Fuzzy logic optimization with regression analysis on EDM machining parameters of Si3N4-TiN ceramic composites

Author:

Selvarajan L.1ORCID,Venkataramanan K.2ORCID,Rajavel R.3,Senthilkumar T.S.4

Affiliation:

1. Department of Mechanical Engineering, Mahendra Institute of Technology (Autonomous), Tamilnadu, India

2. Department of Mechanical Engineering, Mahendra Polytechnic College, Tamilnadu, India

3. Mechanical Engineering Department, Mahendra Institute of Engineering and Technology, Tamilnadu, India

4. Department of Mechanical Engineering, K. Ramakrishnan College of Technology, Tamilnadu, India

Abstract

Electro discharge machining (EDM) is a cycle for molding tough materials and framing profound contour formed openings by warm disintegration in all sort of electrically conductive materials. The goal of the venture to be concentrating because of working parameters of EDM for machining of silicon nitride-titanium nitride in the machining qualities with copper electrode, for example input Spark on time (Son), current (Ip), Spark off time (Soff), spark gap and dielectric pressure on the metal removal rate (MRR) and Electrode Wear Rate (EWR) were analyzed. Subsequently, using Taguchi analysis of various plots like Mean effect plots, Interaction plots, and contour plots, performance characteristics are looked at in relation to multiple process factors. Fuzzy logic and Regression analysis is utilized to combine various reactions into a solitary trademark record known as the Multi Response Performance Index (MRPI).The trial and anticipated qualities were in a decent programming instrument for discovering the MRPI esteem. For numerous performance aspects, such as material removal rate, electrode wear rate and so on, the optimal process parameter combination was established using fuzzy logic analysis. The key process factors, which included spark off time and current, were found using an ANOVA based on a fuzzy algorithm. Topography on machined surface and cross-sectional view of conductive Si3N4-TiN composite and surface characteristics of machined electrode is examined by SEM analysis and identified the best hole surface and worst hole surface. Sensitivity analysis is being utilized to determine how much the input values, such as Ip, Son and Soff, will need to alter in order to get the desired, optimal result. In the complexity analysis, each constraint of the machine, composite and process is addressed. Future researches might look into various electrodes to assess geometrical tolerances including angularity, parallelism, total run out, flatness, straightness, concentricity, and line profile employing other optimization methodologies to achieve the best outcome. The findings of the confirmatory experiment have been established, indicating that it may be feasible to successfully strengthen the spark eroding technique.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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