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Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
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Multiobjective Flexible Job-Shop Rescheduling With New Job Insertion and Machine Preventive Maintenance
IEEE Transactions on Cybernetics
|March 14, 2022
Summary
This study addresses flexible job-shop rescheduling with new jobs and imperfect preventive maintenance (PM). An improved algorithm optimizes scheduling and maintenance, demonstrating effectiveness and analyzing maintenance impacts.
Area of Science:
- Operations Research
- Industrial Engineering
- Manufacturing Systems
Background:
- Real-world production frequently involves dynamic events like new job insertions and machine preventive maintenance (PM).
- Addressing these disruptions requires integrated approaches to production scheduling and maintenance planning.
Purpose of the Study:
- To investigate the flexible job-shop rescheduling problem (FJRP) considering both new job insertions and imperfect preventive maintenance (IPM).
- To develop a multiobjective optimization model for jointly optimizing production scheduling and maintenance planning.
- To propose an efficient algorithm for solving the complex integrated optimization problem.
Main Methods:
- Development of an imperfect preventive maintenance (IPM) model with proven optimality.
- Formulation of a multiobjective optimization model for integrated production and maintenance.
- Proposal of an improved nondominated sorting genetic algorithm III with adaptive reference vector (NSGA-III/ARV), featuring hybrid initialization and a critical-path-based local search (LS).
- Utilizing Taguchi experimental design for parameter tuning and performance analysis.
Main Results:
- The proposed NSGA-III/ARV algorithm demonstrates superior performance and convergence speed.
- The developed IPM model is verified as effective through comparative analysis.
- Numerical simulations confirm the effectiveness of the improved operators and the overall algorithm.
- Analysis reveals the impact of different maintenance effects on optimal decisions and integrated schemes.
Conclusions:
- The study successfully integrates flexible job-shop rescheduling with imperfect preventive maintenance.
- The proposed NSGA-III/ARV algorithm provides an effective solution for complex optimization problems.
- Understanding the impact of maintenance effects is crucial for optimal integrated maintenance-production scheduling.
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