Of digital twins and threads: New metaphors weave new meaning

Dec. 15, 2015

An enormous opportunity and challenge for industrial companies today is smartly integrating data from the software-based tools—and the people that use them—along an entirely different axis.

As I reflect on the many ideas raised in the course of our first Smart Industry conference, the growing import of two related concepts stuck with me: those of the digital twin and the digital thread. The digital twin refers to a digital model of a particular asset that includes not only its design specifications and the engineering models that describe its behavior, but also the operational data and as-built data unique to that particular machine and its life experience. Similarly, the term digital thread refers to an integrated view of asset or product data woven throughout its lifecycle and across historically siloed functional perspectives. (For more information on these concepts, read the stories based on presentations given at the Smart Industry conference: GE's Colin Parris on the digital twin, and Bill King of the Digital Manufacturing & Design Innovation Institute on the digital thread.) 

The fact that industry has found it useful to latch onto these new metaphors indicates a new level of subtlety not encompassed by our older vernacular. It also imbues a deeper meaning to the phrase that’s often over-used to describe the value proposition of the Industrial Internet of Things (IIoT): “delivering the right information to the right place at the right time.”


Building a smarter industry isn’t just about enabling real-time decision-making based on the latest information, nor is it about integration solely along the vertical dimension of the Purdue model pyramid. An enormous opportunity and challenge for industrial companies today is smartly integrating data from the software-based tools—and the people that use them—along an entirely different axis. Namely, through time.

Take the design process for a typical capital project—a new line or perhaps a new plant. In the continuous process industries there exist well-evolved simulation tools to aid in process design, but how well do they really integrate with the mechanical design tools they feed? Do process engineers’ systems allow them to “design for constructability,” based on feedback from a plant’s mechanical design systems?

Similarly, sophisticated tools for three-dimensional plant design provide for instrumentation and control wiring and schematics—and in some cases even accommodate control system configuration—but instrumentation, control and optimization strategies still tend to bring up the design caboose. How many process designs could have been dramatically improved by the control strategy innovations of automation specialists had they been involved from the beginning?

In the end, the smart industry opportunity and challenge is not just a technical integration problem but a cultural one. Can people responsible for upstream lifecycle functions understand and accommodate the priorities of those downstream when a better lifecycle outcome is at stake? And are feedback mechanisms in place to affect those changes?

Often, the least risky path forward is the way we did things last time. Those companies that succeed in tomorrow’s smarter industry landscape are those that embrace these integration challenges, effectively pulling together data and information across time to provide solutions optimized not just for right now, but for a lifetime as well. 

P.S. We're starting to pull together the agenda for next year's Smart Industry Conference & Expo, to be held September 26-28, 2016, at The Drake Hotel in Chicago. Hundreds of industry professionals will convene to discuss how smarter devices and sensors, pervasive digital networks and increasing powerful software applications continue to transform industry. Watch a video of 2015 conference highlights, and request more information on attending or presenting at Smart Industry 2016 as it becomes available.