How to Overcome the Challenges of Adopting Digital Twins in Manufacturing

Digital twins are increasingly gaining attention for their ability to drive intelligence through smart manufacturing systems. Through a combination of simulation software, Internet-connected sensors and machine learning algorithms, they can offer a range of benefits for keeping up with a wildly evolving manufacturing landscape.

However, despite their advantages, it is important to also be cognizant of the barriers that often stand in the way of successful digital twin adoption. What do manufacturers need to keep in mind before they even get started on their digital twin journey? How do they scale up? Who needs to be involved?

Engineering.com caught up with Dr. Emile Glorieux, senior research engineer at the Manufacturing Technology Centre (MTC) in UK, to discuss the various factors that need to be taken into consideration when implementing digital twins. The MTC is a research and technology organization that supports the adoption of digital manufacturing technologies by translating academic research into working solutions for manufacturers.

Engineering.com: What are the trends for digital twin adoption in the UK and Europe?

Dr. Emile Glorieux: We see that the adoption and implementation of digital twins is focusing mostly on building a new factory or rebuilding an existing one with new systems.

Also, when the initial concept of digital twin was introduced, it was more or less presented for an entire factory and all the processes within it. That’s not really the trend we see at the moment. The focus is more on a specific subsystem or scope within the factory—because it’s a trade-off between the costs and benefits you get from the digital twin.

What kinds of subsystems are suitable for digital twinning?

One element is around intelligent control of processes—so you want to operate a process in the most optimal way, but it includes lots of different aspects that need to be considered to decide the control parameters. That’s where a model is quite useful to suggest the control parameters.

Predictive and preventive maintenance is an area that we’ve been working on as well as optimization to minimize waste and schedule operations. And then we’re also starting to look at minimizing energy consumption.

We would imagine that the more complex the activity, the more a digital twin would be helpful.

Exactly. And the more time crunch there is. If on-time delivery and rapid production is one of the unique selling propositions of a manufacturer, then having a digital twin on that side of activities makes sense. If you always have long lead times, then there’s no benefit in having connectivity between the sales, purchasing and operation side of your organization.

Tell us about the challenges that manufacturers face during the adoption of digital twins.

One general challenge is that adopting a digital twin will initially be quite a disruptive change that affects many areas of an organization. It’s not just in the workshop or just in the design. Therefore, it’s carefully managing that it is adopted across these different areas that are aligned to each other and somewhat synchronized, in line with the purpose and goal of the digital twin.

Another challenge is that there’s a learning curve to start using the digital twin. There are a lot of different solutions out there that can be used out of the box, but ultimately the challenge is to then decide: “Which one do I need now? What do I need in two years’ time, and what do I need in five years’ time?” There’s that learning curve of what are the different solutions, since there are a lot of different terms used within the area.

As manufacturers have a lot going on anyway, to then get on top of that is often a challenge. For larger manufacturers, they might have the expertise in-house to investigate that—but for the smaller ones, it’s even more challenging to figure that out.

One of the challenges for new factories is the timeline for developing and deciding on the digital twin. While you’re designing your product, your new factory, your production system, you want to already start thinking about your digital twin—but you don’t have all the information yet. You might still be changing your new product or you haven’t designed your operation and your production system. To synchronize the two can be a challenge because you need certain data, but you don’t have it yet, but then you need it to make certain decisions on the digital twin side.

In manufacturing, it’s always a challenge to retrofit new technologies on pieces of legacy equipment in an existing factory, and digital twins are no exception there. It can be very costly to install new sensors. Especially when the production system is in operation, it’s very costly to interrupt operation, install some sensors, commission the controls. And so, the benefits of the digital twin need to justify the cost of having to do that work.

Could you provide some advice for de-risking the challenges in adopting digital twins?

One piece of advice is to not forget about the twin side of the concept. Don’t just focus on the digital side, but have a long-term vision of what the digital twin needs to do. Look to see what’s the best solution for the company. To maximize the benefits from a digital twin, it’s important that its improvements are tailored to your system.

