SOM-Kmeans Based Machine Tools Energy Efficiency Grade Evaluation

doi:10.3901/JME.2023.07.295

Abstract

Abstract: The evaluation of machine tool energy efficiency grade is the basis for improving energy efficiency. Most of the existing evaluation methods mostly use energy utilization and specific energy to evaluate the energy efficiency of specific machining processes, without considering the influence of machining capacity on machine tool energy efficiency evaluation. To comprehensively evaluate machine tools energy efficiency grade, the machine tools energy efficiency grade evaluation method based on Self-organizing Map and Kmeans (SOM-Kmeans) is proposed in terms of machining capacity and energy consumption characteristics. Firstly, the energy consumption and machining capacity characteristics are analyzed, and then the multi-period energy consumption characteristics and machining capacity index are constructed. Secondly, the cluster analysis of machine tool energy efficiency information is carried out using SOM-Kmeans and the machine tool energy efficiency grade is obtained based on principal component analysis (PCA). Finally, the effectiveness and practicability of the proposed method are verified by actual cases.

Key words: machine tool energy efficiency grade, machining capacity, energy consumption characteristics, cluster analysis

CLC Number:

TG501

CUI Jiabin, LI Congbo, CAO Huajun, CHEN Xingzheng, WANG Junjian, DAI Tao. SOM-Kmeans Based Machine Tools Energy Efficiency Grade Evaluation[J]. Journal of Mechanical Engineering, 2023, 59(7): 295-306.

References

[1] 国家统计局. 中国统计年鉴[M]. 北京:中国统计出版社,2021. National Bureau of Statistics. China statistical yearbook[M]. Beijing:China Statistics Press,2021.
[2] VELCHEV S,KOLEV I,IVANOV K,et al. Empirical models for specific energy consumption and optimization of cutting parameters for minimizing energy consumption during turning[J]. Journal of Cleaner Production,2014,80:139-149.
[3] LI B,TIAN X,ZHANG M. Modeling and multi-objective optimization method of machine tool energy consumption considering tool wear[J]. International Journal of Precision Engineering and Manufacturing-Green Technology,2022,9(1):127-141.
[4] GUTOWSKI T,DAHMUS J,THIRIEZ A. Electrical energy requirements for manufacturing processes[C]. Proceedings of 13th CIRP International Conference on Life Cycle Engineering. Leuven,Belgium,2006,31(1):623-638.
[5] 国家市场监督管理总局,中国国家标准化管理委员会. GB 37479-2019,风管送风式空调机组能效限定值及能效等级[S]. 北京:中国标准出版社,2020. State Administration for Market Regulation,Inspection and Quarantine of the People's Republic of China Standardization Administration. GB 37479-2019,Minimum allowable values of energy efficiency and energy efficiency grades for ducted air conditioners[S]. Beijing:Standards Press of China,2020.
[6] 中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会. GB 21519-2008,储水式电热水器能效限定值及能效等级[S]. 北京:中国标准出版社,2008. General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China Standardization Administration. GB 21519-2008,Minimum allowable values of energy efficiency and energy efficiency grades for electrical storage water heaters[S]. Beijing:Standards Press of China,2008.
[7] 国家市场监督管理总局,国家标准化管理委员会. GB 18613-2020 电动机能效限定值及能效等级[S]. 北京:中国标准出版社,2021. State Administration for Market Regulation,Standardization Administration. GB 18613-2020 Minimum allowable values of energy efficiency and values of efficiency grades for motors[S]. Beijing:Standards Press of China,2021.
[8] 谢俊,刘飞,蔡维. 机床服役过程能量效率的可预测特性及预测方法研究[J]. 机械工程学报,2019,55(17):172-184. XIE Jun,LIU Fei,CAI Wei. Research on the characteristics and methodology for predicting energy efficiency during the service process of machine tools[J]. Journal of Mechanical Engineering,2019,55(17):172-184.
[9] WESTERMANN H,KAFARA M,STEINHILPER R. Development of a reference part for the evaluation of energy efficiency in milling operations[J]. Procedia CIRP,2015,26:521-526.
[10] Japanese Standards Association. TS B 0024-1:2010,Machine tools test methods for electric power consumption-part1:Machining centres[S]. Japan:Japanese Standards Association,2010.
[11] Chen,X,Li C,TANG Y,et al. Integrated optimization of cutting tool and cutting parameters in face milling for minimizing energy footprint and production time[J]. Energy,2019,175:1021-1037.
[12] International Organization for Standardization. ISO 14955-3:2020,Machine tools-Environmental evaluation of machine tools-Part 3:Principles for testing metal-cutting machine tools with respect to energy efficiency[S]. ISO Technical Committee,2020.
[13] JI Q,LI C,ZHU D,et al. Structural design optimization of moving component in CNC machine tool for energy saving[J]. Journal of Cleaner Production,2020,246:118976.
[14] JEREMI W,LEONESIO M,BIANCHI G. Integrated energy analysis of cutting process and spindle subsystem in a turning machine[J]. Journal of Cleaner Production,2018,170:1459-1472.
[15] XIE J,CAI W,DU Y,et al. Modelling approach for energy efficiency of machining system based on torque model and angular velocity[J]. Journal of Cleaner Production,2021,293:126249.
[16] XIAO Q,LI C,TANG Y,et al. Energy efficiency modeling for configuration-dependent machining via machine learning:A comparative study[J]. IEEE Transactions on Automation Science and Engineering,2020,18(2):717-730.
[17] 李聪波,朱岩涛,刘飞,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):120-129. LI Congbo,ZHU Yantao,LIU Fei,et al. Multi-objective NC milling parameters optimization model for energy efficiency[J]. Journal of Mechanical Engineering,2016,52(21):120-129.
[18] 庹军波,刘飞,张华,等. 机床固有能量效率的内涵及其评价方法[J]. 机械工程学报,2018,54(7):167-175. TUO Junbo,LIU Fei,ZHANG Hua,et al. Connotation and assessment method for inherent energy efficiency of machine tools[J]. Journal of Mechanical Engineering,2018,54(7):167-175.
[19] 国家市场监督管理总局,国家标准化管理委员会. GB/T 40735-2021,数控机床固有能量效率的评价方法[S]. 北京:中国标准出版社,2022. State Administration for Market Regulation,Standardization Administration. GB/T 40735-2021,Method for inherent energy efficiency evaluation of computer numerical control machine tools[S]. Beijing:Standards Press of China,2022.
[20] SCHUDELEIT T,ZÜST S,WEGENER K. Methods for evaluation of energy efficiency of machine tools[J]. Energy,2015,93:1964-1970.
[21] NAN F,LI Y,JIA X,et al. Application of improved SOM network in gene data cluster analysis[J]. Measurement,2019,145:370-378.
[22] YU J,ZHOU K,YANG S. Land use efficiency and influencing factors of urban agglomerations in China[J]. Land Use Policy,2019,88:104-143.
[23] BRO R,SMILDE A K. Principal component analysis[J]. Analytical Methods,2014,6(9):2812-2831.
[24] ZHANG X,YU T,XU P,et al. An intelligent sustainability evaluation system of micro milling[J]. Robotics and Computer-Integrated Manufacturing,2022,73:102-239.