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Energy modeling for variable material removal rate machining process: an end face turning case

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Abstract

Material-cutting energy modeling is the key technology of energy modeling of machining process, being the foundation of energy optimization. The material-cutting power changes dynamically during variable-material removal rate (MRR) machining process. Hence, the energy characteristic of variable-MRR machining process is more complicated than that of constant-MRR machining process. In this paper, a modeling method of material-cutting energy for variable-MRR machining process is proposed. The dynamic power characteristics are fully considered in this method, and the impacts of cutting parameters on material-cutting energy are also considered. Experimental studies were conducted to obtain the fitting coefficients of the proposed energy model. Finally, energy calculations of four actual end face turning processes were performed. The results show that the predictive accuracy of all tested end face turning cases is above 90 %. The proposed method provides an accurate energy model for process planning in metal cutting process, which helps manufacturers determinate the energy-optimal process plan.

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References

  1. Duflou JR, Sutherland JW, Dornfeld D, Herrmann C, Jeswiet J, Kara S, Hauschild M, Kellens K (2012) Towards energy and resource efficient manufacturing: a processes and systems approach. CIRP Ann - Manuf Technol 61(2):587–609

    Article  Google Scholar 

  2. Calvanese ML, Albertelli P, Matta A, Taisch M (2013) Analysis of energy consumption in CNC machining centers and determination of optimal cutting conditions. In: Proceedings of 20th CIRP International Conference on Life Cycle Engineering, Singapore, pp 227–232.

  3. Dahmus J, Gutowski T (2004) An environmental analysis of machining. 2004 ASME International Mechanical Engineering Congress and Exposition. ASME, Anaheim, CA, United states, pp 643–652

    Google Scholar 

  4. Mouzon G, Yildirim MB, Twomey J (2007) Operational methods for minimization of energy consumption of manufacturing equipment. Int J Prod Res 45(18–19):4247–4271

    Article  MATH  Google Scholar 

  5. Rahimifard S, Seow Y, Childs T (2010) Minimising embodied product energy to support energy efficient manufacturing. CIRP Ann - Manuf Technol 59(1):25–28

    Article  Google Scholar 

  6. International Energy Agency (IEA) (2007) Tracking industrial energy efficiency and CO2 emission. OECD/IEA, Paris

    Google Scholar 

  7. 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

    Article  Google Scholar 

  8. Yan J, Li L (2013) Multi-objective optimization of milling parameters—the trade-offs between energy, production rate and cutting quality. J Clean Prod 52:462–471

    Article  Google Scholar 

  9. Bhushan RK (2013) Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites. J Clean Prod 39:242–254

    Article  Google Scholar 

  10. 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

    Article  Google Scholar 

  11. 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

    Article  Google Scholar 

  12. Diaz N, Redelsheimer E, Dornfeld D (2011) Energy consumption characterization and reduction strategies for milling machine tool use. In: Proceedings of the18th CIRP International Conference on Life Cycle Engineering., pp 263–267

    Google Scholar 

  13. Jia S, Tang RZ, Lv JX (2013) Therblig-based modeling methodology for cutting power and its application in external turning. Comp Integ Manuf Syst 19(5):1015–1024

    Google Scholar 

  14. 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

    Article  Google Scholar 

  15. Zhang Y (2013) Energy efficiency techniques in machining process: a review. Int J Adv Manuf Technol 71(5–8):1123–32

    Google Scholar 

  16. Fysikopoulos A, Pastras G, Alexopoulos T, Chryssolouris G (2014) On a generalized approach to manufacturing energy efficiency. Int J Adv Manuf Technol 73(9–12):1437–52

    Article  Google Scholar 

  17. Peng T, Xu X (2014) Energy-efficient machining systems: a critical review. Int J Adv Manuf Technol 72(9–12):1389–406

    Article  Google Scholar 

  18. 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):1701–8

    Article  Google Scholar 

  19. Wang X, Luo W, Zhang H, Dan B, Li F (2015) Energy consumption model and its simulation for manufacturing and remanufacturing systems. Int J Adv Manuf Technol. doi: 10.1007/s00170-015-7057-7

  20. Gutowski T, Murphy C, Allen D, Bauer D, Bras B, Piwonka T, Sheng P, Sutherland J, Thurston D, Wollf E (2005) Environmentally benign manufacturing: observations from Japan, Europe and the United States. J Clean Prod 13(1):1–17

    Article  Google Scholar 

  21. Gutowski T, Dahmus J, Thiriez A (2006) Electrical energy requirements for manufacturing processes. In: Proceedings of the 13th CIRP International Conference on Life Cycle Engineering, Leuven, May 31st-June 2nd, pp 623–627.

