Evaluation on models of calculating energy consumption in metal cutting processes: a case of external turning process

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• 作者：Qianqian Zhong ; Renzhong Tang ; Jingxiang Lv…
• 关键词：Metal cutting processes ; Energy consumption models ; Model evaluation ; Evaluation criteria
• 刊名：The International Journal of Advanced Manufacturing Technology
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：82
• 期：9-12
• 页码：2087-2099
• 全文大小：3,015 KB
• 参考文献：1.Mukherjee I, Ray PK (2006) A review of optimization techniques in metal cutting processes. Comput Ind Eng 50(1–2):15–34. doi:10.​1016/​j.​cie.​2005.​10.​001 CrossRef
  2.Ma J, Ge X, Chang SI, Lei S (2014) Assessment of cutting energy consumption and energy efficiency in machining of 4140 steel. Int J Adv Manuf Technol 74(9–12):1701–1708. doi:10.​1007/​s00170-014-6101-3 CrossRef
  3.Dahmus JB, Gutowski TG An environmental analysis of machining. In: 2004 ASME International Mechanical Engineering Congress and Exposition, IMECE 2004, November 13, 2004–November 19, 2004, Anaheim, CA, United states, 2004. American Society of Mechanical Engineers, Manufacturing Engineering Division, MED. American Society of Mechanical Engineers, pp 643–652. doi:10.​1115/​imece2004-62600
  4.Li W, Kara S (2011) An empirical model for predicting energy consumption of manufacturing processes: a case of turning process. Proc Inst Mech Eng B J Eng Manuf 225(9):1636–1646. doi:10.​1177/​2041297511398541​ CrossRef
  5.Avram O, Stroud I, Xirouchakis P (2011) A multi-criteria decision method for sustainability assessment of the use phase of machine tool systems. Int J Adv Manuf Technol 53(5–8):811–828. doi:10.​1007/​s00170-010-2873-2 CrossRef
  6.Box GEP, Draper NR (1987) Empirical model-building and response surfaces. Wiley series in probability and mathematical statistics. John Wiley & Sons, Oxford, England
  7.Arrazola PJ, Ozel T, Umbrello D, Davies M, Jawahir IS (2013) Recent advances in modelling of metal machining processes. CIRP Ann Manuf Technol 62(2):695–718. doi:10.​1016/​j.​cirp.​2013.​05.​006 CrossRef
  8.Fang N (2003) Slip-line modeling of machining with a rounded-edge tool—Part I: new model and theory. J Mech Phys Solids 51(4):715–742. doi:10.​1016/​S0022-5096(02)00060-1 MATH CrossRef
  9.Luong LHS, Spedding TA (1995) A neural-network system for predicting machining behaviour. J Mater Process Technol 52(2–4):585–591. doi:10.​1016/​0924-0136(94)01626-C CrossRef
  10.Munoz AA, Sheng P (1995) An analytical approach for determining the environmental impact of machining processes. J Mater Process Technol 53(3–4):736–758. doi:10.​1016/​0924-0136(94)01764-r CrossRef
  11.Yang QB, Liu ZQ, Shi ZY, Wang B (2014) Analytical modeling of adiabatic shear band spacing for serrated chip in high-speed machining. Int J Adv Manuf Technol 71(9–12):1901–1908. doi:10.​1007/​s00170-014-5633-x CrossRef
  12.Iwata K, Osakada K, Terasaka Y (1984) Process modeling of orthogonal cutting by the rigid-plastic finite-element method. J Eng Mater Technol Trans ASME 106(2):132–138CrossRef
  13.Kim KW, Lee WY, Sin HC (1999) A finite-element analysis of machining with the tool edge considered. J Mater Process Technol 86(1–3):45–55
  14.Lalwani DI, Mehta NK, Jain PK (2008) Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel. J Mater Process Technol 206(1–3):167–179. doi:10.​1016/​j.​jmatprotec.​2007.​12.​018 CrossRef
  15.Tang J, Du J, Chen Y (2009) Modeling and experimental study of grinding forces in surface grinding. J Mater Process Technol 209(6):2847–2854. doi:10.​1016/​j.​jmatprotec.​2008.​06.​036 CrossRef
  16.Mori M, Fujishima M, Inamasu Y, Oda Y (2011) A study on energy efficiency improvement for machine tools. CIRP Ann Manuf Technol 60(1):145–148. doi:10.​1016/​j.​cirp.​2011.​03.​099 CrossRef
  17.Draganescu F, Gheorghe M, Doicin CV (2003) Models of machine tool efficiency and specific consumed energy. J Mater Process Technol 141(1):9–15. doi:10.​1016/​s0924-0136(02)00930-5 CrossRef
  18.Peng T, Xu X (2014) Energy-efficient machining systems: a critical review. Int J Adv Manuf Technol 72(9–12):1389–1406. doi:10.​1007/​s00170-014-5756-0 CrossRef
