Posted: 23 Dec. 2019 3 min 57 sec min. read

The future of work in manufacturing: digital twin engineers

With the advent of the fourth industrial revolution, new jobs have been emerging at an alarming rate—and it’s getting harder and harder to anticipate what skills are needed. But what if you could see into the next decade and discover what the manufacturing jobs of the future look like? This series of articles builds out actual potential job descriptions and experiences that could emerge in response to new technologies, providing insight on how manufacturers can meet the talent demands of the future.

Let’s draw a picture. Imagine a future where the visual representations that help you design, manufacture, and market your products are based on an incredible array of new modelling tools powered by digital innovation, yielding visualizations with previously undreamed-of precision and utility. Now imagine the worker who would be able to produce and work with those visualizations.

If you’re having trouble with the second part, it may be because that worker does not exist today. Sure, for years manufacturers have used visualizations to understand how a product will look and function—from the back of the napkin, to blueprints, to models made of clay and computer-assisted designs. But in the future of manufacturing, advanced technologies will enable a whole new range of possibilities when it comes to visualization—it just requires someone who can do it.

Enter the digital twin engineer

We’ll call him Gintas DeFrank. It’s the year 2024 and Gintas’s job is to create virtual replicas (or twins) of jet engines. He takes engineering tooling and product structures and integrates these with digital elements into a single design. He then acts as a link between the product twin and the performance twin.

While replicas can be used at any stage of a product’s life, Gintas and his colleagues use theirs to predict and respond to customer issues. He works directly with customers to calculate the remaining useful life of a particular engine so that maintenance can be performed on an as-needed versus a less productive fixed schedule. When problems arise, he addresses them using real-time data analysis and advanced technologies, areas he is familiar with from previous jobs as an eEngineering applications manager and an artificial intelligence systems engineer.

In 2024, digital twin engineers like Gintas are found in a variety of industries and along several points of the manufacturing process, from designing the factory and the assembly line to maintaining the final product. They make it possible to see virtually inside any physical asset, system, or structure. This provides invaluable help in optimizing design, monitoring performance, predicting maintenance, and improving the overall experience for manufacturer and customer alike.

Gintas’s job is helped immeasurably by the digital tools he has at his disposal. For example, he creates the digital twins with 3D software and uses powerful computing to run detailed simulations across different conditions. On one day, he may want to know how an engine performs at 40 degrees below zero; on another, he tests it with 100-mile-per-hour crosswinds. The digital twin produces valuable information to test tolerances and understand performance under virtually any condition.

His personal productivity also benefits from the digital toolbox. Voice-enabled apps give him status updates, arrange his schedule, or deliver instructions to colleagues. Other tools use machine learning to help identify potential problems, track issues in the broader environment, and interact with colleagues, suppliers, and customers.

What’s different?

So what in the description of Gintas’s job is new? To be sure, his role in helping his company better understand its products’ behaviour already exists in manufacturing operations. But what’s different is that he spends less time on product development and production design, and more time on generating business insights and performing analytics to predict outcomes. Perhaps most importantly, Gintas can devote more time to customers and improving the product by listening and learning about any issues and concerns.

This is a truly radical change in the way manufacturers work together with asset operators and customers. It enhances collaboration, accelerates innovation, leads to smarter products, and creates new services and revenue opportunities.

Getting out in front

While Gintas’s job might not exist in the exact manner described above, there are lessons to be learned from imagining what his job may entail. Just think about the range of skills Gintas will need to have—from experience in AI engineering and advanced analytics to customer relations and program management.

Digital twining is quickly becoming a manufacturing imperative. Understanding who will be using it and how is critical as the competition for talent escalates and the drive for differentiation in the marketplace intensifies. The activities Gintas is engaging in will come to pass in one form or another—and manufactures need to be ready.

To learn more about what jobs will look like in the digital era, read our Future of work in manufacturing article on Deloitte Insights.

Key contact

Vincent Rutgers

Vincent Rutgers

Global Leader—Industrial Products & Construction

Vincent Rutgers is the global leader of the Industrial Products & Construction (IP&C) sector at Deloitte Touche Tohmatsu Limited (Deloitte Global) and a Consulting Partner at Deloitte Netherlands. As a consulting partner, he has been the global lead client partner (GLCSP) for a large Dutch IP&C client since 2013. Vincent has more that 25 years of experience working with major companies in the manufacturing, telecom, and utility sectors. His key areas of expertise include providing management consulting advisory on cost management, pricing, strategy development, new start ups, cost reduction, change management, and large transformations. Vincent studied production process optimization and initially worked for global manufacturing companies. He joined Deloitte in 2012 and led Deloitte Digital in the Netherlands before focusing on his GLCSP role.