1 / 27

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”

yovela
Télécharger la présentation

Motivation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related