Aggregate Planning

Meaning and Definition

Meaning of Aggregate Planning
• Aggregate Planning is an intermediate planning method used to
determine the necessary resource capacity a firm will need in order to
meet its expected demand.
• It is an intermediate range capacity planning, usually covering 2/3 to
12/18 months. In other words, it is the matching of capacity and the
demand in such a way that cost are minimized.
• Aggregate planning is a technique for adjusting production to the ups
and downs of demand.
• An aggregate plan gets its name from the fact that it must include
demand forecasts, resources and capacity and express these as an
aggregate, or combined, strategy Setting objectives through aggregate
planning may help your small business run more efficiently.
Definition
The term Aggregate Planning is defined as, “An operational activity
which does an aggregate plan for the production process, in advance of
2 to 18 month, to give an idea to management as to what quantity of
materials and other resources are to be procured and when, so that
the total cost of operations of the organization is kept to minimum
over that period”.

It is not concerned with individual products, but with a single aggregate

product representing all products.
Planning Horizon
Aggregate planning: Intermediate-range
capacity planning, usually covering 2 to 12 months.
The goal of aggregate planning is to achieve a
production plan that will effectively utilize the
organization’s resources to satisfy expected
demand.

Long range

Intermediate
range
Short
range

Now 2 months 1 Year

Planning Horizons
Long-range plans
(over one year)
Research and Development
New product plans
Capital investments
Facility location/expansion
Top
executives Intermediate-range plans
(2 to 12 months)
Sales planning
Production planning and budgeting
Operations Setting employment, inventory,
managers subcontracting levels
Analyzing operating plans

Short-range plans
(up to 3 months)
Job assignments
Operations Ordering
managers, Job scheduling
supervisors, Dispatching
foremen Overtime
Part-time help
Responsibility Planning tasks and horizon Figure 13.1
 Objectives of Aggregate Planning
⚫ Minimize cost and maximize profits
⚫ Minimize inventory investment
⚫ Minimize changes in workforce levels
⚫ Minimize changes in production rates
⚫ Maximize utilization of plant and equipment
 Manufacturing and Service
Aggregate Plans
Production Plan (manufacturing aggregate plan):
A managerial statement of the period-by-period (time-phased)
production rates, work-force levels, and inventory investment, given
customer requirements and capacity limitations.

Staffing Plan (service aggregate plan):

A managerial statement of the period-by-period staff sizes and
labour-related capacities, given customer requirements and capacity
limitations is known as service aggregate plan.
Aggregate Planning Inputs
⚫ Demand forecasting for ⚫ Costs
aggregate unit
⚫ Inventory carrying
⚫ Resources
⚫ Back orders
⚫ Workforce/production rate
⚫ Facilities and equipment ⚫ Hiring/firing
⚫ Policies ⚫ Overtime
⚫ Subcontracting ⚫ Inventory changes
⚫ Overtime ⚫ subcontracting
⚫ Inventory levels
⚫ Back orders
Aggregate Planning Outputs
⚫ Total cost of a plan
⚫ Projected levels of:
⚫ Inventory
⚫ Output
⚫ Employment
⚫ Subcontracting
⚫ Backordering
AGGREGATION
⚫ Aggregation is important because it is not possible to
predict with accuracy the timing and volume of
demand for individual items
The ways to aggregate:
⚫ Aggregate units of output per month
⚫ Dollar value of total monthly output
⚫ Measures that relate to capacity such as labor hours

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Aggregate Planning Strategies
⚫ Active strategy
⚫ Passive strategy (reactive strategy)
⚫ Mixed strategy
 Passive (reactive) Strategies in Aggregate
Planning: Basic Approaches
1) Chase approach
The chase method helps the firms to match production
and demand by hiring and firing workers as necessary to
control output. The Capacities (workforce levels,
production schedules, output rates, etc.) are adjusted to
match demand requirements over the planning horizon.
 Chase Demand
Demand

Units

Production

Time

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Russell/Taylor Oper Mgt 3/e Ch 11 - 12
Advantages:
• Anticipation inventory is not required, and investment
in inventory is low
• Labour utilization is kept high

