Aggregate Planning Chapter 12 1 utdallas.edu/~metin

Chapter 12
Aggregate Planning
1
utdallas.edu/~metin
Learning Objectives
 Review
of forecasting
 Forecast errors
 Aggregate
planning
2
utdallas.edu/~metin
Phases of Decisions
 Strategy
or design:
 Planning:
 Operation

Forecast
Forecast
Actual demand
Since actual demands differs from forecasts so does
the execution from the plans.
– E.g. Supply Chain concentration plans 40 students per year
whereas the actual is ??.
3
utdallas.edu/~metin
Characteristics of forecasts


Forecasts are always wrong. Should include expected value and
measure of error.
Long-term forecasts are less accurate than short-term forecasts. Too
long term forecasts are useless: Forecast horizon
– Forecasting to determine
» Raw material purchases for the next week
» Annual electricity generation capacity in TX for the next 30 years

Aggregate forecasts are more accurate than disaggregate forecasts
– Variance of aggregate is smaller because extremes cancel out
» Two samples: {3,5} and {2,6}. Averages of samples: 4 and 4.
» Variance of sample averages=0
» Variance of {3,5,2,6}=5/2

Several ways to aggregate
– Products into product groups
– Demand by location
– Demand by time
utdallas.edu/~metin
4
Forecast Variability implies time zones
Frozen and Flexible zones
Volume
Firm Orders
Frozen Zone
Forecasts
Flexible Zone
Time
5
utdallas.edu/~metin
Time Fences in MPS
1
2
“frozen”
(firm or
fixed)
3
4
Period
5
6
“slushy”
somewhat
firm
7
8
9
“liquid”
(open)
Time Fences divide a scheduling time horizon into three
sections or phases, referred as frozen, slushy, and liquid.
Strict adherence to time fence policies and rules.
6
utdallas.edu/~metin
Planning Horizon
Aggregate planning: Intermediate-range capacity planning,
usually covering 2 to 12 months. In other words, it is matching the
capacity and the demand.
Long range
Short
range
Now
Intermediate
range
2 months
1 Year
7
utdallas.edu/~metin
Overview of Planning Levels

Short-range plans (Detailed plans)
– Machine loading
– Job assignments

Intermediate plans (General levels)
– Employment
– Output

Long-range plans
– Long term capacity
– Location / layout
– Product/Process design
8
utdallas.edu/~metin
Listen to Tom Thumb’s manager
-
-
-
Need more space in 2005 to expand the store
Allocate 25% of the floor space to fresh produce
During the winter months employ 6 cashiers during rush hours
On Wed before Thanksgiving, employ 12 cashiers throughout the
day
In the next two weeks, no Italian parsley will be delivered.
Shelve Dill instead of parsley
9
utdallas.edu/~metin
Why aggregate planning

Details are hard to gather for longer horizons
– Demand for Christmas turkeys at Tom Thumb’s vs Thanksgiving turkeys

Details carry a lot of uncertainty: aggregation reduces variability
– Demand for meat during Christmas has less variability than the total
variability in the demand for chicken, turkey, beef, etc.

If there is variability why bother making detailed plans, inputs will
change anyway
– Instead make plans that carry a lot of flexibility
– Flexibility and aggregation go hand in hand
10
utdallas.edu/~metin
Aggregate Planning
 Aggregate
planning: General plan
– Combined products = aggregate product
» Short and long sleeve shirts = shirt

Single product
– Pooled capacities = aggregated capacity
» Dedicated machine and general machine = machine

Single capacity
– Time periods = time buckets
» Consider all the demand and production of a given month together


Quite a few time buckets
When does the demand or production take place in a time bucket?
11
utdallas.edu/~metin
Planning Sequence
Corporate
strategies
and policies
Economic,
competitive,
and political
conditions
Business Plan
Aggregate
demand
forecasts
Establishes production
and capacity strategies
Production plan
Establishes
production capacity
Master schedule
Establishes schedules
for specific products
12
utdallas.edu/~metin
Aggregate Planning Inputs

Resources
– Workforce
– Facilities


Demand forecast
Policy statements
–
–
–
–
Subcontracting
Overtime
Inventory levels
Back orders
 Costs
–
–
–
–
–
–
Inventory carrying
Back orders
Hiring/firing
Overtime
Inventory changes
subcontracting
13
utdallas.edu/~metin
Aggregate Planning Outputs
 Total
cost of a plan
 Projected levels of inventory
–
–
–
–
–
Inventory
Output
Employment
Subcontracting
Backordering
14
utdallas.edu/~metin
Strategies

Proactive
– Alter demand to match capacity

Reactive
– Alter capacity to match demand

Mixed
– Some of each
15
utdallas.edu/~metin
Demand Options
to Match Demand and Capacity
 Pricing
– Price reduction leads to higher demand
 Promotion
– Not necessarily via pricing
– Free delivery, free after sale service
» Some Puerto Rico hotels pay for your flight
 Back
orders
– Short selling: Sell now, deliver later
 New
demand
– Finding alternative uses for the product
16
utdallas.edu/~metin
Capacity Options
to Match demand and Capacity

