Maximizing Innovation Using Digital Twin Technology

Companies wanting to compete and innovate need to use all the technology at hand. Digital twin technology can maximize productivity in ever-changing and demanding markets.

Brian Irwin, Accenture
Brian Irwin, Accenture

Analyzing high volumes of data to create ever-smarter, connected services and experiences has become essential to industrial manufacturer success. But maximizing the use of such data to sustain success in an increasingly demanding market is a major challenge for organizations. Applying digital twin technology could be one answer.

A digital twin is part of a series of technologies that help industrial organizations gain more insights from data to develop the latest innovations in digitally enabled products. By using digital twins that provide virtual replicas of products, processes, and services, companies can visualize, test, and continually improve products. While the concept is not necessarily new, it is growing as a much-needed tool to optimize data use in today’s data-driven products age.

According to Accenture research, 70 percent of surveyed data analysts say they don’t have access to everything they need to adequately perform their function. Using a digital twin is not only an invaluable resource for industrial product development, it can also help companies accelerate speed to market, enhance supply chain capabilities and ecosystem partnerships, and continuously optimize operations.

Moreover, a digital twin can provide long-term manufacturing benefits, including, several progressively advanced levels. The third, most advanced level enables companies to analyze real-time data from sensors embedded in the technology’s virtual model. This then, for instance, allows organizations to predict failure rates and understand how certain modifications can help increase production of the products involved.

As an example, a major car company, using computer-generated imagery capabilities, developed a digital twin image of one of its motor blocks to simulate the motor’s components at various speeds. They then shared the analysis simultaneously across engineering and design departments, which helped not only fine-tune the motor’s performance but also streamline numerous work processes.

 

The journey

So, how should industrial organizations begin? Digital twin technologies can greatly enhance business and operations for industrial companies. Integrating this technology takes several steps:

  • Assess recently designed and built operating assets. These legacy systems will likely include digitized plans and drawings created with modern computer-aided design (CAD) tools—making the application of digital twin technology relatively straightforward. Today’s technology also can make 3D or virtual images of any industrial asset, including older, traditional production lines.
  • Prepare to convert legacy systems for the retrofitting of digital twin technology. This includes applying learning machine tools, once 3D imaging is available, to extract relevant engineering data from legacy documentation and integrate it into a 3D image. This will make it possible to connect sensor data that provides live operational monitoring and algorithms needed to support advanced simulation and prediction capabilities.
  • Be systematic.The wider organization should also be made aware of the potential value that a digital twin can deliver. Start small by working with a twin that operational and engineering teams can use to demonstrate the positive impact it can have on their role. Taking this approach will help secure their buy-in and encourage the creation of even more advanced, intelligent digital twins that can help drive company growth.
  • Transform digital twin testing into training and retraining components for staff to help them develop expertise in applying more sophisticated versions of the technology.
  • Further improve safety throughout a company’s operations by leveraging the safety benefits of a digital twin. Using this technology minimizes the requirement for human interaction and physical monitoring within potentially hazardous plant areas, which can reduce potential workplace accidents. A digital twin can remotely inspect operations in hazardous areas, assessing live data for issues that can be modified without direct human contact.

 

Master the future

Data has become a critical engine for driving ever-more innovative digital products, services, and experiences. Industrial manufacturers that can master its use by applying technologies like a digital twin can sustain success in the changing industrial market.

 

>>Brian Irwin, brian.irwin@accenture.com, is managing director, leading Accenture’s Automotive and Industrial practice in North America, as well as the Industry X.0 Consulting practice.

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