STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Mechatronics and Automation

Optimization of Machining Parameters for End Milling of 1018 Mild Steel using Taguchi based Grey Relational Analysis

  1. Rajesh Kain
  2. Manoj Kumar Gaur
  3. Saurabh Agrawal

Abstract

The present work investigate the parametric optimization of end milling operation for 1018 mild steel with multiresponse criteria based on Taguchi approach with the Grey relational Analysis. Taguchi’s L9 orthogonal array which takes nine experimental runs was used to execute the design matrix of machining parameters. Cutting speed (CS), Feed (FD), Cutter RPM and Depth of cut (DOC) are optimized with the consideration of multiple performance characteristics namely Machining time (MT), Cycle time (CT) and Material removal rate (MRR). In the applied methodology, a grey relational grade is obtained to solve the end milling process with the multiple performance characteristics. Additionally, the Analysis of Variance (ANOVA) is also applied to investigate the most influential parameter that affects the response entities most. Finally, confirmation tests were performed to sort a comparison between the experimental results and predicted values. Experimental results have shown that machining performance in the end milling process can be improved efficiently by using this approach.

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