IBM has announced Maximo Asset Monitor, a new AI-powered monitoring solution designed to help maintenance and operations leaders better understand and improve the performance of their high-value physical assets.
An extension of IBM's Maximo capabilities, this new solution provides AI-powered anomaly detection and enterprise-wide visibility into critical equipment performance for faster problem identification.
According to a 2016 report by analyst firm Aberdeen Research, unplanned downtime can cost a company as much as $260,000 an hour. A comprehensive view of asset performance across operations may help reduce downtime, but that visibility has been difficult to achieve due to fragmented legacy systems, data silos and geographic barriers.
With Maximo Asset Monitor, organizations can now aggregate data from across the enterprise and combine it with advanced predictive analytics and AI to identify operational patterns. Capabilities like AI-powered anomaly detection can help organizations identify the most important alerts among the hundreds generated daily from critical assets. This can help teams respond quickly to the most critical anomalies and gain greater insights into root cause variables that lead to asset failure.
"As critical assets become more connected, intelligent, and complex, the model for operating and maintaining them must evolve. Organizations must move faster to spot patterns and react to maintenance issues quickly, accurately and safely," said Kareem Yusuf, general manager, IBM IoT. "With the launch of the new Maximo Asset Monitor solution, IBM is helping organizations better understand their data and automate workflows with preventative, predictive and prescriptive maintenance actions to help extend asset life and improve operations. According to IDC, monitoring performance and scheduling repairs with predictive maintenance can reduce maintenance costs by 15%-20%, improve asset availability by 20%, and extend the lives of machines by years."
For more information, visit www.ibm.com/products/maximo