Digital Twins Accelerate Sustainability

Does your organization care about sustainability? If so, leveraging digital twin technology can help you surge ahead to meet your future goals.
A digital twin is a software-based replica of a physical asset. Although the concept is now associated with the Industrial Internet of Things (IIoT), the earliest digital twins were designed to make product lifecycle management easier. Instead of investing time and effort into the laborious process of building and evaluating new product features, you can explore the impacts of product features, characteristics, and material selection virtually. (Tao et al., 2018)

These new digital capabilities can have huge impacts on sustainability. Exploring new aspects of products without building prototypes directly reduces material waste, and it’s faster, easier and cheaper to test out more options in software as well. For example, modern Computer Aided Design (CAD) software provides what-if analysis that lets you determine full lifecycle costs, from creation to disposal, for the 3D design you create. Materials simulators in these CAD packages let you specify what material types are feasible for your designs, and the software will explore thousands of combinations and recommend the most sustainable outcome. (Paudel & Fraser, 2013)

Because product designers can see the impact of their design decisions in real time, they can make better choices to support sustainability. In addition, being able to see how product design and material selection can change total emissions helps the designer make better choices for the planet.

These are just the simplest examples, though. In the Industry 4.0 era, digital twins are being used to amplify the value of simulation. Optimizing operations and predicting failures is much easier (and in some cases, possible) when there is a software system to manipulate. (Boschert & Rosen, 2016) For example, a blast furnace at a steel mill can’t shut down without weeks of up-front planning, and it costs millions of dollars a day to take a blast furnace offline for repairs and process changes.

In any industry, digital twins can make it possible to test new methods and techniques without compromising the production schedule, losing money, or risking asset damage. So in addition to helping companies reach their sustainability goals, by design — digital twins can be used to advance quality goals as well.

Additional Resources:

Boschert, S., & Rosen, R. (2016). Digital twin—the simulation aspect. In Mechatronic Futures (pp. 59-74). Springer, Cham.

Paudel, A. M., & Fraser, J. M. (2013). Teaching Sustainability in an Engineering Graphics Class with Solid Modeling Tool. 120th ASEE Annual Conference and Exposition, Jun 23-26.

Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018). Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 94(9-12), 3563-3576.

This entry was posted in EHSQ and tagged , , , , by Nicole Radziwill. Bookmark the permalink.

About Nicole Radziwill

Nicole Radziwill is a quality manager and data scientist with more than 20 years leadership experience in software, telecommunications, research infrastructure, and higher education. Prior to joining Intelex, she was an associate professor of data science and production systems at James Madison University, Assistant Director for End to End Operations at the National Radio Astronomy Observatory (NRAO), managed software product development for the Green Bank Observatory (GBO), and managed client engagements for Nortel Networks and Clarify (CRM). She is an ASQ-certified manager of operational excellence (CMQ/OE), an ASQ-certified Six Sigma Black Belt (CSSBB), and contributed to the development of ISO 26000—“Guidance on Social Responsibility.”

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