Guide to digital twins
06 February 2020
With confusion still surrounding their purpose, Deon van Aardt, Systems Architect at SolutionsPT, shines the spotlight on digital twins and asks: can manufacturers afford to ignore their existence?
‘Digital twin’ is a term that has spread throughout the manufacturing industry in recent years, yet it is only now that organisations are beginning to fully understand the concept and becoming aware of the benefits this new technology can deliver to their operations.
With the rise to prominence in recent years of Industry 4.0, smart factories and the Industrial Internet of Things (IIoT), manufacturing sites have become increasingly digitised environments. However, one element of Industry 4.0 still remains a mystery to some manufacturers – digital twins.
A technological breakthrough that has been talked about in manufacturing circles since the early ‘00s, digital twins are only now getting the recognition they deserve thanks to the arrival of the IIoT, which has made them more cost-effective and, therefore, more attractive to companies.
A digital twin is a digital model of a process, service or product, such as a piece of machinery, that lives in the private or public cloud. Using sensors, data regarding the performance and condition of the physical – or ‘living’ – twin can be collected and the digital twin is created when this data is contextualised and stored. The data is then made available across an organisation so that companies can see how it is performing in real-time, enabling better systems monitoring and management to take place and providing valuable insights into their operations.
By analysing the collected data, a digital twin also allows manufacturers to see how their assets have performed historically and predict how they will perform in future, enabling engineers to identify any issues before they occur and prevent them from taking place, increasing uptime, efficiency, productivity and profitability. This is particularly helpful as it allows the operational life cycle of the physical twin to be increased, improving return on asset investments.
Digital twins also allow workers to make decisions based on data and facts rather than opinions, enabling better-informed decision making to take place and helping the workforce identify and rapidly rectify any value leaks. In manufacturing plants with multiple production lines, for example, digital twins can capture data on all the lines, such as the amount of time they are in operation per day and average production speeds. By improving the understanding of the performance of the lines, companies can then predict when a particular line is likely to encounter issues, such as overheating, and schedule maintenance before the issue is able to occur, improving uptime and productivity.
So, with digital twins capable of delivering numerous benefits, why have some companies so far failed to adopt the technology?
A perception exists that the amount of work required to create them is simply too great, however, with cutting-edge industrial software now readily available, it has actually never been easier or more affordable for companies to digitally model their operational assets. Software such as AVEVA System Platform, an operating system for industrial applications, enables users to build models of their operations using an intuitive drag and drop system that is simple and quick to use. Models created this way can also be upscaled incrementally in both scope and size, enabling them to easily adapt to changing priorities or business strategies as they grow over time and helping businesses reduce future operating costs.
And, once the digital twin has been designed and created, all that remains is for plant engineers to install the necessary components and ensure they are correctly aligned across the physical and digital versions before operation can begin.
With the adoption of technology that bridges the OT and IT worlds, security is an important consideration and digital twins need to be effectively monitored and managed in order to ensure the environment remains secure. Fortunately, numerous intrusion/anomaly detection and disaster resilience solutions designed to keep operations safe now exist.
The manufacturing industry has always relied on the adoption of new technology in order to survive and thrive and this is truer than ever today. By adopting digital twin technology, manufacturers can enhance the performance of their assets and increase their operational life cycles while also maximising their return on asset investment, reducing operating costs and increasing operational efficiencies which maximise profitability.
With a variety of cost-effective software now available which enable the creation and use of digital twins, businesses simply cannot afford to ignore their existence any longer.
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