Multi-Objective Parametric Optimization of Micro-Electro Discharge Machining of Hastelloy C276 Super Alloy Using Response Surface Methodology and Particle Swarm Optimization
M. Parthiban, M. Harinath, V.S.S. Krishaanth, B. Logesh, Ahamed N.J. Musthak
{"title":"Multi-Objective Parametric Optimization of Micro-Electro Discharge Machining of Hastelloy C276 Super Alloy Using Response Surface Methodology and Particle Swarm Optimization","authors":"M. Parthiban, M. Harinath, V.S.S. Krishaanth, B. Logesh, Ahamed N.J. Musthak","doi":"10.4028/p-a7elpi","DOIUrl":null,"url":null,"abstract":"The need for the application of superalloys in aerospace industries in recent years has increased owing to its benefits such as extensive load-bearing capability under high temperatures. Hastelloy is one such superalloy that is extensively utilized in the aerospace sector because of its good corrosion and heat resistance among the other nickel-based superalloys. In this work, the investigation is conducted to understand the effects of input process parameters such as voltage, pulse off time (Toff), and pulse on time (Ton) on the response variables, namely Material removal rate (MRR), Tool wear rate (TWR), Overcut (OC), and Taper Ratio (TR) during micro-EDM of Hastelloy C276. For micro drilling the Hastelloy C276 material, a copper electrode with a diameter of 0.5 mm is utilized. To investigate the connections between the input and output characteristics, a technique known as the Response Surface Methodology (RSM), which is a collection of mathematical and statistical methodologies, is applied. The experimental runs are carried out with the help of the RSM-based Box-Behnken design (BBD). The experimental outcomes were computed, and ANOVA was used to identify the most influential variables. In addition, particle swarm optimization (PSO) was utilized to optimize the results, which were compared to the Response surface methodology approach. The outcomes of the PSO-optimized results revealed a strong correlation between expected and experimental outcomes over the RSM approach.","PeriodicalId":8039,"journal":{"name":"Applied Mechanics and Materials","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mechanics and Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-a7elpi","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The need for the application of superalloys in aerospace industries in recent years has increased owing to its benefits such as extensive load-bearing capability under high temperatures. Hastelloy is one such superalloy that is extensively utilized in the aerospace sector because of its good corrosion and heat resistance among the other nickel-based superalloys. In this work, the investigation is conducted to understand the effects of input process parameters such as voltage, pulse off time (Toff), and pulse on time (Ton) on the response variables, namely Material removal rate (MRR), Tool wear rate (TWR), Overcut (OC), and Taper Ratio (TR) during micro-EDM of Hastelloy C276. For micro drilling the Hastelloy C276 material, a copper electrode with a diameter of 0.5 mm is utilized. To investigate the connections between the input and output characteristics, a technique known as the Response Surface Methodology (RSM), which is a collection of mathematical and statistical methodologies, is applied. The experimental runs are carried out with the help of the RSM-based Box-Behnken design (BBD). The experimental outcomes were computed, and ANOVA was used to identify the most influential variables. In addition, particle swarm optimization (PSO) was utilized to optimize the results, which were compared to the Response surface methodology approach. The outcomes of the PSO-optimized results revealed a strong correlation between expected and experimental outcomes over the RSM approach.