Fuzzy based modeling and optimization of EDMed response of Zircaloy-2-Reference-Cited by-同舟云学术

Fuzzy based modeling and optimization of EDMed response of Zircaloy-2

Published:2024-02 Issue: Volume:33 Page:
ISSN:2634-9833
Container-title:Composites and Advanced Materials
language:en
Short-container-title:Composites and Advanced Materials

Author:

Kumar Jitendra¹,Soota Tarun¹,Sunil BD Y²,Gupta Nakul³,Rajput Sunil Kumar¹,Sachan Prachi⁴,Saxena Kuldeep K⁵^ORCID,Jule Leta Tesfaye⁶

Affiliation:

1. Department of Mechanical Engineering, Bundelkhand Institute of Engineering and Technology Jhansi, Jhansi, India

2. Department of Mechanical Engineering, Institute of Aeronautical Engineering, Hyderabad, Telangana

3. Department of Civil Engineering, GLA University, Mathura, India

4. Department of Mathematics, Deshbandhu college, University of Delhi, Delhi, India

5. Division of Research and Development, Lovely Professional University, Phagwara, India

6. Department of Physics, College of Natural science, Dambi Dollo University, Dambi Dollo, Ethiopia

Abstract

In this work, fuzzy model was developed that predicts response parameters and surface properties of an electrical discharge machined Zircaloy-2. Taguchi L18 mixed design was used to perform the experiments using different process parameters (polarity, pulse-on-time, pulse-off-time, tool electrode material, and peak current). Material removal rate (MRR) and tool wear rate (TWR) were chosen as machining response parameters, whereas number of particles (NoP) and the percentage particle area (PPA) for surface properties of EDMed surface. Digital image processing tool was used to evaluate the surface properties. Fuzzy-Sugeno (FS)-model was developed to predict MRR, TWR, NoP, and PPA. Model accuracy was found to be 94% for MRR and TWR, and 92% for NoP and PPA. Maximum MRR 1.53 × 10−3 mm3/min found when machining was performed using graphite tool with negative polarity. Fuzzy Sugeno-GRA method was successfully implemented to predict optimal response corresponding to high value of GRG.

Publisher

SAGE Publications

Link

https://journals.sagepub.com/doi/pdf/10.1177/26349833241249749

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