A Methodology for Selection of Condition Monitoring Techniques for Rotating Machinery

Abstract

Rotating machinery generally consist of a driver machine such as a motor and a driven machine or load such as a compressor or pump. Several condition monitoring (CM) techniques have been developed over the years for the predictive maintenance of rotating machinery. An appropriate selection of these techniques needs to be established for maximizing the ROI (Return on investment) of such systems. This paper proposes a methodology for the proper selection of CM techniques based on factors such as fault detectability, fault severity, cost, ease of data collection, noise, and system criticality. Effective techniques are recommended based on applicability in the industrial scenario and research done till now. A careful scoring system was adopted and weightage was given to each factor by expert opinion depending on its importance in the industrial environment. Multi-criteria decision-making (MCDM) was used to obtain comparable technique combination scores. The effectiveness of a single technique was found limited in rotating machinery, effective combinations were made and scored according to important factors. Final scores were obtained and top combinations were chosen for non-critical, sub-critical, and critical systems. A possible way of implementation is also shown for remote monitoring through literature.