Industry 4.

0 Awareness Seminar Report organized at Rajkot

Source: CMTI as on 24 Apr 2019

1. Date of the Seminar 13thApril, 2019

2. Organizers Department of Heavy Industry,
Govt. of India & Central
Manufacturing Technology Institute,
Bangalore
3. Title of the seminar Awareness Programme “Workshop
on Smart Manufacturing & Industry
4.0”
4. Programme Schedule (enclosed a copy in pdf)
5. Report: suggested contents  Awareness about various Smart
( 1 ) Main takeaway / good suggestions Enterprises and Industry 4.0
 Challenges in adoption of Smart
Manufacturing
 Role of Sensors and data
acquisition in Industry 4.0
 Concepts of Smart Machines,
Intelligent Machines and Smart
Metrology
 Smart Foundry applications &
Case Study
( 2 ) Clusters covered  Foundry & Machining Cluster
from Rajkot, Morbi,
Surendranagar,
 Machine Tools Cluster from
Rajkot, Surendranagar,
Jamnagar
 Brass cluster from Jamnagar
  Professors & Researchers from
Rajkot, Kalol, Morbi
( 3 ) Nos attended 119
( 4 ) Success stories that need to be -NA-
compiled / shared
6. List of Speakers with contact details (enclosed a copy in MS Word)
7. Presentations (enclosed copies in pdf)
8. Resource persons for providing -NA-
consultancy, skilling, guidance etc.
9. Photographs Jpeg images (enclosed)
10. Learning from the seminar From organizers/ subject point of
view for action in the next seminar
to improve further
Learning outcome from the
organiser’s perspective

(-)
 More Industry specific case
studies are to be covered
(+)
 Created awareness on
futuristic technology of Smart
Manufacturing & I 4.0

 Seminars of this kind should

be done at Rajkot in future
also
 Department of Heavy Industries
Government of India (An Autonomous R&D Institute Under
Ministry of Heavy Industries & Public Enterprises, Govt.of India)

AWARENESS PROGRAMME
Workshop on
SMART MANUFACTURING &
INDUSTRY 4.0
13 APRIL 2019, RAJKOT, GUJARAT
Detailed Schedule

Time Programme
10.30 - 10.33 Saraswati Vandana

10.33 - 10.38 Lighting of Lamp

10.38 - 10.50 Welcome & Introduction to CMTI by Director

10.50 – 11.00 Introduction & Honouring the Guests

11.00 - 11.10 Address by Guest of Honour Jt.Secretary / Director, DHI

11.10 – 11.40 Address by Chief Guest Shri. P.G. Jadeja, CMD Jyoti CNC Automation Ltd.

11.40 – 12.00 Tea Break

Introduction to Smart Manufacturing , IIoT & Industry 4.0
12.00 – 12.45
- Dr. Nagahanumaiah, Director, CMTI
Smart Machines & Intelligent Machining
12.45 - 13.30
- Shri. Prakash Vinod, Scientist-F & Head NMTC
13.30 - 14.30 Lunch
Smart Sensors and Controllers
14.30 – 15.00
- Shri. V S Shanmugaraj, Scientist-F & Head, SVT
Precision & Smart Metrology
15.00 – 15.30
- Shri. K Nirajan Reddy, Scientist-E & Head, UPE
Smart Foundry - A Case Study
15.30 – 16.00
Prof.. Amit Sata and Dr. Nagahanumaiah
CMTI Technologies and Technology Transfer Modalities
15.45 - 16.45
- Dr. N. Balashanmugam, Jt. Director, CMTI
CMTI Regional Center Activities and Future Expansion Scope
- Shri. Abhishek Suchak, Incharge – CMTI Regional Centre
Head Office : Tumkur Road, Bangalore – 560022; Website: www.cmti-india.net
Regional Centre : Centre for Advancement of Manufacturing Technology, NSIC Campus, Aji
Industrial Area, Bhavnagar Road, Rajkot – 360003 Gujarat.
Ph: 0281-2384128 Email: cmtirc.cmti@nic.in
List of Speakers for Awareness Programme “Workshop on Smart Manufacturing &
Industry 4.0” organized at Rajkot on 13th April 2019.

Sl. No. Speaker Details Contact details

1. Dr. Nagahanumaiah Director, CMTI, Bangalore

director.cmti@nic.in

2. Dr. N. Balashanmugam, Jt. Director, CMTI, Bangalore

balashanmugam.cmti@nic.in

3. Prof. Amit Sata Professor, Marwadi Education

Foundation, Rajkot

4. Shri. Prakash Vinod Scientist-F & Head NMTC,

CMTI, Bangalore
prakashv.cmti@nic.in

5. Shri. V S Shanmugaraj, Scientist-F & Head, SVT,

CMTI, Bangalore
shanmugaraj.cmti@nic.in

6. Shri. K Nirajan Reddy, Scientist-E & Head, UPE,

CMTI, Bangalore
niranjan.cmti@nic.in

7. Shri. Abhishek Suchak, In charge – CMTI Regional Centre,

Rajkot
cmtirc.cmti@nic.in
 www.cmti-india.net

Industry 4.0
IIoT and Smart Manufacturing

Dr. Nagahanumaiah
Director, CMTI

Central Manufacturing Technology Institute 23-Apr-19

Tumkur Road, Bangalore 1
 Overview www.cmti-india.net

• About CMTI
• Smart Manufacturing
• IoT-Big Data-IIoT
• Industry 4.0 @ DHI/CMTI
• Industry 4.0 Challenges, Facts and Roadmap
• Summary
 CMTI Focus www.cmti-india.net

Machines and Manufacturing Processes

Academia –IITs, Industry,
Govt, Industry, other
IISc, CSIR Academia, National
Stakeholders
International imperatives
experts….

Mandate,
SDGs

Incubation, Tryouts,
CMTI Deployment, Product
Dev., Services, to
Research - Technology -
industries, stakeholders
Training - Application
…

Research-Technology-Training-Application
 What CMTI Would Offer
We Undertake Research, Develop Technologies and Machines,
www.cmti-india.net

Train Manpower and Deploy into Industrial Applications

Ultra Precision Machine Tools

Special Purpose Machines
Sensors and Controllers
Textile Machinery
Aircraft LRUs and Test Rigs
Precision Metrology
Smart Manufacturing and Industry 4.0
Additive Manufacturing
Industry Employable Manpower (Skilling & Reskilling)
Technology Transfer and Incubation

MADE – IN – INDIA
 Smart Machines & Aggregates -Metal Cutting
Ultra Stiff Ultra Precision Projection Microstereo www.cmti-india.net
Intelligent Ultra Precision lithography Scanning Tunnelling
Turning Machine Diamond Turning Machine Microscope

Ultra Precision Machine Tool Sub-Systems Nano Finishing Manufacturing & Fabrication Solutions

Hydrostatic Slide Aerostatic Spindle

Abrasive Flow Micro Mold & Needle Micro machining & spiral
Finishing Machine Array grooving of special alloy
components

Surface Engineering
Spindle Error Analyzer DLC coated germanium lens, cutting tools
and surgical blades
 Design & Development-SPMs www.cmti-india.net

Centreless grinding machine Perch on facing & boring Flexible multi

for Automobile industry
machine for ship building gauging inspection
industry system Parallel Kinematics
Machine

Single and double cutter head

Centerless Bar Turning Machine Performance Test
Vertical Planetary Mixing
Rig for Pumps
Machines - upto 5 ton
 Product Development www.cmti-india.net

