Design of Experiments is a method to predict the optimum conditions of a process to reduce the time and number of experiments to be conducted with limited resources. In this paper, a comparative work on design and analysis of experiments between Taguchi method and response surface methodology is carried out in predicting the set of optimal conditions for obtaining the best surface roughness of commercially pure titanium powder metallurgy component using wire electrical discharge machining process. With surface roughness of the Titanium as the response and pulse on time, pulse off time, and sintering temperature of the wire electrical discharge machining process as the affecting factors, the optimum conditions for the surface roughness of the material have been predicted and analysed. Analysis of variance is used to identify the significant factors affecting the system. Both methods gave the same results and the Taguchi approach requires less number of experiments compared to response surface methodology and the predicted surface roughness of the components with the Taguchi method is 2.4 µm, whereas it is between 2.41-3.04 µm with the Response Surface Methodology. The factor Pulse on Time (N) shows a significant effect on the response of the system.

Photochemical Machining (PCM) is a non-conventional machining process which produces stress free complex flat metal components. Optimization of process parameters for Photochemical machining of SS316L steel is done using Taguchi method and the results are compared with results obtained through Response surface methodology (RSM) available in literature. The objective of this work is to predict the optimal machining conditions of PCM to achieve minimum undercut for SS316L steel. The Factors affecting the response of the model are: Etching Time (Ti), Temperature (T) and Etchant Concentration (C) in PCM. This work shows that Taguchi method is faster compared to RSM in predicting the optimal conditions for minimizing defects in PCM process. Taguchi method requires only 9 experiments for finding optimal conditions whereas RSM requires 20 experiments saving about 55% of time and effort.