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Service-oriented global optimization integrating maintenance grouping and technician routing for multi-location multi-unit production systems

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  • Guojin Si
  • Tangbin Xia
  • Ershun Pan
  • Lifeng Xi

Abstract

With the product-service requirement of modern production enterprises, service-oriented manufacturing and its corresponding operations and maintenance have gained growing attention. Advances in sensor technology and wireless communication, promoting lessors to propose new strategies for intelligent maintenance decision-making of geographically distributed manufacturing enterprises. In this article, we present a comprehensive strategy for solving the maintenance grouping and technician routing problem of multi-location multi-unit production systems. Based on real-time machine degradation, we estimate the failure rate of leased machines and establish a time-varying maintenance cost function to quantify the trade-off between early maintenance and delayed maintenance. Unlike group maintenance of a single system, we integrate the travel time between systems and the maintenance capacity of technician teams into a mixed-integer optimization model to provide the dynamic preventive maintenance scheme. Finally, numerical examples are employed to illustrate the effectiveness of the proposed strategy and explore some managerial insights for the lessor’s daily management.

Suggested Citation

  • Guojin Si & Tangbin Xia & Ershun Pan & Lifeng Xi, 2022. "Service-oriented global optimization integrating maintenance grouping and technician routing for multi-location multi-unit production systems," IISE Transactions, Taylor & Francis Journals, vol. 54(9), pages 894-907, June.
    • Handle: RePEc:taf:uiiexx:v:54:y:2022:i:9:p:894-907
    DOI: 10.1080/24725854.2021.1957181
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    Cited by:

    1. Si, Guojin & Xia, Tangbin & Li, Yaping & Wang, Dong & Chen, Zhen & Pan, Ershun & Xi, Lifeng, 2023. "Resource allocation and maintenance scheduling for distributed multi-center renewable energy systems considering dynamic scope division," Renewable Energy, Elsevier, vol. 217(C).

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