  22. Kara S, Li W (2011) Unit process energy consumption models for material removal processes. CIRP Ann - Manuf Technol 60(1):37–40

    Article  Google Scholar 

  23. Balogun VA, Mativenga PT (2013) Modelling of direct energy requirements in mechanical machining processes. J Clean Prod 41:179–186

    Article  Google Scholar 

  24. Lv JX, Jia S, Tang RZ (2014) Therblig-based energy supply modeling of CNC machine tools. J Clean Prod 65:168–177

    Article  Google Scholar 

  25. Dietmair A, Verl A (2009) A generic energy consumption model for decision making and energy efficiency optimization in manufacturing. Int J Sustain Eng 2(2):123–133

    Article  Google Scholar 

  26. Dietmair A, Verl A (2009) Energy consumption forecasting and optimization for tool machines. Modern Machinery Sci J 3:62–67

    Google Scholar 

  27. 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

    Article  Google Scholar 

  28. Avram OI, Xirouchakis P (2011) Evaluating the use phase energy requirements of a machine tool system. J Clean Prod 19(6–7):699–711

    Article  Google Scholar 

  29. 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

    Article  Google Scholar 

  30. Liu F, Liu J, He Y (2009) Automatic collection method of machining progress information for large-size workpieces based on reference power curve. J Mech Eng 45(10):111–117

    Article  Google Scholar 

  31. 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

    Article  Google Scholar 

  32. Tristo G, Bissacco G, Lebar A, Valentinčič J (2015) Real time power consumption monitoring for energy efficiency analysis in micro EDM milling. Int J Adv Manuf Technol 78(9–12):1511–21

    Article  Google Scholar 

  33. Li J, Lu Y, Zhao H, Li P, Yao Y (2013) Optimization of cutting parameters for energy saving. Int J Adv Manuf Technol 70(1–4):117–124

    Google Scholar 

  34. Wang Q, Liu F, Wang X (2013) Multi-objective optimization of machining parameters considering energy consumption. Int J Adv Manuf Technol 71(5–8):1133–1142

    Google Scholar 

  35. Campatelli G, Lorenzini L, Scippa A (2014) Optimization of process parameters using a response surface method for minimizing power consumption in the milling of carbon steel. J Clean Prod 66:309–316

    Article  Google Scholar 

  36. 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

    Article  Google Scholar 

  37. Diaz N, Ninomiya K, Noble J, Dornfeld D (2012) Environmental impact characterization of milling and implications for potential energy savings in industry. Procedia CIRP 1:518–523

    Article  Google Scholar 

  38. Bayoumi AE, Yücesan G, Hutton DV (1994) On the closed form mechanistic modeling of milling: specific cutting energy, torque and power. J Mater Eng Perform 3(1):151–158

    Article  Google Scholar 

  39. Liu F, Xu ZJ, Dan B (1995) Energy characteristic of mechanical machining system and its application. China Machine Press, Beijing

    Google Scholar 

  40. Kordonowy DN (2002) A power assessment of machining tools, bachelor of science thesis in mechanical engineering. Massachusetts Institute of Technology, Cambridge, Massachusetts

    Google Scholar 

  41. Stute H, Limed EVD (1995) Transmissions and efficiencies for machine tools. Industrial indicator. 5–8

  42. China Machinery Industry Federation (1997) Machining technology handbook. China Machine Press, Beijing

    Google Scholar 

  43. Ai X, Xiao SG (1994) Handbook of cutting parameters, 3rd edn. China Machine Press, Beijing

    Google Scholar 

  44. Camposeco-Negrete C (2013) Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA. J Clean Prod 53:195–203

    Article  Google Scholar 

  45. Jia S, Tang RZ, Lv JX (2014) Machining activity extraction and energy attributes inheritance method to support intelligent energy estimation of machining process. J Intell Manuf. doi: 10.1007/s10845-014-0894-7

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Correspondence to Renzhong Tang.

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Jia, S., Tang, R., Lv, J. et al. Energy modeling for variable material removal rate machining process: an end face turning case. Int J Adv Manuf Technol 85, 2805–2818 (2016). https://doi.org/10.1007/s00170-015-8133-8

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  • DOI: https://doi.org/10.1007/s00170-015-8133-8

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