Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization

• Published in: Applied energy Vol. 314; p. 118927
• Main Authors: Xia, Tangbin, Si, Guojin, Shi, Guo, Zhang, Kaigan, Xi, Lifeng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.05.2022
• Subjects: energy conservation; Energy efficiency; issues and policy; Maintenance resources constraints; Multiple maintenance actions; Selective maintenance; Series–parallel system; sustainable development; Multiple maintenance actions; Series–parallel system; Energy efficiency; Maintenance resources constraints; Selective maintenance
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2022.118927

•An energy-oriented selective maintenance policy (ESMP) is developed.•ESMP policy is applied to series–parallel multi-unit systems under sustainable manufacturing.•Preventive maintenance and preventive replacement can be optimized comprehensively.•Optimal maintenance schemes are obtained under limited maintenance resources.•ESMP policy achieves a significant improvement of energy efficiency in batch production. With the industry sustainable development and increasing awareness of energy conservation, many manufacturing enterprises prefer to develop the operation and maintenance (O&M) with high production throughput and low energy consumption. In reality, many manufacturing systems are required to conduct a sequence of predefined missions with finite breaks between any two consecutive missions. To successfully complete the next mission production, maintenance actions are arranged and performed on machines during each scheduled break. In this paper, an energy-oriented selective maintenance policy (ESMP) for series–parallel systems is investigated. At each break, multiple maintenance actions with different impacts on machine degradation are available under limited maintenance resources. To obtain the throughput-and-energy based maintenance scheme, we first model the system energy efficiency based on system throughput and energy consumption. Then, we integer the energy efficiency modeling, production throughout analysis, and selective maintenance scheduling into an optimization model. And the model objective is to find the appropriate maintenance action for each machine at each break subject to cost and duration constraints. Numerical examples have been addressed to demonstrate the performance and adaptability of our proposed ESMP in long-term selective maintenance scheduling. Finally, a comparative analysis with traditional reliability-oriented policy shows the significant improvement of energy efficiency.