Optimization of responses in single and multi-point machining processes using Dragon-fly algorithm coupled with TOPSIS and VIKOR decision-making approaches

Abstract

Due to complex production practices, it is becoming crucial to provide greater thermal management and friction reduction in manufacturing processes. Lubricants play a crucial role by effectively reducing friction, minimizing wear and tear thereby extending the lifespan of the tool. It is observed that there is a shortage of studies associated with the machining of hard materials like Ti-6Al-4V. The present work has therefore focused on the machining of high-grade Titanium alloy under dry and Neem oil aerosol-mist spray wet conditions. The machining is performed on two kinds of machining processes, such as plain facing with single point tool and co-axial turn-mill facing with multi-point cutting tools on computer numerical controlled Turn-mill machine tool. Furthermore, there are very few articles reported on usage of Neem oil (AzadirachtaIndicaL.) as a lubricant. This has motivated the authors to use Neem oil in a mist condition to minimize the quantity of coolant, without compromising on the tool temperature, surface quality, and tool-wear. The responses obtained are subjected to regression analysis to evolve the fitness functions. Multi-objective optimization of these functions is than adopted using Dragon-fly algorithm (MODA) under the constraints of the machining parameters. A set of Pareto optimal solutions for each of the machining cases are obtained and are further evaluated using TOPSIS and VIKOR decision-making approaches to achieve the optimal values of the cutting parameters. The optimum parameters for single point cutting under wet conditions were observed as speed (592 rpm), feed (0.058 mm/rev) and depth of cut (1.00 mm).The corresponding values of responses were tool temperature (37.05 oC), surface roughness (0.128 μm) and tool wear (155.19 μm). The equivalent values for multi-point cutting were determined as 510 rpm, 0.086 mm/rev and 0.25 mm. The responses for these optimal conditions are 32.17 oC, 0.725 μm and 45.72 μm in that order.

Multi-attribute optimization of eco-manufacturing based criteria in CNC manufacturing systems using an evolutionary algorithm

“…This makes the solutions more applicable to real-world scenarios and adaptable to optimization. Ramena et al [6] investigated the use of neem oil mist as a lubricant in CNC lathe and turn-mill machining of hard materials like Ti-6Al-4V. A balance between tool temperature, surface quality, and tool wear was achieved through optimization with the dragonfly algorithm.…”