Aggregate planning and mps om

Aggregate Planning and
Master Production
Scheduling (MPS)

Overview of Aggregate Planning
 Aggregate planning begins with a forecast of aggregate demand for the intermediate range.
 This is followed by a general plan to meet demand requirements by setting output,
employment, and finished-goods inventory or service capacities.
 Managers must consider a number of plans, each of which must be examined in light of
feasibility and cost.
 If a plan is reasonably good but has minor difficulties, it may be reworked.
 Aggregate plans are updated periodically, often monthly, to take into account updated forecast
and other changes.

For Example
At the end of the aggregate production planning exercise, a
garments manufacturer may arrive at the following plan
Produce at the rate of 9000 meters of cloth everyday during the
months of January to march Increase it to 11000 meters during
April to august and change the production rate 10,000 meters
during September to December
Carry 10% of monthly production as inventory during the first
nine months of production
Work on a one-shift basis throughout the year with 20%
overtime during July to October

Aggregate Planning Inputs
• Resources
• Workforce/production
rate
• Facilities and equipment
• Demand forecast
• Policies
• Subcontracting
• Overtime
• Inventory levels
• Back orders
• Costs
• Inventory carrying
• Back orders
• Hiring/firing
• Overtime
• Inventory changes
• subcontracting

Aggregate Planning Outputs
Total cost of a plan
Projected levels of:
Inventory
Output
Employment
Subcontracting
Backordering

Aggregate Planning Strategies
Proactive
• Involve demand options: Attempt to alter demand to
match capacity
Reactive
• Involve capacity options: attempt to alter capacity to
match demand
Mixed
• Some of each

Demand Options
Pricing
Promotion
Back orders
New demand

Pricing
• Pricing differential are commonly used to shift demand from peak
periods to off-peak periods, for example:
• Some hotels offer lower rates for weekend stays
• Some airlines offer lower fares for night travel
• Movie theaters offer reduced rates for matinees
• Some restaurant offer early special menus to shift some of the
heavier dinner demand to an earlier time that traditionally has
less traffic.
• To the extent that pricing is effective, demand will be shifted so that
it correspond more closely to capacity.
• An important factor to consider is the degree of price elasticity of
demand; the more the elasticity, the more effective pricing will be in
influencing demand patterns.

Promotion
Advertising and any other forms of promotion, such as
displays and direct marketing, can sometimes be very
effective in shifting demand so that it conforms more
closely to capacity.
Timing of promotion and knowledge of response
rates and response patterns will be needed to achieve
the desired result.
There is a risk that promotion can worsen the
condition it was intended to improve, by bringing in
demand at the wrong time.

Back order
An organization can shift demand to other periods by
allowing back orders. That is , orders are taken in one
period and deliveries promised for a later period.
The success of this approach depends on how willing
the customers are to wait for delivery.
The cost associated with back orders can be difficult
to pin down since it would include lost sales, annoyed
or disappointed customers, and perhaps additional
paperwork.

New demand
• Manufacturing firms that experience
seasonal demand are sometimes
able to develop a demand for a
complementary product that makes
use of the same production process.
For example, the firms that produce
water ski in the summer, produce
snow ski in the winter.

Aggregate Plan to Master Schedule
For a short planning range 2-4 months:
Master schedule: The result of
disaggregating an aggregate plan;
shows quantity and timing of specific
end items for a scheduled horizon.
Rough-cut capacity planning:
Approximate balancing of capacity and
demand to test the feasibility of a
master schedule.

Master Production Scheduling
Master Production Schedule (MPS) - A detailed disaggregation of the
aggregate production plan, listing the exact end items to be produced by a
specific period.
• More detailed than APP & easier to plan under stable demand.
• Planning horizon is shorter than APP, but longer than the lead time to produce the
item.
• Note: For the service industry, the master production schedule may just be the
appointment log or book, where capacity (e.g., skilled labor or professional
service) is balanced with demand.

Master Production Scheduling
The MPS - the production quantity to meet demand from all sources & is used for
computing the requirements of all time-phased end items
System nervousness - small changes in the upper-level-production plan cause
major changes in the lower-level production plan
Firms use a time fence to deal with nervousness by separating the planning horizon into –
1. Firmed Segment (AKA demand time fence), from current period to several weeks into
future. Can only be altered by senior management
2. Tentative segment (AKA planning time fence), from end of firmed segment to several
weeks into the future

The Master Production Scheduling Problem
MPS
Placed Orders
Forecasted Demand
Current and Planned
Availability, eg.,
•Initial Inventory,
•Initiated Production,
•Subcontracted quantities
Master Production
Schedule:
When & How Much
to produce for each
product
Capacity
Consts.
Company
Policies
Economic
Considerations
Product
Charact.
Planning
Horizon
Time
unit
Capacity
Planning