High Speed Rapier Loom - 450 Twin Screw Continuous Hydraulic Filters
Mixer

Battery operated hydraulic Pressure Endurance tester Pressure Impulse Test

system to charge parking
brake accumulator of aircraft
 Test Rigs for Machine Tool Testing
Telescopic Cover Test Rig performance evaluation www.cmti-india.net
Electro Hydraulic Force Exciter Dynamic behaviour
of telescopic covers of machine tool slides study of machine tools and structures

Spindle Test Rig for performance testing

 Vision Based Solutions
MEDICAL INDUSTRY AUTOMOTIVE INDUSTRY www.cmti-india.net

AUTOMATED INSPECTION OF SURGICAL SCREW FOR AUTOMATED INSPECTION OF RETAINING BUSH FOR M/S
M/S ADLER MEDIEQUIP PVT LTD FINE TOOLS INDIA PVT LTD
Defects identified in
injection mould
component
 Flash
 Cracks
Dimensional Measurements 636 sizes of 30
 Black spots
features each
 Color
Inspection Accuracy: 5-7 µm.
variation
AGRO INDUSTRY  Missing
feature
AUTOMATED INSPECTION OF DRIPPERS FOR M/S
Inspection rate of 3 p/
UDYOGI INDUSTRIES sec
ENGRAVED LABEL INSPECTION ON SCOOTER
FRAME AND BARREL COMPONENT

Detection of blocked holes, root flash &

collar flash, broken edges, circularity of top
and bottom sections
Inspection rate of 600 p/ min M/sForbes
M/s Forbes India
India (P) Ltd(P) M/s Mico Bosch (P) Ltd
 Additive Manufacturing
Remanufacturing of Turbocharger for Remanufacturing of Pump Gear Shaft for www.cmti-india.net

HAL Engine Div. Bangalore Bi-metallic parts deposition

M/s Cummins Pune
(Steel on Al-Bronze ) by DMD

Honey Comb type Orifice (DMLS) Model of Aircraft by Direct laser

Mould for Ball Bearing Retainer metal sintering
 Made in India
www.cmti-india.net

Need:
 Bridging the Technology
Key Initiatives 2018-
Gap Research –Technology Development – Training 2024
 Factoring Sectorial (Machine and Manufacturing Processes)
developments into Mfg.
 Adoption of latest  Smart Manufacturing
technologies
 Driving Innovation
Design and
Micro &
 Game changing
Nano Design Smart Demonstration Center
 Sustainable / Green Mfg. Manufacturing
Innovation
 Skill development Manufacturing
Innovation
 Center of Excellence
Fluid Power
for Textile Machinery
Transformation: Test Rig &
Product
Additive
 Support for Capital Goods Manufacturing
 Indian Institute of
Development
Sector
 Support for Strategic Sector Innovative
 Embracing futuristic Manufacturing (I3M)
Automation
Technologies
& Machine Sensor
 Enhancing scientific & Skill
Vision
technical expertise Development
for Advanced
Technology  Design Innovation and
 Augmentation & upgradation Mfg
of facilities Manufacturing
 Up scaling of operations Excellence
Improvement
to Outreach
Infrastructure Programmes
(II&AA)
 www.cmti-india.net

IoT – IIoT – Smart Manufacturing – Smart Factory

(The Manufacturing Revolution?)

Competitive Advantage in
Market
Innovation; Responsiveness;
Cost Effective; First to Market

Smart Enterprises
Predict – Digitize and Share – Analytics – Automate

I4.0
 www.cmti-india.net

23 April 2019 13
 Manufacturing Revolution
(Industry 1.0 to Industry 4.0) www.cmti-india.net

Industry 1.0 Industry 2.0 Industry 3.0 Industry 4.0

FIRST SECOND THIRD FOURTH
Industrial Revolution Industrial Revolution Industrial Revolution Industrial Revolution
Key Change:
Introduction of IoT and
Key Change: Cyber-Physical Systems
Introduction of driven by Augmented Reality
Key Change: Electronics, PLC Devices, & Real Time Intelligence
Introduction of mass Robots and IT to
Key Change:
Manufacturing Production automate Production
Introduction of
Mechanical Production lines powered by Electric
Equipment driven by Energy
Water and Stream Power

Level Of Complexity
Augmented Reality Driven CPS

PLC Driven Robots

Vintage Electric Conveyor Belt

18th Century Mechanical Loom

End of 18th Century End of 19th Century Q4 of 20th Century Start of 21th Century
 Electronics Innovation www.cmti-india.net

IoT - IIoT – Smart Mfg. – Smart Factory

These “smart, connected products”—made possible by vast improvements in processing power and device
miniaturization and by the network benefits of ubiquitous wireless connectivity—have unleashed a new era of
competition.”

Sensors & Actuators

Connectivity Big Data & Analytics Cloud Computing Internet of Things
1933 1971 2010
1998 1999
First room thermostat AlohaNet is first John Masey, Chief Cloud computing is The IoT and
introduced public wireless packet interconnectivity creat
Scientist at SGI presents a introduced to the
data network novel possibilities for
paper titled “Big enterprise
Data„and the Next Wave electronics
of Infrastress”
Smart Manufacturing Sustainability www.cmti-india.net

The Business of
Open Architecture
Market, Valuation
The Business Model of Data & Innovation
of Data Collective Wisdom
Big Data Collective
Practice Valuation Innovation & Converting Knowledge to
Collective vs. Proprietary Practice Wisdom
Smart Enterprise Smart
Open Architecture Manufacturing
Converting Information
Smart Factory Manufacturing to Knowledge

Data Valuation Data & Device Integration &

Collective vs. Orchestration Converting Data
Proprietary to Information
IoT Secure Data Highways

Secure I, P and SaaS

 IoT + Big Data = IIoT www.cmti-india.net

• Internet of Things (IoT): Devices with electronics and

sensors connected to public telecome network and internet

• Big Data: Large data sets that may be analyzed

computationally to reveal patterns, trends, and
associations, especially relating to human behaviour and
interactions.

• Industrial Internet of Things: A network of physical objects,

systems, platforms and applications that contain embedded
technology to communicate and share intelligence with
each other, the external environment and with people.

• IoT + Big Data = Industrial Internet

 What is Smart Manufacturing? www.cmti-india.net

Value Chain Network Based Manufacturing

Business Mapping SAP information

Systems, ERP
Into operation

Customer
Supply Chain
Distribution Center
Smart
Factory
Tracking &
traceability
Dynamic plant configuration and readiness
Smart Grid
Dynamic product component/material configuration
Dynamic inventory minimization & management
Graphics courtesy of Rockwell Automation
 Smartness in Manufacturing Value Chain www.cmti-india.net

• Smart Manufacturing Intelligence

– Deeper understanding of the manufacturing process through modeling and analysis
– New capacity to observe and take action on integrated patterns of operation
through networked data, information, analytics, and metrics
– Dynamic management of energy and material resources

• Smart Manufacturing Practice

– Generating and orchestrating the use of sensor-based, data-driven manufacturing
intelligence
– Applying integrated performance metrics constructed for real-time action
– Reusing, scaling and repurposing integrated practice using a common infrastructure

• Smart Manufacturing Execution

– Dynamic orchestration of decision/action workflows in heterogeneous
environments without losing control of state
• across different time constants and seams, including supply chain
• multi-vendor discrete, continuous, operational and human/social applications
– Applications that can share data and data that can share
 Smart Systems Testbeds www.cmti-india.net

Enterprise &
Smart Machine In-Production High
Dynamic Decisions Supply Chain Design & Planning
Line Operations Fidelity Modeling
Decisions

Performance
Machine product Better management Variability Design models in
management global
management complex behaviors reduction production
integrated decisions

