Demystifying digital twins for manufacturing

October 21, 2022


In a rapidly changing environment, manufacturing firms face many challenges. These include transitioning to more sustainable business models and ensuring products meet the quality requirements of customers. As such, companies are investing in significant changes to maintain competitiveness. However, these changes also carry significant risks if they don’t pan out.

Digital technology is at the heart of many of these changes. Technologies such as artificial intelligence, IoT devices and advanced analytics promise to increase productivity. Now, digital twins are also well-established as part of this high-tech ecosystem. However, the role of digital twins is slightly different. Instead, they can be critical in identifying the right investments and mitigating the risks involved with making other significant changes. So, in this article, we aim to demystify digital twins and explore how you can utilise them in your business.

Demystifying digital twins for manufacturing

What is a digital twin?

A digital twin is a virtual representation of a physical asset. While the term itself is relatively new, the concept is similar to existing research and development and factory planning operations. These teams use computer-aided design (CAD) to create highly accurate plans for new products and even entire factories. Digital twinning is, in many ways, an evolution of the CAD model, albeit one that uses real-time data associated with the physical asset. This advanced application allows decision-makers to create a ‘what-if’ analysis on a far grander scale.

An example: Digital twin of a factory

Let’s take a digital twin of an entire factory as an example. This digital twin is a virtual representation of the entire shop floor, including every machine and process. With sensors placed around the factory collecting real-time data from routine operations, the digital twin offers a highly accurate and current view of the entire facility. This allows you to tweak parameters in real-time to identify potential bottlenecks through production.

For example, you might identify a bottleneck between assembly and despatch. You could use your factory’s digital twin to determine what happens when you move the assembly area nearer to the goods-in section. This simulation could answer whether the change eliminates a particular bottleneck or reduces the overall lead time. On the other hand, it may lead to undesirable consequences like bottlenecks elsewhere along the production line. Ultimately, the point of digital twinning is to determine the effects of a proposed change in a risk-free environment.

Unilever is an example of a manufacturer that makes extensive use of digital twinning to boost the efficiency of its production processes. The company uses virtual models of its factories to simulate complex what-if scenarios to identify the best operational conditions of its shop floors.

An example: Digital twin of a product

Digital twinning doesn’t have to be for the entire factory. It can also be for a specific product, operation, or other assets. For example, let’s assume that an aerospace manufacturer is having difficulties predicting and improving the lifespan of its jet engines. By creating a virtual model of those jet engines and running tests on the said model, they can determine how long pilots can safely use an aircraft before the risks increase to an unacceptable level.

NASA was one of the first pioneers of digital twinning to reduce the chances of failure in its spacecraft. Their original concept is the same one used today. It consists of three key parts – the physical asset (in this case, a spacecraft), a virtual representation of the asset, and the connections between the two of them.

What are the use cases and benefits of digital twins?

However, digital twins aren’t something that only large and extremely well-funded enterprises can take advantage of. There are numerous practical examples for manufacturing/engineering SMEs too. Here are some of the most noteworthy:

  • New Product Introduction: Introducing new products has always meant assuming a degree of risk. For example, it could negatively impact existing production lines and resources. However, creating a digital twin of your factory and a proposed product can help determine the impact, thus allowing decision-makers to take a more cautious and informed approach.
  • Investments in Plant: Implementing new machinery is a significant investment that can increase capacity and capability, but it can also carry risks. With a digital twin, you can see whether the new machinery will deliver the benefits you are anticipating. Additionally, you can identify the risks before investing and look for ways to mitigate them.
  • Optimising Operations: Creating an entire virtual layout of your factory can give you a 360° view of all of your operations to determine how certain changes could positively (or negatively) impact your bottom line or overall production processes.
  • Product development: Product research and development is another area where digital twins are enormously valuable. For example, implementing changes to existing products should ideally be done in a virtual environment first. This simulation will determine whether the change will lead to the improved qualities you anticipated.
  • Employee Training: Digital twins also offer a safe way to train employees in using new equipment without risking costly mistakes or compromising worker safety. This application is especially important for preparing employees to use potentially dangerous machinery.
  • Supply Chain Optimisation: You can use digital twins to simulate entire supply chains and optimise your use of resources like raw materials. You can even use digital twins to quantify the business impact of acute supply shortages. Armed with these insights, you can take proactive steps to mitigate the risks.

The most significant difference between digital twins and more traditional simulations is that they use real-time data to enhance accuracy. The best examples of digital twins in manufacturing are machines equipped with sensors that monitor essential parameters. By feeding both real-time and historical data to the digital twin, analysts can conduct tests and take actions to reduce the chances of failure or improve the efficiency of their operations.

How to get started with digital twins

Digital twins for engineering companies and manufacturing SMEs can be complex and difficult to implement. But the benefits are indisputable. The best approach is to start small at a low cost, typically by pinpointing a specific issue that you’d like to resolve. For example, with the current energy crisis, perhaps you want to reduce your power consumption. In this case, a digital twin should help you find the optimal performance level of your machinery without having a negative impact on your production lines.

Above all, successful digital twinning requires accurate data. This is why the digitisation of the shop floor should be a top priority. Machines and operations should be monitored in real-time using internet-connected sensors that share data across a centralised, web-based platform for enhanced accessibility and seamless workflows. Armed with this steady stream of accurate data, you will have the foundational infrastructure necessary to reap the many advantages of digital twins.

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