Companies have been digitizing products, processes, and equipment for a long time. The concept of a digital replica, or twin, of a physical object, has been around in product engineering for decades. It has helped engineers to visualize their designs in 3D as well as perform tests and simulations in a virtual environment before any component is procured or manufactured.
With the advance and convergence of multiple technologies, the digital twin of a product or an asset is poised to enter a new era, expanding from engineering to manufacturing, supply chain, logistics, continuous operations at the client’s site, to decommissioning and disposal. That expansion is creating unprecedented opportunities for efficiency gains and cost reductions. And most important, it is enabling totally new business models to come to existence.
How is digital twin being shaped by advances and cost reduction in technology?
The decreasing cost of sensors and increasing computational capabilities have enabled three main capabilities: the industrial Internet of Things (IIoT), artificial intelligence (AI), and machine learning (ML). These capabilities make it possible and affordable to create an exact digital replica of something in the physical world.
Here’s how that process works: Sensors gather data from the physical object to reconstruct it in the digital space. Artificial intelligence and machine learning enable the analysis of operations represented by the digital model based on the big data generated by IIoT sensor network. Ultimately, actions on the asset, based on the outcome of the analysis, will be implemented to control and operate the asset connected by IIoT network. The model build, analysis, diagnostic, and commands dispatched to the asset are independent of where the real object or facility is located.
Data captured from the physical object through sensors is used to build a digital model of that object. Analysis, monitoring, and simulations can be run in the digital model. Based on the results, the model can send information to the physical object to alter and adjust its operations.
What is a digital twin?
First, let’s define the term digital twin. It is a virtual model that replicates the functions of a physical thing. It contains three main components: the physical thing itself (which resides in the real space), a digital model in the virtual space, and the connection of data and information through sensors that tie the virtual and real assets together.
The original digital twin concept model is not new. It is based directly from the works of Dr. Michael Grieves and John Vickers in the book “Virtually Perfect: Driving Innovative and Lean Products through Product Lifecycle Management” (pg. 133).
However, with emerging technologies such as IIoT, Big Data, edge computing, machine learning, and predictive analytics, the digital twin concept model can provide greater insights into “live” (real-time or near real-time) data, enabling manufacturers and asset operators to proactively improve, optimize, and transform their businesses.
What are the benefits of running a digital twin of your operations?
The digital twin provides insights on current asset operations in real conditions in real time, without interfering with the operation. It does this in a data-driven way, offering insights on how to improve its operation, improve efficiency or discover potential risks and issues. It enables businesses to take action before an issue becomes critical.
It helps with training employees by enabling the testing of new products or procedures before doing so in the real world, where the cost of fixing issues can be the difference between success and failure.
It provides closed-loop engineering by applying design adjustments to the system to reduce opportunities for failure and increase the total return on the assets.
The digital twin for business
The digital twin transforms the collaboration between manufacturers of products and operators of assets.
IIoT infrastructure is the foundation layer, serving as a platform where all the things (machines, equipment, etc.) are connected. That platform enables the creation of the digital twin with a real-time data feed. The digital twin is the capability that drives new processes and business models, such as predictive maintenance, pay-for-outcome business models, closed-loop engineering, predictive quality, track & trace, connected logistics (transportation monitoring and routing), connected manufacturing, remote service management, and many other processes and business models – including those that we cannot yet envision. Ultimately, it makes the digital supply chain and smart factories a reality.
In the future, a network of digital twins that synchronize the physical world with the virtual world in real time will accelerate innovation and optimize operations throughout the value chain, from design to operations, to customer services, and closing the loop back to design. In the process, it will improve performance, add predictive capabilities, and ultimately enhance the decision-making process in ways to be unveiled by the trailblazers.
For more on how intelligent technology is disrupting the manufacturing industry, see Building The Intelligent Supply Chain.