Transcript Aggregate Planning - Sihombing15's (Haery Sihombing)

Aggregate Planning
Determine the quantity and timing of
production for the immediate future
 Objective is to minimize cost over the
planning period by adjusting
 Production rates
 Labor levels
 Inventory levels
 Overtime work
 Subcontracting
 Other controllable variables
Aggregate Planning
Required for aggregate planning
 A logical overall unit for measuring
sales and output
 A forecast of demand for intermediate
planning period in these aggregate units
 A method for determining costs
 A model that combines forecasts and
costs so that scheduling decisions can
be made for the planning period
Aggregate Planning
Marketplace
and
demand
Demand
forecasts,
orders
Product
decisions
Research
and
technology
Process
planning and
capacity
decisions
Workforce
Aggregate
plan for
production
Master
production
schedule and
MRP
systems
Detailed
work
schedules
Raw
materials
available
External
capacity
(subcontractors)
Inventory
on
hand
Figure 13.2
Aggregate Planning
 Combines appropriate resources
into general terms
 Part of a larger production planning
system
 Disaggregation breaks the plan
down into greater detail
 Disaggregation results in a master
production schedule
Aggregate Planning Strategies
1. Use inventories to absorb changes in
demand
2. Accommodate changes by varying
workforce size
3. Use part-timers, overtime, or idle time to
absorb changes
4. Use subcontractors and maintain a stable
workforce
5. Change prices or other factors to
influence demand
Capacity Options
 Changing inventory levels
 Increase inventory in low demand
periods to meet high demand in
the future
 Increases costs associated with
storage, insurance, handling,
obsolescence, and capital
investment
 Shortages can mean lost sales due
to long lead times and poor
customer service
Capacity Options
 Varying workforce size by hiring
or layoffs
 Match production rate to demand
 Training and separation costs for
hiring and laying off workers
 New workers may have lower
productivity
 Laying off workers may lower
morale and productivity
Capacity Options
 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
Capacity Options
 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
Capacity Options
 Using part-time workers
 Useful for filling unskilled or low
skilled positions, especially in
services
Demand Options
 Influencing demand
 Use advertising or promotion to
increase demand in low periods
 Attempt to shift demand to slow
periods
 May not be sufficient to balance
demand and capacity
Demand Options
 Back ordering during highdemand 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
Demand Options
 Counterseasonal product and
service mixing
 Develop a product mix of
counterseasonal items
 May lead to products or services
outside the company’s areas of
expertise
Aggregate Planning Options
Option
Advantages
Disadvantages
Some Comments
Changing
inventory
levels
Changes in
Inventory holding
human resources cost may
are gradual or
increase.
none; no abrupt
Shortages may
production
result in lost
changes
sales.
Applies mainly to
production, not
service,
operations
Varying
workforce
size by
hiring or
layoffs
Avoids the costs
of other
alternatives
Used where size
of labor pool is
large
Hiring, layoff, and
training costs
may be
significant
Aggregate Planning Options
Option
Advantages
Disadvantages
Some Comments
Varying
production
rates
through
overtime or
idle time
Matches seasonal
fluctuations
without hiring/
training costs
Overtime
Allows flexibility
premiums; tired
within the
workers; may not aggregate plan
meet demand
Subcontracting
Permits flexibility
and smoothing
of the firm’s
output
Loss of quality
control; reduced
profits; loss of
future business
Applies mainly in
production
settings
Aggregate Planning Options
Option
Advantages
Disadvantages
Some Comments
Using parttime
workers
Is less costly and
more flexible
than full-time
workers
High turnover/
training costs;
quality suffers;
scheduling
difficult
Good for unskilled
jobs in areas with
large temporary
labor pools
Influencing
demand
Tries to use
excess capacity.
Discounts draw
new customers.
Uncertainty in
Creates marketing
demand. Hard to
ideas.
match demand to Overbooking
supply exactly.
used in some
businesses.
Aggregate Planning Options
Option
Advantages
Back ordering May avoid
during highovertime. Keeps
demand
capacity
periods
constant.
Counterseasonal
product and
service
mixing
Disadvantages
Some Comments
Customer must be Allows flexibility
willing to wait,
within the
but goodwill is
aggregate plan
lost.
Fully utilizes
May require skills
resources; allows or equipment
stable workforce
outside the firm’s
areas of
expertise
Risky finding
products or
services with
opposite demand
patterns
Quantitative Techniques For APP
Pure Strategies
 Mixed Strategies
 Linear Programming
 Transportation Method
 Other Quantitative
Techniques

