Chapter 13
Aggregate Planning
An Overview of Aggregate Planning
Market
Demand
Product
decisions
(Chapter 4)
Research and
Technology
Work Force
Process planning &
capacity
p
y decisions
(Chapter 5)
Demand
forecasts,
orders
(Chapter 3)
Raw materials
i l
available
Inventory on
hand
Aggregate
plan
Master
M
t production
d ti
schedule &
MRP systems
(Chapter 15)
External
capacity
(subcontractors)
Detailed Work
Schedules
(Chapter 17)
12-2
Aggregate planning
It is an intermediate-range capacity
planning,
p
a
g, usua
usually
y covering
co e g 2 to 12
months.
Long range
Short
range
Now
IIntermediate
t
di t
range
2 months
1 Year
12-3
O
Overview
i
off Pl
Planning
i L
Levels
l
• Long-range
L
plans
l
– Long term capacity
– Location/layout
l
• Intermediate plans (2 to 12 months)
– Employment
– Inventory
Aggregate
Planning
g
• Short-range plans
– Machine loading
g
– Job assignments
12-4
Aggregate What?
• Demand for products in a family or
broad category
• Capacities from various sources
– Regular time
– Overtime
– Subcontracting
12-5
Aggregate Planning Example
Keepdry, a small manufacturing company (200 employees),
produces umbrellas. The company produces the following three
product lines: 1) the Executive Line, 2) the Durable Line and 3) the
Compact line shown in the following figure.
figure
Executive
Line
Durable
Line
Compact
Line
12-6
Aggregate Demand
10000
10000
8000
8000
6000
7000
6000
5500
4500
4000
2000
0
Jan
Fe b
Ma r
Apr
Ma y
J un
How can we meet demand?
12-7
Aggregate Unit
• In reality, production involves many products
in a variety
y of ways.
y
• As a medium-range planing tool, aggregation
does not need that level of detail.
• Therefore, products are lumped together to
form on one “product
product,” which is often in units
and hours.
12-8
Aggregate Unit -Example
Product
P
d t
Production time/unit (Hr)
Monthly demand (Units)
A
5
200
B
2.5
100
C
0.75
1000
Total production time required =
5(200) + 2.5(100)
2 5(100) + 00.75(1,000)
75(1 000) = 22,000
000 hours/month
12-9
Aggregate Unit - Capacity
Production capacity must be measured in the same
units as the aggregate
gg g
p
product.
For example
example, with 50 full time employees
employees, there are
(50 workers)(8 hours/day)(25 days/month) = 10,000
hours of production time available in a typical month
of 25 working days.
12-10
Aggregation Planning
Aggregate units are not actually produced, so the
aggregate
gg g
p
plan should be converted into
appropriate production schedules for individual
products which share the same p
p
process or machine
in the same period.
Answers to the sizing and time of production for
individual products may be obtained by
disaggregation -- breakdown of the aggregate plan
into a master production schedule (MPS), and we
will come back to this issue later.
12-11
What if current capacity is not enough?
What options
p
are available for better AP?
Demand Options
• Alternatives that may reduce the forecasted
demand fluctuations
– Advertising and price cuts/increase
– Backordering during high demand period
– Counter-seasonal product mixing
12-12
Wh t options
What
ti
are available
il bl ffor b
better
tt AP?
Supply Options
• Alternatives that may be available to change
intermediate- or short-term capacity
y g work force size by
y hiring
g or layoffs
y
– varying
– varying capacity through the use of overtime
or idle time
– using part-time workers
– changing
h
i inventory
i
t
levels
l
l
– subcontracting
12-13
Relevant Options and Their Costs
• Cost of hiring and laying off workers
• Inventory
I
t
holding
h ldi costs
t
• Overtime costs
• Subcontracting costs
12-14
Summary overview for more complex problems
Inputs to the
gg g
Planning
g Process
Aggregate
• A forecast of aggregate demand covering an
i t
intermediate-term
di t t
planning
l
i h
horizon
i
(6
(6-18
18 months)
th )
• The alternative means available to adjust short-to
medium-term system capacity, the costs of using each
alternative and the extent each alternative impacts
capacity
y
in terms of workforce
• The current status of the system
level, inventory level and production rate
12-15
Summary overview for more complex problems
Outputs off the
h
Aggregate
gg g
Planning
g Process
•Ap
production p
plan: aggregate
gg g
decisions
for each period in the planning horizon
about
– workforce level
– production
d ti rate
t
– inventory level
• Projected costs of the production plan
over the planning horizon
12-16
Aggregate Planning
Formal Statement
• Given the demand forecast Ft , t = 1,..., T
Pt : Production rate at time t
• Determine W : Workforce level at time t
t
I t : Inventory
ve to y level
eve at time
t et
• To minimize the relevant costs over the
planning horizon T.
12-17
Two Key Supply Strategies for Meeting
Demand
• Chase
Ch
demand:
d
d
– Matching capacity to demand; the planned
output for
f a period
d is the
h expected
d demand
d
d for
f
that period (without using inventory).
• Level capacity:
– Maintaining
g a steady
y rate off regular-time
g
output while meeting variations in demand by
y overtime
a combination of options (inventory,
etc).