Untapped enterprise
Benchmarking Rapid qualification Risk and
degrees of freedom in Product/material
machine-product components products compliance
efficiency, performance in-production ability
interactions materials management
time

Machine-power Integrated Tracking New product,

Business operational
manage computational traceability material technology
tradeoff decisions
management materials engineering genealogy insertion

Adaptable External partner

machine integration into
configurations business process
 Smart Manufacturing Ecosystem www.cmti-india.net

Power Mgmt &

Energy Grid Heating - Furnaces
Smart Manufacturing
Platform Open Infrastructure

• SM Software Marketplace
Line Operations

Suppliers
SM Value Proposition
Distribution
Applications Sustainability
& Safety
Context
Mapping
Private Data
Event Data Time Series
Customers
Smart Manufacturing
Platform Appliance
Production Calibration & Sensor
Models Maintenance Data
Traditional Manufacturing Automation
Environment and Software Tools
 IIoT Integration www.cmti-india.net

World Economic Forum Agenda 2015, Accenture. Industrial Internet of Things: Unleashing
the Potential of Connected Products and Services. January 2015
 Smart Manufacturing: Multi-Layered
Seams, Time, Data & Action www.cmti-india.net

Machines – People - Materials Dynamic Manufacturing Ecosystem

Design Materials & Product In

Prototype Qualification Service
Data Process Tech Manufacturing
Macro Layer
Focus: 10x Multiple
10s Pass Variability
Control & Automation

control loops Reduction; Supply

Time – days Chain Information

Business Systems
Meso Layer Focus: 100x Event
Variability/Tradeoff
100s Adjustment; Dynamic
control loops Performance Mgmt.;
Time -hours Integrated Metrics

1000s Micro Layer Focus: Insertion,

control loops Qualification, ICME, High
Time - minutes Fidelity Dynamic
Operations

Source: SMLC
Multifaceted Innovation – IoT/IIoT – www.cmti-india.net

Smart Manufacturing – Smart Factory

 IIoT Integration means… www.cmti-india.net

Integration RFID

Everything CONNECTED Mob

ile
 SMART Foundry 2020 (2016–2020) www.cmti-india.net

Sustainable Metalcasting by Advanced Research and Technology

Goal: Ultra-compact SMART Foundry, for sensor-driven automatic and
economic production of small intricate metal parts with high quality

DST Sanction = Rs. 8,25,15,160 Industry Contribution = Rs. 1,25,00,000

PIs: Co-PIs:
Dr. Savithri, NIIST, Trivandrum Dr. Arati V. Mulay, College of Engg., Pune
Dr. Sudip Kr. Samanta, CMERI, Durgapur Dr. Amit Sata, MEF College, Rajkot
Dr. A.M. Kuthe, VNIT, Nagpur Dr. Atul Sharma, IIT Bombay, Mumbai
Dr. G. Sutradhar, Jadavpur Univ, Kolkata Dr. Elizabeth Jacob, NIIST, Trivandrum
Industry: Dr. J.V.L. Venkatesh, SGGS Inst., Nanded
3D Foundry Tech Pvt Ltd., Mumbai Dr. Mayur Sutaria, CHARUSAT, Anand
Atomberg Technologies Pvt. Ltd., Mumbai Dr. Shyam Karagadde, IIT Bombay, Mumbai
Aha 3D Pvt. Ltd., Jaipur Dr. Vasudev Shinde, DKTE TEI, Ichalkaranji
Marcopolo Products Pvt. Ltd., Kolkata Mentors: Prof. B. Ravi, IIT Bombay
TREELabs Foundation, Mumbai Dr. Nagahanumaiah, CMTI Bangalore
Proposed SMART Foundry 2020 www.cmti-india.net

Sustainable Metalcasting by Advanced Research and Technology

Tooling Methods Process INPUT

Part CAD PREPARATION
Design Design Simulation

3D Pattern Automatic Melting + Inert/Vacuum

MFG.
Printer Molding Pouring MMC Process

Build status, Mold, Mixture, Weight, Power, Pressure, Flow,

SENSORS: Material, Accuracy Moisture, Weight Temperature Vibration, Mixing

Foundry Data Analytics Engine

Visualization Evaluation Optimization

ANALYTICS (Dashboard) (Quality, Time) (Process Par.)
Data
Material

Adding intelligence to manufacturing using Cloud, Big Data (from sensors) and Analytics
 www.cmti-india.net

Smart Foundry
Foundry Operation
Smart Foundry Business
Policy
Model of Data
Company
Big Data Business Model
- Innovate
Practice Valuation - Practice Knowledge to
Collective vs. Proprietary - Dominate Wisdom
Smart Foundry Enterprise Smart
Frog / Cloud Computing Management
Process Diagnosis –
Data Mapping–Process Smart Foundry – Manufacturing Prognosis-Control =
Analytics – Storage = C (Data-Information-Man-M/c-Matl.) Knowledge
Data Valuation Sensors, Data Acquisition: Device Converting Data
Control Data- Integration & Orchestration
IoT to Information
Real Data –
Corrected Data Process parameter, System controllers, Manpower Foundry
(actionable)
Resources
(Proprietary/
Autocast 3D Printing Molding M/c Melt - Pour
Shared)
Typical Foundry Data www.cmti-india.net
 Example: Automatic Molding Machine www.cmti-india.net

Investor /
Customers
Board
Software: Module -A Material Data
• Mold design data • Sand test data
Manager
• Pattern design • Resin properties
• Methoding results • Hardner property

Melting &
Pouring
Regularities

Process
Machine & Controller Data
Fettling & Analytics
Sand Reclaim

3D Printing Machine Data

Module –B1 Module –B2
• Pattern Actual data • Working (Spec.)
Resources limits
• Pattern Material Machine • Operation data
• Non-functional data Plant Utility • Real (Sensor) data
Smart Foundry Operation Version -1 www.cmti-india.net
 Smart Foundry Operation – V2 www.cmti-india.net

Casting Design & Methoding Regularities

(SS @ Trivendurm) Board (@ New Delhi)
(BR @ Mumbai)

Cloud
Sand Reclaimer & Quality
Process Data Analytics Manager
Pre-production - (EJ @ Triv.) (VS @ Kollhapur)
Post production: (AS @ Gj)

3D Printing of Pattern Mold Making Melting casting

(SS @ Trivendurm) (CMERI @ Durgapur) (Mayur @ Anand)
 www.cmti-india.net

23 April 2019 33
 Data cloud
Information flow and data
management Command & Feedback Signals
Management Information
www.cmti-india.net
HIGH SPEED HMC Diagnostic Signals
HIGH SPEED VMC

Real time health monitoring

Master controller with

CAD/CAM, PLM, MIS, ERP

Tool hive with

MASTER overhead
transportation
LEGACY MC 1 CONTROL

Multitasking machine

SMART
MANUFACTURING
LEGACY MC 2 DEMO CELL @
CMTI
Loading and unloading
Tool
station(Manual)
Washing setting(Manual)
station
RM and forgings Physical
Verification
CMM
-RFID Tagging

Assembly /
Packaging
AGV control & Shipping
station

23-04-2019 34
 Technologies to be developed for SMART
www.cmti-india.net

Factory Demonstration
• Smart Machines and Devices
– Developing pulg and play solutions to convert legacy machines to
smart machines for specific benefits
– Precision and multi functional smart machines
– Sensors Technologies: CMTI focused develop MEMS based
sensors for Temperature, Acoustics, Pressure and Flow
measurement
• Manufacturing Process Modeling and AI
– ANN based process models for metal cutting processes
– Operation/process planning models
• IIoT for manufacturing
– Machine to machine connection protocols
– Cloud computing
– Distributed manufacturing
 Consortium www.cmti-india.net