Pure Strategies
QUARTER
Spring
Summer
Fall
Winter
Example:
SALES FORECAST (LB)
80,000
50,000
120,000
150,000
Hiring cost = $100 per worker
Firing cost = $500 per worker
Regular production cost per pound = $2.00
Inventory carrying cost = $0.50 pound per quarter
Production per employee = 1,000 pounds per quarter
Beginning work force = 100 workers
Level Production Strategy
Level production
(50,000 + 120,000 + 150,000 + 80,000)
= 100,000 pounds
4
QUARTER
Spring
Summer
Fall
Winter
SALES
FORECAST
80,000
50,000
120,000
150,000
PRODUCTION
PLAN
INVENTORY
100,000
100,000
100,000
100,000
400,000
Cost of Level Production Strategy
(400,000 X $2.00) + (140,00 X $.50) = $870,000
20,000
70,000
50,000
0
140,000
Chase Demand Strategy
QUARTER
SALES PRODUCTION
FORECAST
PLAN
Spring
Summer
Fall
Winter
80,000
50,000
120,000
150,000
80,000
50,000
120,000
150,000
WORKERS
NEEDED
80
50
120
150
WORKERS WORKERS
HIRED
FIRED
0
0
70
30
20
30
0
0
100
50
Cost of Chase Demand Strategy
(400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000
Mixed Strategy


Combination of Level Production and Chase
Demand strategies
Examples of management policies



no more than x% of the workforce can be laid off in
one quarter
inventory levels cannot exceed x dollars
Many industries may simply shut down
manufacturing during the low demand season
and schedule employee vacations during that
time
Mixing Options to Develop a Plan
 Chase strategy
 Match output rates to demand forecast
for each period
 Vary workforce levels or vary
production rate
 Favored by many service
organizations
Mixing Options to Develop a Plan
 Level strategy
 Daily production is uniform
 Use inventory or idle time as buffer
 Stable production leads to better
quality and productivity
 Some combination of capacity
options, a mixed strategy, might be
the best solution
Graphical and Charting Methods
 Popular techniques
 Easy to understand and use
 Trial-and-error approaches that do
not guarantee an optimal solution
 Require only limited computations
Graphical and Charting Methods
1. Determine the demand for each period
2. Determine the capacity for regular time,
overtime, and subcontracting each period
3. Find labor costs, hiring and layoff costs,
and inventory holding costs
4. Consider company policy on workers and
stock levels
5. Develop alternative plans and examine
their total costs
Planning - Example 1
Month
Jan
Feb
Mar
Apr
May
June
Expected Demand
Production Days
900
700
800
1,200
1,500
1,100
6,200
22
18
21
21
22
20
124
Demand Per Day
(computed)
Total expected demand
Average
requirement = Number of production days
6,200
=
= 50 units per day
124
41
39
38
57
68
55
Production rate per working day
Planning - Example 1
Forecast demand
70 –
60 –
Level production using average
monthly forecast demand
50 –
40 –
30 –
0 –
Jan
Feb
Mar
Apr
May
June
22
18
21
21
22
20






= Month
= Number of
working days
Planning - Example 1
Cost Information
Inventory carrying cost
$ 5 per unit per month
Subcontracting cost per unit
$10 per unit
Average pay rate
$ 5 per hour ($40 per day)
Overtime pay rate
$ 7 per hour
(above 8 hours per day)
Labor-hours to produce a unit
1.6 hours per unit
Cost of increasing daily production rate
(hiring and training)
$300 per unit
Cost of decreasing daily production rate
(layoffs)
$600 per unit
Planning - Example 1
Month
Production at
50 Units per Day
Demand
Forecast
1,100
900
1,050
1,050
1,100
1,000
900
700
800
1,200
1,500
1,100
Jan
Feb
Mar
Apr
May
June
Table
13.3units
Total
Monthly
Inventory
Change
+200
+200
+250
-150
-400
-100
Ending
Inventory
200
400
650
500
100
0
1,850
of inventory carried over from one
month to the next = 1,850 units
Workforce required to produce 50 units per day = 10 workers
Planning - Example 1
Costs
Calculations
Inventory carrying
$9,250
Regular-time labor
49,600
Other costs (overtime,
hiring, layoffs,
subcontracting)
Total cost
Table 13.3
(= 1,850 units carried x $5
per unit)
(= 10 workers x $40 per
day x 124 days)
0
$58,850
Total units of inventory carried over from one
month to the next = 1,850 units
Workforce required to produce 50 units per day = 10 workers
Planning - Example 1
7,000 –
Cumulative demand units
6,000 –
5,000 –
4,000 –
Reduction
of inventory
Cumulative level
production using
average monthly
forecast
requirements
3,000 –
2,000 –
Cumulative forecast
requirements
1,000 –
Excess inventory
–
Jan
Feb
Mar
Apr
May
June
Planning - Example 2
Month
Jan
Feb
Mar
Apr
May
June
Expected Demand
Production Days
900
700
800
1,200
1,500
1,100
6,200
22
18
21
21
22
20
124
Demand Per Day
(computed)
41
39
38
57
68
55
Minimum requirement = 38 units per day
Production rate per working day
Planning - Example 2
Forecast demand
70 –
Level production
using lowest
monthly forecast
demand
60 –
50 –
40 –
30 –
0 –
Jan
Feb
Mar
Apr
May
June
22
18
21
21
22
20






