Virtual systems could help you build greater agility into your supply chains
Even before Covid-19, supply chains faced unprecedented levels of social, economic and technological disruption. Unforeseen risks were already a daily threat, and the average lifespan of a company on the S&P500 had fallen to just 18 years. Today, if your business is to survive, you need to be able to predict the future, and digital twin technology could be the answer.
Ultimately, digital twin technology (DT tech) offers a vision of the future, or in fact multiple potential futures, by analysing data from a product or system and anticipating the outcome of set scenarios. The DT tech market will be worth US$48.2bn by 2026, according to a recent Markets and Markets research report. That’s an increase of nearly $45bn in six years.
How does it work?
A digital twin is a virtual representation of a physical object or system over its entire lifecycle. Whether a bridge, a jet engine or an entire power station, sensors on the physical object collect real-life data and feed it into a cloud-based system; the collated information is mapped out to create a virtual version of the object as it functions. The digital copy can be analysed to understand how it will respond to different environments, situations and stressors, and predictions can be made as to the adjustments needed to achieve desired performance.
Early adopters, largely among the automotive, manufacturing and medical industries, recognised the advantages across operations, monitoring and training. In comparison, the benefits for supply chain management have been slower to emerge.
Will supply chains benefit?
In terms of supply chains the concept is the same; data collected from virtual replicas of assets, warehouses, logistics and inventory positions is used to simulate the supply chain’s strengths, vulnerabilities and overall performance, enabling the team to pinpoint where optimisation is possible.
Digital twins also lend themselves to scenario planning, allowing businesses to respond to specific needs rather than making reactionary decisions – an especially valuable tool in the aftermath of a pandemic.
For procurement and supply chain professionals it doesn’t get much more exciting than being able to see problems in their supply chains months in advance, allowing them ample opportunity to mitigate risks rather than manage crises. But the benefits of DT tech aren’t solely about fighting fires. The data they offer up supports prescriptive decision-making and lends confidence to the decision-making process. DHL is one such company currently using DT tech to optimise performance. Its Tetra Pak digital twin warehouse uses real-time data from the physical warehouse in Singapore to track performance and optimise storage management.
Of course, the most obvious benefit of DT tech lies with the bottom line. General Electric has had its finger on the pulse of DT tech since the formation of its digital department in 2015. Colin Parris, senior vice president and chief technology officer says: “We use analytics and digital twin capabilities to extract usable business insights. This provides us with the ability to tie insights to business outcomes by automating workflows, by interfaces to customers, and integrating with the control system in a customer’s facility.” GE has so far benefited from US$1.5bn in cost savings.
Accenture named DT tech one of the top five strategic technology trends of 2021, and believes more businesses are adopting it because they now know how to apply it. According to Michael Biltz, Accenture Technology Labs managing director, “Businesses are finally figuring out how to scale these projects across a fleet of projects, rather than a single one-off.”
Belcorp, a cosmetics firm based in Peru, has been using DT tech for over 10 years, claiming it has helped address questions such as where new production and distribution capacity should be based, and how adding a new supplier will affect the supply chain.
DT tech is far from a mature system and challenges remain as to how to use it to maximum effect and glean insights from the large volumes of data it produces. The Identity Management Institute estimates that 75% of digital twins will be integrated with at least five endpoints by 2023. Such a massive amount of data being collected from numerous endpoints poses a nightmare in terms of potential security breaches.
There is also the issue of cross-application use. There are a number of different types of DT tech depending on the area of focus, such as product development, supply chains, manufacturing and people. While the tech for each is advancing, the process of sharing models across applications is proving troublesome.
For most, however, the positives outweigh the negatives. According to Thomas Kaiser, senior vice president of IoT, at SAP, “Digital twins are becoming a business imperative, covering the entire lifecycle of an asset or process and forming the foundation for connected products and services. Companies that fail to respond will be left behind.”