Cutting parameter optimization for machining operations considering carbon emissions. (20th January 2019)

• Record Type: Journal Article
• Authors: Zhou, Guanghui; Lu, Qi; Xiao, Zhongdong; Zhou, Ce; Tian, Changle
• Is Part Of: Journal of cleaner production. Volume 208(2019)
• Page Start: 937
• Page End: 950
• Publication Date: 2019-01-20
• Subjects: Carbon emissions -- Cutting parameters -- Multi-objective optimization -- Non-cooperative game theory -- Non-dominated sorting genetic algorithm; 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.2018.10.191
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: With the aggravation of global warming and implementation of carbon policies such as carbon tax and carbon labeling, manufacturing enterprises have to cope with the stress from eco-environment and production cost. Cutting parameters in the part machining process have a huge impact on energy and material consumption, cutting time and economy of manufacturing system. The traditional cutting parameters are always selected based on human experience and handbooks, which lacks the attention on energy and material saving. In this paper, a cutting parameter optimization method for machining operations considering carbon emissions is proposed to balance cutting indexes, i.e., carbon emissions, cutting time and cutting cost, in the part machining process. Firstly, the numerical relationships between cutting parameters and cutting indexes are analyzed. Particularly, considering the processing capacity of a workshop and machining features, formalized tables named c-PBOM-W (Carbon emissions integrated Process Bill of Material for Workshop) and c-PBOM-P (Carbon emissions integrated Process Bill of Material for Part) are designed to evaluate carbon emissions easily. Then, a multi-objective parameter optimization model is proposed. By introducing non-cooperative game theory, an improved algorithm, Non-cooperative Game theory Integrated NSGA-II (NG-NSGA-II), is developed to solve the model. Finally, a cylindrical turning is taken as a case to illustrate the rationality of the proposed cutting parameter optimization method. The simulation results show that the NG-NSGA-II has a better performance than NSGA-II. Thus, the proposed method could provide the optimal cutting parameters in the part machining process to decrease carbon emissions, cutting time, and cutting cost.