Aggregate Planning and Master Production

Scheduling (MPS)

Aggregate Planning

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.

Hieratical planning system

For ExampleAt 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 OutputsTotal cost of a planProjected levels of:

InventoryOutputEmploymentSubcontractingBackordering

Aggregate Planning StrategiesProactive

• Involve demand options: Attempt to alter demand to match capacity

Reactive• Involve capacity options: attempt to alter capacity to

match demandMixed

• Some of each

Demand OptionsPricing PromotionBack ordersNew demand

Demand OptionsPricing

PromotionBack ordersNew demand

Pricing

Promotio

n

New

deman

d

Back oreder

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.

PromotionAdvertising 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 orderAn 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 ScheduleFor 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(MPS)

Master Production SchedulingMaster 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 management2. Tentative segment (AKA planning time fence), from end of firmed

segment to several weeks into the future

The Master Production Scheduling Problem

MPS

Placed OrdersForecasted DemandCurrent and PlannedAvailability, eg.,•Initial Inventory,•Initiated Production,•Subcontracted quantities

Master ProductionSchedule:When & How Muchto produce for eachproduct

CapacityConsts.

CompanyPolicies

EconomicConsiderations

ProductCharact.

PlanningHorizon

Timeunit

CapacityPlanning

MPS Example: Company Operations

Mashing(1 mashing ton)

Boiling(1 brew kettle)

Fermentation(3 40-barrelferm. tanks)

Filtering(1 filter tank)

Bottling(1 bottling

station)

Grain cracking(1 millingmachine)

Fermentation Times:

Brew Ferm. TimePale Ale 2 weeksStout 3 weeksWinter Ale 2 weeksSummer Brew 2 weeksOctoberfest 8-10 weeks

Example: Implementing the Empirical Approach in Excel# Fermentors: 1 Unit Cap: 200 Shelf Life: 20

Microbrewery PerformanceWeek 0 1 2 3 4 5 6 7 8 9 10# Fermentors Req'd 0 0 0 0 0 0 0 0 0 0Feasible Loading?Min # Fermentors Req'd 2 2 2 2 2 2 2 2 2 2Fermentor 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: 2Week 0 1 2 3 4 5 6 7 8 9 10Demand 45 50 40 40 40 40 40 40 40 40Scheduled Receipts 200Fermentors Released 1Inventory SpoilageInventory Position 100 255 205 165 125 85 45 5 -35 -40 -40Net Requirements 35 40 40Batched Net ReceiptsScheduled ReleasesFermentors SeizedTotal Fermentors Occupied

Stout Fermentation Time: 3Week 0 1 2 3 4 5 6 7 8 9 10Demand 35 40 30 30 40 40 40 40 50 50Scheduled ReceiptsFermentors ReleasedInventory SpoilageInventory Position 150 115 75 45 15 -25 -40 -40 -40 -50 -50Net Requirements 25 40 40 40 50 50Batched Net ReceiptsScheduled ReleasesFermentors SeizedTotal Fermentors Occupied

Problem Decision Variables: Scheduled Releases

# Fermentors: 1 Unit Cap: 200 Shelf Life: 20

Microbrewery PerformanceWeek 0 1 2 3 4 5 6 7 8 9 10# Fermentors Req'd 0 0 0 0 0 1 1 0 0 0Feasible Loading?Min # Fermentors Req'd 2 2 2 2 2 2 2 2 2 2Fermentor Utilization 0% 0% 0% 0% 0% 100% 100% 0% 0% 0%Total Spoilage 0 0 0 0 0 0 0 0 0 0

Pale Ale Fermentation Time: 2Week 0 1 2 3 4 5 6 7 8 9 10Demand 45 50 40 40 40 40 40 40 40 40Scheduled Receipts 200Fermentors Released 1Inventory SpoilageInventory Position 100 255 205 165 125 85 45 5 165 125 85Net RequirementsBatched Net Receipts 200Scheduled Releases 200Fermentors Seized 1Total Fermentors Occupied 1 1

Stout Fermentation Time: 3Week 0 1 2 3 4 5 6 7 8 9 10Demand 35 40 30 30 40 40 40 40 50 50Scheduled ReceiptsFermentors ReleasedInventory SpoilageInventory Position 150 115 75 45 15 -25 -40 -40 -40 -50 -50Net Requirements 25 40 40 40 50 50Batched Net ReceiptsScheduled ReleasesFermentors SeizedTotal Fermentors Occupied

Testing the Schedule Feasibility

# Fermentors: 1 Unit Cap: 200 Shelf Life: 20

Microbrewery PerformanceWeek 0 1 2 3 4 5 6 7 8 9 10# Fermentors Req'd 0 1 1 1 0 1 2 1 1 0Feasible Loading? NOMin # Fermentors Req'd 2 2 2 2 2 2 2 2 2 2Fermentor Utilization 0% 100% 100% 100% 0% 100% 200% 100% 100% 0%Total Spoilage 0 0 0 0 0 0 0 0 0 0

Pale Ale Fermentation Time: 2Week 0 1 2 3 4 5 6 7 8 9 10Demand 45 50 40 40 40 40 40 40 40 40Scheduled Receipts 200Fermentors Released 1Inventory SpoilageInventory Position 100 255 205 165 125 85 45 5 165 125 85Net RequirementsBatched Net Receipts 200Scheduled Releases 200Fermentors Seized 1Total Fermentors Occupied 1 1

Stout Fermentation Time: 3Week 0 1 2 3 4 5 6 7 8 9 10Demand 35 40 30 30 40 40 40 40 50 50Scheduled ReceiptsFermentors ReleasedInventory SpoilageInventory Position 150 115 75 45 15 175 135 95 55 5 155Net RequirementsBatched Net Receipts 200 200Scheduled Releases 200 200Fermentors Seized 1 1Total 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 inventoriesNetRequirements

Lot SizingScheduledReleases

Resource (Fermentor)Occupancy Product i

FeasibilityTesting

Master Production Schedule

ScheduleInfeasibilities

ReviseProd. Reqs

Compute FutureInventory 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