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Achieving machining effectiveness for AISI 1015 structural steel through coated inserts and grey-fuzzy coupled Taguchi optimization approach

Publication Type : Journal Article

Publisher : Structural and Multidisciplinary Optimization

Source : Structural and Multidisciplinary Optimization, Springer, Volume 63, p.63 (2020)

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Keywords : AISI 1015 steel, Flank wear, Fuzzy, grey relational analysis, Multi-response optimization, Surface roughness, Taguchi

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2020

Abstract : Multi-objective optimization technique has become an essential step in the selection of cutting parameters. The intension of this research study is to analyze the performance characteristics of coated carbide inserts on their measured output responses during machining AISI 1015 steel. This paper targets to optimize the machining parameters such as speed, cutting depth, feed rate, cutting fluid flow rate, and coating material when multiple responses like surface roughness and flank wear were considered at the same time during turning. This research study also intends to examine scientifically the effect of machining parameters on quality measures during machining structural AISI 1015 steel. Cathodic arc evaporation–coated titanium aluminum nitride (TiAlN), titanium aluminum nitride/tungsten carbide-carbon (TiAlN/WC-C), and uncoated CNC inserts were used for the study. SEM and energy-dispersive X-ray analysis were performed to confirm the presence of coated elements. Micro-hardness was measured for coated, pure inserts, and TiAlN/WC-C-coated tool exhibited a higher hardness of 22.11 GPa compared with pure and coated tools. Five process parameters were used for this study, each at three stages. The experimental design was laid based on Taguchi’s L27 orthogonal array. In this research study, a multi-objective hybrid optimization technique comprising grey relation and fuzzy logic conjugated with the Taguchi design of experiments was used. The process parameters were optimized by grey relation analysis followed by fuzzification using Mamdani fuzzy engine and then optimized through Taguchi analysis. The parameter combination of speed 500 rpm, depth of cut of 1 mm, a feed rate of 0.05 mm/rev, cutting fluid flow rate at high level, and TiAlN/WC-C coating was found to be the optimum input parameters. The confirmatory test was also performed to validate the hybrid optimization approach.

Cite this Research Publication : C. Moganapriya, Rajasekar, R., P Kumar, S., T. Mohanraj, Gobinath, V. K., and Saravanakumar, J., “Achieving machining effectiveness for AISI 1015 structural steel through coated inserts and grey-fuzzy coupled Taguchi optimization approach”, Structural and Multidisciplinary Optimization, vol. 63, p. 63, 2020.

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