Digital engineering: The enterprise journey toward digital twins in an industrial metaverse

The world of emerging technology has always been awash with buzzwords, and it is our job as industry analysts to try and make sense of what is happening or going to happen in and around our fields of expertise. We are seeing the evolution and convergence of technology approaches and a shift in the industrial sector from what was previously called "digital transformation" toward a fuller view of the digital ecosystem, creating an opportunity for the concept of "digital engineering" to be the next major service advancement in operational technology, or OT.  

Let us consider what has happened so far in technical advancements of the industrial and operational technology world. The diagram below represents a timeline that shows the impact of emerging technologies on solving problems or improving processes in industrial venues such as factories.

Originally, factories were fairly self-contained units centered on an enterprise back-office system, or in industrial parlance, a manufacturing resource planning, or MRP, system. These systems are composed of a suite of applications that coordinate manufacturing processes, such as product planning, parts purchasing and inventory control, as well as product distribution, fulfilment, and order tracking. The emergence of enterprise resource planning, or ERP, systems in the late 1980s added finance, accounting, human resources, and marketing application modules to the existing MRP functions. In a sense, digital engineering, digital twins and the industrial metaverse are taking all organizations back to the manufacturing roots of the systems that most businesses now use to operate. As factory machinery is instrumented to enable the collection of industrial data, this data is beginning to flow outside the factory walls and feed back-office enterprise applications.

It should be noted that not everyone is at this stage of development, but we are describing a general direction of travel. The connectivity of factories was also apparent as enterprise IT systems underwent a shift to more cloud-based approaches and localized planning systems were replaced with edge and cloud applications. Organizationally, IT and OT groups must cooperate since the technology being applied in each area is of the same form and type. Data, in particular the IoT data in OT, becomes the unifier. This leads to doing more with the data, as well as the evolution of AI/ML processes such as predictive maintenance. The evolution of AI/ML technology approaches is also key to the advancement of autonomous robotics, leading to "smarter" facilities being operated. Technology such as augmented reality, or AR, (with smart glasses or even smartphones) exists on the shop floor to help engineers get remote support or see extra detail about work that needs to be performed.

The response to the pandemic has spurred these activities to deploy advanced technologies — with national lockdowns and shelter-in-place directives, the ability to remotely assist local field engineers (and in some cases the internal enterprise teams themselves), to take over the management and maintenance of equipment, has been the difference between a business surviving or going under.

The take-up of cloud services by organizations has been boosted by the need for the rapid deployment of online access to customers and suppliers, and for employees to work from home. This change in approach from large IT applications to cloud-based services also offers more scope for cross-supplier services to be woven together via digital threads (a digital thread is a data-driven architecture that links together information generated across the life cycle of a product or process) to support an operational digital twin, or to make quicker changes in things like supply chain flow. 

We have been covering all of this for many years within the IoT practice of 451 Research, the technology research arm of S&P Global Market Intelligence, and as the OT and IT worlds converge, there is relevance across technology sectors.

That leads us to the future. To quote science-fiction author William Gibson: "The future is already here — it's just not evenly distributed." This means that, when we describe some of the buzzwords, it can seem a little disorientating or not yet part of the familiar world. However, we are at a significant point in time.

Just as in the 1990s and turn of the century, when lots of business processes became monolithically automated with the adoption of ERP systems, it looks as if we are about to enter another big shift in the use of technology by enterprises. As we begin to understand the potential of digital engineering and digital twins to transform current processes and operational functions, making them more collaborative and flexible, the opportunity to transition to the digital age is huge. Whereas in IT transformation you are proceeding application by application, with digital engineering you can create a connected product, process or service that quickly eliminates large costs and creates new value streams.  

Digital twins represent the coming together of all the IoT data, plant information, and location- and machine-specific information, including size, shape, and components. They are the complete live data model that AI/ML processes work on to produce predictive and prescriptive maintenance suggestions.

A full digital twin represents the physical world accurately and needs to exist somewhere that it can be engaged with. This is where the virtual world approaches a point at which the seeds of the metaverse come into play. The evolving user interfaces of AR and VR use 3D content, such as a full digital twin. If multiple people are engaging with the twin, then that becomes a shared access multiuser virtual world. These live digital environments are also where autonomous robots can be trained. Engineering-level simulations can explore improvements and other possibilities with the twin as the source. We are entering metaverse and industrial metaverse territory.

All this technology and the processes to implement it blends the physical and digital and is being described as "digital engineering." This is a key focus area for us going forward as it creates the future of the industrial metaverse.

451 Research is part of S&P Global Market Intelligence. For more about 451 Research, please contact 451ClientServices@spglobal.com.