Disadvantages:
• Expense of adjusting output rates and/or workforce levels
• Alienation of workforce
Example:
400000
2) Level Approach
The Level method allows for a constant rate of
production and uses inventory levels to absorb fluctuations
in demand. The Capacities (workforce levels, production
schedules, output rates, etc.) are kept constant over the
planning horizon
Advantages:
• Stable output rates and workforce levels
Disadvantages:
• Greater inventory investment is required
• Increased overtime and idle time
• Resource utilizations vary over time
 Level Production
Demand

Production
Units

Time

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Russell/Taylor Oper Mgt 3/e Ch 11 - 11
Example:
 Capacity and Demand
Importance
• If capacity and demand are nearly equal emphasis should
be placed on meeting demand as efficiently as possible.
• If capacity is greater than demand the firm might choose
promotion and advertising in order to increase demand.
• If capacity is less than demand the firm might consider
subcontracting a portion of the work load.
Demand and Capacity Options to Satisfy the Demand
Over the Planning period
⚫ Proactive: Involve demand options: Attempt to change
demand to match capacity
✔ Influence the demand
✔ Backordering
✔ Producing counter-seasonal products
⚫ Reactive: Involve capacity options: Attempt to change
capacity to match demand
✔ Changing inventory Levels
✔ Varying workforce size by hiring or firing (layoffs)
✔ Varying production rate through overtime or idle time
✔ Subcontracting
✔ Using part-time workers
 Demand Options (Proactive)
1. Influencing demand
◆ Use advertising or promotion
to increase demand in low
periods
◆ Attempt to shift
demand to slow
periods
customers to voluntarily shift
the demand count structures,
and limited period product promotions.

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 Demand Options
2. Back ordering during high- demand
periods
◆ Requires customers to wait for an order
without loss of goodwill or the order
◆ Most effective when there are few if any
substitutes for the product or service
◆ Often results in lost sales

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 Demand Options
3. Producing counterseasonal products
◆ Develop a product mix of
counter-seasonal items (furnaces and
air conditioners)
◆ However, may lead to products or
services outside the company’s areas
of expertise

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 Capacity Options (Reactive)
1. Changing inventory levels
◆ Increase inventory in low demand
periods to meet high demand in the
future
◆ High inventory may increase
costs associated with storage,
insurance, handling,
obsolescence, and capital
investment
◆ Low inventory may cause
shortages which may mean lost
sales due to long lead times and
poor customer service
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 Capacity Options(Reactive)
2. Varying workforce size by hiring or
firing (layoffs)
◆ Training and separation costs (benefit
severiance) for hiring and laying off
workers
◆ New workers may have lower productivity
◆ Laying off workers may lower morale and
productivity

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 Capacity Options (Reactive)
3. Varying production rate through
overtime or idle time
◆ Allows constant workforce
◆ May be difficult to meet large increases in
demand
◆ Overtime can be costly and may drive
down productivity
◆ Absorbing idle time may be difficult

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 Capacity Options
4. Subcontracting
◆ Temporary measure during periods of peak
demand
◆ May be costly
◆ Assuring quality and timely delivery may be
difficult
◆ Exposes your customers to a possible
competitor

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 Capacity Options (Reactive)
5. Using part-time workers
◆ Useful for filling unskilled or low skilled
positions, especially in services

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 Aggregate Planning Methods/
Techniques
Techniques for aggregate planning range from informal
trial-and-error approaches, which usually utilize simple tables or
graphs, to more formalized and advanced mathematical techniques.

Some Common Techniques;

• Graphical/ Charting Method

• Linear Programming
• Simulation
Graphical method
⚫ Aggregate planning using the graphical method involves
plotting various production and demand levels on a graph
to visually determine the optimal production plan that
minimizes costs or maximizes profits while satisfying all
constraints.
 Roofing Supplier Example 1
(Graphical Apprach)
Production Demand Per Day
Month Expected Demand Days (computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38
Apr 1,200 21 57
May 1,500 22 68
June 1,100 20 55
6,200 124
Table 13.2
Average Total expected demand
requirement = Number of production days
6,200
= = 50 units per
124
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 Roofing Supplier Example 1
Forecast Demand
Production rate per working day