• Total Funding: 29 Crore under DHI capital goods scheme

• CMTI (DHI Funding) = 80%
• Industries = 20%
– Indian Machine Tool Manufacturers Association (IMTMA) = 1
Crore
– Utthunga Technologies Pvt. Ltd. Bangalore – 1 Crore
– L&T Technology Services, Bangalore (discussions are in progress)
• Constraints
• Convincing Indian industries to invest on this Industry 4.0
initiative is still daunting task.
– Poor awareness
– No single and universal solutions that ensure RoI
– Technologies need to be customized to specific industry
 Smart Manufacturing Demo and www.cmti-india.net

Development Cell
(SMDDC @ CMTI)

Objectives
Ingenious - Indigenous solutions to MSMEs

Smart Machines and Devices

Smart Manufacturing Protocols/Technologies
Industry Employable Manpower (Skilling & Reskilling)
Technology Transfer and Incubation
 Smart Building Blocks for Legacy Machines -
Mazak H400N – Legacy Machine www.cmti-india.net

MAKE MAZAK
MODEL H400N
Year of Manufacture 1996
Machine Type 4 Axis HMC
Control System Siemens 828D

MAZAK H400N
Scope : Smart Energy Management
Key Outcomes
Monitoring of Energy consumption
Distinguishing Idle energy and production energy
Power quality(Harmonic analysis done to ensure
machine internal electrical health)
Cycle time analysis based on power signature
KPI such as Energy per piece and identify
optimization potential through analytics to build a
Energy Monitoring Machine Cabinet Temp. Monitoring
business case
Spindle Health Monitoring Coolant pH and Refractive index
Machine Vibration Monitoring Monitoring
Hydraulic unit Monitoring Overall Machine Performance-OEE
IOT Enabled SMART Metal Cutting Machine www.cmti-india.net

Empower a Legacy Machine with Smart features to improve

process efficiency
Sensor Modules
 Temperature : spindle coolant Temp.
 Pressure : Spindle coolant pressure
 Vibration : Machine health
 Evaluate TcP (tool center point) drift
 Energy : Downtime of the machine
 Vision : In-situ inspection / Quality

Benefits • Predictive machine maintenance

• IOT enabled connected machine • Energy monitoring
• Remote access of machine health and • Better process control
process data • Improved part quality
• Real time Machine health monitoring • Reduced machine down time39
 Implementation Scheme www.cmti-india.net

Cloud
Machine
Storage
RTD PT100 sensors
Thermal Analog
Webserver
LEM Current Transducer

Current Analog

Accelerometer Local Edge Upload

Accelerometer Controller Controller

Communication
Analog

Serial
Pressure
Pressure
Analog
Computer Vision
RS 232 Dataset
Dashboard
 Snapshots of Web portal
Thermal Behavior of Machine(graphical) www.cmti-india.net
 Snapshots of Web portal
Machine Energy Monitoring (graphical) www.cmti-india.net
 Implementation: For the Demonstration of IOT Enabled Additive
Manufacturing www.cmti-india.net

A IOT enabled Control GUI has been developed to control the 3D printer in a closed
loop. The following features have been implemented.
 Cloud based 3D printing by uploading G-code via Any internet connected
device, i.e Mobile Phones & Tablets.
 Cloud based closed loop monitoring of process parameters & Temperature
signatures of subsystems of 3D printer
 A complete live fabrication process can be viewed online via IOT process
monitoring camera
 IOT Dash Board for Additive Manufacturing Machines www.cmti-india.net

 A complete IOT based dash board has been developed for process
monitoring of an
 additive manufacturing machine. It monitors temperature of extruder, base
plate & motors
 along with ambient humidity inside the machine & with material feed
monitoring.
 SMART METROLOGY LAB
www.cmti-india.net

Smart Inspection Facility encompassing

– Smart Measuring Instruments
– Smart Quality Monitoring
– Smart Process Monitoring

Smart Inspection Lab

A smart inspection and data management application for digital metrology is setup.
The application would collect, store, present digital data from Smart Bluetooth enabled instruments and data from other
instruments/ equipments / gauges and CMM.
Data analytics such as Cp, Cpk are also performed to provide process capability information.
 Summary www.cmti-india.net

• IoT + Big Data = Industrial Internet of Things

• What’s Different
– Cheap hardware
– Unlimited computing power
– Internet everywhere

• Product/Service Hybrids
– Change they way customers buy
– Rethink your go to market strategy

• Innovate & Dominate – Capacity Building

 Industry 4.0/Smart Factory Roadmap www.cmti-india.net

• What is Industry 4.0? Awareness???

– Industry 4.0 is not a technology, it is the current trend
that focus on data exchange and automation in
manufacturing.
– Predicting the process characteristics by acquiring the
data, digitising, sharing and analysing this data to
generate an information that can be used to
control/monitor/enterprise operation in the entire
value chain of product manufacturing.
– For Example, in metal cutting Industry 4.0 focus must
be on technological interventions that enhance spindle-
on-time, reducing machine breakdown and change in
machining conditions that ensure increase in
productivity.
 Industry 4.0/Smart Factory Roadmap www.cmti-india.net

• Prime headwinds in India

– Hard mindset for the change
– Skilled manpower: Availability & retining of the right
manpower
– Low technology maturity level: Many disruptive
technologies are being developed in parallel, maturity
level is low. Sustainability over a period might calls for
additional investments in future.
– High operational and MOR cost: Recurring cost is
expected to be quite high owing to limited resources
and proprietary technologies.
– Cost vs. benefits: No universal technologies,
customization??. One of the biggest questions in the
minds of investors is whether I4.0 technologies will
bring added market? If yes, will it be same for all?
 Industry 4.0/Smart Factory Roadmap www.cmti-india.net

• Developing technology building blocks & Customization

• Ingenious and Indigenous technologies
• Possible Approaches
– Converting individual legacy machines into smart
machines: The legacy machines to be embedded with
appropriate sensors that acquire process conditions in-
situ and process analytics using built-in process models.
– Connecting the machines: The shop floor networking
with appropriate M2M interfaces.
– Connecting networked shop floors to public network:
Use of cyber physical systems connects these
networked shop floor to public network and internet.
– Big data analytics and enterprises management
(MES/ERP) depending on the scale of operation,.
 Capacity Building ……….
www.cmti-india.net

• Smart and Sustainable

Manufacturing
– Innovative products
– Innovative processes
– Machines and Systems
• Sustainable Supply Chain
• Creative Value Chain
• Skilled and Creative HR
What is Required
• Industry 4.0 ?

• Smart and
Modular
Machines

• IOT - Bigdata,
Process
Analytics
 www.cmti-india.net

Product Innovation – Is it a Challenge?

Indian Education System:
 Science and Engineering study are in isolation
 School Education is rather percentage focused
 No active and participatory learning
 Example: Manufacturing is taught by faculty who had never operated
lathe
Social Obligation
 No importance to own passion
 We rather think more for comfort of next generation
Limited resources
 Look for Jugaad innovation: low cost solution and short cuts
 Low risk and short sight deliverables
 Passion towards imported technology that ensure RoI immediately
Poor Networking
 Throw on the wall approach: Everyone brings idea and thinks it works
for everyone
 No room for other’s views
 Social status: Religions, political ideologies
 Poor ethical standards
 Product-Process: Come with Engineers www.cmti-india.net

• To package and serve processed water

• Four parts? List…..
• Are they same?
• What are the differences?
• Guess, how they are being manufactured?
• Four parts?: Bottle, cap, label, water

• Are they same?: No

• Say difference?
– Material? ….different
– Geometry and size? ….. different
– Accuracy? ….. Non-uniform

• Making?
– Process?..... different
– Time?..... Different
– Cost? …… different
 Separate but Collaborate and Cooperate www.cmti-india.net

• 15-16 components
• 4-5 material
• Size all are different
• Highly precise

• How do you make?