12-18
Chase Strategy: Example
The forecasted demands (in thousand)
Month
1
2
3
4
5
Demand
12
11
13
11
12
6
15
Summary information
Current workforce
12 employees
p y
Production capacity 1,000 boxes/employee/month
Payroll cost
$1,730/person/month
Hiring cost
L ff costt
Layoff
$200
$300
12-19
Chase Strategy: Example
The forecasted demands (in thousand)
Month
1
2
3
4
5
Demand
12
11
13
11
12
6
15
Summary information
Current workforce
12 employees
p y
Production capacity 1,000 boxes/employee/month
Payroll cost
$1,730/person/month
Hiring cost
L ff costt
Layoff
$200
$300
12-20
Chase Strategy: Example-Solution
Month
Demand
D
d
(in 1000)
Employee
E
l
E l
Employee
Rqrd.
Hired
Layoffs
1
12
12
2
11
11
3
13
13
4
11
11
5
12
12
1
6
15
15
3
74
1
2
2
6
3
Total cost = 74 ((1730)) + 6(200)
( ) + 3(300)
( ) = $130,120
12-21
Level Strategy with Inventory: Example
The forecasted demands (in thousand)
Month
1
2
3
4
5
Demand
12
11
13
11
12
6
15
Summary information
Current workforce
Production capacity
y
cost
Payroll
12 employees
1,000 units/employee/month
$1,730/person/month
,
p
Inventory holding cost
Initial inventory
$0.17/unit/month
2,000 units
12-22
Level Strategy: Example-Solution
Month
Demand
D
d
(in 1000)
Employe
e Level
IInventory
t
(i
(in 1000)
Beginning
Ending
1
12
12
2
2
2
11
12
2
3
3
13
12
3
2
4
11
12
2
3
5
12
12
3
3
12
3
0
72
15
13
Ending Inv. = Beginning Inv. + Production - Demand
6
15
Total cost = 72 (1730) + 14
14,000(0.17)
000(0 17) = $126
$126,940
940
12-23
Summary overview for more complex problems
Basic Relationships
• Period-ending
g inventories or backlogs
g are
determined using the inventory balance equation
EI t = EI t - 1 + (O t - F t )
where O t = R t + OT t + S t
• A shortfall between the amount available to the
market [output during the period plus beginning
inventory]
y and the market demand is made up
p
(buffered) by inventory, backlog, overtime, parttime labor and/or subcontracting
g
12-24
Examples 1 and 2 on Pages 553-554
(Assigned problems 1 and 2)
• Aggregate
A
planning
l
i for
f next 6 period.
i d
• Production options
p
– Regular time, Overtime, Subcontractor
• Backlogs are also allowed
12-25
Examples 1 and 2
(Assigned problems 1 and 2)
• Conditions in Example 1
– Steady
y rate of regular
g
time output
p ((level
strategy) = 300 units/month
12-26
Examples 1 and 2
(Assigned problems 1 and 2)
• Conditions in Example 2
– Steady
y rate of regular
g
time output
p ((level
strategy) = 280 units/month
p
is available,, but maximum
– Overtime option
overtime is 40 units/month
12-27
(Assigned problems 1, 2, and 3)
• File name: AggregatePlanning_Example1 in Excel
template
Solutions
• 1: $6,350
• 2a: $4,670
• 2b: $4,800
$4 800
•T
Turn iin original
i i l EXCEL printouts
i t t with
ith your name
12-28
on (Due by ???)
Disaggregating the Aggregate Plan
• Breaking down the aggregate plan into
p
p
product requirements
q
in order
specific
to determine labor requirements,
materials and inventory requirements
materials,
• The result is a master schedule
– quantity and timing of specific end items
for a scheduled horizon
12-29
Figure
gu e 12-66
Master Scheduling Process
Inputs
Outputs
Beginning
g
g inventory
y
Forecast
Customer orders
Projected
j
inventory
y
Master
scheduling
Master production schedule
Uncommitted inventory
12-30
Figure
gu e 12-7
Output 1. Projected On-hand Inventory
Beginning
Inventory
64
Forecast
Customer Orders
(committed)
Projected on-hand
inventory
Customer orders are
larger than forecast in
week 1; p
projected
j
onhand
is 64-33 = 31
1
30
JUNE
2
3
30 30
4
30
5
40
33
20
10
4
2
31
1
-29
Forecast is larger than
customer orders in week 2;
projected
p
j
on-hand
inventory is 31-30 = 1
JULY
6
7
40 40
8
40
Forecast is larger than
customer orders in week 3;
projected
p
j
on-hand
inventory
12-31
is 1-30 = -29
Output 2. Master Production Schedule
64
Forecast
Customer Orders
(committed)
Projected on-hand
inventory
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
-29
MPS
6
40
7
40
8
40
70
1 + 70 – 30 = 41
12-32
2. Master Production Schedule
64
Forecast
Customer Orders
(committed)
Projected on-hand
inventory
MPS
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
70
6
40
7
40
1
-39
8
40
70
11 + 70 – 40 = 41
12-33
2. Master Production Schedule
64
Forecast
Customer Orders
(committed)
Projected on-hand
inventory
MPS
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
