Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption. (10th November 2017)

• Record Type: Journal Article
• Authors: Deng, Zhaohui; Zhang, Hua; Fu, Yahui; Wan, Linlin; Liu, Wei
• Is Part Of: Journal of cleaner production. Volume 166(2017)
• Page Start: 1407
• Page End: 1414
• Publication Date: 2017-11-10
• Subjects: Energy consumption -- CSEC -- Multi-objective optimization -- Subjective and objective comprehensive weight -- Quantum 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.2017.08.022
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: In order to reduce the energy consumption of machine tool, the process parameters were optimized by the optimization model with the cutting specific energy consumption (CSEC) and the processing time. Based on the energy consumption characteristics of the numerical control (NC) machine tool, the energy consumption module of NC machine tool was analyzed. The power composition of machining process which was based on energy consumption module was proposed, and then CSEC was given with the cutting process parameters. The optimization model to minimum cutting specific energy consumption and minimum processing time was established with the process parameters under the actual constraint conditions in the manufacturing process. The multi-objective optimization model was transformed into the single objective optimization model by introducing the subjective and objective comprehensive weights and solved by the quantum genetic algorithm. When the optimization goal was to trade off processing time and CSEC to reduce the energy consumption, the selecting of the milling parameters should consider the complex effect if the constraints could be met with, large feed speed and large milling depth could benefit if the constrains of milling process were met with. The processing energy consumption of optimized process parameters decreased 27.21% compared with that of preferred process parameters while CSEC was reduced 32.07% and the processing time was reduced 34.11%. The proposed approach in this paper provided an efficient solution to reduce the impact of the environment caused by energy consumption and to realize the sustainable manufacturing. Graphical abstract: Image Highlights: The energy consumption module was built based on energy consumption characteristics. The optimization model was proposed to reduce the energy with CSEC and the process time. CSEC and the process time fell with the rise of feed speed, milling depth and milling width.