MPS Example: Company Operations
Mashing
(1 mashing ton)
Boiling
(1 brew kettle)
Fermentation
(3 40-barrel
ferm. tanks)
Filtering
(1 filter tank)
Bottling
(1 bottling
station)
Grain cracking
(1 milling
machine)
Fermentation Times:
Brew Ferm. Time
Pale Ale 2 weeks
Stout 3 weeks
Winter Ale 2 weeks
Summer Brew 2 weeks
Octoberfest 8-10 weeks

Example: Implementing the Empirical Approach
in Excel
# Fermentors: 1 Unit Cap: 200 Shelf Life: 20
Microbrewery Performance
Week 0 1 2 3 4 5 6 7 8 9 10
# Fermentors Req'd 0 0 0 0 0 0 0 0 0 0
Feasible Loading?
Min # Fermentors Req'd 2 2 2 2 2 2 2 2 2 2
Fermentor Utilization 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Total Spoilage 0 0 0 0 0 0 0 0 0 0
Pale Ale Fermentation Time: 2
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 45 50 40 40 40 40 40 40 40 40
Scheduled Receipts 200
Fermentors Released 1
Inventory Spoilage
Inventory Position 100 255 205 165 125 85 45 5 -35 -40 -40
Net Requirements 35 40 40
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout Fermentation Time: 3
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 35 40 30 30 40 40 40 40 50 50
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position 150 115 75 45 15 -25 -40 -40 -40 -50 -50
Net Requirements 25 40 40 40 50 50
Scheduled Releases
Fermentors Seized

Problem Decision Variables:
Scheduled Releases
Week 0 1 2 3 4 5 6 7 8 9 10
# Fermentors Req'd 0 0 0 0 0 1 1 0 0 0
Feasible Loading?
Total Spoilage 0 0 0 0 0 0 0 0 0 0
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 45 50 40 40 40 40 40 40 40 40
Inventory Spoilage
Inventory Position 100 255 205 165 125 85 45 5 165 125 85
Net Requirements
Batched Net Receipts 200
Scheduled Releases 200
Fermentors Seized 1
Total Fermentors Occupied 1 1
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 35 40 30 30 40 40 40 40 50 50
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position 150 115 75 45 15 -25 -40 -40 -40 -50 -50
Net Requirements 25 40 40 40 50 50
Scheduled Releases
Fermentors Seized

Testing the Schedule Feasibility
Week 0 1 2 3 4 5 6 7 8 9 10
# Fermentors Req'd 0 1 1 1 0 1 2 1 1 0
Feasible Loading? NO
Total Spoilage 0 0 0 0 0 0 0 0 0 0
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 45 50 40 40 40 40 40 40 40 40
Inventory Spoilage
Net Requirements
Batched Net Receipts 200
Scheduled Releases 200
Fermentors Seized 1
Total Fermentors Occupied 1 1
Week 0 1 2 3 4 5 6 7 8 9 10
Demand 35 40 30 30 40 40 40 40 50 50
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Net Requirements
Batched Net Receipts 200 200
Scheduled Releases 200 200
Fermentors Seized 1 1
Total Fermentors Occupied 1 1 1 1 1 1

The Driving Logic behind the Empirical Approach
Demand Availability:
•Initial Inventory Position
•Scheduled Receipts due to initiated
production or subcontracting
Future inventories
Net
Requirements
Lot Sizing
Scheduled
Releases
Resource (Fermentor)
Occupancy Product i
Feasibility
Testing
Master Production Schedule
Schedule
Infeasibilities
Revise
Prod. Reqs
Compute Future
Inventory Positions

Master Schedule
 The result of disaggregating the aggregate plan is a master schedule
showing the quantity and timing of specific end items for a scheduled
horizon, which often covers about six to eight weeks ahead.
 The master schedule shows the planned output for individual products
rather than an entire product group, along with the timing of production.
 It should be noted that whereas the aggregate plan covers an interval of,
say, 12 months, the master schedule covers only a portion of this. In other
words, the aggregate plan is disaggregated in stages , or phases, that may
cover a few weeks to two or three months.
 The master schedule contains important information for marketing as well
as for production. It reveals when orders are scheduled for production and
when completed orders are to be shipped.

• Master schedule
• Determines quantities needed to meet
demand
• Interfaces with
• Marketing: it enables marketing to make valid
delivery commitments to warehouse and final
customers.
• Capacity planning: it enables production to
evaluate capacity requirements
• Production planning
• Distribution planning

Master
Scheduling
Beginning inventory
Forecast
Committed
Customer orders
Inputs Outputs
Projected inventory
Master production schedule
ATP: Uncommitted inventory

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