In Newcastle, England, an entire city can be replicated using a digital twin to test the resilience of its underlying infrastructure in case of natural disaster or other disruptive event. Elsewhere, Siemens AG says a team of young engineers at Electra Meccanica “designed, simulated, and manufactured its new electric car in only two years, thanks to [a] digital twin.” The U.S. Air Force uses digital twins to monitor sophisticated aircrafts, and General Electric is moving out in full force—with a chief digital officer at its helm—to offer digital twins for ships, wind turbines, injection-molded equipment, and just about any physical asset.

What is a digital twin?

A digital twin is a software model of a physical asset. A constellation of sensors, strategically placed on a physical asset, picks up data and feeds to a remote location, nearby or anywhere in the world. Data streams regularly and is updated, often in real time, to provide a precise model of the physical asset.

The physical asset can be anything from a machine, aircraft, ship, automobile, truck or even a human being. The data provides a precise replica of the asset. The digital twin is an ideal tool for monitoring systems and can be used in the design to make better prototypes and tool up for production.

Wherever you look, digital twins are blazing new trails in asset modeling and simulation. According to research conducted by The Market Reports, the digital twin market is about $1.8 billion in the United States; they predict it will double every two years until 2025.

GE expects digital twins to be developed for new assets “at birth.” This will not only allow real-time monitoring but will also enable voluminous data, or big data, to be gathered and used to predict, forecast, prevent and very accurately monitor. The company is investing $4 billion in digital technologies and reported that their digital products generated another $4 billion in revenues last year. GE isn’t the only firm pursuing this niche; others include Ansys, Dassault Systèmes, Honeywell International Inc., IBM Corp., Microsoft, Oracle, Siemens AG and PTC.

A new digital face for physical assets

Through the efforts of these large firms, the digital twin is a product of another industrial revolution that is providing a new digital face to physical assets. McKinsey and Co. described the digitization of machinery as a “no-regret” move for companies seeking to better compete and excel.

“Digital-based business models provide attractive opportunities for growth and efficiency,” said McKinsey partners Matthias Breunig and Niko Mohr in their 2017 article, “Digital Machinery: How Companies Can Win the Changing Manufacturing Game.”

There are different applications of digital twins. First, as Siemens explains, there’s the digital twin of production. The simulated model “involves every aspect, from the machines and plant controllers to entire production lines in the virtual environment.” The accuracy of the simulation helps optimize complex and costly production and provides finite details such as PLC code generation and can prevent error and premature failure—before production and operation ever begins. As a result, sources of error or failure can be identified and prevented before actually starting the production process.

Second, there’s the digital twin of performance: A simulated model of a physical asset is supplied with a stream of operations data from real-time production. This enables accurate remote monitoring to predict when preventive maintenance is required, reduce downtime and energy consumption, and offer other benefits.

Measurable outcome?

GE claims the implementation of digital twins can increase asset reliability by 93–99 percent in just two years; reduce reactive maintenance by 40 percent in less than a year; reduce the time to achieve outcomes or desired results by 75 percent; and avoid about $11 million in lost production by promptly predicting problems before they occur.

The metrics and results from the digital twin will drive their implementation. For electrical contractors, this means digital twins will be in their vocabulary soon, if not already. While it’s still early stages for the digital twin, as they become more deployed, popular and valued, those who can speak their benefits and understand their implementation will be in good stead moving forward.