1 Introduction to Operations Management Aggregate Planning CHAPTE R 12.

1Introduction to Operations Management

Aggregate Planning

CHAPTER

12

2Introduction to Operations Management

Planning Horizon

Aggregate planning: Intermediate-range capacity planning, usually covering 2 to 12 months. (Also called Macro planning)

ShortrangeShortrange

Intermediate rangeIntermediate range

Long rangeLong range

Now 2 months 1 Year

Personnel assignment, machine loading, etc

Employment level, output capacity, etc

Location, process and service selection, capacity (facility size), etc

3Introduction to Operations Management

Objective of Aggregate Planning

To develop a feasible production plan on an aggregate level that achieves a balance of expected demand and supply– usually demand and supply are converted to

aggregate units such as labour-hours, working days, general product units, etc.

4Introduction to Operations Management

Planning Sequence

Corporatestrategies

and policies

Economic,competitive,and political conditions

Aggregatedemandforecasts

Business Plan

Production plan

Master schedule

Establishes productionand capacity strategiesEstablishes productionand capacity strategies

Establishesproduction capacity

Establishesproduction capacity

Establishes schedulesfor specific products

Establishes schedulesfor specific products

5Introduction to Operations Management

Basic approaches

Level capacity: Maintaining a steady rate of regular-time output while meeting variations in demand by a combination of options.

Chase demand: Matching capacity to demand; the planned output for a period is the expected demand for that period.

6Introduction to Operations Management

Aggregate Planning Approaches

Maintain a level workforce Maintain a steady output rate Match demand period by period Use a combination of decision

variables

7Introduction to Operations Management

Level and Chase Strategies

Quantity

Output less than demand

Output exceedsdemand

Output abovenormal

Output belownormal

Normalcapacity

Outputlevel

Normalcapacity

Demand

Level Output Strategy

Chase Demand Strategy

Demand

Demand

8Introduction to Operations Management

Cumulative Graph

1 2 3 4 5 6 7 8 9 10

Cumulativeproduction

Cumulativedemand

Cum

ulat

ive

outp

ut/d

eman

d

9Introduction to Operations Management

Example - a personal plan

A HKUST UG student– One year expenses

» tuition 40,000» transportation 1000 x 12 = 12000» food and meal 2000 x 10 = 20000» summer 5000 x 2 = 10000» others 500 x 12 = 6000

– Total 88,000

10Introduction to Operations Management

Example - a personal plan

A HKUST UG student– plan income

» Government loan, etc 40000» private tutoring 2000 x 12 = 24000» part time job 2000 x 10 = 20000» summer job 6500 x 2 = 13000» family money 1000 x 10 = 10000

– Total 107000» saving 107000 - 88000 = 19000

Objective: income meets expenses; maximize saving; etc. (What do you call this?)

11Introduction to Operations Management

General steps in aggregate planning

1. Forecast demand in the period

2. Develop plan(s) to meet the demand by setting levels on output, employment, inventory, etc.

3. The plans are refined or reworked until a feasible and satisfactory plan is uncovered.

12Introduction to Operations Management

Options to affect demand level

Pricing– e.g., shift demands from peak periods to off-peak

periods. The more the elasticity, the more effective pricing will be on the demand pattern.

Promotion Backorders (depend on customers’ willingness) Develop new demand (market) during off-peak

period

13Introduction to Operations Management

Options to affect capacity Hire and fire workers - depends on the intensity of

labour used, the strength of the union, corporate culture, labour laws, etc.

Overtime/slack time - to keep a skilled workforce and allows employee to increase earnings

Partime workers - depend on nature of work Inventories - smooth production and buffer

against demand surge; could be costly Subcontracting - capacity increase in a short time

without heavy investment; less control

14Introduction to Operations Management

Average Inventory

Averageinventory

Beginning Inventory + Ending Inventory2

=

15Introduction to Operations Management

Mathematical Techniques

Linear programming: Methods for obtaining optimal solutions to problems involving allocation of scarce resources in terms of cost minimization.

Linear decision rule: Optimizing technique that seeks to minimize combined costs, using a set of cost-approximating functions to obtain a single quadratic equation.

16Introduction to Operations Management

Summary of Planning Techniques

T e c h n i q u e S o l u t i o n C h a r a c t e r i s t i c s

G r a p h i c a l /c h a r t i n g

T r i a l a n de r r o r

I n t u i t i v e l y a p p e a l i n g , e a s y t ou n d e r s t a n d ; s o l u t i o n n o t n e c e s s a r i l yo p t i m a l .

L i n e a rp r o g r a m m i n g

O p t i m i z i n g C o m p u t e r i z e d ; l i n e a r a s s u m p t i o n sn o t a l w a y s v a l i d .

L i n e a rd e c i s i o n r u l e

O p t i m i z i n g C o m p l e x , r e q u i r e s c o n s i d e r a b l ee f f o r t t o o b t a i n p e r t i n e n t c o s ti n f o r m a t i o n a n d t o c o n s t r u c t m o d e l ;c o s t a s s u m p t i o n s n o t a l w a y s v a l i d .

S i m u l a t i o n T r i a l a n de r r o r

C o m p u t e r i z e d m o d e l s c a n b ee x a m i n e d u n d e r a v a r i e t y o fc o n d i t i o n s .

