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  • Digital Twin

A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the Construction Tech Review Advisory Board.

Director of Digital Twin at Flex

Zohair Mehkri

How Digital Twins are Enhancing Digital Transformation in the Manufacturing Industry

Employing Digital Twins

We've been deploying simulation and digital twins for several years at Flex, and the journey has been a rapid one, covering a lot of ground in a short space of time.

Our segments are so diverse that we've been able to apply the technology to many different areas. As our learning curve accelerated, we deployed digital twins on product and market segments that are very different from one another. We’re now at the point where we can directly apply best practices from one segment to another.

Flex as a Company

Flex is a global diversified manufacturing services company. With advanced manufacturing and design facilities in more than 30 countries and a global workforce of over 170,000 people, we design, build, and deliver products for customers across six major industry segments, including health, automotive and computing. Last year, Flex generated over $30 Billion in revenue.

Fitting the Digital Twin Fit

When you think about the manufacturing process, there are a lot of different capabilities that must be expertly coordinated, including design, materials, logistics, supply chain, and manufacturing to ensure efficiency, scale, and consistent high quality.

The product life cycle naturally begins with design: materials selection, prototyping, testing, certification, etc. That process can be done by our customers or in collaboration with our specialist design centres. Once the design and material selection steps are final, digital twin helps us to configure the entire manufacturing process and all the discrete processes within it.

Our digital twin team works with the customer and across our organisation, including our supply chain team, as well as shipping and logistics teams, to fully understand the scope of the project.

Once we understand the supply chain flow of how much material we're getting and when and where it's going to be delivered, we can then create a digital twin to simulate the process flow, from raw materials coming into finished goods going out.

We can even visualise the production space before it's even built. By creating a simulation of a process, a factory or an environment, we can build a digital model, a digital twin of a real environment. With a digital twin, we can iterate trillions of 'what if' scenarios to unblock bottlenecks and optimise processes, whether that's in materials selection, on the shop floor, or in our warehouses.

When some people think of a digital twin, they might imagine a cartoon or animation. At Flex, we use high-fidelity visualisations to show what an environment looks like. This is crucial because the better the visualisation, the better the conversations we can have with our customers, and this often leads to better decisions and better business outcomes.

One of the things we've learned over the course of our journey is how important different types of technologies are in the success of digital twins. We never thought, as a manufacturing company, that we would be looking at things like game development, for example, alternatively, how the quality of the graphics, visualisation and software has led us to speak to game developers and companies that focus on graphics.

Benefits of Deploying Digital Twins

Digital twin technologies result in faster time to market. Customer product life cycles are getting shorter, and they're getting faster. That means we need to be agile and fast while controlling quality and cost. Digital twins are important in helping us get us there.

As digital twin technology continues to evolve and the intersection of devices and AI engines are built into advanced simulation software, it will unlock even greater predictive accuracy

Traditionally, production lines would evolve over time through trial and error. But when trial and error inform your decisions, you burn through time and money to find the right balance.

For example, if we can predict that something's going to happen, we either stop it from happening or create the environment in which it can happen. This helps to avoid unexpected costs before it's incurred. Events like this are visible in a digital twin and allow predictive planning to avoid the issues and the costs. Digital twins allow you to factor in things that you typically would have left out.

Future for Digital Twins

A digital twin facilitates closed-loop innovation. This means that the virtual model collects data from the physical environment, re-creates it and tests the effects of any number of scenarios involving variables across the entire physical environment. These are pushed back to the physical environment. Yes, that does mean having software making physical changes in the real world.

This allows a manufacturing site to create a roadmap to improve its physical efficiencies. This continuous synchronisation is paving the way to the next generation of reality, where the physical and digital worlds converge.

As digital twin technology continues to evolve and the intersection of devices and AI engines are built into advanced simulation software, it will unlock even greater predictive accuracy.

It all relies on the quality of the data, but with full-fidelity information and the ability to analyse test scenarios, digital twins can increase visibility across the environment, make predictive assessments of production-line changes and enable organisations to make better decisions about how to improve their operations.

The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.
The Leadership Perspectives forum brings together voices shaping construction technology and innovation. Participation is by invitation only. It features leaders who are not merely observing technological change, but actively contributing to it through digital transformation and execution-driven insights.
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