Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption

被引:73
作者
Deng, Zhaohui [1 ,2 ]
Zhang, Hua [1 ,2 ]
Fu, Yahui [1 ,2 ]
Wan, Linlin [1 ,2 ]
Liu, Wei [1 ,2 ]
机构
[1] Hunan Univ Sci & Technol, Hunan Prov Key Lab High Efficiency & Precis Machi, Xiangtan 411201, Peoples R China
[2] Hunan Univ Sci & Technol, Intelligent Mfg Inst, Xiangtan 411201, Peoples R China
关键词
Energy consumption; CSEC; Multi-objective optimization; Subjective and objective comprehensive weight; Quantum genetic algorithm; MINIMIZING POWER-CONSUMPTION; RESPONSE-SURFACE METHOD; ROUGHNESS; TAGUCHI; METHODOLOGY; PREDICTION; MODELS; LIFE;
D O I
10.1016/j.jclepro.2017.08.022
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1407 / 1414
页数:8
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