– Different processes
– Measurement and testing
– Precision assembly
 CAR: Smart and Reliable but Economical
www.cmti-india.net

• ~ 15,000 parts
• Varieties of material
• Huge number of manufacturing processes
• Varying degree of assembly accuracy
• Manufactured by different vendors
• As an user, I want…
– More features
– High level of comfort
– Looks good
– Big/small
– Cost? … It should be less
– Time? … Today, if not now
• Do you think manufacturer’s job is easy?
• I am not a manufacturing engineer, am I
responsible?, Is it my headache?....
Everyone in the chain
– Designer, control engineer, supplier,
customer….
 Manufacturing – Serves for All www.cmti-india.net

[source: www.hitachi-tool.com.jp]
[source: www.phorn.co.uk]
• Removing material
• Shaping material
– Change in phase
– No phase change
• Adding material
• Assemble atoms
 www.cmti-india.net

Active Learning

Why plan for ‘Active’ Lectures?

Problem of Attention span
Psychological constraints on learning:

Concentration drops with sustained and unchanging low level activity

(such as sitting and listening), but to follow lecture content concentrated
effort is required).
10 – 15 mins
Students attention is typically maintained for _____________ minutes???
 www.cmti-india.net

Experiential Learning

I hear and I forget. I see and I remember. I do

and I understand. – Confucius (Chinese
Philosopher)
 Academia – R&D Lab. - Industry www.cmti-india.net

How can you do PBL, isn’t that what

“active learning” we have been
in mathematics? doing for the last
20 years with our
student projects?
That just won’t
work in
engineering

Retention,
We can’t afford to motivation,
spend time to teach engagement,
them skills that are learning, blah!!
unrelated to the core
subjects?
Policy and Management www.cmti-india.net

 Multi-Institutional Pan India Consortium

 Sustainable Technology Development is

Systematic Process - Follow Deming cycle

 Active learning is the key for great success

 Like minded people for right cause - Mantra

 Conclusions www.cmti-india.net

• First motivate ourselves to motivate others

• Our junior colleagues and students are the seeds
of today and are the crops of the future
• Active learning is the key in Science and
Engineering Education
• Students attention is typically maintained for
_____________
10 – 15 mins minutes???

•Made for India – Our weakness

•Make in India – Our Process
•Made in India – Our Pride
 www.cmti-india.net

THANKS!

Central Manufacturing Technology Institute, Tumkur

Road, Bengaluru - 560022, Karnataka, India
Email: director.cmti@nic.in; naga.cmti@nic.in
Ph. 9449842675
 Smart Machine tool and Intelligent
Machining

Prakash Vinod
Scientist-F & Head-Nano Manufacturing Technology Centre
Central Manufacturing Technology Institute, Bengaluru
 Outline

1 Introduction

2 Features of a smart machine tool

3 Introduction to Intelligent machining

4 Development of an Intelligent Ultraprecision Machine Tool

5 Intelligent Machining – CMTI initiatives

Central Manufacturing Technology Institute 2
 Introduction

 Smart machine is an intelligent device that uses machine-to-machine (M2M)

communication and are able to make decisions and solve problems without
human intervention.
 An Intelligent machine tool takes the CAD data, the materials and the set-
up plans as inputs and can take autonomous decisions and produce accurate
machined parts with quality, machine condition and productivity data as
outputs
 Machining processes evolved around Sensing, process model, knowledge
base and process control is intelligent machining.
 Development of technology for smart machine tools and intelligent machining
is one of focus area of CMTI activities
 Improvement in accuracy of products , along with productivity and ease of
operation is our targets for technology development in this domain
Central Manufacturing Technology Institute 3
 Main Features of a smart machine tool

• Adaptation to Changing conditions

1

• Open Architecture CNC and sensor interface

2

• Extensive Information processing capability

3

• Real time compensation of Geometrical & Thermo-elastic displacement errors

4

• Sensor based machine condition monitoring, Self Diagnostics

5

• Tool condition monitoring

6
4
Central Manufacturing Technology Institute
 Main Features of a smart machine tool

• Vibration and chatter control

7

• Sensor based Process monitoring

8

• Models for machining processes, Integration of sensory input with stored models
9 and process optimization/Control

• On Machine Metrology and automatic handling of work piece accuracy

10

• Provision for sharing & storing knowledge, IOT enabled

11

5
Central Manufacturing Technology Institute
 Concept of a Intelligent machine tool

Operator

Designed performance,
Work material, accuracy
required, workpiece
geometry, Depth entry
and exit CL Data
Generation Cutting Process Post-process
Measurement
Machine Drive

Servo
Supervision Control
Database

LEVEL 1

LEVEL 2 (Cutting Force, Temperature....)

LEVEL 3 (ON/OFF-line improvement with component measurement)

Central Manufacturing Technology Institute 6

Smart Machine tools – Enabling Technology –
Recent developments

Central Manufacturing Technology Institute 7

 What is Intelligent Machining

Sensors Process Models

Machining
processes
-Metal cutting
-Grinding

Intelligent Machining
Central Manufacturing Technology Institute 8
 Process Models

Knowledge-based systems

Neural Networks

Genetic Algorithms

Fuzzy Logic

Central Manufacturing Technology Institute 9

 Software Structure of Intelligent Machining

Filtering Learning

Data Knowledge:
Information
From the sensors Tool wear state,
Features which condense
Workpiece surface quality,
important signal information
Process control

Central Manufacturing Technology Institute 10

 Benefit from Intelligent Machining

1 Enhance reliability

2 Improved accuracy

3 Increase efficiency

4 Prevent damage

Central Manufacturing Technology Institute 11

Development of an Intelligent Ultra
Precision Turning Machine

12
 Intelligent Ultra precision Turning Machine (iUPTM)

A state of the art smart machine with intelligent features, developed by CMTI, for producing non-ferrous ,
IR and polymer components with optical quality . IUPTM a world-class, next generation machine tool with in-
built intelligence.
Applications: Electro-optics, Space, Defense, Ophthalmic Industries, Photonics
Intelligent Machine error Intelligent Machine Diagnostics
compensation Intelligent Ultra Precision  Spindle & Slide Health Monitoring
Real-time Positioning, Turning Machine (iUPTM)  On Machine Spindle balancing
Geometrical & Thermo elastic developed at CMTI  Sensor fault detection
error compensation taking  Tool condition monitoring
feedback from sensors mounted
on machine Remote monitoring,
diagnostics & control
Open architecture Motion through internet
Control
Can integrate user developed Intelligent Machining &
control algorithms Prognostics
Surface error predictions for
intelligent machining

Diamond Turned Mirrors

on CMTI’s iUPTM for
industrial applications
 iUPTM – Features
Modular, Future upgradeable
Linear Motor driven Real time machine error
Open Architecture Aerostatic slide Correction(Geometric, positioning &
Motion Controller thermally induced) Real time
diagnostics
Ultraprecision
(machine health, tool
Aerostatic spindle
wear)
Real time
Mist coolant Prognosis
system
Intelligent
Intelligent Machine
Ultraprecision Intelligence Intelligent
machining
Turning Machine
Natural Granite
base

