A DoE–TOPSIS method-based meta-model for parametric optimization of non-traditional machining processes. (2nd May 2019)

• Record Type: Journal Article
• Authors: Chakraborty, Shankar; Chatterjee, Prasenjit; Das, Partha Protim
• Is Part Of: Journal of modelling in management. Volume 14:Number 2(2019)
• Page Start: 430
• Page End: 455
• Publication Date: 2019-05-02
• Subjects: Optimization -- Modelling -- Manufacturing -- Design of experiments -- TOPSIS -- Meta-model -- Non-traditional machining process -- Process parameter -- Response; Industrial management -- Mathematical models -- Periodicals; Industrial management -- Computer simulation -- Periodicals; Business -- Mathematical models -- Periodicals; Business -- Computer simulation -- Periodicals; 658.4033
• DOI: 10.1108/JM2-08-2018-0110
• Languages: English
• ISSNs: 1746-5664

Abstract

Abstract : Purpose: To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers. Design/methodology/approach: In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores. Findings: For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time. Practical implications: As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers. Originality/value: This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.