonymously to
refer to a central value of a discrete set of numbers specially the sum of the values
divided by the number of values.
Notation: Arithmetic Mean for a sample is denoted by and population mean by .
Mathematically: For data set (X1, X2, X3Xn),
( + + + )
=
Note:
1. It produces the lowest amount of error from all other values in the data set.
2. Larger the sample size closer the sample mean to population mean.
3. It includes every value in data set as part of the calculation.
Uses of mean:
1. Mean is the best measure of central tendency for interval and ratio scales of
measurement.
2. Mean is often used when data is symmetric and unimodal, that is when the data is
not skewed.
3. It is used when we want to study variation between multiple samples.
Caution:
1. Mean is susceptible to the influence of outliers.
2. Mean is usually not a good measure of central tendency for skewed distribution.
 Example:

Median
Definition: A Median is the value separating the higher half of a data sample (or a data
population) from the lower half. It is the middle value when the data is in order of
magnitude.
Notation: Median is denoted by M or
Mathematically:
1. Arrange the data in ascending or descending order.
2. For odd no. of data points, Median = Middle value
3. For even no. of data points, Median = Mean of middle two values
Note:
1. It is of central importance, as it is the most resistant statistic.
2. The median is the 2nd quartile, 5thdecile and 50th percentile.
Uses of Median:
1. It is preferred when data is ordinal, however it can be calculated for interval/ratio as
well.
2. The median can be used as a measure of location for skewed distributions.
3. It can be used when end-values are not known.
4. It can also be used when one requires reduced importance to be attached to outliers.
5. A median can be defined or ordered one-dimensional data.
Example:
 Mode

Definition: The Mode is the value that appears most frequently in a set of data.
Note:
1. It is the value that is most likely to be sampled.
2. The highest bar in a bar chart or histogram represents mode.
3. There may be more than one mode for a data set.
One mode Unimodal
Two modes Bimodal
Three modes Trimodal
More than three modes Multimodal
Limitation: Limitation of mode is that it does not provide us a very good measure of
central tendency when the most common mark is far away from the rest of the data in
the data set.

Central Tendencies: Relationship

Mathematically,
2 Mean = 3 Median Mode

Measure of Dispersion
Measures of Dispersion are descriptive statistics that describe how similar a set of data
are to each other. The three frequently used measures are:
1. Range
2. Variance
3. Standard Deviation

Low High
Closeness in numerical value of data

Measure of dispersion

High Low

Range

Standard Deviation & Variance

 Measure of position

Percentile
Definition: A percentile (or a centile) is a measure used in statistics indicating the value
below which a given percentage of observations in a group of observations fall.
Elements in a data set are rank ordered from the smallest to the largest.
The values that divide a rank-ordered set of elements into 100 equal parts are called
percentiles. E.g. the 80th percentile is the value (or score) below which 80% of the
observations may be found.
An observation at the 50th percentile would correspond to the median value in the set.
Similarly, Deciles are the values that divide a rank ordered set of elements into 10equal
parts.
Uses: Percentiles are calculated as a means of dividing the distribution of values into 2
or more groups. They are used to determine where to draw the line between observed
values within the distribution.
Calculation:
 Example:

Quartile

In descriptive statistics, the quartiles of a ranked set of data values are the three points
that divide the data set into four equal groups, each group comprising a quarter of the
data.
Quartiles help us measure how data is distributed in the two arms on either side of the
median.
Inter Quartile Range (IQR) measures the middle fifty percent of the data.
Mathematically, IQR = Q3 Q1
Calculation methodology for Quartiles

Box Plots

Z Score

Definition: A zscore (or standard score) indicates how many standard deviations an
element is from the mean.