= Month
= Number of
working days
Planning - Example 2
Cost Information
Inventory carrying cost
$ 5 per unit per month
Subcontracting cost per unit
$10 per unit
Average pay rate
$ 5 per hour ($40 per day)
Overtime pay rate
$ 7 per hour
(above 8 hours per day)
Labor-hours to produce a unit
1.6 hours per unit
Cost of increasing daily production rate
(hiring and training)
$300 per unit
Cost of decreasing daily production rate
(layoffs)
$600 per unit
Planning - Example 2
In-house production = 38 units per day
x 124 days
= 4,712 units
Subcontract units = 6,200 - 4,712
= 1,488 units
Planning - Example 2
Cost Information
$ 5 per unit per month
Inventory carry cost
In-house production = 38$10units
per day
per unit
x $124
5 perdays
hour ($40 per day)
Average pay rate
= 4,712
$ 7 perunits
hour
Subcontracting cost per unit
Overtime pay rate
(above 8 hours per day)
Costs Subcontract
Labor-hours
to produce a unit units
= Calculations
6,200
- 4,712
1.6 hours
per unit
Regular-time
labor
$37,696
7.6 workers
1,488
units
Cost
of increasing
daily production
rate = (=
$300
per
unit x $40 per
day x 124 days)
(hiring and training)
Cost
of decreasing daily production
rate
Subcontracting
14,880
(layoffs)
Table 13.3
Total cost
$52,576
perunits
unit x $10 per
(=$600
1,488
unit)
Planning - Example 3
Month
Jan
Feb
Mar
Apr
May
June
Expected Demand
Production Days
900
700
800
1,200
1,500
1,100
6,200
22
18
21
21
22
20
124
Demand Per Day
(computed)
Production = Expected Demand
41
39
38
57
68
55
Production rate per working day
Planning - Example 3
Forecast demand and
monthly production
70 –
60 –
50 –
40 –
30 –
0 –
Jan
Feb
Mar
Apr
May
June
22
18
21
21
22
20






= Month
= Number of
working days
Planning - Example 3
Cost Information
Inventory carrying cost
$ 5 per unit per month
Subcontracting cost per unit
$10 per unit
Average pay rate
$ 5 per hour ($40 per day)
Overtime pay rate
$ 7 per hour
(above 8 hours per day)
Labor-hours to produce a unit
1.6 hours per unit
Cost of increasing daily production rate
(hiring and training)
$300 per unit
Cost of decreasing daily production rate
(layoffs)
$600 per unit
Planning - Example 3
Cost Information
Inventory carryingDaily
cost
Forecast
Month
(units)
Subcontracting
Prod
Rate
cost
per
Jan
900
Average
pay
rate 41
Basic
Production
Cost (demand
x 1.6 hrs/unit
unitx $5/hr)
Extra Cost of
Extra Cost of
Increasing
$ 5 per Decreasing
unit per month
Production
Production
(hiring cost
) per(layoff
Total Cost
$10
unit cost)
$ 7,200
—
— ($40 per$day
7,200
$ 5 per hour
)
6,800
$ 7 per(=hour
2 x $600)
(above 8$600
hours per day)
Feb
700
39
5,600
—
Mar
800
38
6,400
—
Overtime pay rate
Labor-hours to produce a unit
$1,200
1.6
(= 1per
x $600)
hours
unit
$5,700
Apr of increasing
1,200
57
9,600 rate
—
Cost
daily
production
$300 per unit
(= 19 x $300)
(hiring and training)
$3,300
May
1,500
68
12,000
—
Cost of decreasing daily production rate(= 11 x $300)
$600 per unit
$7,800
(layoffs)
June
1,100
55
8,800
—
Table 13.3
(= 13 x $600)
$49,600
$9,000
$9,600
7,000
15,300
15,300
16,600
$68,200
Comparison of Three Plans
Cost
Plan 1
Inventory carrying
$ 9,250
Plan 2
$
0
Plan 3
$
0
49,600
37,696
49,600
Overtime labor
0
0
0
Hiring
0
0
9,000
Layoffs
0
0
9,600
Subcontracting
0
0
0
$58,850
$52,576
$68,200
Regular labor
Total cost
Plan 2 is the lowest cost option
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
General Linear Programming


