A Cutting Parameter Energy-saving Optimization Method for CNC Turning Batch Processing Considering Tool Wear

doi:10.3901/JME.2021.01.217

Abstract

Abstract: In a CNC batch turning process, the increased tool wear will lead to a significant raise of energy consumption. Due to the lack of researches on synergistic effect of tool wear and cutting parameters on energy consumption, this paper proposes an energy aware cutting parameter optimization approach for CNC batch turning by considering tool wear. Firstly, the synergistic mechanism of tool wear and cutting parameters on energy consumption of CNC batch turning is analyzed. On the basis, a multi-objective optimization model for minimizing energy consumption and production time is established with the variables of the cutting parameters under different tool wear conditions. Then a multi-objective simulated annealing algorithm is proposed to solve the optimization model. Compared with the empirical cutting parameters, the total energy consumption can be reduced by 14.9% and the total production time can be reduced by 9.8% with the optimized cutting parameters. This verifies the effectiveness and practicability of the proposed optimization approach.

Key words: tool wear, cutting parameters, CNC batch turning, multi-objective optimization

CLC Number:

TH162

LI Congbo, YU Bisheng, XIAO Qinge, SUN Xin, Lü Yan. A Cutting Parameter Energy-saving Optimization Method for CNC Turning Batch Processing Considering Tool Wear[J]. Journal of Mechanical Engineering, 2021, 57(1): 217-229.

References

[1] 刘飞,王秋莲,刘高君. 机械加工系统能量效率研究的内容体系及发展趋势[J]. 机械工程学报,2013,49(19):87-94. LIU Fei,WANG Qiulian,LIU Gaojun. Content system and development trend of energy efficiency research in mechanical processing system[J]. Journal of Mechanical Engineering,2013,49(19):87-94.
[2] 刘博. 考虑刀具磨损的机床能耗建模及多目标优化方法研究[D]. 哈尔滨:哈尔滨工业大学,2017. LIU Bo. Research on machine tool energy consumption modeling and multi-objective optimization method considering tool wear[D]. Harbin:Harbin Institute of Technology,2017.
[3] 李聪波,朱岩涛,李丽,等. 面向能量效率的数控铣削加工参数多目标优化模型[J]. 机械工程学报,2016,52(21):130-137. LI Congbo,ZHU Yantao,LI Li,et al. Multi-objective optimization model for numerical control milling machining parameters for energy efficiency[J]. Journal of Mechanical Engineering,2016,52(21):130-137.
[4] CAMPOSECO N C,NAJERA J D D C,MIRANDA V J C. Optimization of cytting parameters to minimize energy consumption during turning of AISI 1080 steel at constant material removel rate using robust design[J]. The International Journal of Advanced Manufacturing Technology,2016,83(5-8):1314-1317.
[5] KUMAR R,BILGA P S,SINGH S. Multi-objective using different methods of assigning weights to energy consump-tion respons,surface roughness and material removal rate during rough turing operation[J]. Journal of Cleaner Production,2017,164:45-57.
[6] LI Congbo,LI Li,TANG Ying,et al. A comprehensive approach to parameters optimization of energy-aware CNC milling[J]. Journal of Intelligent Manufacturing,2019(30):123-138.
[7] SHOBA C,SIVAPRASAD D,SUCHARIT A,et al. Investigations of Surface roughness,power consumption MRR and tool wear while turning hybrid composites[C]. Materials Today,August 10,2018(5):16565-16574.
[8] SUN Yujing,SUN Jie,Li Jianfeng,et al. Modeling of cutting force under the tool flank wear effect in end milling Ti6Al4V with solid carbide tool[J].The International Journal of Advanced Manufacturing Technology,2013,69(9-12):2545-2553.
[9] HOU Yongfeng,ZHANG Dinghua,WU Baohai,et al. Milling force modeling of worn tool and tool flank wear recognition in end milling[J]. IEEE/ASME Transactions on Mechatronics,2015,20(3):1024-1035.
[10] TIAN Changle,ZHOU Guanghui,ZHANG Junjie,et al. Optimization of cutting parameters considering tool wear conditions in low-carbon manufacturing environment[J]. Journal of Cleaner Production,2019,226:706-719.
[11] LIU Zhanqiang,GUO Yanbin,SEALY M,et al. Energy consumption and process sustainability of hard milling with tool wear progression[J]. Journal of Materials Processing Technology,2016,229:305-312.
[12] XIE Nan,ZHOU Junfeng,ZHENG Beirong. Selection of optimum turning parameters based on cooperative optimization of minimum energy consumption and high surface quality[C]. Conference on Manufacturing Systems:Procedia CIRP,June 27,2018(72):1469-1474.
[13] GAYATRI R,BASKAR N. Performance analysis of nontraditional algorithmic parameters in machining operation[J]. The International Journal of Advanced Manufacturing Technology,2015,77(1-4):443-460.
[14] 刘飞,徐宗俊,但斌. 机械加工系统能量特性及其应用[M]. 北京:机械工业出版社,1995. LIU Fei,XU Zongjun,DAN Bin. Energy performance of mechanical processing system and appication[M]. Beijing:China Machine Press,1995.
[15] LV Jingxiang,TANG Renzhong,TANG Wangchujun,et al. An investigation into reducing the spindle acceleration energy consumption of machine tools[J]. Journal of Cleaner Production,2017,143:794-803.
[16] 武文革,辛志杰. 金属切削原理及刀具[M]. 北京:国防工业出版社,2009. WU Wenge,XIN Zhijie. Metal cutting principle and tool[M]. Beijing:National Defense Industry Press,2009.
[17] 黄拯滔,杨杰,张超勇,等. 面向能耗的数控铣削过程建模与参数优化[J]. 中国机械工程,2016,27(18):2524-2532. HUANG Zhengtao,YANG Jie,ZHANG Chaoyong,et al. Energy consumption oriented modeling and parameter optimization of NC milling process[J]. China Mechanical Engineering,2016,27(18):2524-2532.
[18] LI Jianguang,LU Yong,ZHAO Hang,et al. Optimization of cutting parameters for energy saving[J]. The International Journal of Advanced Manufacturing Technology,2014,70(1-4):117-124.
[19] MATAI R. Solving multi-objective facility layout problem by modified simulated annealing[J]. Applied Mathematics & Computation,2015,261:302-311.
[20] ZARETALAB A,HAJIPOUR V,SHARIFI M,et al. A knowledge-based archive multi-objective simulated annealing algorithm to optimize series parallel system with choice of redundancy strategies[J]. Computers & Industrial Engineering,2015,80:33-44.
[21] ZHOU Guanghui,YUAN Shengze,LU Qi,et al. A carbon emission quantitation model and experimental evaluation for machining process considering tool wear condition[J]. The International Journal of Advanced Manufacturing Technology,2018,98(1-4):565-577.