Multi response optimization in WEDM of H13 steel using hybrid optimization approach

Abstract

Surface roughness and material removal rate (MRR) are important technological parameters which describe quality of machined surfaces and productivity of machining process. Surface roughness and MRR are significantly influenced by many interactive process parameters dynamically but those are difficult to quantify adequately in any machining process. Wire electrical discharge machining (WEDM) is one of the advanced machining processes which used thin wire as cutting tool for creating intricate features on machined parts. In WEDM, optimizing surface roughness(Ra) and material removal rate (MRR) combinedly by controlling process variables namely pulse on time, pulse off time, wire feed, voltage gap, etc, is difficult task and much needed area of research. In the present work, investigation is made to study and optimize the surface roughness of H13 steel in WEDM. L16 orthogonal array of Taguchi methodology has been used to conduct the experiments. Analysis of variance (ANOVA) has been applied on experimental data to determine the significance of input parameters on surface roughness and MRR. Mathematical relationships are developed to correlate the machining parameters and output responses: surface roughness and MRR. Contour plots have been drawn to illustrate the combined effects of process parameters on output responses. Multi-objective jaya optimization algorithm (MJOA) applied on developed mathematical equations to predict the multi-responses simultaneously. From the study, it is stated that hybridTaguchi method, RSM and MJOA is useful for studying, modeling and optimizing the multiple responses: surface roughness and MRR, simultaneously in WEDM of H13 steel.

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“…However, an elevated value of electric discharge may induce the breaking of wire. (11) • Pulse-off-Time (T OFF ): the time between discharges, referred to as the pulse interval or pulse off time, is measured in microseconds. This duration signifies the interval between successive discharges.…”

How to perform a simultaneous optimization with several response variables

“…Generally, multiple responses must be considered to achieve an overall process improvement is important to note that an optimization process does not necessarily imply the determination of optimal operating conditions, since it is practically impossible to establish the optimal point due to the large number of variables that impact a process. Instead, what can be determined are conditions for improvement from the selection of maximum points determined within a predetermined search space (Alketbi et al, 2022;Ding et al, 2020;Laidani et al, 2020;Rathod et al, 2020).…”

Scientific research trends about metaheuristics in process optimization and case study using the desirability function

“…It is important to note that an optimization process does not necessarily imply the determination of optimal operating conditions since it is practically impossible to establish the optimal point due to the large number of variables that impact a process. Instead, what can be determined are the improvement conditions from the selection of maximum points determined within a predetermined search space (Alketbi et al, 2022;Ding et al, 2020;Laidani et al, 2020;Rathod et al, 2020).…”