Practical storage solutions can determine the success or failure of digital twin projects

Digital twins are being used across the world to connect the physical and virtual worlds. As innovations in AR, VR, machine learning and IoT have proliferated, more opportunities have arisen to accumulate and analyse device data with a view to replicating the operation and performance of these connected tools as well as to enhance systems and operations. As a result, the market has expanded with its value reaching $8.60 billion in 2022, and growth to $137.67 billion is projected by 2030.

As a means of providing useful data on the resilience and functionality of systems and products without impacting on a prototype, digital twins tick many boxes. Their use can lead to a reduction in waste, faster times to market and the delivery of valuable customer insights. Use cases range from production plant twins that can digitally represent a factory, to infrastructure twins which replicate local or international IT assets, networks and processes. Some companies use twins to simulate a single product.

One area in which digital twins have delivered huge value since the pandemic has been in managing global supply chain challenges. The ability to re-configure supply chain operations and use real-time data to create simulated events is allowing organisations to root out bottlenecks and improve efficiency. A twin can also be used to help anticipate disruptions which is improving planning and mitigating delays.

Twinning on the Elizabeth Line

In the civil engineering sector, a digital twin was used in the construction of Transport for London’s Elizabeth Line. This £18.7bn project, which was made up of 73 route miles and 41 stations, relied on a twin to solve the problem of siloed teams and data. It comprised over 250,000 models including everything from lightbulbs to cable trays, with each one ‘twinned’ and labelled from database information on the Elizabeth Line’s physical assets. Because engineers could monitor progress across multiple devices, they could access an AR view of communications, water and electricity beneath any station wall or floor without running the risk of using an outdated map or information, saving effort, time and money.

But digital twins are not only for large projects, and if organisations know what they want to achieve, they can harness the power of the technology to enhance their operational capabilities and deliver a competitive edge.

Data storage and consumption

The key to success is beginning with a manageable pilot project that tests the viability and value of a digital twin in a specific scenario. This identifies problems, limitations and opportunities so the approach can be refined before launching a full-scale digital twin program. There are some things to take into consideration, such as how the data on which the twin will rely will be collected, stored, and protected. This must meet with data management and governance policies and procedures. Buy-in from stakeholders is also essential to ensure the project meets requirements and expectations are aligned.

Setting up a digital twin project can be a data intensive endeavour with data being accessed from sources including sensors, simulations and historical records to create a virtual replica of the physical

product or system. As a result, some organisations will need to consider upgrading their existing IT to manage and access the large volumes of data and serve the need for monitoring, analysis and storage.

They will need enterprise-grade storage devices, such as SSDs, that are optimised to provide large capacity, improved stability and endurance at extreme speeds and performance where it is most needed. These not only help to meet the demands of heavy workloads and deliver long-term efficiency but also provide data protection to comply with the most stringent regulations.

Memory is another consideration. DDR5 server memory can withstand heavy workloads in complex technology initiatives such as those typically found in data centres, so if a digital twin project is likely to need this kind of support, it is vital to ensure that the server memory is optimised and accessible before embarking on the project.

Whilst it is difficult to exactly predict the future for digital twins, the prevailing winds suggest adoption across increasingly different sectors as the technology grows in sophistication and accessibility. The good news is that the infrastructure to support digital twinning already exists globally with flexible layers of connectivity that have created a foundation that can be built on. But there is a caveat, which is that advancing technologies will result in more data collection and an increase in digital sources, a greater degree of data granularity and more frequent collection and dissemination.

So, when planning digital twin projects, organisations must consider the storage and consumption challenges that are inevitable. They need to prepare to accommodate extensive performance demands and look at how they can realise longer-term commercial gains by upgrading storage and memory now at lower price points. Overall, as digital twins evolve, it is the practical underlying solutions to solving novel challenges that will make the difference between success and failure.