Calculation to transform x to z : =
Application:
Z-score facilitates us to understand the distribution of data.
Helps us to determine the exact location of data from the mean on a standard scale
(or score).
Helps us to compare two or more distributions.
 Interpretation of Z-Score

Measure of Shape

Skewness
Skewness speaks of the amount and direction of skew i.e. the deviation of data from
horizontal symmetry.Skewness has no units, it is a pure number, like Z-score.
Skewness can be easily calculated using by SKEW() function in Excel or by using
descriptive statistics under Analysis Toolpak.
Interpretation of co-efficient of skewness -

Caution: The sample skewness doesnt necessarily apply to the whole population.
 Mathematically,
(x x)
= +
( 1)( 2) ns
Where,
xi = ith value of x,
x = sample mean,
n = sample size,
s = standard deviation

Skewness graphs

Kurtosis

Kurtosis tells us how tall and sharp the central peak is, relative to a standard normal
distribution curve.
It can be easily calculated by KURT() function in Excel.
Mathematically,
( + 1) (x x)
= +
( 1)( 2)( 3) ns
Where,
xi = ith value of x,
x = sample mean,
n = sample size,
s = standard deviation
Note: This equation takes into account the sample size and substracts 3 from the
kurtosis, hence with this the kurtosis of a normal distribution is 0.
Graphs and Interpretation: Kurtosis is typically measured with respect to the normal
distribution.
A distribution that is peaked in the same way as any normal distribution, not just
the standard normal distribution, is said to be Mesokurtic.
Platykurtic distributions have peak lower than the mesokurtic distribution. These
are characterised y a certain flatness to the peak and have slender tails.
 A Leptokurtic dsitribution has kurtosis greater than a mesokurtic distribution. These
have peaks that are thin and tall. The tails, to both the right and the left, are thick
and heavy.

Definitions
Parameters:Parameters are descriptive measures of an entire population used as the
inputs for a probability distribution function to generate distribution curves.
Parameters are usually signified by greek letters to distinguish them from sample
statistics. Parameters are fixed constants, that is, they do not vary like variables.
However, their values are usually unknown because it is infeasible to measure an entire
population.
Error:It ususally refers to how much functions, formulas and statistics fail to fully
explain or model a true or theoretical value. In other words, it is the diffrence between
an actual and predicted value. While some degrees of error or uncertainity can exist in
statistical analyses, identifying and quantifying it can at least help us explain its
presence. Residual error, Standard error of fits (SE of fits), Family error rate Type I and
Type II error.
Proportion: A proportion is a portion of a whole, as opposed to a count or frequency.
Proportions let you compare groups of unequal size. For example, our company
manufactures steel. If you were interested in proportion of CaO (by weight) in mixture,
you are not worried about hoe many tons of CaO your plant uses in a day, you are
worried about the proportion of Cao relative to the additives. Assuming that precisely a
quarter of the additives is CaO, the proportion of the CaO could be expressed by a
percentage (50%), a decimal (0.5) or a fraction (1/2).
 Questionnaire
1. Statistics is the science of dealing with certain phenomenon and events.
a. True
b. False
2. Statistical tools like _______________ enable us to predict the future needs,
forecast the future problems and opportunities in business.
a. Regression
b. Time series analysis
c. Bothe of the above
d. None of the above
3. Inferential statistics helps us in describing the data.
a. True
b. False
4. Skewness comes under the branch descriptive statistics.
a. True
b. False
5. Ordinal data has items assigned to categories that do not have implicit or natural
order.
a. True
b. False
6. Discrete data involves
a. Integers
b. Decimals
c. Bothe of the above
d. None of the above
7. Arithmetic mean for a sample is denoted by
a.
b.
c.
d. None of the above
8. Mean refers to a central value of a continuous set of numbers.
a. True
b. False
9. Median is denoted by
a.
b.
c.
d. M
10. For even no. of data points, Median is
a. Middle value
b. Mean of middle two values
c. Both of the above
d. None of the above
11. Median can be used -
a. When we want to study variation between multiple samples
b. When data is not skewed
c. When end-values are not known
d. None of the above
12. The lowest bar in a bar chart or histogram represents mode.
a. True
b. False
13. Relationship between central tendencies
a. 2 Mode = 3 Median Mean
b. 3 Mode = 2 Median Mean
c. 3 Mean = 2 Mode Median
d. 2 Mean = 3 Median Mode
14. Range is equal to
a. XS XL
b. XL - XS
c. XL + XS
d. None of the above
15. Range can be used when you have
a. Ordinal data
b. Binary data
c. Nominal data
d. None of the above
16. Variance is the expectation of the squared deviation of a random variable from its
median.
a. True
b. False
17. Relationship between Standard deviation() and variance is
a. =
b. =
c. =
d. = Variance
18. In case of percentile, the elements in a data set are rank-ordered from the largest to
smallest.
a. True
b. False
19. An observation at the ____ percentile would correspond to the median value in the
set.
a. 20th
b. 45th
c. 100th
d. 50th
20. Deciles are the values that divide a rank ordered set of elements into ____ equal
parts.
a. 20
b. 50
c. 10
d. 30
21. Mathematically, Inter Quartile Range (IQR) is equal to
a. Q3 Q1
b. Q1 Q3
c. Q2 Q1
d. None of the above
22. Match the following:

