Operators face continued challenges in maintaining and operating their plants cost effectively while attempting to drive improvements in reliability and performance. In pursuit of this goal, many operators have recognised the benefits of effectively managing their rotating equipment using centralised management systems, such as DCS, Historians and CMMS where data can be stored, modelled using predictive analytics, and remotely accessed and interrogated. However, the effectiveness of these systems is wholly dependant on the quality of the information in the system. Industry wide programmes, such as refinery of the future and digital oil field of the future, have driven, and continues to drive, the modelling and predictive analytics capability of many systems being implemented. However, the quality of rotating equipment data upon which this modelling is based is still, in many cases, poor.
This paper presents a system that is aligned with these operator goals and integrates with current business systems to improve reliability of rotating equipment. The primary goal is improvement of maintenance activities, through continual review and optimisation of the modelling and measurement. Finally measurement and prevention of failures on rotating equipment can be achieved through the use of innovative wireless technologies developed specifically for machinery monitoring in industrial and hazardous areas. These devices determine machinery condition and allow the implementation of preventative maintenance regimes and thorough root cause analysis (RCA) to be undertaken; this would deliver a steady improvement in performance.