70 –
Level production using average
60 – monthly forecast demand

50 –

40 –

30 –

0 –
Jan Feb Mar Apr MayJune = Month
22 18 21 21 22 20 = Number of
Figure 13.3 working days
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 Roofing Supplier Example 1
Cost Information
Inventory carrying cost $ 5 per unit per month
Subcontracting cost per unit $20 per unit
Average pay rate (regular production) $10 per hour ($80 per day)
$17 per hour
Overtime pay rate
(above 8 hours per day)
Labor-hours to produce a unit 1.6 hours per unit
Cost of increasing daily production rate $300 per unit
(hiring and training)
Cost of decreasing daily production rate $600 per unit
(layoffs)
w o r k f orce
c o n s tant ION
a n 1 – D UC T
Table 13.3 Pl E L P RO
LE V

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 Roofing Supplier Example 1
Production Monthly
Cost Information
Production at 50 Units Demand Inventory Ending
Month
Inventory Days cost per Day
carrying Forecast
$ 5 perChange Inventory
unit per month
Jan 22 cost per unit
Subcontracting 1,100 900 +200
$20 per unit 200
Feb 18 900 700 +200($80 per400
$10 per hour day)
Average pay rate
Mar 21 1,050 800 +250 650
$17 per hour
Overtime pay rate
Apr 21 1,050 1,20(above -150
8 hours per 500
day)
0 1.6 hours per unit
Labor-hours to produce a unit
May 22 1,100 1,50 -400 100
Cost of increasing daily production rate
0 $300 per unit
(hiring and training)
June 20 1,000 1,10 -100 0
Cost of decreasing daily production rate $600 per unit
Total units of inventory carried0 over from one
(layoffs)
month to the next = 1,850 units rce
rkfo1,850
s t a n t wo
Table Workforce
13.3 required to produce 50nunits
1 – n day = 10
coper
Pl a
workers
Workers Required =( 50 unit/day*1.6 hr/unit)/8 hr/worker/day
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 Roofing Supplier Example 1
Production Monthly
Costs
Cost Information
Production at 50 Units Calculations
Demand Inventory Ending
Month
Inventory
Inventory Days cost per Day
carrying
carrying Forecast
$9,250 $ 5 perChange
(= 1,850 unit per
units Inventory
month
carried x $5
Jan
Subcontracting 22 cost per unit
1,100 per
900
$20unit) +200
per unit 200
Feb
Regular-time 18labor 900 99,200 (= 700
10
$10workers+200
per hour x $80 per400
($80per day
day)x
Average pay rate
Mar 21 1,050 124 days) or
800 (6200 x 1.6650
+250 x10)
$17 per hour
Overtime pay rate
Apr costs 21
Other (overtime, 1,050 1,20(above -150
8 hours per 500
day)
hiring, layoffs, 0 1.6 hours per unit
Labor-hours to produce a unit
subcontracting)
May 22 1,1000 1,50 -400 100
Cost of increasing daily production rate
0 $300 per unit
Total cost
(hiring and training) $108,4
June 20 1,000
50 1,10 -100 0
Cost of decreasing daily production rate
0 $600 per unit
(layoffs)
Total units of inventory carried over from one o rce
rkfo1,850
Tablemonth o n s t a nt w
13.3to the next = 1,850 units n 1 –c
Pla
Workforce required to produce 50 units per day = 10
workers
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 Roofing Supplier Example 2
Production Demand Per Day
Month Expected Demand Days (computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38 MIN.
Apr 1,200 21 57
May 1,500 22 68
June 1,100 20 55
6,200 124
Table 13.2
Plan 2 – MİXED STRATEGY: Level the daily production to minimum
requirement over the planning horizon and meet the excess demand
with subcontracting
Minimum requirement = 38 units per day
Constant work force=(38*1.6)/8=7.6 workers
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 Roofing Supplier Example 2
Forecast demand
Production rate per working day

70 –

60 – Level production
using lowest
50 – monthly forecast
demand
40 –

30 –

0 –
Jan Feb Mar Apr MayJune = Month
22 18 21 21 22 20 = Number of
working days
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 Roofing Supplier Example 2
Cost Information
Inventory carrying cost $ 5 per unit per month
Subcontracting cost per unit $20 per unit
Average pay rate $10 per hour ($80 per day)
$17 per hour
Overtime pay rate
(above 8 hours per day)
Labor-hours to produce a unit 1.6 hours per unit
Cost of increasing daily production rate $300 per unit
(hiring and training)
Cost of decreasing daily production rate $600 per unit
(layoffs)

