Four ways digital twins will shake up logistics

The growing sophistication of digital twins is creating new opportunities in logistics to streamline operations, build resilience and improve sustainability.

The concept of digital twins is not new, but its application to logistics has been gradual. The idea of creating a virtual copy of a physical object to study its real-world counterpart first emerged in the 1960s. The term ‘digital twins’ came about in the early 2000s along with its first application to manufacturing. Since then, the necessary technologies continued to evolve and have now reached a point where digital twins can be applied effectively to logistics.

So, what is a digital twin and how does it work? A digital twin is a digital representation of an ‘asset’, which can be an object, process, or system. It uses real-time data (often collected by sensors), historical data, and machine learning to mirror the real-world version’s functionality and status and predict future states. Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes, without need to be explicitly programmed to do so.

Digital twins are enabled by technologies including:

• Internet of Things (IoT) – this system of connected devices and networks makes it possible to collect large volumes of data from a wider range of sources
• Cloud computing – provides the ability to store and access data and computing sources over the internet
• Augmented, mixed and virtual reality – offers the spatial models and visualisations of the digital twin and allows for collaboration and interaction within it
• Artificial intelligence – uses historical and real-time data, as well as machine learning, to model and validate hypotheses

Digital twins have huge potential to help design, visualise, monitor, optimise, and maintain assets more effectively. The Institute of Electrical and Electronics Engineers (IEEE) says digital twins are now one of the most promising technologies linked to Industry 4.0 (the current era of connectivity, automation, advanced analytics, and advanced manufacturing). Today, the global digital twin market has reached a value of over USD 5 billion, according to market research group Fact.MR. By 2033, it is expected to be worth USD 95 billion, representing an impressive compound annual growth rate (CARG) of 34%.

Here are four ways supply chain digital twins will transform logistics.

1. Optimising layout and design at every stage of the supply chain

The digital twin allows for existing and new processes to be modelled, explored, and tested – without ever needing to make any changes in the real world. Taking for example a warehouse, a digital twin can test the addition and interaction of different technologies and software. This can include robots, counting systems, and automated storage and retrieval systems. The digital twin can draw on information from sensors and data from simulations. It can test and improve the layout of the physical warehouse, refining and optimising its operation. It can identify and remove inefficiencies and optimise the working of the warehouse. The digital twin can also be used where a physical or real-world asset does not yet exist. For example, if a new truck is in planning, a digital twin can help validate every aspect of its design and operation, long before the building begins. The same can be applied to other assets like buildings, planes, trains and last-mile delivery. McKinsey estimates that digital twins can help increase revenue by 10%, accelerate time to market by up to 50%, and improve product quality by as much as 25%.

2. Being prepared for anything with digital twin solutions

To date, logistics has relied largely on descriptive analytics (explained by Harvard Business School as ‘what happened?’) and, to an extent, diagnostic analytics (‘why did this happen’?). Digital twins can facilitate predictive analytics (‘what might happen in future?’) and prescriptive analytics (‘what should we do next?’). In other words, digital twins can help move from being reactive to proactive. They can dramatically improve the quality of decision-making and supply chain planning.

Disruptions to the supply chain, plus new challenges emerging in 2023, have highlighted the importance of building resilience and be prepared for everything. Digital twin technology enables ‘what if?’ scenario planning and ensure the supply chain is equipped to withstand any disruption – whether it is the result of bottlenecks, raw material shortages, weather events or something else. A digital twin can be used to conduct virtual stress tests to see how the asset holds up in different scenarios. It can be used to test different responses, helping identify and develop the best approaches. This is quicker and cheaper than running a real-world stress test and allows for endless simulations until the responses are perfected.

Digital twins also facilitate better cooperation and collaboration. They can help bring decision-makers together to evaluate the results of the simulations to reach a collective decision.

3. Switching to predictive maintenance and repair

Digital twin technology can also help move towards predictive maintenance. Businesses benefit from essential equipment operating at peak efficiency. To date, many businesses relied on either corrective maintenance when an issue arose or preventive maintenance where they estimated the life cycle of individual parts and conducted maintenance before a failure.

Sensors can feed data to the digital twin on the asset’s condition, performance, and damage. The digital twin can allow simulations to foresee faulty scenarios, analyse maintenance workflow and test all possible faults. Instead of reacting to machinery breaking down, digital twins proactively deal with maintenance so assets can be repaired in as part of a more convenient and optimised timelines, and not when it can disrupt flow and interrupt the supply chain.