Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics

This article addresses an approach based on the Taguchi method with grey relational analysis for optimizing turning operations with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. Optimal cutting parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. Tool life, cutting force, and surface roughness are important characteristics in turning. Using these characteristics, the cutting parameters, including cutting speed, feed rate, and depth of cut are optimized in the study. Experimental results have been improved through this approach.     

Optimization of process parameters of friction welding of UNS S31803 duplex stainless steels joints

This article presents an approach based on Taguchi method and Grey relational analysis to optimize process parameters of friction welding of UNS31803 duplex stainless steel. The main objective is to maximize mechanical properties like tensile strength, hardness and impact toughness and to minimize corrosion rate. Heating pressure, heating time, upsetting pressure and upsetting time were the four process parameters taken each at three levels. According to Taguchi quality design concept, an L9 orthogonal array was selected for experiments. The best combination of process parameters was found by both Taguchi method and Grey relational analysis. The influence of the process parameters on overall quality characteristics of the friction welding process was evaluated by the analysis of variance (ANOVA) method. The confirmation test results with optimal parameters confirmed the effectiveness of the proposed method in this study. Later, comparison was done between Taguchi method and Grey relational analysis on the basis of improvement in multiresponse signal to noise (S/N) ratio over initial process parameters. Grey relational analysis was proved to be a better technique than Taguchi method for optimization of multiple responses.     

Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

The present investigation focuses on the multiple performance machining characteristics of GFRP composites produced through filament winding. Grey relational analysis was used for the optimization of the machining parameters on machining GFRP composites using carbide (K10) tool. According to the Taguchi quality concept, a L27, 3-level orthogonal array was chosen for the experiments. The machining parameters namely work piece fiber orientation, cutting speed, feed rate, depth of cut and machining time have been optimized based on the multiple performance characteristics including material removal rate, tool wear, surface roughness and specific cutting pressure. Experimental results have shown that machining performance in the composite machining process can be improved effectively by using this approach.