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Production Scheduling for the McGuiness & Co. Microbrewery

Production Scheduling for the McGuiness & Co. Microbrewery. A Production Planning & Control Framework. Tactical Planning. Demand Forecasting. Production Scheduling. Capacity Planning. Material Requirements Planning. Execution. Sales order Processing. Purchasing. Production Control.

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Production Scheduling for the McGuiness & Co. Microbrewery

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  1. Production Scheduling forthe McGuiness & Co. Microbrewery

  2. A Production Planning & ControlFramework Tactical Planning Demand Forecasting Production Scheduling Capacity Planning Material Requirements Planning Execution Sales order Processing Purchasing Production Control Recording Inventory records Shop-floor data Collection

  3. The Production Scheduling Problem Capacity Consts. Company Policies Product Charact. Economic Considerations Placed Orders Production Scheduling Master Production Schedule: When & How Much to produce for each product Forecasted Demand Current Inventory Positions Already Initiated Production Planning Horizon Time unit Capacity Planning

  4. Problem Specialization for McGuinness Microbrewery Case Study • Capacity Constraints: Number and capacity of fermentors • Company Policies: • Product cannot be shelved for more than 2 months • Production in a fermentor can be started at any level of its capacity. • Product Characteristics: • Production lead times • Economic Considerations: (Unnecessary) Inventories should be minimized (consistent with the Just-In-Time philosophy) • Planning Horizon: 6-12 months (based on production lead times, product seasonalities, and product obsolescence) • Time unit: 1 week (based on the order of production lead times)

  5. Possible Approaches • Empirical Approach: Spreadsheet-based Simulation • Analytical Approach: Mathematical (Integer) Programming formulation

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

  7. Example: Implementing the Empirical Approach in Excel

  8. Inventory Position: IPi = max{IPi-1,0}+ SRi+BNRi -Di (Material Balance Equation) (IPi-1)+ Di i SRi+BNRi IPi Computing Inventory Positions and Net Requirements Net Requirement: NRi = abs(min{0, IPi})

  9. Problem Decision Variables: Scheduled Releases

  10. Testing the Schedule Feasibility

  11. Fixing the Original Schedule

  12. Infeasible Production Requirements

  13. Modeling the Inventory Spoilage

  14. A feasible schedule with spoilage effects

  15. Computing Spoilage and Modified Inventory Position Spoilage: SPi = max{0, IPi-1-(SRi-1+SRi-2+…+SRi-sl+1) -(BNRi-1+BNRi-2+…+BNRi-sl+1)} Inventory Position: IPi = max{IPi-1,0}+ SRi+BNRi -Di-SPi (Material Balance Equation) (IPi-1)+ Di i SPi SRi+BNRi IPi

  16. Advantages and Disadvantages of the Empirical Approach • Advantages: • Easy to present and motivate • Provides clear visibility to the problems and their underlying causes • Supports effective and efficient “what-if” analysis • Provides modeling flexibility • Disadvantages • No guarantee for optimality or exhaustive search for a feasible solution • Hard to trace for more complex production environments

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