Abstract
This paper envisages on enhancing the cutting environments for exterior irregularity (Ra), tool wear (Tw), and material removal rate (MRR) obtained in machining of Spheroidal graphite SG 500/7. Machining trials are accomplished at the VMC using Titanium Nitride (TiN), Titanium Aluminum Nitride (TiAlN), Titanium Carbo-Nitride (TiCN), and Zirconium Nitride (ZrN) covered carbide-cutting tools on SG 500/7 material. Cutting speed, tool material, and feed rate are preferred as the cutting factors. Taguchi L16 orthogonal array is used to design of a tryout. The weight of each criterion is required for calculating the weighted normalized matrix is determined by the analytic hierarchy process (AHP) method. The best cutting environments and their preferences depend on relative nearness value determined using technique for order preference by similarity to ideal solution (TOPSIS). This combined practice is a multi-objective optimization method which has been implemented to simultaneously minimize tool wear, exterior irregularity, and maximize material removal rate (MRR). The statistical outcome shows that significant improvement in the MRR and lowers the exterior irregularity and tool wear using the optimal combination of drilling process parameter obtained by this collective technique.
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Chavan, P., Patil, A. (2020). Taguchi-Based Optimization of Machining Parameter in Drilling Spheroidal Graphite Using Combined TOPSIS and AHP Method. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_70
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DOI: https://doi.org/10.1007/978-981-13-8196-6_70
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