a. i 1, ii 3, iii 2, iv 4
b. i 2, ii 1, iii 4, iv 3
c. i 3, ii 1, iii 4, iv 2
d. None of the above
23. Skewness can be easily calculated using _________function in Excel.
a. KURT()
b. SKW()
c. SKEW()
d. None of the above
24. Coefficient of skewness of a statistical distribution is -0.62. What does it infer?
a. The distribution is moderately skewed to the right
b. The distribution is highly skewed to the left
c. The distribution is highly skewed to the right
d. The distribution is moderately skewed to the left
 25. Which of the following is true?
a. Leptokurtic distribution >Mesokurtic distribution >Platykurtic distribution
b. Platykurtic distribution <Mesokurtic distribution > Leptokurtic distribution
c. Platykurtic distribution >Mesokurtic distribution > Leptokurtic distribution
d. None of the above
26. Consider the following set of data: -30, -20, 10, 50, and 150. Choose the correct
option showing the range and mean of this data set:
a. Range 120, Mean 52
b. Range 120, Mean 32
c. Range 180, Mean 32
d. Range 140, Mean 10
27. Which of the following depicts the symmetry of a distribution?
a. Mean
b. Median
c. Variance
d. Skewness
28. Consider the two data sets below and choose the correct statement:
Data Set A: 100, 40, 20, 80, 25
Data Set B: 20, 40, 75, 30, 200
a. Range A = Range B
b. Median A = Median B
c. Median A > Median B
d. None of these
29. Continuous Data example
a. No. of defects
b. Temperature
c. A & B
d. None of these
30. Range can be calculated by
a. Max. value Min. value
b. Min. value Max. value
c. Max. value Std. deviation
d. Min. value Std. deviation

Answer key:

1. b 7. c 13. d 19. d 25. b

2. c 8. b 14. b 20. c 26. c
3. b 9. d 15. a 21. a 27. d
4. a 10. b 16. b 22. c 28. b
5. b 11. c 17. a 23. c 29. b
6. a 12. b 18. b 24. d 30. a
 Improvement Fundamentals
Clarification of common terms
Terms Full Form Explanation
Literally means small change in Japanese;
used parallel to the English word
Kaizen Kaizen improvement. Commonly used today for small
improvements and is a continuous
improvement tool in TQM philosophy.
An improvement presentation format which
Kaizen
shows an improvement (Kaizen) in a BEFORE-
format
AFTER format.
Another 7-step improvement presentation
format (developed at Toyota) based on PDCA.
A3 format Has the steps Background, Current situation,
Goal, Root Cause, Countermeasures, Effect
(impact), Follow up actions.
A 7/8 step problem solving methodology based
QC Story QC Story on PDCA which the QC members use basic tools
to solve problems in a Quality Circle.
A generic term used for employee engagement
activities in an organisation where people work
SGA Small Group Activities in small groups to solve problems of their work
area. This is generally used for employee
motivation and morale.
Same as Quality Circle; were known earlier (in
QCC Quality Control Circles
Japan) as QCC
A group of voluntary workers who agree to
QC Quality Circle work on problems in their area and create this
forum to solve their problems.
An iterative 4 step problem solving
methodology which assumes that the problem
PDCA Plan-Do-Check-Act
is solved best when you follow this cycle P-D-C-
A. Also Known as Deming cycle.

