Digital twinning is an interesting technology gaining momentum in applications across a wide range of industries and organisations. It enables planners to improve plant and equipment utilisation with the aid of digital models (twins) of real physical assets or installations.
Although the concept of digital twins is not new, the digitisation supporting Industry 4.0 and IIoT has become a major enabler. Furthermore, because the technology used is scalable, it is suitable across a wide range of industries from individual robot applications and machine designs to complex plants and infrastructure projects.
What is a digital twin?
According to Schneider Electric, digital twins are a digital representation of a physical assets. They are mirror images that represent the structure and behaviour of that asset in real life. This includes the design specifications and engineering models that detail its materials, components and behaviour unique to the specific asset.
Digital twins allow a more effective lifecycle assessment of a system’s current and future capabilities from design to operations and optimisation. They are complete 360° digital representations of a physical asset, from a pump, motor, turbine, or an entire plant. At the concept phase, fast evaluation of design alternatives are assessed and iterated through variable specifications allowing integrated asset modelling of interacting but separate systems. During design, they allow analysis of processes, equipment and operations through many simulations for optimal safety, reliability and profitability.
Benefiting from digital twins
One real benefit is that of creating a digital twin first to simulate an operation before building the physical asset. Moreover, it provides an insight of problems before they happen, resulting in safe, more efficient and profitable operations.
In the Industrial Ethernet Book, an article from Schneider Electric considers the benefits of digital twins in an industrial automation environment. They believe that in addition to helping with Product lifecycle management (PLM), digital twins will become a major feature of all automation systems. It then becomes a matter of what your put in the digital twin not whether you design one. The digital twin will be a common part of the system, and companies ignoring the technology will be left behind.
Importantly, for wider adoption, digital twin technology it must improve the customer’s Operating Expenses (OpEx) or the Capital Expenses (CapEx). From the simulation aspects alone, it is clear how this technology will reduce both these expenses. Customer will have confidence they are buying the best automation system and have an accurate estimation of the capital expense.
John Browett, of the CC-Link Partner Association (CLPA), believes Industry 4.0 applications needs more than the automation of production lines. It needs accurate digital images of physical assets and processes to predict events and optimize operations in near real-time. An automation system may comprise of several digital twins and physical devices and smart, fast-reacting factories will perform better by linking real application with the digital image almost in real time.
More companies are developing and implementing digital models that match equipment, machines, systems and processes used in their production lines. These digital twins provide a unique tool for control and PLM. They simulate what might happen in the real-world application, such as component interactions or component wear rate and failure.
The right software platform
An effective IoT enabled software platform is essential for production companies to coordinate and manage digital transformation. The ‘Elements for IoT’ solution from CONTACT Software, a new member of Mitsubishi Electric’s e-F@ctory Alliance achieves this. Data transparency for individual machines and devices across many locations allows for efficient planning, management and predictive maintenance.
Digitalisation of manufacturing, using these tools offers improved ROI for automation investment by increasing production uptime using predictive maintenance. It also creates an opportunity for new business models, such as machine as a service and service contracts based on predictive maintenance, driven by live information and intelligent systems.
Moreover, it also supports managing the complete lifecycle of machinery from a single reference point. The development of a virtual operational model starts with CAD files of the equipment which and then connected to a physical production site.
Digital twins are modelled using live data from machine tools, robots, PLCs and other Smart devices. They then provide maintenance on-demand, to accurately predict service requirements, improving operational efficiency and reducing downtime.
Where to start
Many companies have close working relationships with the major automation manufactures, so are in a good place to start. According to a paper from Deloitte University Press, digital twins have many applications across a product’s life cycle. Operating in real-time, they may answer questions previously unanswerable questions, providing kinds of value considered inconceivable a few years ago.
Deloitte however, also warns about making models overly complex by adding too much unnecessary detail. They believe an approach that is either too simplistic or too complex could kill the momentum to move forward. They offer the figure below as a possible approach that falls somewhere between.
Recruiting a new generation of engineers
Schneider Electric also believes that digital twin technology will bring the fun back into working in the industrial automation segments. Anything to lure the “Millennial” generation to want to build the next generation self-configuring, self-adapting industrial automation systems must be a good thing.