IBM and Black & Veatch are collaborating to jointly market Asset Performance Management (APM) solutions, including remote monitoring technologies that combine near real-time data analytics with AI to help customers keep equipment and assets running at peak performance and reliability.
The companies are collaborating on solutions combining Black & Veatch Asset Management Services (AMS) and digital analytics with IBM Maximo Application Suite which are designed to help organizations support more resilient operations for industrial, energy and utilities assets.
"Organizations in every industry need to figure out how to use the vast amounts of data generated within their own systems," said Kareem Yusuf, IBM general manager for AI applications and blockchain. "Monitoring insights that combine AI and machine learning technology with deep industry expertise can help organizations make better sense of their data and use it to manage their assets better. IBM and Black & Veatch are collaborating to deliver insights that can be applied to improve the performance of assets and extend their lifespans."
Black & Veatch operates four monitoring and diagnostics centers and has vast experience with near real-time, detection and analysis of emerging problems by running thousands of models and scenarios to predict changes in asset performance. IBM Maximo Application Suite's Assist, Monitor, Health, Predict and Visual Inspection capabilities aim to integrate Black & Veatch monitoring and diagnostics expertise and data analytics with maintenance management to bring them into the field where the insights can be applied.
The two companies are also planning to expand the IBM Digital Twin Exchange using Black & Veatch's digital twin asset models. "Digital twins will be a necessary part of the industrial sector's digital future because of the detailed understanding they provide and expert analysis they enable for complex assets," said Dave Brill, vice president and director of asset management services with Black & Veatch. "The IBM Digital Twin Exchange can make this level of understanding more accessible by connecting customers in asset-intensive industries and in need of digital twins with members of IBM's rapidly growing partner ecosystem that can share their models. As part of this collaboration, Black & Veatch plans to develop digital twin asset models to sell through the Digital Twin Exchange, expanding the library's inventory."
According to the companies, as they are faced with aging equipment, tightening budgets, increased regulation and rapidly changing market dynamics, operators and engineers require increased visibility into their equipment performance and asset conditions. Remote monitoring technology can help organizations understand their assets better by providing a near real-time view of operations. Once data is collected, it can enable both predictive and conditions-based maintenance, where problems are proactively corrected before they escalate into system breakdown, in an effort to limit downtime and maximize productivity.
AI and machine learning can help bridge reduce "alarm fatigue" by sorting through the thousands of incoming datapoints, so organizations can prioritize alerts and decisively plan their actions. This collaboration combines IBM's software, artificial intelligence and machine learning expertise with Black & Veatch's engineering expertise to offer solutions that can help reduce thousands of incoming data points to a handful of actionable escalations by making predictions and then screening and diagnosing alerts. With more than 20 years of experience in near real-time data analytics, Black & Veatch provides a deep understanding of how facilities and systems operate, and its expertise and models are used to train IBM's AI to help detect anomalies and support monitoring at scale.
For more information on remote monitoring and asset maintenance, go to www.bv.com/services/asset-management/monitoring-maintenance.
For more information about IBM Maximo Application Suite, visit www.ibm.com/maximo.