(LP) Model
LP gives an optimal solution, but
demand and costs must be linear
Let
Wt = workforce size for period t
 Pt =units produced in period t
 It =units in inventory at the end of period t
 Ft =number of workers fired for period t
 Ht = number of workers hired for period t

LP MODEL
Minimize Z = $100 (H1 + H2 + H3 + H4)
+ $500 (F1 + F2 + F3 + F4)
+ $0.50 (I1 + I2 + I3 + I4)
Subject to
Demand
constraints
Production
constraints
Work force
constraints
P1 - I1
I1 + P2 - I2
I2 + P3 - I3
I3 + P4 - I4
1000 W1
1000 W2
1000 W3
1000 W4
100 + H1 - F1
W1 + H2 - F2
W2 + H3 - F3
W3 + H4 - F4
= 80,000
= 50,000
= 120,000
= 150,000
= P1
= P2
= P3
= P4
= W1
= W2
= W3
= W4
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Transportation Method- Example 1
QUARTER
EXPECTED
DEMAND
REGULAR
CAPACITY
OVERTIME
CAPACITY
SUBCONTRACT
CAPACITY
1
2
3
4
900
1500
1600
3000
1000
1200
1300
1300
100
150
200
200
500
500
500
500
Regular production cost per unit
Overtime production cost per unit
Subcontracting cost per unit
Inventory holding cost per unit per period
Beginning inventory
$20
$25
$28
$3
300 units
Transportation Tableau
PERIOD OF USE
PERIOD OF PRODUCTION
1
Beginning
1
2
2
0
Inventory
300
Regular
600
3
—
20
300
6
—
23
100
29
1000
100
34
100
37
500
Subcontract
28
31
34
Subcontract
Regular
23
—
26
1200
25
28
150
31
150
28
31
—
1300
Overtime
200
Regular
250
—
23
25
—
28
500
1300
Overtime
200
Subcontract
500
Demand
900
1500
1600
34
20
28
Subcontract
4
—
31
20
300
26
28
1200
Capacity
9
—
25
Regular
Unused
Capacity
4
Overtime
Overtime
3
3
3000
250
500
1300
200
31
500
20
1300
25
200
28
500
250
Transportation Method- Example 1
REGULAR
SUBENDING
PERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY
1
2
3
4
Total
900
1500
1600
3000
7000
1000
1200
1300
1300
4800
100
150
200
200
650
0
250
500
500
1250
500
600
1000
0
2100
Transportation Method- Example 2
Demand
Capacity:
Regular
Overtime
Subcontracting
Beginning inventory
Sales Period
Mar
Apr
May
800
1,000
750
700
50
150
100
Costs
Regular time
Overtime
Subcontracting
Carrying
$40
$50
$70
$2
per tire
per tire
per tire
per tire
700
50
150
tires
700
50
130
Transportation Method- Example 2
Important points
1. Carrying costs are $2/tire/month. If
goods are made in one period and held
over to the next, holding costs are
incurred
2. Supply must equal demand, so a
dummy column called “unused
capacity” is added
3. Because back ordering is not viable in
this example, cells that might be used to
satisfy earlier demand are not available
Transportation Method- Example 2
Important points
4. Quantities in each column designate the
levels of inventory needed to meet
demand requirements
5. In general, production should be
allocated to the lowest cost cell
available without exceeding unused
capacity in the row or demand in the
column
Management Coefficients Model
 Builds a model based on manager’s
experience and performance
 A regression model is constructed
to define the relationships between
decision variables
 Objective is to remove
inconsistencies in decision making
Other Quantitative Techniques
Linear decision rule (LDR)
 Search decision rule (SDR)
 Management coefficients model

Hierarchical Nature of Planning
Production
Planning
Capacity
Planning
Resource
Level
Product lines
or families
Aggregate
production
plan
Resource
requirements
plan
Plants
Individual
products
Master
production
schedule
Rough-cut
capacity
plan
Critical
work
centers
Components
Material
requirements
plan
Capacity
requirements
plan
All
work
centers
Manufacturing
operations
Shop
floor
schedule
Input/
output
control
Individual
machines
Items
Available-to-Promise (ATP)

