Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3 |
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| Authors: | Domnita Fratila Cristian Caizar |
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| Institution: | 1. Climate Change Research Division, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea;2. Center for Convergent Chemical Process, Korea Research Institute of Chemical Technology, 141 Gajeong-ro, Yuseong-gu, Daejeon 34114, Republic of Korea;3. University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea;4. Future Energy Plant Convergence Research Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea;1. Department of Mechanical Engineering, Faculty of Engineering, Karabük University, 78050 Karabük, Turkey;2. Department of Mechanical Education, Faculty of Technical Education, Düzce University, 81620 Düzce, Turkey;1. Advanced Manufacturing Laboratory, Institute of Infrastructure Technology Research and Management (IITRAM), Ahmedabad 380026, India;2. Institute of Machine Construction and Operations Engineering, University of Zielona Gora, Z. SzafranaSt, 65-516, Zielona, Gora, Poland;3. Department of Manufacturing Engineering and Automation Products, Opole University of Technology, 76 Proszkowska St, 45-758, Opole, Poland;4. Mechanical Design and Production Engineering Department, Cairo University, Giza 12613, Egypt;1. University of the Basque Country (UPV/EHU), Department of Mechanical Engineering, Alameda de Urquijo s/n, 48013 Bilbao, Spain;2. University of Huelva (UHU), Department of Chemical Engineering and Material Science, Campus de El Carmen, Chemical Product and Process Technology Research Center (Pro2TecS), 21071 Huelva, Spain;1. Department of Mechanical Engineering, Sinop University, 57030, Sinop, Turkey;2. Department of Manufacturing Engineering, Technology Faculty, Gazi University, 06500, Ankara, Turkey |
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| Abstract: | This paper outlines the Taguchi optimization methodology, which is applied to optimize the cutting parameters in face milling when machining AlMg3 (EN AW 5754) with HSS (high speed steel) tool under semi-finishing conditions in order to get the best surface roughness and the minimum power consumption. Beside the conventional flood lubrication, the investigations include the minimal quantity lubrication and the dry milling. These environment-friendly cutting techniques are considered two practical ways to the cleaner manufacturing in the context of the sustainable production. The parameters evaluated are the cutting speed, the depth of cut, the feed rate and the cooling lubrication techniques (cutting fluid flow). The appropriate orthogonal array, signal to noise (S/N) ratio and Pareto analysis of variance (ANOVA) are employed to analyze the effect of the mentioned parameters on the good surface finish (surface roughness). This paper illustrates the application of the techniques for single performance characteristics optimization, which employs the weighting factors to each of the S/N ration of the responses to obtain a multi-response S/N ratio for each trial of the orthogonal array and, finally, a single optimal process parameters setting. Using Taguchi method for the design of experiments (DOE), it is investigated the significant influence and the parameters interaction effect with minimum number of trials as compared with a full factorial design. |
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