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    A Single Machine Scheduling Problem Considering Machine Availability Constraints
    WANG Jinfeng, CHEN Lu, YANG Wenhui
    Journal of Shanghai Jiao Tong University    2021, 55 (1): 103-110.   DOI: 10.16183/j.cnki.jsjtu.2019.173
    Abstract737)   HTML3)    PDF(pc) (949KB)(383)       Save

    The study described in this paper is derived from a real rotor production workshop where low reliability leads to poor quality of workpieces. A single machine scheduling problem considering machine availability constraints is addressed. The availability is defined by the machine reliability, which can be restored by preventive maintenance. Preventive maintenance with different improvement factors is defined in the mathematical model to minimize the total tardiness. A genetic algorithm is designed to solve the problem. Numerical results show that the proposed approach can effectively deal with the impact of machine availability constraints on production scheduling. Sensitivity analyses provide valuable managerial insights for real workshop scheduling.

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    Optimization Model of Maintenance and Spare Parts Ordering Policy in Multivariate Degradation System
    YANG Zhiyuan, ZHAO Jianmin, CHENG Zhonghua, GUO Chiming, LI Liying
    Journal of Shanghai Jiao Tong University    2021, 55 (7): 858-867.   DOI: 10.16183/j.cnki.jsjtu.2019.221
    Abstract608)   HTML8)    PDF(pc) (2404KB)(302)       Save

    Aimed at the decision-making problem of condition-based maintenance and spare parts ordering for systems with multiple dependent degradation processes, an optimization model of system maintenance and spare parts ordering policy is developed under the condition of continuously monitoring. First, the Gamma process and Copula function are used to develop the system multivariate degradation model. Then, the system maintenance and spare parts ordering policy based on the control limit strategy is proposed. Considering the influence of system degradation on maintenance cost, the analytical expression of the expected maintenance cost rate under long-term operation conditions is obtained. At the same time, an approximate expression of the expected maintenance cost rate is proposed to simplify the model calculation. The optimal preventive replacement threshold and spare parts ordering threshold of the system are obtained by using the artificial bee colony algorithm under the cost criterion. The case analysis shows that it is necessary to consider degradation in maintenance decision-making. Compared with the existing policy, the comprehensive optimization of preventive replacement and spare parts ordering thresholds can effectively reduce the maintenance cost of the system.

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    Opportunistic Maintenance Modeling for Serial Production Systems with Stochastic Production Waits
    NING Xiaohan, ZHOU Xiaojun
    Journal of Shanghai Jiao Tong University    2021, 55 (10): 1281-1290.   DOI: 10.16183/j.cnki.jsjtu.2020.320
    Abstract432)   HTML9)    PDF(pc) (1382KB)(314)       Save

    In order to make full use of the maintenance opportunities brought by stochastic production waits caused by external factors such as shortage of raw materials and insufficient demands, the notions of mass center and gravity windows are introduced and an opportunity maintenance decision-making model combining the time window and the gravity window is proposed for multi-unit serial production systems. Considering both internal maintenance opportunities caused by equipment mandatory maintenance and external maintenance opportunities caused by production waits, the optimal maintenance strategy is obtained by minimizing the total maintenance cost rate of the system in the planning period. The example analysis shows that the combination of the time window and the gravity window has prominent advantages in reducing the total maintenance cost, and can effectively solve the uncertainty of the arrival and duration of production waits.

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