The Predictive Asset Optimization solution, which features IBM's predictive analytics software and business consulting services, harnesses big data from instrumented assets and identifies irregularities in the manufacturing process, spots product irregularities and forecasts a range of asset performance risks before a problem arises.
Essentially, the solution leverages big data to uncover manufacturing and distribution risks and intervene before any asset disruptions might occur.
Operating, maintaining and managing assets throughout their lifecycle are major expenses, made even more critical by the frequency of unpredicted machine failures. Asset downtime, especially, if unplanned, is a multimillion-dollar issue for organizations, and the related unscheduled maintenance costs can range from three to 10 times the cost of scheduled maintenance, IBM said.
"The world is entering a new era of smart"”where decisions will be based on facts, data and increasingly on the ability to apply analytics to massive data sets and extract very precise business insights," Fred Balboni, senior partner, Big Data Analytics, IBM Global Business Services, said in a statement. "Companies realize they have a new opportunity to capitalize on big data to address some of the intractable issues of the past, drive new levels of business efficiency and create new levels of value for their customers. Our data shows us that businesses that are applying analytics to structured and unstructured data are outperforming their competitors in every industry."
