Management of assets has become increasingly sophisticated. In the same way that scheduled maintenance has been overtaken by methods such as condition-based or reliability-centred maintenance, advances have been made in predictive maintenance. The evolution of predictive analytics software tools allows organisations to identify and resolve issues before they become problems. They can use historical condition and performance data to identify facilities, plant or equipment that has a high probability of experiencing similar failures, or detect groups of equipment or machines experiencing anomalous behaviour.
These predictive analytics tools, such as IBM’s SPSS, use data from repair history, warranty data, asset management systems like Maximo, and even real-time data from sensors, controllers, actuators, and SCADA, to increase uptime and reduce maintenance costs.
The same predictive capabilities can be applied not just to maintenance, but to the supply chain, to work order and resource scheduling, and to operational planning.
Certus is one of a handful of organisations in Australia who combine deep knowledge of asset management with a deep knowledge of predictive analytics to optimise asset performance.