On machine
Pneumatic Vibration Dynamic
isolator Balancing
Vacuum holding of
Job, Vacuum Active Vibration
Sensors (Vibration, force, Adaptive
assisted chip Control
Temp., AE, Pressure, etc) Control
extraction

Central Manufacturing Technology Institute 14

 Real-time geometrical error compensation module
 Development of error synthesis model using HTM method
 Formulation of error correction vector for the X axis and Z axis
 Error mapping using laser interferometer system for measurement of linear position error,
straightness error, orthogonal error and angular errors
 Designing the neural network and training it with the measured data.
 Extracting the key network parameters (weights and biases) and programming the real-time
calculations.
 Development of a „C‟ program for real time calculation of errors for compensation using error
correction vector
All geometrical
errors X Error correction
X Positions vector
Geometrical Error HTM Model
estimation using
Neural Networks
Z Positions

Z Error correction
vector
Block diagram of Real time Geometrical error compensation module

Central Manufacturing Technology Institute 15

Real Time Geometrical error compensation module -
Volumetric error plot for correction

Central Manufacturing Technology Institute 16

Geometrical error correction of X-axis in real time
through NN based program

17
Central Manufacturing Technology Institute
Geometrical error correction of X-axis in real time through
NN based program

Central Manufacturing Technology Institute 18

 Real-time Thermal Error Compensation for Machine
Tools

X1

X2 Y1

Flow Chart for Thermal Error Compensation

The Thermal induced displacement Errors can be reduced from 50 micrometres to 3 micrometres with the compensation
system. 19
Central Manufacturing Technology Institute
 Improvement in Machining accuracy with Real Time
thermal error compensation
Problem Statement : The radius use to go out of specification after machining of 5 to 6
components.

Spherical profile component machined in DTM

Parameter Specification
Radius (mm) 3.288 ± 0.001
Form (µm) 1.2

Nanoshape UPCMM
Central Manufacturing Technology Institute 20
Real-time Thermal Error Compensation Strategy for
Precision Machine tools

Real-time
Temperature
Acquisition

“C” Program reads

Motion Controller-
the temperature
Position correction
Real-time values
Operating
System (RTOS)

Writes the “C” Computes the

deformation errors thermal
in global variable deformation errors
based on NN

Central Manufacturing Technology Institute

21
Online Health Monitoring Of Machine Tool Spindle

Features:
• Autonomous, in-situ spindle health monitoring
system based on sensor feedback
• Online spindle problem identification using
frequency analysis.
• HMI provides “a basic window for machine
operators” and another window for “advanced
diagnostics ” with alarms.

Tools used
• LabVIEW for Data Acquisition,
Signal Processing and Human-
Machine interface layers
• MATLAB for Health
Assessment and Prognostics
layers
• Vibration Data accusation &
FFT analysis using NI DAQ
Card/Labview has been tried
out
• HMI Development &
Diagnostics using Labview
Central Manufacturing Technology Institute 22
Tool Condition Monitoring in Ultra precision Machining

23
Central Manufacturing Technology Institute
Tool Condition Monitoring In Ultra Precision Machining

Features:
• The system has Sensors, Signal
processing stages, Tool wear
estimation & Decision making
systems.
• User-friendly human-machine
interface for decision making

24
Central Manufacturing Technology Institute
 On-Machine Dynamic Balancing

Tools Used:
Accelerometer & Tacho
Probe/Encoder
Matlab Data Acquisition/
LabVIEW
Data Acquisition Card
Connecter Block

Flow Chart for balancing module

25
Central Manufacturing Technology Institute
 On Machine Tool Setting And Monitoring By CMTI-Optical
Tool Set Station (OpToSS)
Optical Tool Set Station (OpToSS):
 Tool Radius Measurement
 Tool Position offset (X & Z)
 Tool Height Setting (within 6µm)
 Tool Inspection (Damage & Wear)
 Light Intensity Control for Diamond & CBN Tools

Accuracy ≤ 5 µm
Kinematic mount ≤ 1.6 µm
Repeatability
Resolution 0.8 µm
Approx. Weight 2.5 Kg
(Ergonomically designed for ease
of handling and mounting)

Central Manufacturing Technology Institute

26
Optical Tool Set Station (OpToSS)

Central Manufacturing Technology Institute 27

 Sensor Failure Detection using Principal Component Analysis

 In iUPTM , multiple sensors are used for error compensations,

diagnostics and prognosis.
 Any failure in those Sensors can cause process disturbances, Loss of
control, loss of performance.
 Sensor degradations are difficult to detect and identify due to
correlative interactions.
 Automatic detection and identification of sensor faults is an asset for
effective monitoring and control of the process.

Central Manufacturing Technology Institute 28

 IOT Enabled “SMART” Metal Cutting Machine -
empowering a Legacy Machine @CMTI
Smart features Machine Tool: Milling Machine(5 axis
Sensor modules VMC)
 Temperature : Machine thermal plot
 Vibration : Machine health
 Evaluate TcP (tool center point) drift Dashboard
 Pressure : Spindle coolant pressure
 Energy : Downtime of the machine
 Vision : In-situ inspection / Quality

Outcome Outputs
 Generate diagnosis reports / action plan  IOT enabled connected machine
 Classify reports based on severity  Remote access of machine health and process data
 Real time Machine health monitoring
 Enable deep dive information for better process
 Energy monitoring
understanding  Better process monitoring 29
 Establish data base for further analytics  Reduced machine down time
 Converting a Legacy 3D printer to IOT enabled printer

A IOT enabled Control GUI has been developed to control the 3D printer in a closed loop. The following features
have been implemented.
 Cloud based 3D printing by uploading G-code via Any internet connected device, i.e Mobile Phones & Tablets.
 Cloud based closed loop monitoring of process parameters & Temperature signatures of subsystems of 3D printer
 A complete live fabrication process can be viewed online via IOT process monitoring camera

Central Manufacturing Technology Institute 30

 IOT Dash Board for 3D printer

A complete IOT based dash board has been developed for process monitoring of an additive manufacturing
machine. It monitors temperature of extruder, base plate & motors along with ambient humidity inside the
machine & with material feed monitoring.

31
Central Manufacturing Technology Institute
PREDICTION OF SURFACE FINISH IN DIAMOND TURNING
PROCESS

32
 Design of experiments

Machine Specifications
Work piece: Aluminium 6061 T6, Shape: Flat
Sl. No. Parameter Description
Tool : Natural mono crystalline diamond tool, Zero
1 Max. Work piece Size 400 mm Dia. Rake angle, nose radius of 3mm.
2 Surface Finish (Ra) ≤ 10.0nm
3 Speed range, rpm 50-7000
4 Load Capacity 85 Kg
5 No. of Axes (X,Z,C) 3

Vibration measurements : Uniaxial Piezo-electric

accelerometer and Vibration analyser
Surface roughness measurements : Optical Profiler

Central Manufacturing Technology Institute 33

 Prediction of Surface roughness-MRA

 Independent variables:
 Cutting conditions:
 Speed (S)
 Feed(f)
 Depth of Cut (doc)
 Vibration from Process:
 Vibration in tangential cutting force direction, Vx
 Vibration in feed direction, Vy
 Vibration in thrust cutting force direction, Vz
 Dependent variable: Surface finish
The Final equation obtained to estimate the surface finish is :
Surface finish = 5.7356 – 0.0003*S – 0.0018*f + 0.0313*doc + 48.0286*Vx - 197.563*Vy +
150 *Vz

