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Motivation

Capacity Planning in a General Supply Chain with Multiple Contract Types Stephen C. Graves and Xin Huang May 2008. Motivation. Prior research has developed algorithms and software for modeling and optimizing the inventory across a supply chain – “strategic inventory placement model”

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Motivation

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  1. Capacity Planning in a General Supply Chain with Multiple Contract TypesStephen C. Graves and Xin HuangMay 2008

  2. Motivation • Prior research has developed algorithms and software for modeling and optimizing the inventory across a supply chain – “strategic inventory placement model” • Impetus for current research – develop and deploy a tactical model to provide decision support for determining capacity levels across a supply chain

  3. Intent • Develop a framework to support capacity planning decisions in a supply chain with • Multiple products • Each product requires multiple processes (or components) • Each resource provides capacity for one or more processes • Need to determine the right level and type of capacity investments • Need to account for network interrelationships, demand uncertainty, multiple time periods, & different capacity contracts.

  4. Work to Date • Developed framework for structuring models • Developed and tested algorithms for determining the amount, type and timing of capacity investments across a complex multi-product supply chain • Implementation of user-friendly software is underway

  5. Model assumptions • Given demand forecast and contract prices, we first make capacity decisions: • For each resource how much capacity to reserve and with what type of contract • Then we learn what the actual demand is and decide how to allocate capacity to meet demand as best as possible • Objective is to maximize revenue net of capacity costs

  6. Example 1 Laptop A A & T Chip Set A Display A Foundry 1 Foundry 3 CM 1

  7. Example 1: Sample Input Data Table 1: Table of Product Information Table 2: Table of Resource Price Inputs

  8. Example 1: Model Outputs The Expected Total Profit:$601,623 Mean – Laptop A: 2200

  9. Example 1: Performance Statistics

  10. Example 3 Laptop A Laptop B A & T Chip Set B Display B A & T Chip Set A Display A Foundry 1 Foundry 3 CM 1 Foundry 4 Foundry 3 CM 2 Foundry 2 CM 1 Foundry 3

  11. Example 3: Sample Input Data Table 5: Table of Product Information Table 6: Table of Resource Price Inputs

  12. Questions of Interest • Which suppliers should the manufacturer choose? • What types of contract should we use for each supplier? Only fixed-price contract? Only option contract? Or Both. • How much capacity should we buy?

  13. Example 3: Model Outputs The Expected Total Profit:$1,183,981 Mean – Laptop A: 2200 Mean – Laptop B: 1000

  14. Example 4 S1 S2 S3 • Compare the following four strategies • Plan the capacity as given in the figure without option capacity • Use a common process to replace process 2a and 2b • Add option capacity to process 2a and 2b • Combine strategy S2 and S3 1 2 1 2 1 2 1 2a 2b 3 1 2 3 1 2a 2b 3 1 2a 2b 3 1 2 3 1 2a 2b 3 S4 1 2 1 2 3 1 2 3

  15. Example 4: Data • Both products have the same price: changes from 66 to 150 • Demand information: • E[D_1] = 500, STD(D_1) = 100, E[D_2] = 500, STD(D_2) = 100 • Fixed price contracts: • [p_1, p_2a, p_2b, p_3] = [10, 50, 50, 10] • Option contracts: • Reservation Price = 5, Exercise Price = 50

  16. Example 4 (S2+S3)/S1 S4/S1 Extra Profit (%) S3/S1 S2/S1 Profit Margin

  17. Example 5: Multi-period Planning • A Supply Chain Network • 2 Products, 3 Processes, and 12 Periods. • Each process has 4 different types of contract • 1 period, 3 periods, 6 periods, and 12 periods • Each contract has 4 terms • Duration, Fixed-price, Option reservation price, and Option exercise price 1 2 1 3 2 1 3 2

  18. [ [ ] ] E E D D 1 2 Sample Demands

  19. Sample Prices • Prices: • Product 1: 65; Product 2: 65. • Costs: • All processes have the same price structure.

  20. Results

  21. Results (cont.) Process 1 Process 2 Process 3

  22. Summary • Have developed a framework to support capacity planning decisions for supply chain • Have developed solution algorithms for single period and multi-period problems • To do • develop a case study to test and validate approach • finalize prototype software with user friendly interface

  23. Collaboration Opportunities • Need a test case(s) to validate and refine framework • Are we looking at problem in right way? • Does the data exist to test model? • Can our algorithms result in better decisions? • What’s critical/non-critical in how we are viewing problem? • Interest in internships for LFM or SDM students for “beta testing” • Contact Steve Graves (sgraves@mit.edu) or Xin Huang (xinhuang@mit.edu)

  24. Example 2 Laptop B A & T Chip Set B Display B Foundry 4 Foundry 3 CM 2

  25. Example 2: Sample Input Data Table 3: Table of Product Information Table 4: Table of Resource Price Inputs

  26. Example 2: Model Outputs The Expected Total Profit:$556,320 Mean – Laptop B: 1000

  27. Example 2: Performance Statistics

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