机床能量效率测试方法的多场景综合评价研究

doi:10.3901/JME.2023.07.265

摘要/Abstract

摘要： 机床量大面广，能耗总量巨大，提升机床能量效率已经成为发展绿色制造的重要内容。如何选择合适的机床能效测试方法是支撑机床设计、用户采购、运行优化和节能改造等场景下提升机床能量效率的基础性问题。为此，首先总结和比较了八种能效测试方法的内涵和特点，包括参考样件法、参考过程法、比能法、组件定标法、ISO 14955-3标准、GB/T 40735标准、固有能效潜力评估法和固有曲面法。然后，从五个场景(指导高能效机床优化设计、评选高能效机床制定能效标签等)和七个维度(操作耗时程度、操作难易程度、机床对比适用度等)评价机床能效测试方法。其中，运用层次分析法(AHP法)确定特定场景下七项评价指标的权重因素和各项评价指标下八种能效测试方法权重因素，并通过一致性检验来验证评价结果的有效性和准确性。

关键词: 机床能效, 能效测试, 能效评价, 能效标签, 层次分析法

Abstract: Machine tools are in enormous quantity and consume great amount of energy. Improving the energy efficiency of machine tools has become an important part of the development of green manufacturing. It is a fundamental problem to select appropriate test methods for machine tool energy efficiency in the scenarios of machine tool design, user procurement, operation optimization and energy saving transformation. Therefore, the connotation and characteristics of the eight energy efficiency testing methods were summarized and compared, including reference part method, reference process method, specific energy consumption method, component benchmark method, ISO 14955-3 standard, GB/T 40735 standard, inherent energy efficiency potential assessment method and inherent surface method. Then, the energy efficiency test method of machine tools was evaluated from five scenarios (guidance for optimal design of high energy efficiency machine tools, selection of high energy efficiency machine tools and design of energy efficiency labels, etc) and seven dimensions (time required, simplicity of the test method and comparison of machine tools, etc).The analytic hierarchy process (AHP) is used to determine the weight factors of seven evaluation index in specific scenarios and the weight factors of eight energy efficiency testing method under each evaluation index. The validity and accuracy of the evaluation results were verified by consistency test.

Key words: machine tool energy efficiency, energy efficiency test, energy efficiency evaluation, energy efficiency label, analytic hierarchy

中图分类号:

TG501

王旭, 朱倩, 刘培基, 于方圆. 机床能量效率测试方法的多场景综合评价研究[J]. 机械工程学报, 2023, 59(7): 265-275.

WANG Xu, ZHU Qian, LIU Peiji, YU Fangyuan. Multi-scene Comprehensive Evaluation of Energy Efficiency Testing Methods for Machine Tools[J]. Journal of Mechanical Engineering, 2023, 59(7): 265-275.

