A combined approach of nature-inspired Firefly Algorithm and Weighted Principal Component Analysis in machining of Inconel X-750

Abstract

Electrical discharge machining (EDM) is the primary unconventional machining process used for very hard conductive materials. Inconel-750 is used in various high-performance applications like aerospace, automobiles, etc. due to its improved mechanical properties. During machining, various parameters significantly affect machining performances. It is not easy for a manufacturer to make a compatible balance between parameters and responses simultaneously. In this paper, a novel hybridization module is developed for EDM of Inconel-750 using the brass tool. Taguchi based L9 orthogonal array has been used for experimentation and two optimization modules. Namely, Utility theory (UT) and Weighted Principal Component has been fruitfully coupled with a relatively new nature-inspired Firefly Algorithm(FA) to achieve the desired value of rate of material removal (MRR) and Surface roughness (SR). WPCA embedded FA performs better than Utility coupled FA modules in terms of R 2 , F and P-value with model accuracy of 89.03%. The optimal settings are fund as Ip-12 amp, Ton-63µs, Toff-7µs, V-40 volts and fitness value as 0.97213. The WPCA-FA shows higher application potential and can be forwarded to the manufacturing sectors for quality monitoring and productivity concerns.

Multiobjective optimization of electric discharge machining of an Al–SiCp composite using the Taguchi–PCA method as well as the firefly and cuckoo search algorithms

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