Using Predictive Analytics in Maintenance

predictive analytics for maintenence
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.

China Pollutes Less and Impacts Global Iron Ore Pricing


Iron Ore Pellet 2014

Some sources estimate that China has over 400 Steel Mills. Therefore, a shift to reduce pollution has lowered output from some “bad actor” mills in China reducing overall supply while the global demand for steel is expected to increase in 2014. As basic economics suggests, increase demand with lowered supply means higher prices. The Platts outlook report on global iron ore stated that pellet premiums are expected to remain firm into the first half of 2014 as supply growth struggles to keep pace with an increase in global demand.

Steel Mills are very susceptible to global demands and pricing fluctuations. Stay tuned for a new Advanced Analytics solution by Predikto to help steel mills predict asset delays while also predicting production yields by batch. Plant Managers and Maintenance Managers are constantly striving to maximize yield, reduce asset failures, and improve overall efficiencies. We believe Predikto is unique positioned to help Steel Mills make significant improvements to their bottom line.