IBM today announced Maximo Asset Monitor, a new AI-powered monitoring solution designed to help maintenance and operations leaders better understand a
IBM today 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 market-leading IBM Maximo capabilities, this new solution will help unlock essential insights with AI-powered anomaly detection and provide enterprise-wide visibility into critical equipment performance. The result is faster problem identification that can inform better decisions and reduce downtime.
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, Ph.D., 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.“
IBM is recognized by analyst firm IDC as a leader in Enterprise Asset Management applications.
IBM Maximo is deployed across 99 countries, seven continents and used by many of the world’s largest organizations. IBM has a long history of working with organizations like Novate Solutions®, Inc. to help monitor and manage their assets and operational performance.
Novate Solutions leverages Maximo Asset Monitor to expand process control services
Novate Solutions is an industrial technology and engineering services firm in California that is collaborating with IBM to develop a new, scalable, remote monitoring and support service for industrial manufacturers. The application of IBM Maximo Asset Monitor enabled by AI and analytics leverages existing infrastructure collected from SCADA systems to detect anomalies to predict system failures.
The analysis of data by engineering professionals at Novate’s Support Operations Center provides insights into the root cause of an anomaly and its process implications. These experts are able to identify events that may warrant immediate proactive intervention which enables maintenance and engineering support teams to take action before the control system is designed to react. The ultimate goal of Novate is to improve production reliability and reduce costly unplanned downtime.
“Our goal is to revolutionize how industrial manufacturers utilize data and technology to improve production metrics by providing a scalable service that virtually every manufacturer can afford. We are collaborating with IBM to enable this transformation by leveraging AI technology with IoT data and analytics,” said Rob Mora, executive vice president, Novate Solutions, Inc.
“The ability to recognize anomalies in real-time and proactively make changes to operations can have a tremendous impact on increasing plant reliability and driving continuous improvement for manufacturers of any size.”