Abstract
Manufacturing processes, such as machining, transform raw materials into finished goods, and these processes consume significant energy. There is an increasing concern about the energy required for such processes and the environmental consequences attributable to the generation of the energy. Reducing the energy required to perform machining operations will not only reduce the environmental footprint, but also provide economic benefits. To that end, the effects of cutting conditions (e.g., feed and speed) and tool geometry (diameter and number of teeth) on the power required for an end milling operation are investigated experimentally. Experimental results are presented from a cutting mechanism perspective with the goal of understanding the role of the process variables. The specific cutting energy (SCE) is found decreasing when material removal rate increases, but there is substantial variation about the general trend. In essence, the cutting parameters and the tool geometry influenced the changes of average chip thickness and cutting speed, which cause the shear deformation energy changes and eventually collectively influence the SCE’s change. Based on the experiments, suggestions on selecting process parameters are provided to improve milling energy efficiency.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Reference
International Energy Agency (IEA) (2016) World energy outlook special report 2016 : energy and air pollution. http://www.iea.org/publications/freepublications/publication/WorldEnergyOutlookSpecialReport2016EnergyandAirPollution.pdf. Accessed 23 Aug 2018
Gutowski T, Dahmus J, Thiriez A (2006) Electrical energy requirements for manufacturing processes. In: Proceedings of 13th CIRP international conference on life cycle engineering. Leuven, Belgium, pp 5–11
Peng T, Xu X (2014) Energy-efficient machining systems: a critical review. Int J Adv Manuf Technol 72(9–12):1389–1406
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
Wang B, Liu ZQ, Song QH, Wan Y, Shi ZY (2016) Proper selection of cutting parameters and cutting tool angle to lower the specific cutting energy during high speed machining of 7050-T7451 aluminum alloy. J Clean Prod 129:292–304
Cook NH (1966) Manufacturing analysis, 1st edn. Addison-Wesley Publishing Company, Boston, pp 36–38
Merchant ME (1945) Mechanics of the metal cutting process II. Plasticity conditions in orthogonal cutting. J Appl Phys 16:318–324
Shaw MC (2004) Metal cutting principles, 2nd edn. Oxford University Press, Oxford
Oxley PLB (1962) Shear angle solutions in orthogonal machining. Int J Mach Tool Des Res 2(3):219–229
Huang Y, Liang SY (2003) Cutting forces modeling considering the effect of tool thermal property - application to CBN hard turning. Int J Mach Tools Manuf 43(3):307–315
Karpat Y, Özel T (2006) Predictive analytical and thermal modeling of orthogonal cutting process-part I: predictions of tool forces, stresses, and temperature distributions. Trans ASME J Manuf Sci Eng 128(2):435–444
Lalwani DI, Mehta NK, Jain PK (2009) Extension of Oxley’s predictive machining theory for Johnson and Cook flow stress model. J Mater Process Technol 209(12–13):5305–5312
Sutherland JW, DeVor RE (1986) An improved method for cutting force and surface error prediction in flexible end milling systems. ASME J Eng Ind 108(4):269–279
Kline WA, Devor RE, Lindberg JR (1982) The prediction of cutting forces in end milling with application to cornering cuts. Int J Mach Tool Des Res 22(1):7–22
Martellotti ME (1945) An analysis of the milling process: part II-down milling. Trans Am Soc Mech Eng 67:223–251
Sabberwal AJP (1962) Cutting forces in down milling. Int J Mach Tool Des Res 2:27–41
Kline WA, Devor RE (1983) The effect of runout on cutting geometry and forces in end milling. Int J Mach Tool Des Res 23(2/3):123–140
Koenigsberger F, Sabberwal AJP (1961) An investigation into the cutting force pulsations during milling operations. Int J Mach Tool Des Res 1:15–33
Fang F, Xu F, Lai M (2015) Size effect in material removal by cutting at nano scale. Int J Adv Manuf Technol 80(1–4):591–598
Endres WJ, DeVor RE, Kapoor SG (1995). A dual-mechanism approach to the prediction of machining forces, part 1: Model development. J Manuf Sci E-T ASME 117(4):526–533
Wu X, Li L, He N, Hao X, Yao C, Zhong L (2016) Investigation on the ploughing force in microcutting considering the cutting edge radius. Int J Adv Manuf Technol 9(86):2441–2447
Balogun VA, Edem IF, Adekunle AA, Mativenga PT (2016) Specific energy based evaluation of machining efficiency. J Clean Prod 116:187–197
Shen Z, Sun X, Liu G, Chen M (2007) The milling mechanism of Ti6Al4V based on average cutting thickness. J Shanghai Jiaotong U 41(4):614–618 (in Chinese)
Ma J, Ge X, Chang S, 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
Lv JX, Tang RZ, Jia S (2014) Therblig-base d energy supply modeling of computer numerical control machine tools. J Clean Prod 65:168–177
Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. In Proceedings of the 7th International Symposium on Ballistics 21(1):541–547
Acknowledgements
Magdalene Jackson is thanked for providing valuable insight and advice.
Funding
Research of this paper is supported by the National Natural Science Foundation of China (NO. 51675314) and Project from Ministry of Industry and Information Technology of China (No. NO.201656261-1-3).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhou, L., Li, F., Zhao, F. et al. Characterizing the effect of process variables on energy consumption in end milling. Int J Adv Manuf Technol 101, 2837–2848 (2019). https://doi.org/10.1007/s00170-018-3015-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-018-3015-5