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RESEARCH TEAM

RESEARCH TEAM. INVESTIGATORS G. Berkstresser S. Fang R. King T. Little H. Nuttle J. Wilson. Textiles and Apparel Mgmt. Industrial Engineering Industrial Engineering Textiles and Apparel Mgmt. Industrial Engineering Industrial Engineering. STUDENTS H. Cheng S. Lertworasirikul

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RESEARCH TEAM

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  1. RESEARCH TEAM INVESTIGATORS G. Berkstresser S. Fang R. King T. Little H. Nuttle J. Wilson Textiles and Apparel Mgmt. Industrial Engineering Industrial Engineering Textiles and Apparel Mgmt. Industrial Engineering Industrial Engineering STUDENTS H. Cheng S. Lertworasirikul Y. Liao S. Wang Ph.D. Operations Research Ph.D. Industrial Engineering Ph.D. Industrial Engineering Ph.D. Operations Research

  2. SUPPLY CHAIN

  3. OBJECTIVES • Develop Decision Support Tools for Integrated Supply Chain Design and Management • Incorporate vagueness and uncertainty through the use of Fuzzy Mathematics. • Demonstrate prototypes.

  4. SUPPLY CHAIN MODELING AND OPTIMIZATIONUSING SIMULATION & SOFT COMPUTING • Supply chains involve the activity and interaction of many entities. • Decision makers typically have imprecise goals. • e.g. “Low work – in – process” • Some system parametersmay also be imprecise. • e.g. “Production rate” • Discrete event simulationcan help design and analyze supply chains. • Manyconfigurations and courses of action need to be investigated. • Even experts have to spend a considerable amount of timesearching for good alternatives. • Soft computing guided simulation speeds upthe process.

  5. Supply Chain Configuration Knowledge Extraction Input - Performance Data Simulation Goals met? Yes Stop No Fuzzy System / Relationship Identification Activate Fuzzy Rules/Logic Soft Computing Guided Simulation ITERATIVE PROCESS SCHEME

  6. RULE BASE GUIDE TO SUPPLY CHAIN RECONFIGURATION • Rule example 1: If Overall work-in-process is High then Change in production rate in the Cutting facility is Positively Small. • Rule example 2: If Overall work-in-process is High and Utilization at the cutting facility is High then Change in production rate in the Cutting facility is Positively Large.

  7. Membership Iteration RESULTS • Satisfactory results (high service level) achieved in few iterations.

  8. Retailer C u s t o m e r s Manufacturer Supplier DC Retailer Manufacturer Supplier DC Retailer Manufacturer Retailer Analyse and Compare Designs and Operational Practices Subcontractor SUPPLY CHAIN INTEGRATOR

  9. Configuration Create your own supply chain using the drag&drop feature Set/Adjust Parameters Specify/adjust parameters using dialog boxes Simulation Simulate the integrated operation of the supply chain Reporting Obtain detailed performance measure report STEPS

  10. SUPPLY CHAIN CONFIGURATION

  11. PARAMETER SETTING

  12. DUE-DATE NEGOTIATOR • A tool for order delivery date negotiation between a manufacturer and customers. • Version 1 - bargaining with monetary penalty and compensation • Version 2 - explore resource expansion alternatives • Version 3 – real time order entry • Methodology: Genetic Algorithms, Fuzzy Modeling, Fuzzy Logic

  13. DUE-DATE NEGOTIATOR Assignment / Bargainer

  14. DUE-DATE NEGOTIATOR Resource Utilization

  15. DUE-DATE NEGOTIATOR Assignment / Scheduler

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