参考文献

[1] 刘培基,刘飞,王旭,等. 绿色制造的理论与技术体系及其新框架[J]. 机械工程学报,2021,57(19):165-179. LIU Peiji,LIU Fei,WANG Xu. The theory and technology system of green manufacturing and their new frameworks[J]. Journal of Mechanical Engineering, 2021,57(19):165-179.
[2] 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 architecture and future trends of energy efficiency research on machining systems[J]. Journal of Mechanical Engineering,2013,49(19):87-94.
[3] 刘飞. 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. Energy characteristics and application of machining system[M]. Beijing:China Machine Press,1995.
[4] DAHMUS J,GUTOWSKI T. An environmental analysis of machining[C]//2004 ASME International Mechanical Engineering Congress and RD&D Expo. November 13-19,2004. Anaheim,California USA.
[5] 刘飞,刘培基,李聪波,等. 制造系统能量效率研究的现状及难点问题[J]. 机械工程学报,2017,53(5):1-11. LIU Fei,LIU Peiji,LI Congbo,et al. The statue and difficult problems of research on energy efficiency of manufacturing systems[J]. Journal of Mechanical Engineering,2017,53(5):1-11.
[6] 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.
[7] 王秋莲,刘飞. 数控机床多源能量流的系统数学模型研究[J]. 机械工程学报,2013,49(7):5-12. WANG Qiulian,LIU Fei. Research on mathematical model of multi-source energy flows for CNC machine tools[J]. Journal of Mechanical Engineering,2013,49(7):5-12.
[8] HU S,LIU F,HE Y,et al. An on-line approach for energy efficiency monitoring of machine tools[J]. Journal of Cleaner Production,2012,27:133-140.
[9] XIAO Q,LI C,TANG Ying,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.
[10] 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.
[11] 刘培基,刘霜,刘飞. 数控机床主动力系统载荷能量损耗系数的计算获取方法[J]. 机械工程学报,2016,52(11):121-128. LIU Peiji,LIU Shuang,LIU Fei. Calculating method for additional load loss coefficient of spindle system of CNC machine tools[J]. Journal of Mechanical Engineering,2016,52(11):121-128.
[12] 刘培基. 机床固有能效要素获取方法及其应用研究[D]. 重庆:重庆大学,2015. LIU Peiji. Acquisition method and applications of inherent energy efficiency factors in machine tools[D]. Chongqing:Chongqing University,2015.
[13] CAI W,LIU F,XIE J,et al. An energy management approach for the mechanical manufacturing industry through developing a multi-objective energy benchmark[J]. Energy Conversion and Management,2017,132:361-371.
[14] CAI W,LIU F,ZHANG H,et al. Development of dynamic energy benchmark for mass production in machining systems for energy management and energy-efficiency improvement[J]. Applied Energy,2017,202:715-725.
[15] 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.
[16] MA F,ZHANG H,GONG Q,et al. A novel energy efficiency grade evaluation approach for machining systems based on inherent energy efficiency[J]. International Journal of Production Research,2021,59(19):6022-6033.
[17] 尚振东. 重型数控铣镗床能耗特性及能效评价方法研究[D]. 哈尔滨:哈尔滨工业大学,2019. SHANG Zhendong. Research on characteristics and performance evaluation of energy consumption of heavyduty CNC milling and boring machine tools[D]. Harbin:Harbin Institute of Technology,2019.
[18] SCHUDELEIT T,ZÜST S,WEGENER K. Methods for evaluation of energy efficiency of machine tools[J]. ENERGY,2015,93:1964-1970.
[19] International Standardization Organization. ISO 14955-1:2017 Machine tools-Environmental evaluation of machine tools-Part 1:Design methodology for energy-efficient machine tools[S]. Geneva:ISO,2017.
[20] International Standardization Organization. ISO 14955-2:2018 Machine tools-Environmental evaluation of machine tools-Part 2:Methods for measuring energy supplied to machine tools and machine tool components[S]. Geneva:ISO,2018.
[21] International Standardization Organization. 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]. Geneva:ISO,2020.
[22] 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:China Standards Press,2022.
[23] LIU Peiji,LIU Fei,QIU Hang. A novel approach for acquiring the real-time energy efficiency of machine tools[J]. Energy,2017,121:524-532.
[24] SAATY T L. The analytic hierarchy process:Planning,priority setting,resource allocation[J]. European Journal of Operational Research,1982,9(1):97-98..
[25] JIS TS B 0024-1:2010. Machine tools E test methods for electric power consumption-part 1:Machining centres[S]. Tokyo:Japanese Standards Association,2010.
[26] JIS TS B 0024-2:2010. Machine tools e test methods for electric power consumption-part 2:numerically controlled turning machines and turning centres.[S]. Tokyo:Japanese Standards Association,2010.
[27] JIS TS B 0024-3:2010. Machine tools e test Methods for electric power consumption-part 3:horizontal grinding wheel spindle and reciprocating table type surface grinding machines[S]. Tokyo:Japanese Standards Association,2010.
[28] JIS TS B 0024-4:2010. Machine tools e test methods for electric power consumption-part 4:Cylindrical grinding machines[S]. Tokyo:Japanese Standards Association,2010.
[29] WESTERMANN H 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.
[30] 杨增光. 数控加工标准样件设计及能耗数据管理系统研究[D]. 哈尔滨:哈尔滨工业大学,2013. YANG Zengguang. Research on standard sample design of NC machining and energy consumption data management system[D]. Harbin:Harbin Institute of Technology,2013.
[31] MICHAEL K. Energieeffizienz-Kennziffer fur Maschinensysteme:Eine Moglichkeit des Maschinenvergleichs[J]. Werkstatt + Betrieb:WB,2011,144(12):60,62-64.
[32] DIETMAIR A,VERL A. A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing[J]. International journal of sustainable engineering,2009,2(2):123-133.
[33] LI W,KARA S. An empirical model for predicting energy consumption of manufacturing processes:a case of turning process[J]. Proceedings of the Institution of Mechanical Engineers,Part B:Journal of Engineering Manufacture,2011,225(9):1636-1646.
[34] GUTOWSKI,DAHMUS,THITIEZ,et al. A thermodynamic characterization of manufacturing processes[C]//IEEE International Symposium on Electronics & the Environment. IEEE,2007.
[35] SCHUDELEIT T,ZÜST S,WEISS L,et al. Machine tool energy efficiency-a component mapping-based approach[J]. International Journal of Automation Technology,2016,10(5):717-726.
[36] 李聪波,肖溱鸽,李丽,等. 基于田口法和响应面法的数控铣削工艺参数能效优化方法[J]. 计算机集成制造系统,2015,21(12):3182-3191. LI Congbo,XIAO Qinge,LI Li,et al. Optimization method of NC milling parameters for energy efficiency based on Taguchi and RSM[J]. Computer Integrated Manufacturing Systems,2015,21(12):3182-3191.
[37] KARA S,LI W. Unit process energy consumption models for material removal processes[J]. CIRP Annals,2011,60(1):37-40.
[38] ZHAO G,LI C,LV Z,et al. Specific energy consumption prediction model of CNC machine tools based on tool wear[J]. International Journal of Computer Integrated Manufacturing,2020,33(2):159-168.
[39] KORDONOWY,DAVID N. A power assessment of machining tools[M]. Gambridge:Massachusetts Institute of Technology,2006.
[40] LAREK R,BRINKSMEIER E,MEYER D,et al. A discrete-event simulation approach to predict power consumption in machining processes[J]. Production Engineering,2011,5(5):575-579.
[41] SCHUDELEIT T,ZÜST S,WEISS L,et al. The total energy efficiency index for machine tools[J]. Energy,2016,102(5):682-693.