17Introduction to Operations Management

Example (p.602)

Period 1 2 3 4 5 6 Total

Forecast demand 200 200 300 400 500 200 1800

The VP of Operations is about to prepare the aggregate plan that will cover six periods in the horizon. The company has forecasted the following demand:

The output cost is $2 per unit at regular time; $3 per unit at overtime; $6 per unit if subcontracted. Average inventory cost is $1 per unit per period. Back orders are possible, however, the Company estimated the cost to be $5 per unit per period. The initial inventory is zero. There are 15 workers and each worker is able to produce 20 units of the product per period. Can you help the VP to develop an aggregate plan?

18Introduction to Operations Management

Example - solution

Suppose the VP wants to use a leveling (capacity) approach, I.e., maintaining a steady rate of output. The total output by the workers at the regular time is 20 x 15 x 6 = 1800 which equals to the forecast demand.

Period 1 2 3 4 5 6 TotalForecast demand 200 200 300 400 500 200 1800Output-regular 300 300 300 300 300 300 1800Output-over timeOutput-subcontractOutput-excess 100 100 0 -100 -200 100 0InventoryInven.-beginning 0 100 200 200 100 0Inven.-ending 100 200 200 100 0 0Inven.-average 50 150 200 150 50 0Backlog 100CostRegular 600 600 600 600 600 600 3600OvertimeSubcontractHire/FireInventory 50 150 200 150 50 0 600Backorders 500 500

Total cost 650 750 800 750 1150 600 4700

20Introduction to Operations Management

Example (p.604)

Chase demand– The VP learned that a regular worker is retiring. Rather than

hiring new worker, the VP decides to use overtime. However, the maximum amount of overtime output is 40 units per period. Suggest an aggregate plan for the VP

– Regular worker produce 14 x 20 units = 280 units per period. The total deficiency is 120 units. These 120 units can be satisfied in 3 periods by overtime and can be produced during the periods of high demand (for cost consideration. Of course, you can put them in other periods too.)

Period 1 2 3 4 5 6 TotalForecast demand 200 200 300 400 500 200 1800Output-regular 280 280 280 280 280 280 1800Output-over time 40 40 40Output-subcontractOutput-excess 80 80 20 -80 -180 80 0InventoryInven.-beginning 0 80 160 180 100 0Inven.-ending 80 160 180 100 0 0Inven.-average 40 120 170 140 50 0Backlog 80CostRegular 560 560 560 560 560 560 3360Overtime 120 120 120SubcontractHire/FireInventory 40 120 170 140 50 0 520Backorders 400 500

Total cost 600 680 850 820 1130 560 4640

22Introduction to Operations Management

Quantitative approach

Suppose the VP wants to use a more quantitative approach that use overtime only and have in mind that the cost be minimized. Can you help him?

Let us define the following notation:

Pt = No. of units produced via regular time at period t, t=1, …, 6

Dt = Demand (in No. of units) at period t, t=1, …, 6

Ot = No. of units produced at period t in overtime, t=1, …, 6

It = Inventory level (in No. of units) at the end of period t, t=1, …, 6

For ease of handling, we introduce the concept of back order Bt at period t. The following is a kind of “conservation law”

It = It-1 + Pt - Dt , t = 1, …, 6.

The Objective function is given by:

Notice that I0 = 0 and B0 = 0, (D1, …, D6) = (200,200,300,400,500,200)

)I B O (P6

1ttttt

1,...,6 t0, I ,B

1,...,6t,40O0

1,...,6t,280P0

1,...,6 t,D B - I - B I O P

subject to

)I 5B 3O (2P

tt

t

t

t1-ttt1-ttt

6

1ttttt

24Introduction to Operations Management

Disaggregating the aggregate plan

The aggregate plan gives the level of demand and supply in aggregate units at the macro level. In order for the company to execute the plan, it needs to disaggregate the plan into appropriate units for implementation and monitoring. The output of this process is a master schedule and a master production schedule.

25Introduction to Operations Management

Master Scheduling Process

Masterscheduling

Beginning inventory

Forecast

Customer orders

Inputs Outputs

Projected inventory

Master production schedule

Uncommitted inventory

26Introduction to Operations Management

Master schedule

A master schedule is a schedule (usually in the form of a table) indicating the quantity and timing (I.e., delivery times) for individual products or a group of individual products.

27Introduction to Operations Management

Master Production Schedule (MPS)

A MPS is a schedule (usually in the form of a table) indicating the quantity and timing of planned production. In creating the MPS, the on-hand inventory is taken into account.

28Introduction to Operations Management

ExampleA Master ScheduleJune July

1 2 3 4 1 2 3 4Forecast demand 30 30 30 30 40 40 40 40

Initial inventory June Julyis 64 1 2 3 4 1 2 3 4Forecast demand 30 30 30 30 40 40 40 40Committed customerorders 33 20 10 4 2Projected on-hand inventoryMPSATP inventory

29Introduction to Operations Management

Initial inventory June Julyis 64 1 2 3 4 1 2 3 4Forecast demand 30 30 30 30 40 40 40 40Committed customerorders 33 20 10 4 2Projected on-handinventoryMPSATP inventory

Solution to MPS example

30Introduction to Operations Management

Initial inventory June Julyis 64 1 2 3 4 1 2 3 4Forecast demand 30 30 30 30 40 40 40 40Committed customerorders 33 20 10 4 2Projected on-handinventory 31 1 41 11 41 1 31 61MPS 70 70 70 70ATP inventory

Solution to MPS Example

31Introduction to Operations Management

Solution to MPS Example

Initial inventory June Julyis 64 1 2 3 4 1 2 3 4Forecast demand 30 30 30 30 40 40 40 40Committed customerorders 33 20 10 4 2Projected on-handinventory 31 1 41 11 41 1 31 61MPS 70 70 70 70ATP inventory 11 56 68 70 70