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A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems

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  • Si, Guojin
  • Xia, Tangbin
  • Gebraeel, Nagi
  • Wang, Dong
  • Pan, Ershun
  • Xi, Lifeng

Abstract

We present an agile maintenance framework where technician assignment and maintenance schedules are planned jointly to ensure timely operation and maintenance (O&M) services. Such an agile framework can quickly respond to organizational scheduling requirements while controlling service costs and not compromising machine reliability. For preventive maintenance (PM) and replacement tasks, a diverse-skilled technician organizing and routing model (D-STORM) is developed for geographically distributed systems with the following decision variables: (1) the scheduled maintenance start time, (2) the appropriate maintenance level (i.e. PM or replacement) for a network of machines, (3) the composition of technician teams subject to constraints controlling the number of technicians per team and their skill levels, (4) the optimal service route for each team. And the two objectives are: (1) maximizing the total reliability improvement and (2) minimizing the total service cost. Other than traditional maintenance policies, we propose a machine-team-technician assignment approach to provide a flexible and unified maintenance framework that can incorporate diverse-skilled technicians and multi-level maintenance operations. Numerical studies show significant advantages in terms of improved reliability and reduced costs, providing a set of alternative solutions for global original equipment manufacturers (OEMs). Moreover, Pareto solutions help OEMs to adopt the most appropriate maintenance scheme for their practices.

Suggested Citation

  • Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2022. "A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:reensy:v:226:y:2022:i:c:s0951832022002873
    DOI: 10.1016/j.ress.2022.108652
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    3. Wu, Jing & Qian, Cunhua & Dohi, Tadashi, 2024. "Optimal opportunity-based age replacement policies in discrete time," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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