Q&A: GE Innovation Engineer Warren Gieck Explains Digital Twins & More

Warren Gieck is an Innovation Engineer, Product Optimization Leader, and all-around digital guru at GE’s Customer Innovation Center in Calgary. We asked him about digital twins, data storage, big data analytics, and working in the age of smart machines.

So what exactly is a “Digital Twin”?

A digital twin is a virtual representation of the real world using physics-based modelling, data analytics, and machine learning.

Does a Digital Twin actually look like a virtual version of its real-world counterpart?

One type of digital twin can be used in the context of a physical design that would provide a version that would “look” like its real-world counterpart. These would be used mostly for form, fit, and function type applications.

However, the real magic is when Digital Twins are developed for operational, process and performance representations. This type of digital twin accurately models the underlying real-world operations of the equipment or process, without needing to represent the physical design.

Are digital twins changing how engineers design machines?

Yes, it allows them to better simulate designs with real-world interfaces, data, and feedback. But digital twins are not only for machines, but processes, layout, planning, as input models for optimization, and more.

What are the limits on data collection and how do we overcome them?

The ability to transmit, utilize, and process data at adequate speeds can be limiting. Faster communication, better data conditioning, processing data at the source with local/edge servers, are all options to improve on these limitations.

Is it possible to have too much data?

Too much data can be a challenge in the context of collecting data that is trivial, has no actionable value, or has multiple redundancies – i.e. collecting data for the sake of collecting data.

Do we need better bandwidth to fully realize the potential of big data? Will we ever have unlimited bandwidth for mobile devices?

Definitely better bandwidth for high data rate locations is required.

The increasing demand and technical limitations on bandwidth for mobile devices will provide limitations for the foreseeable future, until new hardware technologies can provide significant improvements.

What are the most important skills for humans to develop as computers get smarter?

Problem-solving and looking for new ways to innovate. Computers learn from the past or present, but they currently can’t determine things that are completely new.

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