Production Scheduling for the McGuiness

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Production Scheduling forthe McGuiness Co.
Microbrewery
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A Production Planning ControlFramework
Tactical Planning
Demand Forecasting
Capacity Planning
Production Scheduling
Material Requirements Planning
Execution
Sales order Processing
Purchasing
Production Control
Recording
Shop-floor data Collection
Inventory records
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The Production Scheduling Problem
Capacity Consts.
Company Policies
Economic Considerations
Product Charact.
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
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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)

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Possible Approaches

• Empirical Approach Spreadsheet-based Simulation
• Analytical Approach Mathematical (Integer)
  Programming formulation

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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
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Example Implementing the Empirical Approach in
Excel
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Computing Inventory Positions and Net
Requirements
Net Requirement
NRi abs(min0, IPi)
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Problem Decision Variables Scheduled Releases
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Testing the Schedule Feasibility
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Fixing the Original Schedule
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Infeasible Production Requirements
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Modeling the Inventory Spoilage
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A feasible schedule with spoilage effects
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Computing Spoilage and Modified Inventory
Position
Spoilage
SPi max0, IPi-1-(SRi-1SRi-2SRi-sl1)
-(BNRi-1BNRi-2BNRi-sl1)
Inventory Position
IPi maxIPi-1,0 SRiBNRi -Di-SPi
(Material Balance Equation)
Di
(IPi-1)
i
SPi
SRiBNRi
IPi
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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