How digital twins give manufacturers a real-world advantage

These virtual replicas of a physical product, equipment, process or the supply chain help you monitor, simulate and optimize performance.

If you’re creating a new tire, you’ll probably mold a prototype and test it out on the road, then update it with refreshed versions and more safety checks.

If you want to boost production capacity, you can rely on your instincts to try to predict the impact on your assembly lines and react to bottlenecks as necessary.

And if you’re worried about a disruption to your supply chain from a natural disaster, you can consider weather forecasts and other relevant data to create contingencies — and then hope for the best.

But in the Transformative Age, manufacturing companies — particularly those in the automotive sector — have another option that is more nimble, more cost-effective, more cutting-edge and more grounded in the real-time reality of how your business actually operates. It’s called digital twin — a virtual replica of any physical product, equipment or asset, or the supply chain, that you can use as testing grounds for monitoring, simulating and optimizing production, quality and operational performance.

A digital twin could be a virtual version of a tire or a passenger vehicle, the methods for how these items are built or the entire production line. It could even be an entire factory, a network of plants or the end-to-end supply chain. Together with disruptive technologies, such as the Internet of Things (IoT), artificial intelligence, machine learning, process and data mining, and even augmented reality, digital twins are stretching the bounds of what’s possible, enabling the fourth industrial revolution to transform manufacturing for the 21st century.

Through a digital twin, you can simulate your assembly line based on the options, even before you’ve planned your week and see where the process issues lurk. You can even do real-time testing of virtual equipment from an engineering perspective before it’s installed and hard-wired.

Plant infrastructure: How about monitoring a plant without physically being there? With a digital twin, you can do that and more, like walk the shop floor of a plant in Mexico, through virtual reality, and train workers remotely from a laptop. With a digital twin the equipment doesn’t even have to be physically installed to show others how to use it.

Asset maintenance: By monitoring real-time data from IoT sensors in the manufacturing process, your digital twin can also model when maintenance will be needed for critical equipment, or it can even be used to determine the health of an entire production line, factory or network of factories. In a 2018 report, Gartner estimated that businesses (and consumers) will save US$1 trillion each year in asset maintenance by using IoT through digital twins.

Targeted recalls: By tracking key components that go into your product and their serial numbers in a digital twin — providing full traceability — you don’t have to recall tens of thousands of products in the event of a problem. You’re able to narrow your efforts only to those directly impacted — for instance, by pinpointing a shipment of components that experienced corrosion in transit from overseas.

Retail: Digital twin even helps in consumer-facing realms. For instance, a digital twin of the vehicles you produce, with 3D visualization, allows a potential buyer to change the color of a car to one that he or she prefers when shopping online. The same goes for different vehicle options for the interior, providing a richer and more personalized customer experience.

Aftermarket/consumer service: In the used market, consumers have to guess the health of a vehicle, or perhaps look at a Carfax. But if you give the vehicle a digital identity (with a digital twin and blockchain), you can then start to track how often it was serviced, answering questions like: When parts were changed, did they use original equipment manufacturer (OEM) parts or aftermarket parts? Was there an accident that did not get registered, based on an impact analysis?

The twin holds all real-time performance, sensor and inspection data, as well as service history, configuration changes, parts replacement and warranty data.

Supply chain: Digital twin allows you to monitor and simulate events that impact your supply chain — for instance, a natural disaster or a trade dispute with a key country — and how you can proactively react to them.

For instance, if you want to simulate the impact of reduced raw materials from China, a digital twin can help you decide how to fulfill customer commitments efficiently. You can start to model various data points — such as how long the component spends in transit, or whether it’s perishable — and start being more proactive instead of reactive.

But this only scratches the surface of what you can do with a digital twin. In a future article, we’ll explore the supply chain issue more deeply and how other technologies can revolutionize it from end to end.