One of the killer apps for the Industrial Internet of Things (IIoT) is asset management. The reasons being: asset management applications can be applied across every industry, it can save a company from costly—and sometimes dangerous—downtime, and, it can even open up new service-based revenue streams.
Understanding the potential of asset management for companies undergoing their own digital transformation, GE Digital has been strategically planning its approach and offerings in this area, which was boosted by an investment in Meridium, Inc., in 2014. GE made a 26 percent stake in the company, which specializes in asset performance management (APM) software and services for the process industries. And, as a result, added Meridium’s reliability-centric maintenance technology into the GE product portfolio.
Apparently, it all came together rather well, because last month GE announced it acquired its strategic partner for an enterprise value of $495 million, including GE’s initial investment.
The news comes on the heels of GE’s announcement in May of its own Asset Performance Management Suite built on GE’s cloud-based Predix architecture, which the company says is a foundation for developers to build secure IIoT applications.
“As we forge ahead in the Industrial Internet journey, APM is clearly the first application that can leverage the Predix platform to help industrial customers benefit from increased productivity,” said GE Digital CEO Bill Ruh in a statement.
In addition to reliability-centric maintenance, Meridium has experience in cognitive analytics, operational risk management and asset health, as well as intelligent asset strategies. This complements GE’s domain expertise in data acquisition, management, modeling and predictive maintenance.
“We have a robust portfolio that is focused on the asset, but for reliability and maintenance professionals, those tools must live in a work context,” said Jeremiah Stone, general manager of APM Solutions at GE Digital. Meridium solves that by bringing capabilities to manage work processes around maintenance risk management, integrity management—meaning how to organize work and capture information—and prioritizing work.
“Predictive alerts are useful, but maintenance and engineering [teams] have to figure out what to do with the information,” Stone said. “They used to have to go to several different sources to get the work done, and now it is integrated into a seamless cohesive whole, which is something we are excited about.”
In addition, Meridium’s foothold is in the oil & gas, power and chemicals industries, whereas GE is in discrete manufacturing, transportation and health care, among other industries. The goal is to maintain each of their respective domain expertise and tailor offerings to specific industries while providing a horizontal platform that can bring down the cost of adoption and speed the time to value.
An example of GE’s mission to expand its depth and breadth of industry best practices was announced last month with the partnership between GE Digital and Gerdau, a Brazilian steel manufacturer. The two companies are working together to boost Gerdau’s industrial operations through asset management. By embarking upon a proof of concept project, GE was able to gather an in-depth understanding on how a steel operation works. On top of that they applied GE’s expertise of identifying anomalies and flagging potential failures—something all manufacturers require.
In the pilot test, GE’s Industrial Performance & Reliability Center (IPRC) in Illinois was monitoring 50 of Gerdau’s assets using SmartSignal, part of GE’s APM suite, which identifies impending equipment failures. The IPRC team uncovered potential issues that could be addressed through early planning and maintenance without any impact to the business. Now the APM suite, including historian software, is connecting 600 assets across 11 plants in Brazil.
As more manufacturers move toward a digital transformation, GE can also leverage Meridium’s business process consulting service. “Meridium is good at assessing operational set up and business processes in place to help operators shift from a break/fix time time-based [model] to predictive condition-based methodologies,” Stone said.
