Information-technology executives for years have talked about the potential for so-called digital twins, a software-backed tool that could be used by large industrial operations.
That promise of predictive maintenance, where software models continuously gather sensor data from the physical engine they represent and use advanced analytics for additional insight, is now starting to happen.
In 10 years, digital replicas of industrial equipment in industries ranging from food and beverage to manufacturing and health care will be widespread, said Elizabeth Hackenson, chief information officer at Schneider Electric SE.
“That’s going to be a competitive advantage, to understand how your assets are performing not only from a maintenance perspective but also profitability,” said Ms. Hackenson, who joined the industrial giant eight months ago and oversees how Schneider’s customers get the most of its new technology options, including digital twins.
Digital twins are software models of sensor-enabled physical assets and designed to monitor performance and help reduce costly unplanned equipment outages. The convergence of advanced technologies such as sensors, cloud services, big data and machine learning has brought this idea to fruition.
By 2020, at least half of manufacturers with annual revenues in excess of $5 billion will have at least one digital twin initiative launched for either products or assets, according to Gartner Inc.
Schneider is among several companies selling software to help customers develop digital representations of physical assets, such as pumps and motors at oil and gas plants and machine building companies. One part of the software also allows customers to calculate the long-term maintenance and estimated potential profit of operating, say, a turbine for a few hours more a day.
This is a new source of revenue for the company, with business has accelerating after Schneider’s reverse takeover of British engineering software provider Aveva Group PLC, a $710 million deal that closed in March.
Schneider is part of an increasingly crowded field developing software models to help control industrial operations. General Electric Co. was an early adopter and for years heralded the potential benefits of digital twins. GE has more than 1.2 million digital twins of physical assets today, up from 660,000 at the end of 2016, according to a spokesperson.
The company built a software platform called Predix to help their customers gather and analyze equipment, but the future of its involvement in digital twins remains uncertain. GE is seeking a buyer for key parts of its digital unit which includes the software that enables digital twins. GE declined to comment.
Digital twins are midway between discovery and adoption on Gartner’s latest Emerging Tech Hype Cycle report, where early publicity is producing hype around the technology. Gartner expects digital twins will gain widespread adoption between five and 10 years, according to the report.
Predictive maintenance has become possible because of the convergence of several technologies including advances in the functionality and economics of sensors, which enables the so-called Internet of Things, as well as data analytics and cloud computing.
Some of the world’s largest companies are betting on saving millions of dollars through predictive maintenance. Chevron Corp., for example, has launched an effort to predict maintenance problems in its oil fields and refineries that could lead to savings of millions of dollars annually, CIO Bill Braun said previously. By 2024, Chevron aims to have sensors connected to much of the high-value equipment that could significantly disrupt oil and gas operations and create lost profit opportunities if they ever broke down.
Chevron is using Internet of Things services from Microsoft Corp., which announced in April it was investing $5 billion in the sector.
Digital twins provide a comprehensive picture, or virtual model, of all the connected ‘things’ that make up a physical object, such as a factory floor, a building or an elevator, said Sam George, director of Microsoft’s Azure Internet of Things division.
“(That makes) it much easier to monitor and manage physical assets at scale,” Mr. George said.