Central Manufacturing Technology Institute 34

Neural network architecture for prediction of surface roughness

35
Prediction of Surface Roughness
Exp. Measured By ANN By MRA
No. Ra (nm)
Estimated % Estimated %
Ra (nm) Error Ra (nm) Error
1 6.48 6.48 0.04 6.25 3.62
2 6.46 6.47 0.21 6.21 3.94
3 6.39 6.39 0.05 6.02 5.72
4 6.94 6.27 9.60 6.58 5.20
5 6.97 6.87 1.45 6.75 3.09
6 6.08 6.09 0.19 5.98 1.66
7 4.74 5.20 9.70 4.87 2.84
8 6.09 6.09 0.07 6.25 2.56
9 Prediction
6.44 of Surface
6.56 Roughness
1.80 6.39 0.82
10 5.94 6.57 10.53 6.89 16.07
11 5.55 5.55 0.00 5.79 4.26
12 5.29 5.30 0.22 5.02 5.01
13 6.42 6.40 0.33 6.75 5.09
14 5.99 5.69 5.05 6.08 1.46
15 6.2 6.19 0.13 6.34 2.31
16 6.14 6.45 4.99 6.32 3.01
17 6.25 6.22 0.43 6.10 2.47
18 6.07 6.07 0.02 5.81 4.22
19 4.68 4.65 0.68 4.86 3.77
20 5.89 5.88 0.13 6.12 3.93
21 6.33 6.30 0.54 6.48 2.35
22 4.52 4.57 1.00 4.69 3.70
23 6.58 6.55 0.39 6.28 4.49
24 5.26 5.25 0.19 5.42 3.13
36
25 5.67 5.28 6.85 5.55 2.12
Comparison of measured and estimated values of
surface roughness

37
Results of the validation experiments using On Machine roughness
prediction module

8
7
Surface Roughness in

6
nanometers

5
4 On Machine
3 Prediction-
ANN
2 Measured
1
0
1 2 3 4 5 6 7

Experiment Number

38
Thank you
Thermal Behaviour of the Machine

Central Manufacturing Technology Institute 40

Energy Monitoring of the Machine

Central Manufacturing Technology Institute 41

Spindle Health Monitoring of the Machine

42
 Smart Sensors & Controls

V. Shanmugaraj
Central Manufacturing Technology Institute (CMTI)
Bangalore
 Smart Sensors & Controls

Internet of Things(IoT)

Sensors Controller Cloud

Smart Sensors & Controls

Smart Manufacturing (IIoT)

 Smart Sensors & Controls

Sensors
– Macro (Conventional)
– Micro (MEMS – Micro Electro Mechanical Systems)
 Smart Sensors & Controls
Sensors
– Temperature (upto 10Hz)
– Pressure
– Flow
– Force
– Torque
– Accelerometers (upto 20 KHz)
– Load Cells
– Acoustic (1 MHz)
– Displacement
– Velocity
– RFID
– Gyroscopes
 Smart Sensors & Controls

Temperature Sensors
– RTDs (Resistive Temperature Detecting)
– Thermistors
– Thermo-couples

– Factors
• Temperature Range
• Sensitivity
 Smart Sensors & Controls

Pressure Sensors
• Absolute – A Sensor that Measures Input Pressure in Relation to a
Zero Pressure – Altitude Measurement
• Differential – A Sensor that Is Designed to Accept
Simultaneously Two Independent Pressure Sources. The Output
Is Proportional to the Difference Between the Two Sources –
Airspeed Measurement
 Smart Sensors & Controls
Flow Sensors
– Variable Area (rotameters)
– Rotating Vane (paddle & turbine)
– Positive Displacement
– Differential Pressure
– Vortex Shedding
– Coriolis Mass
– Ultrasonic
 Smart Sensors & Controls
Force Sensors
– Piezo electric
– Strain Gauge

Torque Sensors
– Strain Gauge
 Smart Sensors & Controls
Accelerometers

– Piezo Resistive
– Piezo Electric
– Strain Gauge
– Inductive
 Smart Sensors & Controls
Load Cells
– Tensile
– Compression
– Bending Beam

– Strain Gauge

Displacement Sensors
– Capacitive
– Eddy Current
 Smart Sensors & Controls

Transduction Principle
– Change in Voltage
– Change in Current
– Change in Resistance
– Change in Capacitance
– Change in Impedance
– Change in Magnetic Field
 Smart Sensors & Controls

• Outcome
– Machine status monitoring
– Higher Productivity
– Lower down time of the machine
– Preventive maintenance
– Better utilization of Resources
Precision and Smart Metrology
K. Niranjan Reddy
Scientist - E & Head – UPE
CMTI, Bangalore.
An Old Saying

If You Measure

“Do it with Utmost Care”

and

“Remember the Measuring Errors”

Metrology

The Science of Precision Measurement

“METRO” & “LOGY” are Greek Words

Meaning

“Measurement” and “Science”

Respectively
Metrology

Metrology Started in Ancient Egypt in

2750 BC

First Unit of Length Was Cubit

Cubit - Length of the Reigning

Pharaoh’s Forearm
Journey towards Precision

• Started in 1775 with Wilkinson machining a

1800 mm bore to 1 mm accuracy
• Today conventional precision machining is
being carried out to dimensional accuracies of
1 m on 100 mm length
Dimensional Accuracies Since 1900

120 12
Accuracy in microns

100 10

IT Grades
80 8
60 6
40 4
20 2
0 0
1900 20 40 60 80 2000 10
Year
What is 1m

Human hair
 50 μm

1 μm

1nm=1/1000 μm
What is 1 arc sec

1 arc sec

Human hair  50 m
The Goal of Metrology

 Accept good products

 Reject bad products

 Better to reject few good ones

than to accept a few bad ones
Classification of Metrology

 Dimensional Metrology
 Surface Metrology
 Co-Ordinate Metrology
 Mass Metrology
 Force Metrology
and So on …..
Precision Measurements and Metrology

BASIC TERMINOLOGIES
Basic Terminologies
 RESOLUTION (of a displaying device)

Smallest value that can be indicated by the

displaying device.
or
Smallest difference between indications of a
displaying device that can be meaningfully
distinguished
Basic Terminologies
ACCURACY

Closeness of agreement between the result of

measurement and the true value of the measurand.

 PRECISION

Closeness of agreement between the results of

successive measurements of the same value of a
quantity carried out under identical conditions at
short intervals of time.
(Precision is also called Repeatability)
Graphic Distinction Between Accuracy and Precision

Precise but not Accurate

Accurate but not Precise

Precise and Accurate

REPRODUCIBILITY
Closeness of agreement between corrected
results of measurements of the same value of
a quantity when the measurements are made
under different conditions.

