Multi-variant hybrid techniques coupled with Taguchi in multi-response parameter optimisation for better machinability of turning alloy steel

Abstract

ABSTRACT Despite having poor cooling property, minimum quantity lubrication (MQL) is very commonly utilised in machining processes because of its superb lubrication, cleanliness, fewer costs and ease of handling. However, the optimum process parameters and the cutting fluid selection are very important for efficient machining. Moreover, an easy technique for optimisation is required so that the technicians can easily find their optimum parameter combinations for any manufacturing process. Considering multiple objectives synchronously for selecting optimum conditions helps to enhance the overall machinability. In this work, optimisation of cooling/lubrication environment, speed and feed were accomplished for minimum cutting temperature, roughness, cutting force along with maximum MRR and chip thickness ratio in turning 42CrMo4 alloy steel. Three powerful multi-variant hybrid techniques, such as Taguchi-based PCA-GRA, PCA-MOORA and DEAR, were implemented for multi-response optimisation, which provided identical results. The optimal process parameters were: MQL with cutting oil with the speed of 352 m/min and feed of 0.10 mm/rev. But among these methods, compared to the complex PCA-GRA, the DEAR is the computationally simplest because it did not require weight calculation before optimisation and then PCA-MOORA. However, the limitation of the DEAR method is that it can work for the problem having conflicting objectives.