Before you start, think about the big picture of where you want to be in five years. Then really break it down and start small in one subsystem, and develop a complete digital twin solution for that. See if it works, learn how to use it, learn how it works, what works for you, what doesn’t work for you.

Look at the adoption of digital twins as a journey without a final destination. It’s something that you break down in steps and stages. You start with step one and two, and then you might redirect or replan. Things like continuous improvement will be key. Have that in mind right from the start, and look for solutions that allow you to accommodate that continuous improvement. Manufacturing has changed, especially in the last three years, and there have been lots of changes in demand. The digital twin needs to allow that and shouldn’t prevent change. It should instead accommodate you to change your system or operations more easily and frequently than before. My advice would be to look for solutions that are tools for your organization to travel along your digitization journey.

As the digital twin is not the destination, once you have your first one, you probably want a second one or better one, or you want to integrate it with another system in your factory. Since a lot of the digital twin side is software, you want to improve and update it regularly.

Because a digital twin has so many different components, you’ll never get it a hundred percent right from the first go. That’s reality. Doing it iteratively and stepwise should reflect in your roadmap. Don’t be afraid to say, “Let’s fail fast, and learn, and then redo.” Especially if you’re at the start of the digital journey. That’s how you get to where you want to be the quickest. You just need a bit of time and investment to get started, and then have a roadmap that covers the different elements of the digital twin. Have a roadmap for sensors, for data handling, for modeling and simulation, for algorithms. Just make sure that the different components are synchronized across your digital twin, because there are a lot of dependencies between these different elements.

When it comes to scaling up, make a second digital twin and a third one and a fourth one. Have these digital twins work together instead of replacing one digital twin with a bigger one. It’s a better approach to keep things modular, and scale up in a way that you don’t have a single point of failure in your system. The second digital twin can be better than the first one, and you can also improve as you go along. The concept of aggregate digital twins comes in when you have multiple digital twins of subsystems working together, exchanging information. I think that’s a better way to scale up than to create one big digital twin that’s supposed to do everything you want. You can have one digital twin for your maintenance, one for your welding process, one for your warehouse.

Right from the start during the planning, involve the different teams. Make sure everybody’s seeing the big overall solution—how it should look, what the purpose of each component is, and how all the pieces of the puzzle will work together. If not all teams are involved from the start, you’ll come to one point where you need something and the other team still needs to be introduced to the concept, understand what the goal is, and be brought on board to the journey. Then you encounter lots of delays and misunderstandings.

Involving all teams is not just key to successful adoption, but it’s also why a digital twin can have so much impact. It forces different areas in the organization to come together and align, so the success lies with that as well.

And then one obvious piece of advice is: don’t forget about cybersecurity. Be aware of things like—where is my data coming from? Where do I store it? Who can access it? How do I use it? Do I want to share it with suppliers or not? Do I want to share it with clients or not? There’s a lot of information and data, and nowadays it’s important to be careful with it.

Don’t forget about the IT side of the digital twin. There’s a lot of software and computers and databases involved. When working within an organization on a digital twin, it’s crucial that the team includes someone from the IT department. It’s so obvious that it’s sometimes overlooked.

Every piece of the puzzle is crucial. You need sensors, you need monitors, you need your connectivity, you need your database, you need your model, you need your algorithm. And if one’s missing, you lose out on the potential of a digital twin. You need the entire solution.

What are your thoughts on the future of digital twin adoption for manufacturers?

I think an emerging trend will be aggregate digital twins. That’s happening now, but what will also happen in the near future is that the control over those digital twins will be extended externally.

Imagine you have a digital twin for a welding process—and the supplier of the welding equipment, and supplier of the metals that need to be welded, will have access to that digital twin. You can say, “The latest batch I supplied to you had these characteristics, so change the voltage and current in this way and you’ll have the right weld for your product.” I think access to the digital twin will be extended across the supply chain where it enables collaboration to get the optimal result.