RELIABILITY
The ability of an item to perform a required
function under stated conditions for a stated
period of time.
Measurement Standard

Material measure or physical property

which defines or reproduces the unit
of measurement of a base or derived
quantity.
Types of Measurement Standard

FUNDAMENTAL OR ABSOLUTE STANDARD

INTERNATIONAL STANDARD
NATIONAL OR PRIMARY STANDARD
REFERENCE STANDARD
SECONDARY STANDARD
WORKING OR STANDARD
 TRACEABILITY

The concept of establishing valid calibration of a

measuring standard or instrument by step-by-
step comparison with better standards upto an
accepted national or international standard.
Hierarchy of Traceability
Primary Standard of Length (Metre)
Established by Interferometry The metre is defined
as the length of the
path travelled by light
Secondary Standard of Length in a vacuum in
Verified by Interferometry 1/299 792 458 second

Grade “00” Slip gauges Calibration Grade

Verified by Interferometry

Grade “0” & “1” Slip gauges

Verified by high magnification comparator

Grade “2” Slip gauges

Verified by high magnification comparator

Work piece
Verified by suitable gauging practice
19
Length Traceability at CMTI

20
Factors effecting the Accuracy of Measurements

S Factors affecting the Standard

W Factors affecting the Work-piece

I Factors affecting the Measuring Instruments

P Factors affecting the Person

E Factors affecting the Environment

Factors affecting the Accuracy of Measurements

Environmental Effects:

 Room Temperature
 Part Temperature Stabilization
 Temperature Variation
 Humidity
 Vibration Level
 Dust Level
 Air Flow
 Lighting
Precision Metrology Laboratory at CMTI

NABL Accredited Dimensional Metrology Lab

Lab conforms to ISO/ IEC 17025:2005
Measurement of Dimension, Form, Surface Texture and Gear Parameters

“India’s one of the kind

metrology lab that is housed
6m below ground”
23
Precision Metrology Laboratory at CMTI

Vibration
Temp: 20
: < 0.2
 0.5C
m

“India’s one of the kind Clean

metrology lab that is housed Noise: Room
<60 dB Class:
6m below ground” 10,000
24
Dimensional Metrology at CMTI

Ultra Precision Co-ordinate Measuring Machine

Co-ordinate Measuring Machine

Gauge Block Interferometer

Surface Metrology at CMTI

Form profiler Roughness Tester

Flatness interferometer Optical Profiler

Trends of Accuracy/ Uncertainty in Length Measurement
Metrology Artefacts

OPTICAL FLAT GLASS HEMISPHERE MASTER CYLINDER

COORDINATE MEASURING MACHINE (CMM) AND MASTER SPHERE

Current Status: In the country most of these artefacts (>90 %) are being imported28
Efforts of CMTI in development of Indigenous
Metrology Artefacts
High Precision Optical Standard Glass Scales

Technical Data
Graduation Pitch : 0.1 mm
Graduation thickness : 12 µm
Grating Accuracy : < 2 µm Technical Data
Range L W T Graduation Pitch : 1°
0-150 mm 175 mm 20 mm 5 mm Graduation thickness : 4 µm
0-10 mm 75 mm 20mm 5 mm
Grating Accuracy : < 2 µm

Linear Standard Glass Scales Angular Standard Glass Scale

In-house facility used:

1. Femtosecond laser micromachining system
2. Confocal Microscope
3. Ultra Precision CMM 29
Transformative Forces Reshaping the
Future of Metrology
The need for Smart Metrology
Smart Metrology Challenges

• Measurement time
Product flow • Accessibility of features
• Motion and handling...

• Temperature
Environment • Humidity
• Vibrations, contamination…

• Multiple features per product

Diversity • Variation between products

• Task-specific uncertainty,
Data handling • Numerical accuracy and Data integrity
• Data fusion from multiple sensors…
Factors to consider in adapting Smart Metrology

INLINE NON-CONTACT:
METROLOGY OPTICAL AND LASER
SYSTEMS

ROBOTS
Smart Metrology Lab

Manual Inspection Auto Ballooning

Data

CMM Data Inspection Reports

Cloud / Server

Wireless Measuring Quality Control

Instruments Data
Smart Metrology Lab

Smart Smart Data Smart Quality

Inspection Management Management
• Automatic • Integration across • Improved
generation of • Inline Traceability
Inspection Data • Manual • Statistical Process
sheet control data
• CMM Inspection
• Wireless (Cp,Cpk)
• Real Time Data
exchange of • Customized
Visualisation
inspection data Inspection reports
Smart Inspection

Smart Inspection Facility encompassing

– Smart Measuring Instruments
– Smart Quality Monitoring
– Smart Process Monitoring

Smart Inspection Lab

A smart inspection and data management application for digital metrology is setup.
The application would collect, store, present digital data from Smart Bluetooth enabled instruments and data
from other instruments/ equipments / gauges and CMM.
Data analytics such as Cp, Cpk are also performed to provide process capability information.
 SMART Automated Inspection System Developed by CMTI
Auto-Correction Feedback

Multi Gauging System Multi Gauging System Multi Gauging System

for Sabot for Penetrator for Tail Piece

The system was developed for comparing

manufactured dimensions of the components with that
of the designed dimensions, record the deviations and
indicate whether the component can be accepted,
rejected or needs rework.
Automatic gauging significantly cuts down the
inspection time
 Eliminates human measurement error
SABOT PENETRATOR TAIL PIECE Measured data is stored and accessed from the
PC for statistical analysis.
Highlights:
Online correction for the dimensional variation by
•Automated Measurement of Internal Thread Parameters, Form Errors and automatically feeding the result of inspection to
Dimensions CNC system
•18 Parameters measured and documented in just over 3 minutes …..
Multi Sensor Implementations

Parallel Sensor Implementation Changeable Sensor

on a Co-ordinate Measuring Implementation on Surface
Machine Texture Measuring Device
Automated Integrations

Faster metrology due to the automated integration of a CMM into material flow by
Robot loading.
Process Correction Solutions

Measurement of X-offset / Tool Radius as well as automatic quick correction for it

from direct measurement of a production asphere.
Thank you
metrologylab.cmti@nic.in
 Focused Ion Beam milling of CMTI logo on a Silicon Wafer.
30kV, 50pA | Total length: 10µm | Height: 2µm approx

Central Manufacturing Technology Institute

A Forerunner in Manufacturing Technologies

Abhishek Suchak

Scientist B
Centre In-charge
Central Manufacturing Technology Institute
(Regional Centre-Rajkot)

Rajkot, 13.04.19
 Contents

About Centre 1
Expansion
Scope
Regional Centre

Catering industries across India

Background Image: SEM image of cross section of layered Electroless plating of Nickel
 About Rajkot Centre
• CMTI established a Regional Centre in Rajkot in 2002
operating from NSIC campus.
• Supports industries in Dimensional Metrology and Material
Testing
• Supports MSMEs in and around Gujarat and Western belt
of India

Current Beneficiaries

Machine Auto
Engineering Metallurgy Foundry Pump Bearing Kitchenware
Tool ancillary

Central Manufacturing Technology Institute | www.cmti-india.net 3

 Objectives
• Services to SMEs in the field of Dimensional metrology,
Material and Metallurgical Testing.
• Provide consultancy services to industries in the region for
establishing manufacturing, test and calibration facilities
and transfer of advanced manufacturing technologies to
enable faster growth of industries.
• Transfer of latest technologies to the industries through
training, seminar and workshops.
• To provide Practical Metrology knowledge to the
Engineering Students through workshops.

Central Manufacturing Technology Institute | www.cmti-india.net 4

 Facilities

Central Manufacturing Technology Institute | www.cmti-india.net 5

 Facilities

Central Manufacturing Technology Institute | www.cmti-india.net 6

 Contents
Centres 2
Expansion
Scope

Scope of Future Expansion

CMTI Regional Centre-Rajkot

Offering technological consultancy through in-house

R&D, Measurement and Calibration services and Human
Resource Development

Background Image: SEM image of Carbon Nano Tubes

 Scope
• NABL Accreditation
• Gear Testing Machine & Software to analyze Pressure angle, Module, Teeth
Profile etc.
• Contour Measuring Machine to cater more complex profiles
• CAD lab to assist MSME in Reverse Engineering
• Coating Thickness Machine to measure coating thickness
• CAM Profile Measuring Machine to check CAM profiles
• Upgradation of Existing LMM to serve various components
• Dedicated Training Programmes for Industries, Engineering Students & Engi
neering Faculties

Central Manufacturing Technology Institute | www.cmti-india.net 8

 Thank you
Looking forward to hear from you