Abstract    This paper presents an approach to analytically determine the most energy efficient toolpath strategy in mechanical machining. This was achieved by evaluating the electrical energy requirement of the NC codes generated for the zag, zigzag, and rectangular contour toolpath strategies. The analytical method was validated by performing pocket milling on AISI 1018 steel with the considered toolpaths using a 3-axis Takisawa Mac-V3 milling machine. The rectangular contour toolpath was the most efficient in terms of the electrical energy demand of the feed axes and cycle time. Pocket milling with the zigzag toolpath strategy resulted in higher electrical energy demand of the feed axes and cycle time by 2% due to acceleration and deceleration characteristics of the machine tool feed axes execution at corners of the toolpath strategy adopted. Also, the electrical energy demand of the feed axes and cycle time for the zag toolpath were higher by 14% and 8%, respectively, due to the number of tool retracts as a result of the executed toolpath strategy. The experimental validation results showed good agreement with the analytical approach presented in this study. It can be deduced that for sustainable machining, the rectangular contour toolpath should be adopted since it has less tool retractions irrespective of the toolpath strategy adopted for machining. This could further enhance the selection of optimum green parameters by shop floor process engineers for sustainable manufacture of products.

Keywords    Energy Efficiency, modelling, Machining, Toolpath Strategies, NC Codes, Feed Axes.

چکیده    در این مقاله یک آنالیز تحلیلی برای تعیین کارآمدترین ابزار استراتژی در ماشینکاری مکانیکی ارائه شده است. این امر با ارزیابی انرژی الکتریکی مورد نیاز کدهای NC تولید شده برای راه حل های مسیرهای استراتژی زاگ، زایگاگ و خطوط مستطیلی ساخته شده است. روش تحلیلی با انجام مراحل جوش بر روی فولاد AISI 1018 با استفاده از دستگاه تراشکاری 3 محور Takisawa Mac-V3 مورد تایید قرار گرفت. این خط کش خطی مستطیل بیشتر از نظر تقاضای انرژی برق محور و زمان چرخه کارآمدترین بود. فرزکاری جیبی با استراتژی چرخش زیگزاگ موجب افزایش تقاضای انرژی الکتریکی در محورهای تغذیه و زمان چرخه به میزان 2 درصد به علت شتاب و ویژگی های کند شدن فرایندهای محور چرخش ماشین ابزار در گوشه های استراتژی ToolPath شده است. همچنین تقاضای انرژی الکتریکی برای محور تغذیه و زمان چرخه برای مسیر ابزار زاگ به ترتیب 14٪ و 8٪ بیشتر بوده اند، این مورد بخاطر تعداد ابزار استراتژی راه انداز اجرا شده است. دراین مطالعه نتایج اعتبار سنجی تجربی حاصل شده، توافق مطلوبی با آنالیز تحلیلی داشته اند. می توان نتیجه گرفت که برای ماشینکاری پایدار، خط کش خطی مستطیل شکل باید اتخاذ شود، زیرا این روش بدون در نظر گرفتن استراتژی toolpath به کمترین ابزار نیاز داشته، که برای ماشینکاری اتخاذ گردید. برای تولید محصول پایدار، انتخاب پارامترهای سبز بهینه توسط مهندسین فرایند کارخانه حائز اهمیت است.

