Optimization of Recast Layer Thickness and Surface Roughness in the Wire EDM Process of AISI H13 Tool Steel Using Taguchi and Fuzzy Logic

Abstract

In this study, the optimization of recast layer thickness and surface roughness (SR) simultaneously in a Wire-EDM process by using Taguchi method with fuzzy logic has been applied. The Wire-EDM process parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., recast layer thickness and SR. Based on the Taguchi method, an L18 mixed-orthogonal array table was chosen for the experiments. Fuzzy reasoning of the multiple performance characteristics has been developed based on fuzzy logic, which then converted into a fuzzy reasoning grade or FRG. As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. Experimental results have shown that machining performance characteristics of Wire-EDM process can be improved effectively through the combination of Taguchi method and fuzzy logic.

Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach

“…In the recent years, fuzzy-logic-based multi-criteria decision making approaches have become very popular in optimization of EDM and other manufacturing processes. Rupajati et al [7] has optimized the multiple performances like recast layer thickness and surface roughness using fuzzy-logic method with the design of Taguchi L 18 mixed-orthogonal array. It was observed that application of this optimization technique significantly improved multiple responses.…”

Experimental Investigation and Multi Response Optimization of WEDM Process of AA7075 Metal Matrix Composites Using Particle Swarm Optimization

“…Hence, the machinability of WEDM strategy on aluminum wants to be investigated. Only a couple of Fuzzy logic analysis together with Taguchi method has been utilized in optimizing high-pace EDM approach for the machining of SKD11 instrument metal [5]. Majumder et al [6] offered using fuzzy algorithm to predict removing rate, tool wear ratio, and surface roughness in traditional and ultrasonic vibration supported EDM process.…”

Optimization of the Physical and Mechanical Properties of a Spline Surface Fabricated by High-Speed Cold Roll Beating Based on Taguchi Theory

“…Based on the actual working conditions of the failure and damage, we set the cold roll-beating spline surface workhardening capacity as V ∈ [139.6%, 149.6%], the cold rollbeating spline surface residual stress as ∈ [−69.79, −88.21], the machining parameters to the cold roll-beating speed as ∈ [1200, 2500], the feed speed as ∈ [20,50], and the roll-beating wheel round corner radius as ∈ [1, 3.5]. According to (12), we solve the spline surface hardening degree and residual stress process capability index. Next, the generalized simple gradient method is used to optimize the overall Taguchi process capability index.…”

“…Rupajati et al used the fuzzy logic of the Taguchi method on the wire-cutting process to optimize the casting layer thickness and the surface roughness simultaneously. By transforming the optimization of complex multiperformance characteristics into the optimization of a single response performance index, they found that a combination of the Taguchi method and fuzzy logic in the wire-cutting process effectively improves the wire-cutting process performance [12]. Chen et al used the Taguchi method and multiobjective quantum-behavior particle swarm optimization to optimize the surface roughness of 7075-T6 aluminum alloy in end milling.…”