70
70
6
40
7
40
8
40
1
31
61
70
70
12-34
Output
p 3. Available-to-Promise Inventory
y
64
Forecast
Customer Orders
(
(committed)
itt d)
Projected on-hand
inventory
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
MPS
Available-toA
il bl t
promise inventory
(uncommitted)
11
6
40
7
40
8
40
1
31
61
70
70
70
70
56
68
70
70
12-35
3. Available-to-Promise Inventory
y
64
Forecast
Customer Orders
(
(committed)
itt d)
Projected on-hand
inventory
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
MPS
Available-toA
il bl t
promise inventory
(uncommitted)
11
6
40
7
40
8
40
1
31
61
70
70
70
70
56
68
70
70
12-36
3. Available-to-Promise Inventory
y
64
Forecast
Customer Orders
(
(committed)
itt d)
Projected on-hand
inventory
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
MPS
Available-toA
il bl t
promise inventory
(uncommitted)
11
6
40
7
40
8
40
1
31
61
70
70
70
70
56
68
70
70
12-37
Inputs of master
scheduling
h d li
Completed
p
Master Schedule
64
Forecast
Customer Orders
(committed)
Projected on-hand
inventory
1
30
2
30
3
30
4
30
5
40
33
20
10
4
2
31
1
41
11
41
MPS
Available-topromise inventory
(uncommitted)
11
6
40
7
40
8
40
1
31
61
70
70
70
70
56
68
70
70
Outputs of master
scheduling
12-38
Chapter 13
Ch
Aggregate Planning
• Discussion questions
– 2, 3, 7, 10
• Solved problem
–2
• Assigned problems
- 1, 2 (turn in Excel printouts)
- AggregatePlanning
gg g
g_Example1
p
in Excel
template
12-39
Aggregate Planning
• Goal: Specify the optimal combination of
–
–
–
production rate
workforce level
inventory on hand
12-40
When workforce level is to be determined..
• Suppose
S
that
th t your production
d ti requirement
i
t
is 1850 units. Each unit takes 5 hours to
produce
• There are 22 working days/month with 8
working hours/day
• How
H
many workers
k
you need
d to meet
production requirement?
p
q
12-41
When workforce level is to be determined..
determined
Production Planning Requirements (units)
Jan.
Feb.
Production requirement
1850
1425
Mar.
1000
Apr.
850
May
y
1150
Jun.
1725
Labor hours requred
Prod hrs.
Prod.
hrs equirement
eq irement
5000
4250
5750
8625
Apr.
22
176
May
22
176
Jun.
20
160
24
33
54
5
9250
hours/unit
7125
(1850 units * 5 hrs.
Number of working days
Production hrs/worker
Jan.
22
176
Feb.
19
152
Mar.
21
168
(22 days * 8 hrs.)
Workers required
Average = 40 workers
53
47
30
9250/176 = 53
12-42
Q
Quanti
ity
With average of 40 workers...
2000
1500
1000
500
0
1
2
3
4
5
6
Month
P d ti requirement
Production
i
t
P d ti capacity
Production
it
Capacity shortage maybe be met through OT or subcontracting
12-43
Summary of Planning Techniques
Technique
Solution
Characteristics
Graphical/
charting
Trial and
error
Linear
ea
programming
Linear
decision rule
Optimizing
Opt
g
Simulation
Trial and
error
Intuitively appealing, easy to
understand; solution not
necessarily optimal.
Computerized;
Co
pute ed; linear
ea assu
assumptions
pt o s
not always valid.
Complex, requires considerable
effort to obtain pertinent cost
information and to construct
model; cost assumptions not
always
l
valid.
lid
Computerized models can be
examined under a variety of
conditions.
Optimizing
12-44
Graphic or Informal Approach
• Provides
P
id a framework
f
k for
f evaluating
l ti an
aggregate plan
• Easy to use and understand
• Graphs of forecasted demand may assist
planner in generating a plan
• Model is flexible but no optimization
• Static - relies on the planner to generate a plan
12-45
Producction Ratte/Workiing Day
Forecast and Average Forecast Demand
80
70
Average of Forecast Demand
60
50
40
30
20
10
0
January February
March
April
May
June
Forecast Demand
d
12-46
Cu
umulativ
ve Deman
nd
Cumulative Forecast
300
250
200
150
100
50
0
January
February
March
April
May
Forecast Demand
June
12-47
Cumulattive Dem
mand
Cumulative Forecast
300
250
Production
Plan
200
150
Cumulative
Forecasted
Demand
100
50
0
January
February
March
April
May
Forecast Demand
June
12-48
Cumulaative Dem
mand
Cumulative Forecast
300
250
Production
Plan
200
150
Cumulative
Forecasted
Demand
100
50
0
January
February
March
April
May
Forecast Demand
June
12-49
A
Aggregate
Planning
Pl
i in
i Services
S i
• Services
S i
occur when
h they
h are rendered
d d
• Demand for service and capacity
available can be difficult to predict
• Labor
L b flexibility
fl ibilit can b
be an advantage
d
t
iin
services
12-50