Optimization in Engineering Research Vol. 1, No. 1, 1-9, 2020 http://dx.doi.org/10.47406/OER.2020.1102 1 Functional Capability of Fused Grey Relational Analysis with Taguchi in MADM for Identifying Optimal Machining Parameters in Turning Inconel 716 Akula Siva Bhaskar Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kurnool – 518002, Andhra Pradesh, India Akhtar Khan * Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kurnool – 518002, Andhra Pradesh, India * Corresponding author Email address: sivabhaskar02@gmail.com; akhtarkhan00786@gmail.com Abstract: Decision-makers in the field of manufacturing often encounter the complication in identifying the best set of machining combinations out of a vast range of available alternative options. Hence there is a demand for elementary, organized and coherent approach or computational mechanism to mentor the decision-makers in selecting particularities and their affiliation in formulating favorable opinions. The present proposed paper demonstrate a unique multi-aspect decision making (MADM) approach, grey relational analysis (GRA), to resolve the judgment complications in the field of manufacture and industrial practitioners. The proposed approach right now is an assimilating grey relational analysis concept with Taguchi design of experiments. This paper presents a draft procedure that administrates the utilization of grey relational analysis to classify the significant process parameters that affects the turning process performance. L9 orthogonal array of design of experiments (DOE) was premeditated in determining experimental test procedure. Cutting velocity, feed and depth of cut as machining criteria, cutting force and surface roughness as output measurand, experiments were performed. Lateral using grey relational analysis, the grey relational grade (GRG) was computed, those ranks the machining parameter combinations to identifying and resolving the influence of particular criterion on the output responses. Test outcome was confirmed that depth of cut is having enhanced important role in minimizing cutting force and surface roughness. This procedure will guide the decision-maker to clear up ambiguity in taking decision regarding the identifying best optimal of machining parameters. Key Words: Multi aspect decision making (MADM), Grey relational analysis (GRA), Taguchi, Design of experiments (DOE), Grey relational grade (GRG). 1. Introduction: A Taguchi design of experiments has present days developed into a dynamic optimization technique for bettering production yield all along experimentation and improvement; hence an immense quality of the product perhaps formed at lowest cost and also rapidly. Taguchi methodology is one of the creditably approach which endeavor the efficient selection process of machining parameters by conducting least possible number of experiments. Moreover, Taguchi method helps in identifying the individual control of machining specifications on the test results by finding out least and highest influencing parameter. Taguchi facility utilizes an exclusive set or design termed “Orthogonal array”, to review the unified operational guideline with a limited numeral experimental trail. Within this paper L9 orthogonal array was preferred for designing experiments to optimize machining parameters in turning process.