Predictive Maintenance is the best type of maintenance a company can undertake, but not all assets classes and applications justify Predictive Maintenance. That is why the best type of maintenance is the type that works for each client. The latest technology in Predictive Maintenance is the use of Predictive Analytics. In some cases Predictive Analytics is reaching accuracies above 95% to predict an asset failure. These results are much higher when compared to traditional predictive maintenance techniques like Lubrication Analysis, Infrared, and Vibration. These are all excellent techniques and companies should continue using them if they are seeing success reducing downtimes, extending the lifetime of equipment, and subsequently saving money.
In the MAPCITE blog, Eric Spiegel, CEO of Siemens U.S.A., consider that “while analytics were implemented widely in industries such as banking and communications initially, we view capital-goods organizations as a huge untapped opportunity, driven primarily by the “Internet of things” and the significant potential to optimize product development, supply chain and asset related services. One example is predictive maintenance – if we were able to better predict when critical and expensive equipment is most likely to fail, we could reduce downtimes, extend the lifetime of the equipment, and realize significant savings”. Read the entire story HERE.