  19.Hassan GA, Suliman SMA (1990) Experimental modeling and optimization of turning medium carbon-steel. Int J Prod Res 28(6):1057–1065. doi:10.​1080/​0020754900894277​5 CrossRef
  20.Zhang YJ (2014) Energy efficiency techniques in machining process: a review. Int J Adv Manuf Technol 71(5–8):1123–1132. doi:10.​1007/​s00170-013-5551-3
  21.Balogun VA, Mativenga PT (2013) Modelling of direct energy requirements in mechanical machining processes. J Clean Prod 41:179–186. doi:10.​1016/​j.​jclepro.​2012.​10.​015 CrossRef
  22.Balogun VA, Mativenga PT (2014) Impact of un-deformed chip thickness on specific energy in mechanical machining processes. J Clean Prod 69:260–268. doi:10.​1016/​j.​jclepro.​2014.​01.​036 CrossRef
  23.Li L, Yan J, Xing Z (2013) Energy requirements evaluation of milling machines based on thermal equilibrium and empirical modelling. J Clean Prod 52:113–121. doi:10.​1016/​j.​jclepro.​2013.​02.​039 CrossRef
  24.Gutowski T, Dahmus J, Thiriez A (2006) Electrical energy requirements for manufacturing processes. In: 13th CIRP international conference on life cycle engineering, Leuven, Belgium, pp. 623–628
  25.Kara S, Li W (2011) Unit process energy consumption models for material removal processes. CIRP Ann Manuf Technol 60(1):37–40. doi:10.​1016/​j.​cirp.​2011.​03.​018 CrossRef
  26.Lv JX (2014) Research on energy supply modeling of computer numerical control machine tools for low carbon manufacturing. Thesis (PhD), Zhe Jiang University, Hang Zhou, China
  27.Rajemi MF, Mativenga PT, Aramcharoen A (2010) Sustainable machining: selection of optimum turning conditions based on minimum energy considerations. J Clean Prod 18(10–11):1059–1065. doi:10.​1016/​j.​jclepro.​2010.​01.​025 CrossRef
  28.Jia S, Tang RZ, Lv JX (2014) Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing. J Intell Manuf 25(5):913–931. doi:10.​1007/​s10845-012-0723-9 CrossRef
  29.He Y, Liu F, Wu T, Zhong FP, Peng B (2012) Analysis and estimation of energy consumption for numerical control machining. P I Mech Eng B J Eng 226(B2):255–266. doi:10.​1177/​0954405411417673​
  30.Avram OI, Xirouchakis P (2011) Evaluating the use phase energy requirements of a machine tool system. J Clean Prod 19(6–7):699–711. doi:10.​1016/​j.​jclepro.​2010.​10.​010 CrossRef
  31.Gara S, Bouzid W, Ben Amar M, Hbaieb M (2009) Cost and time calculation in rough NC turning. Int J Adv Manuf Technol 40(9–10):971–981. doi:10.​1007/​s00170-008-1417-5 CrossRef
  32.Lv JX, Tang RZ, Jia S (2014) Therblig-based energy supply modeling of computer numerical control machine tools. J Clean Prod 65:168–177. doi:10.​1016/​j.​jclepro.​2013.​09.​055 CrossRef
  33.Behrendt T, Zein A, Min S (2012) Development of an energy consumption monitoring procedure for machine tools. CIRP Ann Manuf Technol 61(1):43–46. doi:10.​1016/​j.​cirp.​2012.​03.​103 CrossRef
  34.Li W, Zein A, Kara S, Herrmann C An investigation into fixed energy consumption of machine tools. In: 18th CIRP International Conference on Life Cycle Engineering: Glocalized Solutions for Sustainability in Manufacturing, May 2, 2011–May 4, 2011, Braunschweig, Germany, 2011. Glocalized Solutions for Sustainability in Manufacturing—Proceedings of the 18th CIRP International Conference on Life Cycle Engineering. Springer Science and Business Media, LLC, pp 268–273. doi:10.​1007/​978-3-642-19692-8-47
  35.Murray VR, Zhao F, Sutherland JW (2012) Life cycle analysis of grinding: a case study of non-cylindrical computer numerical control grinding via a unit-process life cycle inventory approach. Proc Inst Mech Eng B J Eng Manuf 226(10):1604–1611. doi:10.​1177/​0954405412454102​ CrossRef
  36.Li YF, He Y, Wang Y, Yan P, Liu XH (2014) A framework for characterising energy consumption of machining manufacturing systems. Int J Prod Res 52(2):314–325. doi:10.​1080/​00207543.​2013.​813983 CrossRef
  37.Lanz M, Mani M, Leong S, Lyons K, Ranta A, Ikkala K, Bengtsson N Impact of energy measurements in machining operations. In: ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2010, August 15, 2010–August 18, 2010, Montreal, QC, Canada, 2010. Proceedings of the ASME Design Engineering Technical Conference. American Society of Mechanical Engineers, pp 867–873. doi:10.​1115/​detc2010-28713
