Realizing the Potential of Digital Twins
Digital Twins, and their potential to create efficiencies and boost innovation, continue to be omnipresent in industry publications, white papers and blogs. Gartner has listed Digital Twins as one of the Top 10 Strategic Technology Trends for 2019 and predicts that by 2021, over half of the industrial companies will be using them to gain 10% more efficiency across the product lifecycle. Forbes published an article that predicts that: “[…] we are on the cusp of a digital twin technology explosion”. Companies that utilize the Digital Twin both stand to gain a competitive advantage and a substantial improvement in cycle times of critical processes.
But how do you go about achieving the promise of Digital Twins while at the same time safeguarding the substantial investments made in people, technology and processes?
In a time where ‘Disruption’ seems to be the most used expression when discussing new technologies, it might seem daunting to completely overhaul your systems design, processes and platforms to harness a new digital approach to product development and operations.
The Digital Twin Journey
The good news is: you don’t have to. The journey to implementing a Digital Twin is an evolution from your current systems and processes and organizations get to benefit every step of the way.
Step 1: Identification
The first step on the journey is the identification of the potential benefits that a physics-based Digital Twin can bring to a companies’ R&D processes and organization.
Step 2: Create use case
The projects that stand to benefit most from a Digital Twin -centric approach in terms of efficiency or innovation potential should be prioritized and put forward to the second phase, which is the creation of the use case. Here, the potential scope of Digital Twins in the design process is established and the implementation steps are agreed.
After the use case has been created, the Digital Twin journey consists of either two or three further stages: Proof of Concept (PoC), Subsystem Digital Twin and Full Digital Twin. Each of these stages provides companies with an opportunity to learn about the application of Digital Twins in their environment and produce tangible simulation results. Each stage also provides the building blocks for the next iteration, which means that all of the investments in time and resources made throughout the journey contribute to the end result.
Step 3: Proof of concept
The PoC stage is typically defined as a simplified version of the Digital Twin that focuses on one specific aspect of a machine, for example the behaviour of the hydraulics of a vibratory earth compactor in a natural environment. The PoC builds on data that resides in your existing systems landscape like 3-D CAD Models, hydraulics schematics or powertrain characteristics. This data is then used to model the real-time simulation that underpins the physics-based Digital Twin. One benefit of the PoC is that the simulation produces tangible results that can be analysed for use in R&D. At the same time, the PoC introduces design teams to the Digital Twin development process as well as the software and tools needed to run simulations in real-time.
After the PoC is concluded successfully, the journey can typically take one of two possible routes: a Subsystem Digital Twin to further drill into the simulation of a specific component/subsystem or a Full Digital Twin in order to analyse and predict the behaviour of the entire machine in its environment.
Step 4a: Subsystem Digital Twin
The Subsystem Digital Twin is a good way to deepen the specific simulation that was done in the PoC by creating more accurate models of the Machine, Environment and Work Process definition, which can be used for e.g. sub-task automation, component level analysis or generating training data to create preventive maintenance algorithms. For component suppliers, the Subsystem Digital Twin is a particularly well-suited solution as it allows for accurate analysis and optimized operation of their products while negating the need to do a full integration with a real-life machine.
Step 4B: Full Digital Twin
Finally, the full Digital Twin is an accurate, virtual representation of the Machine, Environment and Work Processes hooked up to the full control system. It enables the analysis and prediction of the behaviour of its real-life counterpart and provides benefits across the product lifecycle. These include early customer involvement and virtual prototyping in R&D, efficient stakeholder Training and tools to help implement AI driven innovations such as predictive maintenance.
A Smooth Pathway to Digital Innovation
Physics-based Digital Twins have the potential to deliver significant efficiency savings and a competitive advantage for early movers. Adopting them into your Product Life Cycle doesn’t have to mean a big disruption to your current systems and processes. By carefully prioritizing use cases, for example in R&D, and embarking upon a Digital Twin journey where each step provides benefits and the foundation for the next one, you can safeguard investment in your current systems while your teams can gradually adopt a Digital-Twin centric R&D approach. So there is no reason to miss out on the potential that Digital Twins can bring to your organization, as a smooth path to Digital Innovation is available.
Learn more about Digital Twins in our on-demand webinar:
Digital Twins: Changing the way we engineer, validate, market and operate our products