Hire and layoff workers, unions are pivotal
– Layoff: Emotional stress
» Fired Moulinex (appliances producer in France) workers start fire at the plant
– Hire: Availability of qualified work force
» Operators at semiconductor plants




Overtime/slack time
– How too use slack time constructively? Training.
– Overtime is expensive, low quality, prone to accidents
Part-time workers
– 35 hour work week of Europe
Inventories, To smooth demands
Subcontracting. Low quality. Reveals technological secrets
17
utdallas.edu/~metin
Fundamental tradeoffs in Aggregate Planning

Capacity (regular time, over time, subcontract)

Inventory

Backlog / lost sales: Customer patience?
Basic Strategies

Chase (the demand) strategy; Matching capacity to demand; the planned output
for a period is the expected demand for that period
– fast food restaurants

Time flexibility from high levels of workforce or capacity;
– machining shops, army

Level strategy; Maintaining a steady rate of regular-time output while meeting
variations in demand by a combination of options.
– swim wear
18
utdallas.edu/~metin
Use inventory
Matching the Demand with
Level or Time flexibility strategies
Demand
Use delivery time
Demand
Demand
19
utdallas.edu/~metin
Chase vs. Level
Chase Approach
 Advantages
Level Approach

Advantages
– Stable output rates and
workforce
– Investment in inventory is low
– Labor utilization in high

 Disadvantages
– The cost of adjusting output rates
and/or workforce levels
Disadvantages
– Greater inventory costs
– Increased overtime and idle
time
– Resource utilizations vary over
time
20
utdallas.edu/~metin
Techniques for Aggregate Planning
 Inputs:
–
–
–
–
Determine demand for each period
Determine capacities for each period
Identify policies that are pertinent
Determine units costs
 Analysis
– Develop alternative plans and costs
– Select the best plan that satisfies objectives
21
utdallas.edu/~metin
Cumulative output/demand
Technique 1: Cumulative Graph
1
Cumulative
production
Cumulative
demand
2
3
4
5
6
7
8
9
10
22
utdallas.edu/~metin
Technique 2: Mathematical Techniques
Linear programming: Methods for obtaining optimal
solutions to problems involving allocation of scarce
resources in terms of cost minimization.
Minimize Costs
Subject to: Demand, capacity, initial inventory
requirements
23
utdallas.edu/~metin
Summary of Planning Techniques
Technique
Solution
Characteristics
Graphical/
charting
Trial and
error
Linear
programming
Simulation
Optimizing
Intuitively appealing, easy to
understand; solution not
necessarily optimal.
Computerized; linear assumptions
not always valid.
Computerized models can be
examined under a variety of
conditions.
Trial and
error
Linear decision rule???
24
utdallas.edu/~metin
Basic Relationships
Example - Relationships
Workforce
Number of
workers in a
period
=
Number of
workers at end of
previous period
+
Number of
new workers
at start of the
period
-
Number of
laid off
workers at
start of the period
-
Amount used to
satisfy
demand in
current
period
Inventory
Inventory at
the end of
a period
=
Inventory at end
of the
previous
period
=
Output Cost
(Reg+OT+Sub)
+
Production in
current
period
+
Hire/Lay Off
Cost
Cost
Cost for a
period
+
Inventory Cost
+
Back-order
Cost
25
utdallas.edu/~metin
Technique 3: Simulation Example
Level Output
Period
Forecast
Policy:
1
2
3
4
5
6
200
200
300
400
500
200
Total
1800
Level Output Rate of 300 per period
Output
Cost
Regular
300
300
300
300
300
300
1800
$2
Overtime
$3
Subcontract
$6
Output-Forecast
100
100
0
-100
-200
100
0
Beginning
0
100
200
200
100
0
Ending
100
200
200
100
0
0
Average
50
150
200
150
50
0
600
$1
0
0
0
0
100
0
100
$5
Regular
$600
$600
$600
$600
$600
$600
$3,600
Inventory
$50
$150
$200
$150
$50
$0
$600
Back Orders
$0
$0
$0
$0
$500
$0
$500
Total Cost of Plan
$650
$750
$800
$750
$1,150
$600
$4,700
Inventory
Backlog
Costs
utdallas.edu/~metin
Average Inventory= (Beginning Inventory + Ending Inventory)/2
26
Technique 3: Simulation Example
Level Output + Overtime
Period
Forecast
Policy:
1
2
3
4
5
6
200
200
300
400
500
200
Total
1800
Level Output Rate+Overtime
Output
Cost
Regular
280
280
Overtime
280
280
280
280
1680
$2
40
40
40
0
120
$3
Subcontract
Output-Forecast
$6
80
80
20
-80
-200
-180
0
Beginning
0
80
160
180
100
0
Ending
80
160
180
100
0
0
Average
40
120
170
140
50
0
520
$1
0
0
0
0
80
0
80
$5
Regular
$560
$560
$560
$560
$560
$560
$3,360
Overtime
$0
$0
$120
$120
$120
$0
$360
Inventory
$40
$120
$170
$50
$0
$0
$520
Back Orders
$0
$0
$0
$0
$400
$0
$400
Total Cost of Plan
$600
$680
$850
$730
$1,080
$560
$4,640
Inventory
Backlog
Costs
27
utdallas.edu/~metin
Aggregate Planning in Services

