Measurement and optimization of surface roughness and tool wear via grey relational analysis,TOPSIS and RSA techniques |
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| Affiliation: | 1. Department of Mechanical Engineering, KCG College of Technology, Chennai 600097, Tamil Nadu, India;2. Department of Mechanical Engineering, Kongunadu College of Engineering and Technology, Thottiam 621215, Tamil Nadu, India;3. Department of Bio-Medical Engineering, Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai 600062, Tamil Nadu, India;1. Research Scholar, Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi,835215,India;2. Associate Professor,Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi,835215,India;1. Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh;2. Mechanical Engineering, NIT-Hamirpur, Hamirpur, India;1. School of Mechanical and Materials Engineering, University College Dublin, Belfield, Dublin 4, Dublin, Ireland;2. Dept. of Mechanical Engineering, University of Aveiro, Campus Santiago, 3810-193 Aveiro, Portugal;3. Dept. of Manufacturing Engineering, Universidad Nacional de Educación a Distancia (UNED), C/ Juan del Rosal, 12, E28040 Madrid, Spain;1. Research Scholar, Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, India;2. Department of Mechanical Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India |
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| Abstract: | Magnesium alloy (Mg alloy) is one among the lightest materials and which has wide applications in the production of aircraft engines, airframes, helicopter components, light trucks, automotive parts and computers parts for its attractive properties. In this paper, a study to analyze the turning properties of magnesium alloy AZ91D in dry condition with polycrystalline diamond (PCD) cutting inserts is presented. Firstly, to investigate turning of magnesium alloy using grey relational analysis and TOPSIS of optimum cutting parameter values. Secondly, to determine using response surface analysis of mathematical model depending on cutting parameters of surface roughness and tool flank wear in turning. The adequacy of the developed mathematical model is proved by ANOVA. The findings from the investigation showed that feed rate and cutting speed are the dominant factors for surface roughness and tool flank wear respectively. |
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| Keywords: | Magnesium Surface roughness Flank wear TOPSIS Optimization |
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