Employee Engagement Activities: Forums and Output Formats

 Our Proposed Approach
First, we would form Quality Circles to cover 100% L06 L07 employees
Quality Circles to be formed in the respective work areas of members so that they solve
problems in QC meetings which they are actually supposed to take care in their day to day
job.
We can use Kaizen output format (BEFORE-AFTER) to start with; this is the simplest way to
represent small improvements.
Then we can slowly graduate QC Story presentation format or A3 presentation format as
the system mature.
For those Quality Circles that are in mature stage, we would continue with the QC Story
output format.

Quality Circles
Evolution of Quality Control & history of Quality Circles
Evolution of Quality Control in Japan
Before Industrial Revolution skilled craftsman served as both Manufacturer and
Inspector
During Industrial Revolution the concept of specialization of labor was introduced.
Statistical approach to Quality Control was started by Shewhart, Deming and Juran.

History of Quality Circles

Quality Circles started in Japan in 1962 (Kaoru Ishikawa) as another method of improving
quality.
In April 1962. Dr. Ishikawa presented this in JUSEs journal Gemba to QC, later co-
ordinated by JUSE for whole of Japan.
The use of Quality Circle has spread beyond Japan, now the most popular SGA (Small
Group Activities) methodology.
In India, QCFI (Quality Circle Forum of India) is promoting such activities.

What is a Quality Circle?

Dr. Kaoru Ishikawa described a Quality Circle as - voluntarily a small group to perform
quality control activities within the same workshop or work area.
A Quality Circle is a volunteer small group composed of members from same work area,
who meet together to discuss workplace improvement and make presentations to
management with their ideas, especially relating to quality of output.
Typical topics are improving
Safety, Health and Environment
Product design and Product quality
Manufacturing processes productivity, yields, losses, maintenance
 Quality Circle Norms
# Aspect of Quality Control Norms / Known facts Suggested for JSW
1 Supervisors / workers (non-
Level L-07 and below
officers)
2 Nominated, to start
with; can become
Joining Criteria Voluntary
voluntary as system
matures
3 Number of members 3-12 5-7 max
4 Work area / department Same work area Same work area
5 Functional area (Ops., Mech., Same or cross
Same or cross functional
Electr. etc) functional
6 Geographical area Same Same
7 Problem solving areas P, Q, C, D, S, M P, Q, C, D, S, M
8 Basic problem solving
Tools used Basic problem solving tools
tools

Quality Circle Functioning

1. Identification of problem 7. Data analysis
2. Selection of problem 8. Development of solution
3. Definition of problem 9. Foreseeing probable resistance
4. Analyzing the problem 10. Trial and check performance
5. Identification of causes 11. Regular Implementation
6. Finding out root causes 12. Follow-up / review

Hierarchy of Quality Circle

Policy making for QC deployment

Steering Decide overall roadmap for 100% coverage
committee Audit, Review and support overall progress

Trained on tools,
Facilitator Supports, trains, coaches,
Generally a line manager / supervisor

Most experienced, capable member of the group

Leader
Conducts QC meetings

4-6 in number, members of the QC belong to the same work area /

Members
cross-functional expertise
 Basics of Quality Circle
QC tools are the means for collecting data, analysing data, identifying root causes and
measuring the results. These tools are related to Numerical data processing.
9 basic tools:
1. Flow Chart
2. Graphs
3. Histogram
4. Check Sheets
5. Pareto
6. Cause and Effect
7. Stratification
8. Scatter
9. Control Chart

Brainstorming
Brainstorming is a group technique for generating new ideas and can be used at various
stages of problem solving. It can be used for identification of problem, finding out the
possible causes to the problem, generating ideas for arriving at a solution, predicting the
possible resistance to the solution, finding out the process to overcome the resistance.