Quantity of items that can be promised to the
customer

Difference between planned production and
customer orders already received
AT in period 1 = (On-hand quantity + MPS in period 1) –
- (CO until the next period of planned production)
ATP in period n = (MPS in period n) –
- (CO until the next period of planned production)
ATP: Example
ATP: Example (cont.)
ATP: Example (cont.)
Take excess units from April
ATP in April = (10+100) – 70 = 40 = 30
ATP in May = 100 – 110 = -10
=0
ATP in June = 100 – 50 = 50
Rule Based ATP
Product
Request
Yes
Is the product
available at
this location?
No
Availableto-promise
Yes
Is an alternative
product available
at this location?
No
Allocate
inventory
Yes
Is this product
available at a
different
location?
No
Is an alternative
product available
at an alternate
location?
Yes
No
Allocate
inventory
Capable-topromise date
Is the customer
willing to wait for
the product?
No
Lose sale
Availableto-promise
Yes
Revise master
schedule
Trigger production
Summary of Aggregate Planning
Methods
Techniques
Solution
Approaches
Important Aspects
Graphical/charting
methods
Trial and error
Simple to understand and easy
to use. Many solutions; one
chosen may not be optimal.
Transportation
method of linear
programming
Optimization
LP software available; permits
sensitivity analysis and new
constraints; linear functions
may not be realistic
Management
coefficients model
Heuristic
Simple, easy to implement; tries
to mimic manager’s decision
process; uses regression
Aggregate Planning for Services
Most services can’t be inventoried
Demand for services is difficult to predict
Capacity is also difficult to predict
Service capacity must be provided at the
appropriate place and time
5. Labor is usually the most constraining
resource for services
1.
2.
3.
4.
Aggregate Planning for Services
Controlling the cost of labor is critical
1. Close scheduling of labor-hours to
assure quick response to customer
demand
2. Some form of on-call labor resource
3. Flexibility of individual worker skills
4. Individual worker flexibility in rate of
output or hours
Law Firm Example
(1)
Category of
Legal Business
(2)
Best Case
(hours)
(3)
Likely
Case
(hours)
Trial work
Legal research
Corporate law
Real estate law
Criminal law
1,800
4,500
8,000
1,700
3,500
1,500
4,000
7,000
1,500
3,000
1,200
3,500
6,500
1,300
2,500
19,500
39
17,000
34
15,000
30
Total hours
Lawyers needed
(4)
Worst
Case
(hours)
(5)
Maximum
Demand in
People
(6)
Number of
Qualified
Personnel
3.6
9.0
16.0
3.4
7.0
4
32
15
6
12
Yield Management
Allocating resources to customers at
prices that will maximize yield or
revenue
1. Service or product can be sold in advance of
consumption
2. Demand fluctuates
3. Capacity is relatively fixed
4. Demand can be segmented
5. Variable costs are low and fixed costs are high
Yield Management
Yield Management (cont.)
Yield Management: Example-1
NO-SHOWS
PROBABILITY
P(N < X)
0
1
2
3
.15
.25
.30
.30
.00
.15
.40
.70
Optimal probability of no-shows
Cu
75
P(n < x) 
=
= .517
Cu + Co
75 + 70
Hotel should be overbooked by two rooms
.517
Yield Management : Example-2
Demand
Curve
Room sales
Potential customers exist who
are willing to pay more than the
$15 variable cost of the room
100
Passed-up
contribution
50
$ margin
= (Price) x (50
rooms)
= ($150 - $15)
x (50)
= $6,750
$15
Variable cost
of room
Some customers who paid
$150 were actually willing
to pay more for the room
Money left
on the table
$150
Price charged
for room
Price
Yield Management : Example-2
Demand
Curve
Room sales
100
Total $ margin =
(1st price) x 30 rooms + (2nd price) x 30 rooms =
($100 - $15) x 30 + ($200 - $15) x 30 =
$2,550 + $5,550 = $8,100
60
30
$15
Variable cost
of room
$100
Price 1
for room
$200
Price 2
for room
Price
Yield Management Matrix
Predictable
Unpredictable
Duration of use
Price
Tend to be fixed
Tend to be variable
Quadrant 1:
Quadrant 2:
Movies
Stadiums/arenas
Convention centers
Hotel meeting space
Hotels
Airlines
Rental cars
Cruise lines
Quadrant 3:
Quadrant 4:
Restaurants
Golf courses
Internet service
providers
Continuing care
hospitals
Making Yield Management Work
1. Multiple pricing structures must be
feasible and appear logical to the
customer
2. Forecasts of the use and duration of
use
3. Changes in demand
72
TIME - BREAK