MULTI-RESPONSE OPTIMIZATION OF END-MILLING PARAMETERS FOR INCONEL 625 USING TAGUCHI COUPLED WITH TOPSIS
Mohanraj Thangamuthu,
Jayanthi Yerchuru,
Nithin Aravind Ramasamy Shanmugam,
Yameni Ravi and
Ali Kaya Gur
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Mohanraj Thangamuthu: Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India
Jayanthi Yerchuru: Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India
Nithin Aravind Ramasamy Shanmugam: Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India
Yameni Ravi: Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India
Ali Kaya Gur: ��Department of Metallurgical and Materials Engineering, Faculty of Technology, University of Firat, Elazig, Turkey
Surface Review and Letters (SRL), 2021, vol. 28, issue 10, 1-11
Abstract:
Using Taguchi design of experiments (DoE), experiments were conducted with 3 factors and 3 levels. The factors were the depth of cut, spindle speed, and feed. The responses were surface roughness, flank wear, material removal rate, and spindle vibration along x (Vx), y (Vy), and z (Vz) axis. To convert the multi-response optimization problem into a single response optimization problem, the technique for order of preference by similarity to ideal solution (TOPSIS) was applied. The S/N of the closeness coefficients from TOPSIS was calculated and optimum machining conditions were obtained. Further, analysis of variance (ANOVA) was performed to verify which input parameter significantly affects the output responses. From TOPSIS optimization, the responses like surface roughness and flank wear were decreased by 0.99% and 2.55%. The vibration in x, y, and z-axis decreased by 3.84%, 16.87% and 12.48% respectively. This optimization significantly enhances the machining characteristics.
Keywords: Milling; Inconel 625; surface roughness; flank wear; vibrations; TOPSIS; ANOVA; multi-response optimization (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0218625X21500967
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