research-article

Joint optimization of preventive maintenance and production scheduling for parallel machines system

Authors:

Wenzhu Liao, Maocai Chen, Xiaoxia YangAuthors Info & Claims

Journal of Intelligent & Fuzzy Systems, Volume 32, Issue 1

Pages 913 - 923

https://doi.org/10.3233/JIFS-161385

Published: 01 January 2017 Publication History

Abstract

This paper deals with the joint problem of production scheduling and maintenance planning as it becomes one important base for intelligent manufacturing. Due to the dual requirements both on cost and delivery date, a multi-objective optimization approach is proposed for parallel machines to allow decision makers to find compromise solution between production scheduling and maintenance planning: minimizing both maximum completion time and total maintenance cost. The new optimization approach is one multiple nondominated improved NSGA-II algorithm based on greedy idea and pre-distribution thinking, which can quickly and effectively seek Pareto optimal solution to solve the joint problem. As well as the introduced idea of averaging machine utilization, the job processing time model is constructed by considering machine degradation to meet real manufacturing situation. Moreover, a penalty function to maintenance (delay or advance) is proposed. Finally, the experimental analysis demonstrates the effectiveness and efficiency of this pre-distributed NSGA-II optimization approach, which could help solve the joint decision-making problem of production scheduling and preventive maintenance for parallel machines system.

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Cited By

Ruiz Rodríguez MKubler Sde Giorgio ACordy MRobert JLe Traon Y(2022)Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machinesRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2022.10240678:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.rcim.2022.102406
Wang ZDeng QZhang LLiu X(2022)Integrated scheduling of production, inventory and imperfect maintenance based on mutual feedback of supplier and demander in distributed environmentJournal of Intelligent Manufacturing10.1007/s10845-022-01996-z34:8(3445-3467)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1007/s10845-022-01996-z
Nguyen KMedjaher KTran D(2022)A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelinesArtificial Intelligence Review10.1007/s10462-022-10260-y56:4(3659-3709)Online publication date: 9-Sep-2022
https://dl.acm.org/doi/10.1007/s10462-022-10260-y

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Joint optimization of preventive maintenance and production scheduling for parallel machines system

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Published In

cover image Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology Volume 32, Issue 1

2017

1104 pages

ISSN:1064-1246

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IOS Press and the authors. All rights reserved.

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IOS Press

Netherlands

Publication History

Published: 01 January 2017

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Cited By

Ruiz Rodríguez MKubler Sde Giorgio ACordy MRobert JLe Traon Y(2022)Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machinesRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2022.10240678:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.rcim.2022.102406
Wang ZDeng QZhang LLiu X(2022)Integrated scheduling of production, inventory and imperfect maintenance based on mutual feedback of supplier and demander in distributed environmentJournal of Intelligent Manufacturing10.1007/s10845-022-01996-z34:8(3445-3467)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1007/s10845-022-01996-z
Nguyen KMedjaher KTran D(2022)A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelinesArtificial Intelligence Review10.1007/s10462-022-10260-y56:4(3659-3709)Online publication date: 9-Sep-2022
https://dl.acm.org/doi/10.1007/s10462-022-10260-y

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