Table 13.3

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 Roofing Supplier Example 2
Cost Information
Inventory carry cost $ 5 per unit per month
In-house production = 38
$10units
Subcontracting cost per unit per unitper day
Average payx 124 days
rate $ 5 per hour ($40 per day)
= 4,712 units
Overtime pay rate
$ 7 per hour
(above 8 hours per day)
Subcontract
Labor-hours units
to produce a unit = 6,200 - per unit
1.6 hours

4,712
Cost of increasing daily production rate
(hiring and training)
$300 per unit

= 1,488
Cost of decreasing units rate
daily production $600 per unit
(layoffs)

Table 13.3

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 Roofing Supplier Example 2
Cost Information
Inventory carry cost $ 5 per unit per month
In-house production = 38
$10units
Subcontracting cost per unit per unitper day
Average payx 124 days
rate $ 5 per hour ($40 per day)
= 4,712 units
Overtime pay rate
$ 7 per hour
(above 8 hours per day)
Costs Subcontract
Labor-hours units
to produce a unit = 6,200 - per unit
Calculations
1.6 hours
Regular-time
Cost 4,712 labor
of increasing rate (7.6$300
$75,392
daily production workers x $80 per day x
per unit
(hiring and training) 124 days) or (4712 x 1.6 x
= 1,488
Cost of decreasing units rate 10)$600 per unit
daily production
Subcontracting
(layoffs) 29,760 (1,488 units x $20 per unit)

Table 13.3
Total cost $105,15
2
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 Roofing Supplier Example 3
Production Demand Per Day
Month Expected Demand Days (computed)
Jan 900 22 41
Feb 700 18 39
Mar 800 21 38
Apr 1,200 21 57
May 1,500 22 68
June 1,100 20 55
6,200 124

d l a y o ffs Table 13.2

h i ri ng an
– D
Plan 3 ASE DEMAN
CH
Production = Expected Demand

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 Roofing Supplier Example 3
Production rate per working day

Forecast demand and

70 – monthly production

60 –

50 –

40 –

30 –

0 –
Jan Feb Mar Apr MayJune = Month
22 18 21 21 22 20 = Number of
working days
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 Roofing Supplier Example 3
Cost Information
Inventory carrying cost $ 5 per unit per month
Subcontracting cost per unit $20 per unit
Average pay rate $10 per hour ($80 per day)
$17 per hour
Overtime pay rate
(above 8 hours per day)
Labor-hours to produce a unit 1.6 hours per unit
Cost of increasing daily production rate $300 per unit
(hiring and training)
Cost of decreasing daily production rate $600 per unit
(layoffs)

Table 13.3

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 Roofing Supplier Example 3
Regular
Cost Information
Production
Inventory carrying cost Cost Extra Cost$of
5 perExtra
unitCost
perofmonth
Daily (demand x Increasing Decreasing
Subcontracting
Forecast cost
Prod per
1.6unit
hrs/unit x $10 perProduction
Production unit
Month (units) Rate $10/hr) (hiring cost) (layoff cost) Total Cost
Average pay rate $ $ 5 per hour ($40 per day)
$
Jan 900 41 — —
14,400 14,400
$ 7 per hour
Overtime pay rate
Feb 700 39 11,200 — (above$1,200 12,4
8 hours per day)
(= 2 x $600) 00
Labor-hours to produce a unit 1.6 hours$600
per unit 13,4
Mar 800 38 12,800 —
(= 1 x $600) 00
Cost of increasing daily production rate $300 per unit
1,2training)
(hiring and $5,700 24,9
Apr 57 19,200 —
00 (= 19 x $300) 00
Cost of decreasing daily production rate $600 per unit
1,5 $3,300 24,3
(layoffs)
May
00
68 24,000
(= 11 x $300)
—
00
1,1 $7,800 25,4
June 13.3
Table 55 17,600 —
00 (= 13 x $600) 00
$99,200 $9,000 $9,600 $117,800
Table 13.4
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 Comparison of Three Plans
Cost Level Mixed Chase