  38.Liu F, Xu z, Dan B (1995) Energy performance of mechanical machining system and its application. China Machine Press, Beijing (in Chinese)
  39.Dietmair A, Verl A, Eberspaecher P (2011) Model-based energy consumption optimisation in manufacturing system and machine control. Int J Manuf Res 6(4):380–401. doi:10.​1504/​ijmr.​2011.​043238 , Special issue on RFID and Adaptive TechnologiesCrossRef
  40.Shi J, Liu F, Xu D, Chen G (2009) Decision model and practical method of energy-saving in NC machine tool. China Mech Eng 11:1344–1346 (in Chinese)
  41.Mativenga PT, Rajemi MF (2011) Calculation of optimum cutting parameters based on minimum energy footprint. CIRP Ann Manuf Technol 60(1):149–152. doi:10.​1016/​j.​cirp.​2011.​03.​088 CrossRef
  42.Hu S, Liu F, He Y, Hu T (2012) No-load energy parameter characteristics of computerized numerical control machine tool main transmission system. Comput Integr Manuf Syst 02:326–331
  43.Jia S, Tang R-Z, Lu J-X (2013) Therblig-based modeling methodology for cutting power and its application in external turning. Comput Integr Manuf Syst 19(5):1015–1024
  44.Altintas Y, Verl A, Brecher C, Uriarte L, Pritschow G (2011) Machine tool feed drives. CIRP Ann Manuf Technol 60(2):779–796. doi:10.​1016/​j.​cirp.​2011.​05.​010 CrossRef
  45.Di R, Pan X, Fan X (2001) Mechanical manufacturing engineering. Zhejiang University Press, Hangzhou (in Chinese)
  46.Wang Q, Liu F, Li C (2013) An integrated method for assessing the energy efficiency of machining workshop. J Clean Prod 52(0):122–133. doi:10.​1016/​j.​jclepro.​2013.​03.​020 MathSciNet CrossRef
  47.Liu Q, Chen X, Wang Y, Gindy N (2008) Empirical modelling of grinding force based on multivariate analysis. J Mater Process Technol 203(1–3):420–430. doi:10.​1016/​j.​jmatprotec.​2007.​10.​058 CrossRef
  48.Abou-El-Hossein KA, Kadirgama K, Hamdi M, Benyounis KY (2007) Prediction of cutting force in end-milling operation of modified AISI P20 tool steel. J Mater Process Technol 182(1–3):241–247. doi:10.​1016/​j.​jmatprotec.​2006.​07.​037 CrossRef
  49.Li JG, Lu Y, Zhao H, Li P, Yao YX (2014) Optimization of cutting parameters for energy saving. Int J Adv Manuf Technol 70(1–4):117–124. doi:10.​1007/​s00170-013-5227-z CrossRef
  50.Schlosser R, Klocke F, Lung D (2011) Sustainability in manufacturing—energy consumption of cutting processes. In: Seliger G, Khraisheh MMK, Jawahir IS (eds) Advances in Sustainable Manufacturing. Springer, Berlin Heidelberg, pp 85–89. doi:10.​1007/​978-3-642-20183-7_​13 CrossRef
  51.He Y, Liu F, Wu T, Zhong FP, Peng B (2011) Analysis and estimation of energy consumption for numerical control machining. Proc Inst Mech Eng B J Eng Ma 226(2):255–266. doi:10.​1177/​0954405411417673​ CrossRef
  52.Liu F, Liu S (2012) Multiperiod energy model of electromechanical main driving system during the service process of machine tools. J Mech Eng 21:132–140 (in Chinese)CrossRef
  53.Hu S, Liu F, He Y, Hu T (2012) An on-line approach for energy efficiency monitoring of machine tools. J Clean Prod 27:133–140. doi:10.​1016/​j.​jclepro.​2012.​01.​013 CrossRef
  54.Liu S, Liu F, Wang Q (2012) Energy efficiency acquisition method for electromechanical main driver system during the service process of machine tools. J Mech Eng 23:111–117 (in Chinese)CrossRef
  55.Al-Sulaiman FA, Sheikh AK, Baseer MA (2004) Empirical models of mechanical and electrical drilling power of mild steel. P I Mech Eng B J Eng 218(9):1181–1189. doi:10.​1243/​0954405041897077​
  56.Diaz N, Redelsheimer E, Dornfeld D Energy consumption characterization and reduction strategies for milling machine tool use. In: 18th CIRP International Conference on Life Cycle Engineering: Glocalized Solutions for Sustainability in Manufacturing, May 2, 2011–May 4, 2011, Braunschweig, Germany, 2011. Glocalized Solutions for Sustainability in Manufacturing—Proceedings of the 18th CIRP International Conference on Life Cycle Engineering. Springer Science and Business Media, LLC, pp 263–267. doi:10.​1007/​978-3-642-19692-8-46
  