Participants are asked to write their ideas anonymously. Then

Nominal Technique the facilitator collects the ideas and the group votes on each
idea. The best idea is chosen.

Each person in a circular group writes down one idea, and then
Group Passing
passes the piece of paper to the next person, who adds some
Technique
thoughts.

This process involves brainstorming the questions, rather than

Question trying to come up with immediate answers and short term
Brainstorming solutions. Questions are important in this technique. We need
a list of questions to reach logically to the best solution.

The process begins with a well-defined topic. Each participant

Team Idea Mapping
brainstorms individually, then all the ideas are merged onto
Method
one large idea map.

When you free write you write whatever comes into your mind.
Free Writing
On finish, read back over the text and decide the solution.
 It typically includes such techniques as free writing, free
speaking, word association, and drawing a mind map, which is
Individual
a visual note taking technique in which people diagram their
Brainstorming
thoughts.Individual brainstorming is a useful method
in creative writing.
Free flowing idea generation
Conducted on definition of the problem
Conventional
Continues till all thoughts are exhaustively captured
Brainstorming
No in process evaluation
Segregate on themes later
Everyone sticks their post it notes on the wall near a similar
idea; then clusters of post it notes representing similar ideas
Affinity Analysis
are created. Ideas reviewed by clusters, then variants are
clubbed under one head to develop solutions.
Writing on slips, postits for issues / KPIs.
Idea Sheet Avoids dominating effect of individuals.
(Brainwriting) Avoids effects of recency factors during discussions.
Takes care of shyness on individuals.
3. Issue / KPI based brainstorming:
Ideas generated along pre-decided KPI branch or issues.
KPI based Bucketing / Categorisation done along with.
Brainstorming 4. Reverse brainstorming:
Ideas around how to make the issue / KPI worse
After evaluation, focus on how to make it better
3. Osborns / Scamper Method:
A series of idea provoking ideas like Substitute?, Combine?,
Adapt?, Modify?, Put to other uses?, Eliminate?, Reverse or
rearrange?
Directed Brainstorming
4. Idea Box:
Specify opportunity and parameters thereof.
Then identify possible variations in them, different
combinations to arrive at the solution(s).

Basic Problem Solving Tools

 QC Story Approach
QC Story Sheet (PDCA Approach)

- Various forms of QC Story formats exist

in various companies.
- All are based on PDCA.
- Most of them are 7/8/9 step processes.
 QC Story Approach (another form of PDCA)

QC Story Example Bar Rod Mill

Identification Upto 50 problems
Categorization into a, b and c
Selection of problems Ranking matrix
Criteria for ranking matrix
Milestone
Process Flow Diagram
Definition of problem
Current situation of the problem
Objectives
Analysis of problem 4W & 1H
Cause & Effect Analysis
Root Cause Analysis Identification
Data Analysis on Root Stratification
Cause Pareto Analysis
Development of Brainstorming
Solution Time Bound & responsibility
Foreseeing probable
Resistance points
resistance
Trial Implementation Data indicating trial and finding
and checking Comparison before and after
performance Graphical comparison
Milestone for full implementation
Regular Data collection
Implementation Comparison before/after
Tangible and intangible gains
Requirement to sustain
Frequency of review of the result
Follow-up/Review &
Standardization
Recurrence Prevention
Incorporating changes in document
Milestone chart and reflections on lessons learnt
 A3 Approach
A3 Thinking
A3 thinking is a lean tool developed at Toyota
It is a systematic problem solving approach-cum-communication tool.
Communicates a problem solving story in PDCA format.
Improves visualization at shop-floor.
Generic A3 Report Format Example:

Example from the plant

 PDCA
PDCA
PLAN-DO-CHECK-ACT or PDCA is an iterative 4-step Quality Management method used for
continuous improvement of processes, products and services.
It was conceptualised by Shewhart and put to use by Deming.

