A digital twin is a virtual model of a process, product or service that is used to detect issues, test, and simulate scenarios on the physical model. Digital twin technology is a game changer for the manufacturing industry. In a recent B2B technology survey, ABI Research finds that while only 4% of manufacturing companies currently have digital twins in operation, a further 83% have at least started to investigate the technology and 29% are planning to trial it within the next 12 months. Current common condition-based monitoring produces only low-quality data, but digital twin simulations can provide quick, accurate insights for what is happening inside machines. Digital twin technology has advanced to ‘digital mastery’ as the digital twin models lead to decisions that affect the physical twin.
“The idea of pairing technology has existed for decades,” says Pierce Owen, Principal Analyst at ABI Research. “Now, machine learning, advanced physics-based simulations, and CAD modelling have expanded the advantages of digital twins to benefit use cases in all industries with high value or mission critical assets.”
Condition-based monitoring connections will grow in the top countries for manufacturing with a CAGR of 24%. As time goes on, a higher percentage of these connections will feed into digital twins, from about 3% in 2016 to about 54% in 2026. Digital twins will minimize down-time and increase efficiency to add billions of U.S. dollars-worth of manufacturing value. Many manufacturers hope to use the IIoT to deepen relationships with customers by alerting them before maintenance is needed and then provide that maintenance. For instance, GE Aviation manages digital twins of all its new jet engines as a service, helping airlines optimize flight and maintenance schedules. GE has built its digital twins offerings on top of its IIoT platform, Predix. Similarly, PTC and Siemens have built their digital twins offerings on Thingworx and Mindsphere.
The popular idea of a digital twins focuses on the basis of CAD 3D modelling, but many of the capabilities of digital twins do not truly require this visual, as long as sensors on the physical object capture data about its condition and position and feed into the digital twin via some form of IoT connection. Although, exact 3D digital twins do exist and GE Digital, National Instruments, PTC and SAP all offer some form of this concept.
“Like industrial cloud platforms, adoption of digital twins has yet to meet its growth potential. Manufacturers have to consider many moving pieces, from what to do at the edge vs. the cloud to simple ROI. They must try to take advantage of this opportunity to optimize asset performance without over-complicating simple operations,” concludes Owen.
These findings are from ABI Research’s ‘Design, Test and Maintain with Digital Twins Report. This report is part of the company’s Industrial Internet research service, which includes research, data, and analyst insights.
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