http://www.iaeme.com/IJMET/index.asp 254 editor@iaeme.com International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 3, March 2017, pp. 254–263 Article ID: IJMET_08_03_028 Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed MULTI ATTRIBUTE DECISION MAKING IN SELECTION OF THE MOST SIGNIFICANT CONDITION MONITORING METHODOLOGY FOR ROTATING MACHINERY Arka Sen Research Scholar, Mechanical Engineering Department, National Institute of Technology, Durgapur, West Bengal, India Manik Chandra Majumder Professor, Mechanical Engineering Department, National Institute of Technology, Durgapur, West Bengal, India Sumit Mukhopadhyay Associate Professor, Mechanical Engineering Department, National Institute of Technology, Durgapur, West Bengal, India Robin Kumar Biswas Chief Scientist, Condition Monitoring and Structural Analysis Group, Central Mechanical Engineering Research Institute, Durgapur, India ABSTRACT This paper deals with various condition monitoring methodology, detailed analysis and evaluation of the accurate methodology through a data based analytical approach of quantitative decision making, which is used for evaluating the most appropriate condition monitoring methodology using Analytical Hierarchy Process (AHP) for a 525MW Turbo –generator set. Key words: Condition Monitoring (CM), Analytical Hierarchy Process (AHP), Turbo Generator Set (TG set), Saaty`s table. Cite this Article: Arka Sen, Manik Chandra Majumder, Sumit Mukhopadhyay and Robin Kumar Biswas, Multi Attribute Decision Making in Selection of the Most Significant Condition Monitoring Methodology for Rotating Machinery. International Journal of Mechanical Engineering and Technology, 8(3), 2017, pp. 254–263. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=3 1. INTRODUCTION Machine faults can be defined as any change in a machinery part or component which makes it unable to perform its function properly. Due to these faults in machine components, they