PDCA or PDSA

Kaizens, Poka Yoke, OPLs

What is Kaizen?
Example from the plant
POKA-YOKE

What is POKA-YOKE? Approaches in Poka-yoke Methods in Poka-Yoke

POKA-YOKE, Mistake Two Poka-Yoke system Poka-Yoke systems

Proofing or Error approaches are utilized in consist of 3 primary
Proofing emerged out of manufacturing which methods:
Lean's quest for ZDQ lead to successful ZDQ: 1. Contact
(Zero Defect Quality) 1. Control Approach- 2. Counting
Mistake proofing system shuts down the process 3. Motion Sequence
Most Poka-yoke devices when an error occurs. Or Each method can be used
are sensor or jig devices keeps the 'suspect' part in a control system or a
that assure 100% in place when an warning system.
compliance all the time. operation is incomplete. Each method uses a
2. Warning Approach- different process
Does not rely on
signals the operator to prevention approach for
operator catching
stop the process and dealing with
mistakes; it identifies the
correct the problem. irregularities.
defect immediately at
Point of Origin Inspection
and provides feedback
for corrective
action, quick feedback
100% of the time.

Example from the plant

 One Point Lesson (OPL)
What is OPL?
OPL is a 5 to 10 minutes (normally take less than 15 minutes) lesson one topic on one
sheet means only One Point illustrated on a sheet of paper as many senses as
possible should be addressed.
It must be written as simple as possible
The Point or Topic can be the Function of Equipment, Installation of Jigs, Cleaning
Method, Types of Lubrication Methods of Inspection etc.
It is generally prepared by supervisors or group leaders or sometimes by operator.

Types of OPL
1. Basic Information Sheet Essential basic information- practical know-how and know-
how of methods
Maintenance activities as e.g. filter changing
Small repair works
Setting of machine functions
Cleaning and checking
Lubricating
2. Problem case study sheet Teaches how to prevent recurrence of an actual
equipment problem
3. Improvement / Kaizen lessons study case describes the approach and key measures
in a successful improvement case study.

Why we need OPL?

To pass on better knowledge
Strengthen the understanding for functions of machines and lines
Improve knowledge about maintenance defect prevention

Which method used to deliver OPL?

Use all sense of people: tasting, feeling, smelling, hearing, seeing; the gathering of
information occurs in
83% by seeing: pictures, sketches, graphs, diagrams, drawings
11% by hearing: whistling, rattling, squeaking
3.5% by smelling: chemicals, smell of fire
1.5% by feeling: surfaces, roughness, heat
1% by tasting: sweet, bitter, salty, sour (food industry)

Who should conduct OPL?