References    1.     Sieminski, A., "International energy outlook", Energy Information Administration (EIA), Deloitte Oil and Gas Conference, Houston, TX, Nov. Vol. 18, No., (2014). 2.     Agency, E.U.S.E.I., "Energy consumption by sector",  AEO2013 Reference Case (Full Report) (2017). 3.     Conti, J., Holtberg, P., Diefenderfer, J., LaRose, A., Turnure, J.T. and Westfall, L., International energy outlook 2016 with projections to 2040. No. DOE/EIA--048 (2016), USDOE Energy Information Administration (EIA), Washington, DC (United States). Office of Energy Analysis. 4.     Chitnis, M., L. C. Hunt, "What drives the change in UK household energy expenditure and associated CO2 emissions? Implication and forecast to 2020." Applied Energy, Vol. 94, (2012), 202-214. 5.     Kianinejad, K., Uhlmann, E. and Peukert, B., "Investigation into energy efficiency of outdated cutting machine tools and identification of improvement potentials to promote sustainability", Procedia CIRP,  Vol. 26, (2015), 533-538. 6.     Balogun, V.A., Edem, I.F. and Mativenga, P.T., "E-smart toolpath machining strategy for process planning", The International Journal of Advanced Manufacturing Technology,  Vol. 86, No. 5-8, (2016), 1499-1508. 7.     Dahmus, J.B. and Gutowski, T.G., "An environmental analysis of machining", in ASME 2004 international mechanical engineering congress and exposition, American Society of Mechanical Engineers, (2004), 643-652. 8.     Edem, I.F. and Mativenga, P.T., "Energy demand reduction in milling based on component and toolpath orientations", Procedia Manufacturing,  Vol. 7, (2017), 253-261. 9.     Diaz, N., Helu, M., Jarvis, A., Tonissen, S., Dornfeld, D. and Schlosser, R., "Strategies for minimum energy operation for precision machining",  (2009).  https://escholarship.org/uc/item/794866g5 10.   Li, W., Zein, A., Kara, S. and Herrmann, C., An investigation into fixed energy consumption of machine tools", Glocalized solutions for sustainability in manufacturing. (2011), Springer, Berlin, Heidelberg. 268-273. 11.   Mori, M., Fujishima, M., Inamasu, Y. and Oda, Y., "A study on energy efficiency improvement for machine tools", CIRP Annals-Manufacturing Technology,  Vol. 60, No. 1, (2011), 145-148. 12.   Kroll, L., Blau, P., Wabner, M., Frieß, U., Eulitz, J. and Klärner, M., "Lightweight components for energy-efficient machine tools", CIRP Journal of Manufacturing Science and Technology,  Vol. 4, No. 2, (2011), 148-160. 13.   Edem, I.F. and Mativenga, P.T., "Impact of feed axis on electrical energy demand in mechanical machining processes", Journal of Cleaner Production,  Vol. 137, No., (2016), 230-240. 14.   Rangarajan, A. and Dornfeld, D., "Efficient tool paths and part orientation for face milling", CIRP Annals-Manufacturing Technology,  Vol. 53, No. 1, (2004), 73-76. 15.   Balogun, V.A., Edem, I.F., Adekunle, A.A. and Mativenga, P.T., "Specific energy based evaluation of machining efficiency", Journal of Cleaner Production,  Vol. 116, (2016), 187-197. 16.   Yan, J. and Li, L., "Multi-objective optimization of milling parameters–the trade-offs between energy, production rate and cutting quality", Journal of Cleaner Production, Vol. 52, (2013), 462-471. 17.   Al-Ghamdi, K.A. and Iqbal, A., "A sustainability comparison between conventional and high-speed machining", Journal of Cleaner Production,  Vol. 108, (2015), 192-206. 18.   Camposeco-Negrete, C., Nájera, J.d.D.C. and Miranda-Valenzuela, J.C., "Optimization of cutting parameters to minimize energy consumption during turning of aisi 1018 steel at constant material removal rate using robust design", The International Journal of Advanced Manufacturing Technology,  Vol. 83, No. 5-8, (2016), 1341-1347. 19.   Balogun, V.A. and Edem, I.F., "Optimum swept angle estimation based on the specific cutting energy in milling aisi 1045 steel alloy", International Journal of Engineering- Transactions A: Basics,  Vol. 30, No. 4, (2017), 591-596. 20.   Edem, I.F. and Mativenga, P.T., "Modelling of energy demand from computer numerical control (cnc) toolpaths", Journal of Cleaner Production,  Vol. 157, (2017), 310-321. 21.   Kramer, T.R., "Pocket milling with tool engagement detection", Journal of Manufacturing Systems,  Vol. 11, No. 2, (1992), 114-123. 22.   El-Midany, T.T., Elkeran, A. and Tawfik, H., "Toolpath pattern comparison: Contour-parallel with direction-parallel", in Geometric Modeling and Imaging-New Trends, 2006, IEEE., (1993), 77-82. 23.   Balogun, V.A., Gu, H. and Mativenga, P.T., "Improving the integrity of specific cutting energy coefficients for energy demand modelling", Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,  Vol. 229, No. 12, (2015), 2109-2117. 24.   Chan, Y.L. and Xu, X., "Evaluation and comparison of lubrication methods in finish machining of hardened steel mould inserts", Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,  Vol. 231, No. 14, (2017), 2458-2467.                                         25.   Toh, C., "A study of the effects of cutter path strategies and orientations in milling", Journal of Materials Processing Technology,  Vol. 152, No. 3, (2004), 346-356. 26.   Park, S.C. and Choi, B.K., "Tool-path planning for direction-parallel area milling", Computer-Aided Design,  Vol. 32, No. 1, (2000), 17-25. 27.   Kim, B.H. and Choi, B.K., "Machining efficiency comparison direction-parallel tool path with contour-parallel tool path", Computer-Aided Design,  Vol. 34, No. 2, (2002), 89-95. 28.   He, Y., Liu, F., Wu, T., Zhong, F. and Peng, B., "Analysis and estimation of energy consumption for numerical control machining", Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,  Vol. 226, No. 2, (2012), 255-266. 29.   Altıntaş, R.S., Kahya, M. and Ünver, H.Ö., "Modelling and optimization of energy consumption for feature based milling", The International Journal of Advanced Manufacturing Technology,  Vol. 86, No. 9-12, (2016), 3345-3363. 30.   Li, C., Li, L., Tang, Y., Yi, Q. and Zhu, Y., "Operational strategies for energy efficiency improvement of cnc machining", in Automation Science and Engineering (CASE), 2016 IEEE International Conference on, IEEE., (2016), 1270-1275. 31.   Edem, I.F., Balogun, V.A. and Mativenga, P.T., "An investigation on the impact of toolpath strategies and machine tool axes configurations on electrical energy demand in mechanical machining", The International Journal of Advanced Manufacturing Technology,  Vol. 92, No. 5-8, (2017), 2503-2509. 32.   Kong, D., Choi, S., Yasui, Y., Pavanaskar, S., Dornfeld, D. and Wright, P., "Software-based tool path evaluation for environmental sustainability", Journal of Manufacturing Systems,  Vol. 30, No. 4, (2011), 241-247. 33.   Tounsi, N., Bailey, T. and Elbestawi, M., "Identification of acceleration deceleration profile of feed drive systems in cnc machines", International Journal of machine tools and manufacture,  Vol. 43, No. 5, (2003), 441-451. 34.   Balogun, V.A., Kirkwood, N.D. and Mativenga, P.T., "Direct electrical energy demand in fused deposition modelling", Procedia CIRP,  Vol. 15, (2014), 38-43.