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.     

Optimizing the Machining Parameters for Minimum Surface Roughness in Turning of GFRP Composites Using Design of Experiments

In recent years, glass fiber reinforced plastics (GFRP) are being extensively used in variety of engineering applications in many different fields such as aerospace, oil, gas and process industries. However, the users of FRP are facing difficulties to machine it, because of fiber delamination, fiber pull out, short tool life, matrix debonding, burning and formation of powder like chips. The present investigation focuses on the optimization of machining parameters for surface roughness of glass fiber reinforced plastics (GFRP) using design of experiments (DoE). The machining parameters considered were speed, feed, depth of cut and workpiece (fiber orientation). An attempt was made to analyse the influence of factors and their interactions during machining. The results of the present study gives the optimal combination of machining parameters and this will help to improve the machining requirements of GFRP composites.     

A Comparative Study of Using Grey Relational Analysis in Multiple Attribute Decision Making Problems

This paper uses grey relational analysis (GRA) method in multiple attribute decision making (MADM) problems. The advantages of using the GRA method include the followings: The results are based upon the original data, and the calculations are simple and easy to understand. It is one of the best methods to help management make decisions under business environment. Finally, an example is provided to show how this GRA method works in dealing with MADM problems. Moreover, the results from other methods are compared including the technique for order preference by similarity to ideal solution and operational competitiveness rating method.     

Optimization of Plasma Arc Welding Parameters by Using the Taguchi Method with the Grey Relational Analysis

The optimal parameters process of plasma arc welding (PAW) by the Taguchi method with Grey relational analysis is studied. The Grey relational grade is used to find optimal PAW parameters with multiple response performance characteristics. The welding parameters (welding current, welding speed, plasma gas flow rate, and torch stand-off) are optimized with consideration of the multiple response performance characteristics (the penetration of root, the weld groove width, and the weld pool undercut). As a result, the improvement percentage of the Grey relational grade with the multiple performance characteristics is 31.8%. It is shown that the multiple response performance characteristics are greatly improved through this study.