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Planning Horizon
Aggregate planning: Intermediate-
range capacity planning, usually
covering 2 to 12 months.
Short
range
Intermediate
range
Long range
Now 2 months 1 Year
Long-range plans
Long term capacity
Location / layout
Intermediate plans (General levels)
Employment
Output
Inventory
Subcontracting
Overtime/Under Time
Short-range plans (Detailed plans)
Machine loading
Job assignments/sequencing/work schedules
Overview of Planning Levels
Hierarchical Approach to Planning
Aggregate Planning
Also called “Sales and Operation
Planning”
The term has been coined by companies to
refer to the process that helps companies
keep demand and supply in balance
What does Aggregate Mean?
Overall terms
Product families or product lines rather than
individual products
Big picture approach to planning
Aggregate, for example # bicycles to be
produced, but would not identify bicycles by
colour, size, type etc.
Aggregate Planning
Quarter 1
Jan Feb Mar
150,000 120,000 110,000
Quarter 2
Apr May Jun
100,000 130,000 150,000
Quarter 3
Jul Aug Sep
180,000 150,000 140,000
Disaggregation
In the manufacturing environment the process of breaking down the aggregate plan into greater detail is called disaggregation
Disaggregation results in Master Production Schedule (MPS)
MPS Purchasing
Production of parts or components
Aggregate Plan to Master
Schedule
Aggregate
Planning
Disaggregation
Master
Schedule
Master schedule: The result of
disaggregating an aggregate plan;
shows quantity and timing of
specific end items for a scheduled
horizon.
Aggregate Planning
It determines the resource capacity a firm will need to meet its demand over an intermediate time horizon
In this time frame it is too early to determine production level by SKU but too late to arrange additional capacity
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
Why Aggregate Planning?
Provides for fully loaded facilities, thus
minimizing
Overloading and under loading
Minimizing cost over the planning period
Adequate production capacity to meet
expected aggregate demand
Optimize balance between demand and
supply
Why Aggregate Planning?
A plan for orderly and systematic change
of production capacity to meet peaks and
valleys of expected customer demand
Getting the most output for the amount of
resources available, which is important in
times of scarce production resources
Steps in Aggregate Planning
1. Begin with sales forecast for each
product that indicates the quantities to be
sold in each time period (usually weeks,
months, or quarters) over the planning
horizon (3-18 months)
2. Total all the individual product or service
forecast into one aggregate demand.
Steps in Aggregate Planning
3. Determine capacities (regular time, OT,
Subcontracting) for each period
4. Identify company policy (chase, level)
5. Determine unit costs for regular time, OT,
subcontracting, holding inventories, back
orders, layoffs etc.
Steps in Aggregate Planning
6. Develop alternative plans and compute
cost for each
7. Select the best alternative that satisfies
company’s objectives
Strategies for Meeting Demand
Proactive
Alter demand to match capacity
Reactive
Alter capacity to match demand
Mixed
Some of each
Strategies for Meeting Demand
Proactive strategies
Influencing Demand
Offer discounts and promotions
Increase advertising in slack periods
Counter seasonal products
Lawnmowers (summer) and snow-blowers (winter)
Strategies for Meeting Demand
Reactive Strategies
Changing inventory levels
Vary workforce size (hiring and lay-off)
Varying shifts
Varying working hours
Varying production through overtime or idle time
Subcontracting
Inputs to Aggregate Planning
Production rates
Demand forecast
Policies on work force changes
Costs (inventory, hiring, firing, OT, sub-
contracting)
Inventory levels
Outputs of Aggregate Planning
Total cost of a plan
Projected levels of
Inventory
Output
Employment
Subcontracting
Inventory Calculations
Inventory Calculations
# Workers Calculations
Graphical Method
Popular techniques
Easy to understand and use
Trial-and-error approaches that do not guarantee an optimal solution
Require only limited computations
Graphical MethodMonth Expected
Demand
Production
DaysDemand /
day
Avg. daily
demand
Jan 900 22 41 50
Feb 700 18 39 50
March 800 21 38 50
April 1200 21 57 50
May 1500 22 68 50
June 1100 20 55 50
6,200 124
Graphical Method
Note: Forecast differs from average demand
Aggregate Planning Techniques
Two pure forms of aggregate planning strategies
Level Production
Maintain constant workforce and adjust inventory
Chase Demand
Hiring and Firing people
Mixed Strategy
Combination of
Overtime, under time, & subcontracting
Part Time employees
Hiring and firing
Inventory
Backordering
Note: When one alternative: Pure Strategy
When two or more are selected: Mixed strategies
Level Strategy
It is an aggregate planning in which daily
or monthly production is uniform
Toyota and Nissan follow this strategy
Finished goods inventory go up or down to
buffer the difference between demand and
production
Works when demand is stable
Level Production Strategy
LEVEL PRODUCTION STRATEGY
Assume begin inventory: 2000
Chase Strategy
It attempts to achieve output rates that
match demand forecast for that period.
