The present work address the problems like low productivity, high manufacturing cost and issues with conventional cooling techniques while machining of 17-4 precipitated hardened stainless steel (PH SS). To overcome these problems, optimization studies have been carried out under cryogenic cooling environment. Cryogenic machining (Liquid nitrogen) is an efficient eco friendly machining technique to satisfy the stringent environmental regulations. In the present work, Taguchi incorporated Gray relational analysis (TGRA) and Taguchi coupled Technique for Order Preference by Similarity to Ideal Solution (T-TOPSIS) optimization techniques have been applied for multi response optimization during rough turning of 17-4 PH SS respectively. The obtained result showed that improved performance was found at the TGRA determined optimum cutting conditions when compared T-TOPSIS technique determined optimum cutting conditions respectively. Furthermore, individual and interaction effect of process parameters on turning performance have been discussed using 3D surface plots. © 2018 Elsevier Ltd