• 作者单位：Qianqian Zhong (1)
  Renzhong Tang (1)
  Jingxiang Lv (2)
  Shun Jia (1) (3)
  Mingzhou Jin (1) (4)
  
  1. Industrial Engineering Center, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China
  2. Xi’an Research Institute of Navigation Technology, Xi’an, 710068, China
  3. Shandong University of Science and Technology, Qingdao, 266590, China
  4. Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, 37996, USA
  
• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering
  Production and Logistics
  Mechanical Engineering
  Computer-Aided Engineering and Design
  
• 出版者：Springer London
• ISSN：1433-3015

文摘

The manufacturing industry has been focusing on calculating energy consumption because of increased sustainability and environmental consciousness, resulting in a large number of calculation models. However, evaluation on these existing models is missing, so that practitioners often have trouble selecting the right energy models. To identify the most appropriate, cost-effective, and easy-to-implement energy models, three tasks were conducted in this paper. First, various experimental or empirical energy consumption models of spindle acceleration, spindle rotation, feed and material removal, and those of machine tool during material removal processes are reviewed. Then, five evaluation criteria, applicability, accuracy, computational efforts, complexity of fitting coefficients, and ease of data collection, are proposed. These criteria are identified based on the general steps to run the calculation models. Finally, the evaluation criteria are applied with the supporting experimental data of external turning to rank the models. This work is expected to assist practitioners in selecting models to calculate energy consumption in metal cutting processes for a particular situation and purpose. Keywords Metal cutting processes Energy consumption models Model evaluation Evaluation criteria