Services occur when they are rendered
– Limited time-wise aggregation

Services occur where they are rendered
– Limited location-wise aggregation

Demand for service can be difficult to predict
– Personalization of service


Capacity availability can be difficult to predict
Labor flexibility can be an advantage in services
– Human is more flexible than a machine, well at the expense of low
efficiency.
28
utdallas.edu/~metin
Aggregate Plan to Master Schedule
Aggregate
Planning
Disaggregation
Master
Schedule
For a short planning range 2-4 months:
 Master schedule: The result of
disaggregating an aggregate plan;
shows quantity and timing of specific
end items for a scheduled horizon.
 Rough-cut capacity planning:
Approximate balancing of capacity
and demand to test the feasibility of a
master schedule.
29
utdallas.edu/~metin
Master Scheduling
Master schedule
– Determines quantities
needed to meet demand
– Interfaces with
»
»
»
»
Marketing
Capacity planning
Production planning
Distribution planning
Master Scheduler
– Evaluates impact of
new orders
– Provides delivery dates for
orders
– Deals with problems
» Production delays
» Revising master schedule
» Insufficient capacity
30
utdallas.edu/~metin
Master Scheduling Process
Inputs
Outputs
Beginning inventory
Forecast
Committed
Customer orders
Projected inventory
Master
Scheduling
Master production schedule
ATP: Uncommitted inventory
31
utdallas.edu/~metin
Preview of Materials Requirement Planning Terminology
Net Inventory After Production
Requirements=Forecast
Assuming that the forecasts include committed orders
Net inventory before production=
Projected on hand inventory in the previous period
- Requirements
Produce in lots if Net inventory is less than zero
Net inventory after production=
Net inventory before production+ Production
32
utdallas.edu/~metin
Projected On-hand Inventory
Beginning
Inventory
64 1
Customer Orders
(committed)
33
Projected on-hand
inventory
31
JUNE
2
3
4
5
30
30
30
40
1
-29
JULY
6
7
8
33
utdallas.edu/~metin
Example: Find ATP with lot size of 70
June
64
July
1
2
3
4
5
6
7
8
Forecast
30
30
30
30
40
40
40
40
Customer Orders
(Committed)
33
20
10
4
2
Projected on Hand Inventory
+
-
+
MPS: Production
-
+
70
Projected on Hand Inventory
31
Available to promise
Inventory until next
production
(uncommitted)
11
1
41
57
-
+
70
11
41
79
1
70
70
31
61
71
???
34
utdallas.edu/~metin
Summary
 Aggregate
planning:
conception, demand and capacity option
 Basic strategy:
level capacity strategy, chase demand strategy
 Techniques:
Trial and Error, mathematical techniques
 Master scheduling
35
utdallas.edu/~metin
Practice Questions
1. The goal of aggregate planning is to achieve a production plan that
attempts to balance the organization's resources and meet expected
demand.
Answer: True Page: 541
 2. A “chase” strategy in aggregate planning would attempt to match
capacity and demand.
Answer: True Page: 548
 3. Ultimately the overriding factor in choosing a strategy in aggregate
planning is overall cost.
Answer: True Page: 550

36
utdallas.edu/~metin
Practice Questions
1. Which of the following best describes aggregate planning?
A) the link between intermediate term planning and short term
operating decisions
B) a collection of objective planning tools
C) make or buy decisions
D) an attempt to respond to predicted demand within the
constraints set by product, process and location decisions
E) manpower planning
Answer: D Page: 541
37
utdallas.edu/~metin
Practice Questions
2.Which of the following is an input to aggregate planning?
A) beginning inventory
B) forecasts for each period of the schedule
C) customer orders
D) all of the above
E) none of the above
Answer: D Page: 561
38
utdallas.edu/~metin
Practice Questions
3.Which of the following is not an input to the aggregate
planning process:
A) resources
B) demand forecast
C) policies on work force changes
D) master production schedules
E) cost information
Answer: D Page: 545
39
utdallas.edu/~metin
Practice Questions
4. Which one of the following is not a basic option for
altering demand?
A) promotion
B) backordering
C) pricing
D) subcontracting
E) All are demand options.
Answer: D Page: 545
40
utdallas.edu/~metin
Practice Questions
5. Which of the following would not be a strategy associated with
adjusting aggregate capacity to meet expected demand?
A) subcontract
B) vary the size of the workforce
C) vary the intensity of workforce utilization
D) allow inventory levels to vary
E) use backorders
Answer: E Page: 546-547
41
utdallas.edu/~metin
Practice Questions
6. Moving from the aggregate plan to a master
production schedule requires:
A) rough cut capacity planning
B) disaggregation
C) sub-optimization
D) strategy formulation
E) chase strategies
Answer: B Page: 559
42
utdallas.edu/~metin