Inventory carrying $ 9,250 $ 0 $ 0

Regular labor 99,200 75,392 99,200
Overtime labor 0 0 0
Hiring 0 0 9,000
Layoffs 0 0 9,600
Subcontracting 0 29,760 0
Total cost $108,450 $105,152 $117,800

Plan 2 is the lowest cost option Table 13.5

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 Mathematical Approaches
◆ Useful for generating strategies
◆ Transportation Method of Linear
Programming
◆ Produces an optimal plan
◆ Management Coefficients Model
◆ Model built around manager’s
experience and performance
◆ Other Models
◆ Linear Decision Rule
◆ Simulation
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APP by Linear Programming
⚫ Linear programming (LP) is a mathematical method used in
aggregate planning to optimize resource allocation over a specified
time period, typically to minimize costs or maximize profits while
satisfying various constraints. In the context of aggregate planning,
LP models help determine the optimal level of production for each
product or service offered by a company, considering factors such as
production capacity, inventory levels, workforce availability, and
demand forecasts.
⚫ 1.Objective Function: Define the objective, such as minimizing total
production costs, including inventory holding costs, hiring and layoff
costs, overtime costs, and subcontracting costs, or maximizing total
profit.
⚫ 2.Decision Variables: Identify decision variables representing the
quantities to be determined, such as the production levels for each
product/service, workforce levels, inventory levels, etc..
APP by Linear Programming Cont.
⚫ 3. Constraints: Specify constraints that must be satisfied, including
production capacity limitations, labor availability, storage capacity, demand
requirements, and any other operational constraints.
⚫ 4. Formulate the LP Model:Construct a mathematical model that expresses
the objective function and constraints as linear equations or inequalities.
⚫ 5. Solve the LP Model: Use LP solvers or optimization software to find the
optimal solution that minimizes costs or maximizes profits while satisfying
all constraints.
⚫ 6. Evaluate Sensitivity: Analyze the sensitivity of the solution to changes in
parameters such as demand forecasts, production capacities, or costs to
understand the robustness of the plan.By applying linear programming to
aggregate planning, companies can make informed decisions to meet
customer demand efficiently, minimize costs, and utilize resources
effectively over a planning horizon
APP by Linear Programming-Example.
Imagine you’re running a factory that makes rifles and pistols. Your goal is to make as
many weapons as possible while keeping costs low.
1. Objective:Your main aim is to minimize the total cost of making rifles and pistols.
2. **Decision:** You need to decide how many rifles and pistols to make.
3. **Constraints:**
- You can only make a certain number of weapons because of limited factory space
and equipment.
- You have a limited number of workers who can only work a certain number of
hours.
- You need to meet the demand for rifles and pistols from your customers.
- You can’t have too many weapons left over in inventory because it costs money to
store them.
4. Mathematical Model:
- You create a formula that calculates the total cost based on how many rifles and
pistols you make.
- You set up equations based on the constraints mentioned above.
5. Solution:
- You use a computer program to find the best combination of rifles and pistols to
make, which will give you the lowest cost while meeting all the constraints.
6. Adjustments:
- If any factors change, like demand or production capacity, you can rerun the
program to find the new best plan.
So, linear programming helps you figure out the most efficient way to produce
weapons by solving mathematical equations, considering all the limitations and goals
you have.
Aggregate Planning Using Linear
Programming-Example 2

QUARTER SALES FORECAST

Spring 80,000
Summer 50,000
Fall 120,000
Winter 150,000

Hiring cost = $100 per worker

Firing cost = $500 per worker
Inventory carrying cost = $0.50 pound per
quarter
Production per employee = 1,000 pounds per
quarter
Beginning work force = 100 workers
APP by Linear Programming
Minimize Z =$100 (H1 + H2 + H3 + H4)
+ $500 (F1 + F2 + F3 + F4)
+ $0.50 (I1 + I2 + I3 + I4)
Subject to
P1 - I1 = 80,000(1)
Demand I1 + P2 - I2 = 50,000(2)
constraints I2 + P3 - I3 = 120,000 (3)
I3 + P4 - I4 = 150,000 (4)
where Production 1000 W1 = P1 (5)
Ht = # hired for
constraints 1000 W2 = P2 (6)
period t
1000 W3 = P3 (7)
Ft = # fired for
period t 1000 W4 = P4 (8)
It = inventory at 100 + H - F = W (9)
1 1 1
end
Work force W 1 + H2 - F 2 = W 2 (10)
of period t
Pt = units constraints W 2 + H3 - F 3 = W 3 (11)
produced W 3 + H4 - F 4 = W 4 (12)
in period t
Wt = workforce
 Disaggregation of Aggregate Plan
◆ Working with aggregate units facilitates
intermediate planning.
◆ But to put this plan into action we should
decompose it, in other words, disaggregate it
and state it in terms of actual units of products
and plan the production for a shorter period of
time
◆ Breaking down aggregate product to real
specific products helps to calculate manpower,
material and inventory requirements in detail.
◆ Disaggregation results in a Master Production
Schedule (MPS) and MPS becomes input to
Material Requirements Planning (MRP).

