Aggregate Planning

Aggregate PlanningAggregate Production Planning is planning about how many units of the product are to be produced on a weekly or monthly basis for the coming six to eighteen months. This plan should be in line with the overall business plan of the company.

It determines the resource capacity needed to meet demand over an intermediate time horizonAggregate refers to all product lines or familiesAggregate planning matches supply and demand

ObjectivesEstablish a company wide game plan for allocating resourcesDevelop an economic strategy for meeting demand

Aggregate Planning Process

Demand Forecasts provided by the Marketing DepartmentBusiness Plan provided by the Top ManagementStrategies for Pure Aggregate Planning considered by the Production Manager Level Output Rate Plan Chase Plan Varying Utilization Rate Plan A combination of the pure planning strategies called the Intermediate Plan is prepared by the Production Manager Disaggregating of the Aggregate Production Plan (Intermediate Plan) is done in order to arrive at a Master ScheduleMaster Scheduling Process Beginning Inventory Status Customer orders committed Tentative Master Production Schedule (MPS) Available-to-promise Inventory Projected on-hand Inventory Tentative MPS is run through the Material Requirements Planning (MRP) Processing Logic to test for feasibilityRough-cut capacity planning Revised Master Production Schedule is fixed by using Time FencesSteps in Effective Aggregate Planning Process Oxford University Press 2013. All rights reserved.

Meeting Demand StrategiesAdjusting capacityResources necessary to meet demand are acquired and maintained over the time horizon of the planMinor variations in demand are handled with overtime or under-timeManaging demandProactive demand management

Strategies for Adjusting CapacityLevel productionProducing at a constant rate and using inventory to absorb fluctuations in demandChase demandHiring and firing workers to match demandPeak demandMaintaining resources for high-demand levelsOvertime and under-timeIncreasing or decreasing working hoursSubcontractingLet outside companies complete the workPart-time workersHiring part time workers to complete the workBackorderingProviding the service or product at a later time period

Level Production

Chase Demand

Strategies for Managing DemandShifting demand into other time periodsIncentivesSales promotionsAdvertising campaignsOffering products or services with counter-cyclical demand patternsPartnering with suppliers to reduce information distortion along the supply chain

Quantitative Techniques For APPPure StrategiesMixed StrategiesLinear ProgrammingTransportation MethodOther Quantitative Techniques

Solving aggregate planning problem involves formulating strategies for meeting demand, constructing production plans from those strategies, determining cost and feasibility of each plan, and selecting the lowest cost plan among the feasible alternatives.The effectiveness of the aggregate planning process is directly related to managements understanding of the cost variables involved and the reasonableness of the scenarios tested.

Pure strategiesPure strategy is varying only one capacity variable in aggregate planning.Level and Chase strategies are example of Pure strategies.

Pure StrategiesHiring cost= $100 per workerFiring cost= $500 per worker Regular production cost per pound = $2.00 Inventory carrying cost= $0.50 pound per quarter Production per employee= 1,000 pounds per quarter Beginning work force= 100 workersExample:

Level Production Strategy

Chase Demand StrategySpring80,00080,00080020Summer50,00050,00050030Fall120,000120,000120700Winter150,000150,000150300

10050 SALESPRODUCTIONWORKERSWORKERSWORKERSQUARTERFORECASTPLANNEEDEDHIREDFIREDCost of Chase Demand Strategy(400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

Mixed StrategyMixed strategy is varying two or more capacity factors to determine a feasible production plan.Combination of Level Production and Chase Demand strategiesThey can incorporate management policies likeno more than x% of the workforce can be laid off in one quarterinventory levels cannot exceed x dollarsMany industries may simply shut down manufacturing during the low demand season and schedule employee vacations during that time

General Linear Programming (LP) ModelLP gives an optimal solution, but demand and costs must be linearLetWt = workforce size for period tPt =units produced in period tIt =units in inventory at the end of period tFt =number of workers fired for period tHt = number of workers hired for period t

LP MODELMinimize Z =$100 (H1 + H2 + H3 + H4)+ $500 (F1 + F2 + F3 + F4)+ $0.50 (I1 + I2 + I3 + I4)Subject toP1 - I1= 80,000(1)DemandI1 + P2 - I2= 50,000(2)constraintsI2 + P3 - I3= 120,000(3)I3 + P4 - I4= 150,000(4)Production1000 W1= P1(5)constraints1000 W2= P2(6)1000 W3= P3(7)1000 W4= P4(8)100 + H1 - F1= W1(9) Work forceW1 + H2 - F2= W2(10) constraintsW2 + H3 - F3= W3(11)W3 + H4 - F4= W4(12)

Transportation MethodWhen hiring and firing is not the option at that time transportation method is usedThe transportation method gathers all the information into one matrix and plans production based on the lowest cost alternatives.

Transportation Method

Transportation Tableau

Other Quantitative TechniquesLinear decision rule (LDR)It is an optimizing technique originally developed for aggregate planning in a paint factory. It solves a set of four quadratic equations the describes major capacity related costs in the factory: Payroll costs, hiring and firing, overtime and under time, and inventory costs.

Search decision rule (SDR)It is a pattern search algorithm that tries to find the minimum cost combination of various workforce levels and production rate.Any type of cost function can be used. The search is performed by computer and may involve the evaluation of thousands of possible solutions, but optimal solution is not guaranteed.

Management coefficients modelIt uses regression analysis to improve the consistency of planning decisions. Techniques like SDR and management coefficients are often embedded in commercial decision support systems or expert systems for aggregate planning.

Hierarchical Nature of Planning

Available-to-Promise (ATP)ATP is the Quantity of items that can be promised to the customer.It is the Difference between planned production and customer orders already receivedAT in period 1 = (On-hand quantity + MPS in period 1) - (CO until the next period of planned production)ATP in period n = (MPS in period n) - (CO until the next period of planned production)

ATP: Example

ATP: Example (cont.)

ATP: Example (cont.)ATP in April = (10+100) 70 = 40ATP in May = 100 110 = -10ATP in June = 100 50 = 50Take excess units from April

Rule Based ATP

Capable to PromiseWhen product is not available then system proposes a capable to promise date, that is subject to customer approval.Capable to promise is the quantity of items that can be produced and made available at later date.

Aggregate Planning for ServicesMost services cant be inventoriedDemand for services is difficult to predictCapacity is also difficult to predictService capacity must be provided at the appropriate place and timeLabor is usually the most constraining resource for services

Yield Management

Yield Management (cont.)

Yield Management: ExampleHotel should be overbooked by two rooms

*******************************