Employees on the shop floor - Foreman, Supervisor
Employees from the maintenance Electricians, Mechanics
Employees from the technical office Engineers, Technicians
Example from the plant
 Questionnaire
1. Full form of SGA
a. Small Group Above
b. Small Group Activity
c. Standardized Group Above
d. Standardized Group Activity
2. Statistical approach to Quality Control was started by
a. Shewhart, Juran & Osborn
b. Shewhart, Osborn & Deming
c. Shewhart, Deming & Juran
d. None of these
3. Who has started the concept of Quality Circles in Japan?
a. Juran
b. Crosby
c. Deming
d. Ishikawa
4. Full form of PDCA
a. Plan-Do-Check-Assign
b. Plan-Do-Check-Act
c. Plan-Do-Check-Assume
d. Plan-Do-Check-Assemble
5. A Quality Circle is a voluntary small group composed of members from same work
area, who meet together to discuss workplace improvement. Currently in our
organization, we have 600+ Quality Circles across all departments. Which of the
following is not a task completed by Quality Circles?
a. Doing Small Improvements and submit Kaizens.
b. Do meetings frequently and discuss the problems in their area
c. Using basic QC tools for problem solving
d. KPI gap analysis
6. Quality Circle is mandatory for
a. L05 & below
b. L07 & above
c. L07 & below
d. L08 & above
7. How many steps will be there in Quality Circle Methodology?
a. 8
b. 10
c. 11
d. 12
8. Steering Committee of QC, audit and review the overall progress.
a. True
b. False
9. Number of basic tools of Quality Circle which are related to numerical data
processing
a. 7
b. 9
c. 8
d. 10
10. Which statement/s is/are true about Brainstorming
a. Means of generating ideas
b. A tool which can be used to identify alternatives
c. A democratic way of generating ideas
d. All of the above
11. Reverse Brainstorming is
a. An approach from bottom to top across an hierarchy
b. To do brainstorming after an idea fails
c. Generating ideas how to make an issue worse
d. None of the above
12. Histogram is used for
a. Demonstrating frequency (data) distribution
b. Arranging data according to priority and using it into a problem solving
framework
c. Manual data gathering
d. None of these
13. There are three types of control charts.
a. True
b. False
14. A3 Thinking is a lean tool developed at
a. Kawasaki
b. Toyota
c. Nissan
d. None of the above
15. Hanumathappa, an employee in Blast Furnace is working on some improvement
project to reduce tuyere burning frequency. His boss was happy to see the
improvement he has done and asked him to rotate the Deming Cycle for one more
time to improve it even more. Hanumathappa asked people around him about
Deming Cycle and came to know that it is another name for PDCA, a continual
improvement philosophy. Help Hanumathappa to match the following regarding the
PDCA cycle:

a. 1-D, 2-B, 3-C, 4-A

b. 1-A, 2-C, 3-D, 4-A
c. 1-B, 2-C, 3-D, 4-A
d. 1-C, 2-D, 3-B, 4-A
16. Throughout the globe, organizations have been achieving milestone in business
excellence by adopting TQM practices. Dr. W. Edward Deming, also known as the
father of TQM believed that Continuous Improvement is a key factor in successful
 implementation of TQM practices. He introduced a four step iterative CI
methodology popular as Deming Cycle. Deming Cycle is also known as:
a. Design-Measure-Improve-Control
b. Plan-Do-Control-Sustain
c. Plan-Produce-Improve-Check
d. Plan-Do-Check-Act
17. Kaizen is a Japanese term used for Small Improvement. QC teams in our plant have
been actively using Kaizen for solving their problems. Which one of the following is
not being shown in a Kaizen document?
a. Before & After situation
b. Root Cause Analysis
c. Scope of Improvement i.e. P, Q, C, D, S, M, E
d. Regression Analysis
18. Error-Proofing refers to the implementation of fail-safe mechanisms to prevent a
process from producing defects. Which of the following is the term used for error
proofing in industries?
a. One Point Lessons
b. Kaizen
c. Poka Yoke
d. Failure Analysis
19. Full form of ZDQ is Zero Defect Quality.
a. True
b. False
20. One Point Lesson (OPL) is a piece of knowledgeable information which is
represented using 80% pictures and 20% text. They are classified into categories to
ensure maximum usability and ease of operating procedures in a work place. Which
of these is not a classification of OPL?
a. Basic Knowledge
b. Improvement
c. Trouble Case
d. Error Proofing
Answer key:

1. b
2. c
3. d
4. b
5. d
6. c
7. d
8. a
9. b
10. d
11. c
12. a
13. b
14. b
15. c
16. d
17. d
18. c
19. a
20. d