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 Master Production Schedule
⚫ It indicates the quantity and timing of
planned production by taking into account
desired delivery quantity and timing as well
as on-hand inventory.
⚫ The MPS is one of the primary outputs of the
master scheduling process.
Rough-cut capacity Planning
(RCCP)
⚫ RCCP involves testing the feasibility of a
proposed MASTER SCHEDULE relative
to available capacities, to assure that no
obvious capacity constraints exist.

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 Disaggregating the aggregate
plan
⚫ For example, televisions manufacturer may have an aggregate
plan that calls for 200 television in January, 300 in February,
and 400 in March.
⚫ This company produces 21, 26, and 29 inch TVs, therefore
this three-month aggregate plan must be translated into
specific numbers of TVs of each type (Master Schedule) prior
to actually purchasing the appropriate materials and parts,
scheduling operations, and planning inventory requirements.
Aggregate Plan to Master Schedule
Jan Feb Mar.
Aggregate
Planning Aggregate
plan 200 300 400

Disaggregation Type Jan. Feb. Mar

21 100 100 100
Master
inch
schedule 26 75 150 200
Master inch
Schedule 29 25 50 100
inch
total 200 300 400
 Master scheduling
⚫ The result of disaggregating the aggregate
plan is a master schedule showing:
✔ the quantity and timing of specific end items
for a scheduled horizon, which often covers
about six to eight weeks ahead.
Master Scheduling Process

Inputs Outputs
Beginning inventory Projected inventory
Master
Forecast Master Production Schedule
Scheduling
MPS
Customer orders Uncommitted inventory
 Master schedule
⚫ Inputs:
⚫ Beginning inventory; which is the actual inventory on hand from
the preceding period of the schedule
⚫ Forecasts for each period demand
⚫ Customer orders; which are quantities already committed to
customers.
⚫ Outputs
⚫ Projected inventory
⚫ Production requirements (MPS)
Example: Master Schedule
A company that makes industrial pumps wants to
prepare a Master Production Schedule (MPS) for June and
July.
✔ Marketing has forecasted demand of 120 pumps for June
and 160 pumps for July.
✔ These have been evenly distributed over the four weeks in
each month: 30 per week in June and 40 per week in July.
Example: Master Schedule
⚫ Now suppose that there are currently 64 pumps in
inventory (i.e., beginning inventory),
⚫ There are customer orders that have been
committed for the first five weeks (booked) and
must be filled which are 33, 20, 10, 4, and 2
respectively.
⚫ Suppose a production lot size of 70 pumps is used.
⚫ Prepare the Master Production Schedule

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 The master schedule before MPS
Beginning
Inventory

Forecast is larger than

Customer orders in week 3

Customer orders are Forecast is larger than

larger than forecast in Customer orders in week 2
week 1
Master Production Schedule (MPS)

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Solution: The master schedule
⚫ The first step you have to calculate the on hand inventory
Week Inventory Requirements Net MPS Projected
from previous inventory inventory
week before MPS
1 64 33 31 31
2 31 30 1 1
3 1 30 -29 70 41
4 41 30 11 11
5 11 40 -29 70 41
6 41 40 1 1
7 1 40 -39 70 31
8 31 40 -9 70 61
Aggregate Planning for Services
1. Most services can’t be inventoried
2. Demand for services is difficult to predict
(Some customers request prompt service or go
elsewhere, if there is a waiting line)
3. Capacity is also difficult to predict
4. Service capacity must be provided at the
appropriate place and time
5. Labor is usually the most constraining
resource for services