A multi-level optimization approach for energy-efficient flexible flow shop scheduling. (20th November 2016)

• Record Type: Journal Article
• Authors: Yan, Jihong; Li, Lin; Zhao, Fu; Zhang, Fenyang; Zhao, Qingliang
• Is Part Of: Journal of cleaner production. Volume 137(2016)
• Page Start: 1543
• Page End: 1552
• Publication Date: 2016-11-20
• Subjects: Energy modeling -- Energy-efficient scheduling -- Flexible flow shop -- Cutting parameters optimization -- Grey relational analysis; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2016.06.161
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The integration of energy efficiency at both machine tool and shop floor levels could bring multiple environmental benefits. In order to explore the potential on energy saving for shop floor management, a multi-level optimization method for energy-efficient flexible flow shop scheduling is proposed, which incorporates power models of single machine and cutting parameters optimization into the energy-efficient scheduling problems. The operation scheme is obtained through multi-level optimization, namely cutting parameters optimization (machine tool level) and optimized scheduling (shop floor level). At machine tool level, cutting parameters of each machine are optimized based on grey relational analysis, where cutting energy and cutting time are considered as the objectives. Based on the established energy consumption model of flexible flow shop, Genetic Algorithm is employed to optimize makespan and total energy consumption simultaneously at shop floor level. The case study for a flexible flow shop is presented to demonstrate the applicability of the proposed multi-level optimization method. The scheduling results show that the multi-level optimization method is effective in assisting schemes selection to reduce the makespan and total energy consumption during production process. Moreover, there exists potential for synergistic energy saving when the multi-level optimization is used. Highlights: A multi-level optimization method for energy-efficient flexible flow shop scheduling is proposed. Cutting parameters optimization is integrated into job scheduling problems. Energy consumption models at shop floor level are established. Processing energy, standby energy, and overhead energy can be reduced by considering cutting parameters optimization. Potential opportunities for energy-saving can be additive when the multi-level optimization is used.