For a short period in history, “Netscape” was a dominant player in the dotcom era. Before we knew about Google, Netscape’s founders had “plucked a brilliant idea from academia and pushed it onto the world’s stage at a time when competition didn’t exist.” At its initial IPO, the company traded at $3 billion and was later acquired by AOL for $10 billion.
For many analysts, the Digital Twin is the darling of the IIoT era. For the last two years, Gartner has included the Digital Twin in its list of top 10 strategic trends. According to one analyst report, the market for the Digital Twin is expected to reach 15.7 billion by 2023.
Digital Twin 101
The Digital Twin is a virtual clone of a physical asset that simulates its behavior in real time. Before its application to the industrial domain, the Digital Twin concept was pioneered by NASA and was originally used to model space missions. At a high level, by accessing a virtual clone of an industrial machine, insights are gained about the quality of production and the likelihood of asset failure. “Digital Twin” has no standard definition; different flavours are provided by vendors such as GE, Siemens, PTC and others.
Applicability to Industrial Plants
The optimal scenario for the Digital Twin is new machinery. This is because generating a Digital Twin for existing plant equipment is very costly and time-consuming. In the Future of IIoT Predictive Maintenance Survey, conducted by students from Emory University in collaboration with Presenso, we received feedback from Reliability and Maintenance practitioners on the topic of the Digital Twin.
Two points stand out.
First, Operational and Maintenance professionals are less familiar with the Digital Twin than we expected. As indicated in Chart 1, most respondents (over 60%) were not familiar with the Digital Twin concept and only 11% believed that the Digital Twin will be mostly or completely deployed within 5 years.
A second issue was explained by Jack Nicholas. As he puts it, the reason for limited adoption is the following:
“Even in fairly new plants, configuration control is rarely practiced to the extent it should be. Drawings are usually out of date (even for newly commissioned assets) and specifications for performance are imprecisely documented over time and are, after a few operating cycles, ignored as assets are driven beyond the original design limits. To construct an accurate digital twin requires extensive research into current performance and condition requirements, not just referral to original plant specs. Keeping a digital twin accurate over a lifecycle is also expensive and requires at least periodic attention by data scientists, modelling specialists and business needs analysts, skills scarce in most organizations and usually available at high cost only from large service providers such as IBM, Accenture, and GE. Any plant modification affecting performance or required reliability conditions requires change to the digital twin model and related algorithms.”
The Case for the Digital Twin
Based on the above assessment, when does use of the Digital Twin technology make sense? In our opinion, these are the important elements:
First, the Digital Twin is germane for large, big-ticket items such as jet engines. Second, if the Digital Twin is bundled with a new product, the industrial plant does not have to hire external vendors to re-create the virtual copy of the underlying asset. Third, the industrial plant must commit to maintaining the accuracy of the Digital Twin. Any modification to the original design must be reflected in the Digital Twin. Without complete accuracy, the Digital Twin’s effectiveness is likely to be compromised.
Summary and Conclusion
A key difference between the Digital Twin and Netscape is that the Digital Twin is a technology category whereas Netscape was a single vendor solution provider. Furthermore, we should remember that the browser concept never disappeared. Netscape’s dominance was replaced by Microsoft (Explorer) and ultimately Google (Chrome) .
At the same time, there are parallels worth considering. The hype about Netscape’s technology was amplified by analysts and thought leaders. Ultimately, Netscape’s pricing and business model were not sustainable.
Although we do not foresee the Digital Twin category disappearing, it is important to recognize that its application may be more limited than some of the analysts and external parties suggest. The research from Operations and Maintenance practitioners suggest that the Digital Twin may be more of a niche solution within Industrial Analytics than a widespread, ubiquitous technology.