Redefining Manufacturing Through Digital TwiningEconomy
The digital twin technology is gaining momentum in industries driven by the Internet of Things (IoT). Although the term "digital twin" is relatively recent, and refers to any virtual and digital representation of a physical object, device, or system, the concept is rooted in the pairing technology developed by the National Aeronautics and Space Administration (NASA) in the 1960s to help in repairs and maintenance of spacecraft that could not be physically monitored.
For the past three decades, manufacturing industries have employed digital representation (such as three-dimensional renderings and CAD models) for assessment purposes. Now, the emergence of big data analytics and artificial intelligence (AI) has created new practices for digital twins with impacts profound enough to develop new economic and business models.
The technology is considered the next big thing in IoT deployment and is placed as one of the top strategic technology trends in 2019, according to Gartner. The global advisory firm estimates that half of the large industrial companies will employ digital twins by 2021, producing a 10% increase in effectiveness.
How does it work?
As digitization is penetrating the manufacturing processes, companies are tempted to use the digital twin technology to optimize product and asset quality and improve the customer and consumer experience.
The digital twin is an "evolving digital profile of the historical and current behavior of a physical object or process that helps optimize business performance", according to Deloitte. The technology is driven by real-time data measurements that can provide insights to help companies see the product design, development, and performance before launching it in the real world, rather than basing assumptions on general expectations.
Digital twins create a "thread" between the digital and physical worlds; the thread represents the lifeblood of the technology because it provides a continuous data stream that connects each stage of the product life cycle, consequently allowing the simulation, testing, analysis, modeling, and monitoring to explore "what-if-scenarios".
The Deloitte report explains that five enabling components make "the journey of interactivity" possible between the digital and physical world.
The sensors generate data that allow the digital twin to capture operational and environmental data connected to the physical process. The integration technology enables the communication between the digital and physical worlds, while the data is analyzed through algorithms and visualization routines to produce insights.
Consequently, the digital representation can identify the deviations from optimal conditions; they can be "logic errors, an opportunity to save costs, improving quality, or achieving greater efficiencies". If the company decided to act upon the findings in the real world, the digital twin "produces the action by way of actuators that trigger the physical process, subject to human intervention". This interaction "completes the closed-loop connection between the physical world and the digital twin".
Digital twins represent "the most talented product technicians with the most advanced monitoring, analytical, and predictive capabilities at their fingertips". It is a living digital model that "provides a full picture of a product or asset with real-time and historical data", and "enable the manufacturers to know their product well when it starts, measure activity and forces applied to it and simulate how it would react and change". The importance of the technology lies in the fact that it helps companies "see their whole business for the first time" and secures their competitive edge.
The digital twin has the potential to drive and create business value that was impossible to attain before the emergence of connected IoT devices and sensors. The technology can improve the overall quality of a product, reduce the operation costs, and identify opportunities for revenue growth.
"Digital twins drive the business impact of the IoT by offering a powerful way to monitor and control assets and processes", according to Alfonso Velosa, research vice president at Gartner. He further suggests, "CIOs will need to work with business leaders to develop economic and business models that consider the benefits in the light of the development costs, as well as ongoing digital twin maintenance requirements".
As for the economic value, Velosa explains that it will vary depending on the company size, industry, and monetization models. For example, developing digital twins is extremely valuable for expensive industrial equipment (like airplane and train engines), and will necessitate continuous updating of data capabilities, and developing adaptive analytics and algorithms.
Digital twinning promises to be "the next revolution in manufacturing"; it provides holistic visibility on performance and operations, and delivers an accurate response to demand, as well as predictive and proactive services. All these values will make the twin digital technology an indispensable element of business strategies for companies who desire to stay ahead of time.