Selection of Optimal Turning Parameters Using Multi-Criteria Decision Methods

The research work presented demonstrates the comparative estimation of different Multi criteria decision methods (MCDM) methods to determine best parametric combination such that the machine can operate with its fullest machining potential. The experiment was designed using L(16)( )Taguchi design taking into consideration revolution per minute (RPM), feed and depth of cut as turning parameters and material removal rate, surface roughness and cutting force as performance characteristics. Methods for example technique for order of preference by similarity to ideal solution, Taguchi established super ranking method and evaluation based on distance from average solution has employed for obtaining optimal turning parameters. The regression equation has been developed to comprehend the mathematical correlation amongst turning variables and performance characteristics. Further, parametric analysis has been carried out to understand the consequence of several turning parameters on performance characteristics. The result shows that both Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) and Evaluation Based on Distance from Average Solution (EDAS) gives the same optimal setting value but the super ranking method shows a different. In all the MCDM method RPM was found to be most dominant factor during turning operation. The validation experiment shows that the optimal setting obtained from TOPSIS and EDAS is better as compared to the Taguchi based super ranking method.

Automated summary

The research compared different Multi Criteria Decision Making methods to find the best parameter combination for optimal performance in machining operation, with revolution per minute (RPM) being identified as the most dominant factor.