chapter 13 aggregate planning
Skip this Video
Download Presentation
Chapter 13 Aggregate Planning

Loading in 2 Seconds...

play fullscreen
1 / 45

Chapter 13 Aggregate Planning - PowerPoint PPT Presentation

  • Uploaded on

Chapter 13 Aggregate Planning. Seasonal variation in demand E.g. Ice Cream Factories Agora on employment and departmental space allocation. Long range. Intermediate range. Short range. Now. 2-3 months. 18 Months. Planning Horizon/Levels.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Chapter 13 Aggregate Planning' - vance-wilson

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
chapter 13 aggregate planning

Chapter 13Aggregate Planning

Seasonal variation in demand

E.g. Ice Cream Factories

Agora on employment and departmental space allocation

planning horizon levels
Long range

Intermediate range




2-3 months

18 Months

Planning Horizon/Levels

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

why do it
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.

Why do it?

Objective of Aggregate Planning

aggregate planning approaches
Maintain a level workforce

Maintain a steady output rate

Match demand period by period

Use a combination of decision variables

Aggregate Planning Approaches
level and chase strategies



Level and Chase Strategies




Level Output Strategy

Output less

than demand



Output exceeds


Chase Demand Strategy

Output above




Output below


cumulative graph










Cumulative Graph

Cumulative output/demand





example a personal plan
An NSU 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

Example - a personal plan
example a personal plan1
A NSU UG student

plan income

Bank 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?)

Example - a personal plan
general steps in ap
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.

General steps in AP
options to affect demand level

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.


Backorders (depend on customers’ willingness)

Develop new demand (market) during off-peak period

Options to affect demand level
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

Options to affect capacity
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.

Mathematical Techniques

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?

example solution


Beginning Inventory + Ending Inventory



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.
example 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.)

Example- Chase demand
quantitative approach
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)

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.

Disaggregating the aggregate plan
Master Scheduling Process

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.



projected on hand inventory
Beginning Inventory

Forecast is larger than Customer orders in week 3

Customer orders are larger than forecast in week 1

Forecast is larger than Customer orders in week 2

Projected On-hand Inventory

Figure 13.8



Relevant important ideas

aggregate planning in services
Services generally have variable processing requirements that make it difficult to establish a suitable measure of capacity.

Capacity availability can be difficult to predict

Services occur when they are rendered. Services cannot be stockpiled or inventoried so they do not have this option. It is considered "perishable,“

An empty hotel room cannot be held and sold later

Demand for service can be difficult to predict

Labor flexibility can be an advantage in services

Aggregate Planning in Services
time fences in mps
Time Fences in MPS
  • Time Fences – points in time that separate phases of a master schedule planning horizon.


“frozen”(firm orfixed)



calculating atp
Calculated only in current week and any week with MPS>0

Current period: on-hand plus any current period MPS, minus all orders in that and subsequent periods until next MPS

Later periods: MPS – all orders until next MPS

Calculating ATP
level production plan
level production plan

Different sales forecast - Same total: 120 units, starts lower, goes higher

chase production strategy
“Chase” production strategy

Production adjusts to meet demand

lot size of 30 units
Lot size of 30 units

Produce if projected balance falls below 5 units

Extra on-hand inventory is “cycle stock”

5 unit “trigger” is safety stock

bom formats
Indented BOM


Frame Assembly



Wheel Assembly


Hubs & Rims



BOM formats
  • Single-level BOM only shows one layer down.

Wheel Assembly



low level code numbers
Low-Level Code Numbers
  • Lowest level in structure item occurs
  • Top level is 0; next level is 1 etc.
  • Process 0s first, then 1s
  • Know all demand for an item
  • Where should blue be?







The low-level code controls the sequence in which the materialis planned in an MRP run: First the materials with low-level code 0 areplanned, then the materials with low-level code 1, and so on. The lowerthe low-level code, the higher the number that is assigned to thematerial.

llc drawing
LLC Drawing
  • Item only appears in one level of LLC drawing
  • Easier to understand
  • Simplifies calculations







final assembly schedule
Master Production schedule is anticipated build schedule

FAS is actual build schedule

Exact end-item configurations

Final Assembly Schedule
schedule stability
Stable schedule means stable component schedules, more efficient

No changes means lost sales

Frozen zone- no changes at all

Time fences

>24 wks, all changes allowed (water)

16-23 wks substitutions, if parts there (slush)

8-16 minor changes only (slush)

< 8 no changes (ice)

Schedule Stability