The performance of a manufactured product is often characterized by a group of responses. These responses in general are correlated and measured via a different measurement scale. This problem is regarded as a multi-response optimization problem, subject to different response requirements. The dimensionality reduction strategy is one of the numerical techniques for the optimization of multiple responses. It aggregates multiple responses into a single dimensionless measure called desirability function. In this study, the results of the three research articles, each considering three different single responses, namely springback, thickness variation and punch force, published by the same author have been taken for multi-objective optimization using desirability function approach for the three responses namely springback, Signal to noise ratio representing the thickness variation and punch force. The results were then compared.