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A Generalized Stochastic Petri-Net Model For Performance Analysis And Allocation Optimization Of A Particular Repair System

Author

Listed:
  • BINFENG LI

    (Industrial Engineering, Tsinghua University, Beijing, 100084, China)

  • XIAOBIN LI

    (Industrial Engineering, Tsinghua University, Beijing, 100084, China)

  • WEIHONG GUO

    (Industrial Engineering, Tsinghua University, Beijing, 100084, China)

  • SU WU

    (Industrial Engineering, Tsinghua University, Beijing, 100084, China)

Abstract

This paper presents a generalized stochastic Petri-net model for performance analysis and allocation optimization of a repair system with interchangeable inventory. A repair system with interchangeable-inventory is an important type of repair-service, which features components that are assembled circularly with interchangeable-component inventory. Despite improved efficiency, major difficulties in model formulation and performance analysis arise due to a complex fork/join structure and the presence of interchangeable-component inventory. In this study, by applying a generalized stochastic Petri-net to model the fork/join structure and interchangeable inventory, a system with one overhaul center and one interchangeable-component repair shop was defined in the Petri-net by places, transitions and tokens. A performance analysis with single and multiple parameters and simulation experiments was performed according to the real field data of high-speed railway locomotives overhaul. With appropriate weights on each portion of the system resources, the optimal design scenario for the allocation of a specific repair system was achieved to control the overall expenditure.

Suggested Citation

  • Binfeng Li & Xiaobin Li & Weihong Guo & Su Wu, 2013. "A Generalized Stochastic Petri-Net Model For Performance Analysis And Allocation Optimization Of A Particular Repair System," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(01), pages 1-19.
    • Handle: RePEc:wsi:apjorx:v:30:y:2013:i:01:n:s021759591250042x
    DOI: 10.1142/S021759591250042X
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