• 20-FEB-2014

IBM and Thiess Mining Solve Equipment Condition Monitoring and Prediction

Natural resources industries, such as energy, oil and gas, mining and agriculture, depend on the effectiveness and productivity of expensive equipment. Most maintenance processes result in costly in-field failures, which can cost a company $1.5M for one day of downtime on a single piece of equipment. In order to have a real bottom-line impact, analytics and modeling need to be integrated with current processes. IBM developed an intelligent condition monitoring technology using the most comprehensive data set ever assembled in this domain. This system proactively presents decision support information to drive actions that reduce downtime, increase fleet productivity, and minimize maintenance costs – in fact, one estimate suggests that a $30B company can save $3B a year implementing predictive maintenance technology.