This strategy can be accomplished by:
Vary workforce levels (hiring and firing)
Chase Demand Strategy
CHASE DEMAND STRATEGY
OVERTIME & SUBCONTRACTING
Chase vs. Level
Chase Approach
Advantages
Investment in inventory
is low
Labor utilization in high
Disadvantages
The cost of adjusting
output rates and/or
workforce levels
Level Approach
Advantages
Stable output rates and
workforce
Disadvantages
Greater inventory costs
Increased overtime and
idle time
Resource utilizations vary
over time
Mixed Strategy
For most firms, neither a chase strategy
nor a level strategy is likely to prove ideal,
so a combination of options must be
achieved to meet demand and minimize
cost
More complex than pure ones but typically
yield a better strategy
Mixed Strategy
Examples
Do not hire or lay off workers, adjust the production
rate by varying the number of shifts, use inventory
and subcontracting to match supply and demand
Do not hire or lay off workers, use subcontracting
during periods of high demand and build inventory
during periods of low demand
MIXED STRATEGY
Linear Programming
Approaches to AP
Finds minimum cost solution related to
regular labour time, overtime,
subcontracting, caring inventory, and costs
associated with changing the size of
workforce
Mathematical Techniques to
Aggregate Planning
Linear Programming
Optimal solutions
Cost minimization
Profit maximization
Appropriate when cost and variable
relationships are linear
Application in industry limited
Transportation Method in AP
Transportation Method in AP
Transportation Method
(An Example)
Total Costs
Period Demand Regular
Production
Overtime Subcontract End
Inventory
1 900 1000 100 0 500
2 1500 1200 150 250 600
3 1600 1300 200 500 1000
4 3000 1300 200 500 0
Total 7000 4800 650 1250 2100
Total Cost: 4800×$20+650×$25+1250×$28+2100×$3 = $153,550
Transportation Method
(Second Example – Prob 7)
Transportation Method: Cost of
Plan Period 1: 50($0)+300($50)+50($65)+50($80)=$22,250
Period 2: 400($50)+50($65)+100($80)=$31,250
Period 3: 50($81)+450($50)+50($65)+200($80)=$45,800
Total Cost: $99,300
Simulation Models in AP
Development of computerized model under variety of conditions to find reasonably acceptable solutions
Advantages Lends itself to problems that are difficult to solve
mathematically
Experimenting system behaviour without any risk
Compresses time to understand system
Understand system behaviour under wide range of conditions
Simulation Models in AP
Limitations
Simulation does not produce optimal
solutions, it merely indicates approximate
behaviour for a set of inputs
Simulations are based on models, and
models are only approximation of reality
Summary of Aggregate
Planning Techniques
Technique Solution
Approach
Characteristics
Spreadsheet Heuristic (trial and
error)
Intuitively appealing,
easy to understand,
solution not optimal
Linear Programming Optimizing Computerized
Simulation Heuristic (trial and
error)
Computerized
models can be
examined under
various scenarios