B.C. Routara

Application of the Entropy Weight and TOPSIS Method on Al–12% SiC Metal Matrix Composite during EDM

The objective of this paper is to find the optimum combination on different machining characteristics during electrical discharge machining process of Al-12%SiC Metal matrix composite. Central composite design (CCD) method is used to investigate the effect of three process parameters such as peak current (Ip), pulse on time (Ton), flushing pressure (Fp) on the four response parameters like Material removal rate (MRR), Tool wear rate (TWR), Radial over cut (ROC) and Surface roughness (SR). The multiple objective problems of machining characteristics are optimized by a combine approach of Technique for order preference by similarity to an ideal solution (TOPSIS) and entropy weight measurement method. The Analysis of Variance (ANOVA) is implemented to identify the statistically significant of the Closeness-coefficient results. Finally confirmation test is conducted to compare the experimental data and the predicted data at its optimum parameter to identify the effectiveness of the proposed method.

Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

Taguchis design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (R a). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v 3-f 2-d 3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v 1-f 1-d 3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach.

The fuzzy inference system approach to a multi-performance characteristic index for surface quality improvement in CNC end milling

Utility embedded fuzzy approach has been adopted for multiple surface quality optimisation of 6061 T4 Aluminium in CNC end milling operation. The purpose is to evaluate the most favourable process environment consisting of selected process parameters viz. spindle speed, feed and depth of cut in order to satisfy multiple requirements of surface integrity. Various surface roughness parameters have been taken into account with a focus to minimise all of them simultaneously. Utility concept has been adopted to convert individual surface roughness parameters into corresponding utility value which have been fed to a fuzzy inference system to obtain a multi-performance characteristic index (MPCI). MPCI has been optimised finally using Taguchi method. Detailed methodology of the proposed approach has been presented with an illustrative example followed by satisfactory result of confirmatory test.

Principal Component Analysis in Grey Based Taguchi Method for Optimization of Multiple Surface Quality Characteristics of 6061-T4 Aluminum in CNC End Milling

The present study highlights a multi‐objective optimization problem by applying Principal Component Analysis (PCA) coupled with grey based Taguchi method through a case study in CNC end milling of 6061‐T4 Aluminum. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of surface quality. In view of the fact, that traditional Taguchi method cannot solve a multi‐objective optimization problem; to overcome this limitation, grey relation theory has been coupled with Taguchi method. Furthermore, to follow the basic assumption of Taguchi method i.e. quality attributes should be uncorrelated or independent; which is not always satisfied in practical situation. To overcome this shortcoming the study applied Principal Component analysis to eliminate response correlation and to evaluate independent or uncorrelated quality indices called Principal Components which were aggregated to compute an overall quality index denoted as overall grey relational grade...

Combined Quality Loss (CQL) Concept in WPCA based Taguchi Philosophy for Optimization of Multiple Surface Quality Characteristics of Mild Steel (AISI 1040) in Cylindrical Grinding

The present study highlights a multi-objective optimization problem by applying Weighted Principal Component Analysis (WPCA) coupled with Taguchi method through a case study in cylindrical grinding of Mild steel AISI 1040. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of surface quality. In view of the fact, that traditional Taguchi method cannot solve a multi-objective optimization problem; to overcome this limitation, WPCA has been coupled with Taguchi method. Furthermore to follow the basic assumption of Taguchi method i.e. quality attributes should be uncorrelated or independent; which is not always satisfied in practical situation. To overcome this shortcoming the study applied Weighted Principal Component analysis (WPCA) to eliminate response correlation and to evaluate independent or uncorrelated quality indices called Principal Components which were aggregated to compute overall quality index denoted as Multi-Response Performance Index (MPI). A combined Quality Loss (CQL) was then estimated which was optimized (minimized) finally. The study combined WPCA and Taguchi method for predicting optimal setting. Optimal result was verified through confirmatory test. This indicates application feasibility of the aforesaid methodology proposed for multiresponse optimization and off-line control of correlated multiple surface quality characteristics in cylindrical grinding.