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Chinese Journal of Management Science ›› 2026, Vol. 34 ›› Issue (9): 173-183.doi: 10.16381/j.cnki.issn1003-207x.2024.1431

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A Dynamic Scheduling and Preventive Maintenance Method Based on Product-machine Assignment

Yang Yang1(), Bin Zhang2, Chenghung Wu2   

  1. 1.School of Information Management and mathematics,Jiangxi University of Finance and Economics,Nanchang 330032,China
    2.Graduate Institute of Industrial Engineering,Taiwan University,Taipei 10617,China
  • Received:2024-08-21 Revised:2025-09-16 Online:2026-09-25 Published:2026-09-01
  • Contact: Yang Yang E-mail:y.yang@jxufe.edu.cn

Abstract:

A joint production dispatching and preventive maintenance problem in multi-product, heterogeneous-machine manufacturing is addressed through a Product-Machine Assignment (PMA) framework. The assignment is formulated as a mixed-integer linear program that matches product types to machines and controls per-machine variety through a penalty parameter κ, achieving a balance between throughput and machine specialization. The assignment decomposes the system into independent multi-product single-machine subproblems, each solved as a continuous-time Markov decision process to coordinate dispatching and preventive maintenance. Combining these yields a near-optimal system policy with computational complexity growing approximately linearly in the number of machines. Numerical experiments on 30 instances, compared with Cμ, First-Come-First-Served, and Round-Robin under throughput and cycle-time metrics, show that PMA maintains throughput while notably reducing cycle time. Additional tests under non-Markovian inter-event times and a real semiconductor workstation dataset exhibit consistent performance. The results indicate that PMA provides a scalable and interpretable approach for real-time joint dispatching and maintenance decisions in large heterogeneous manufacturing systems.

Key words: product-machine assignments, dynamic scheduling, preventive maintenance, Markov decision process

CLC Number: