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As connected devices—anything from the computer built into a car or a fitness wearable to a smart gas meter or wind turbine—have become cheaper to manufacture, their use has grown rapidly. Some form of connected device or system is now in almost every industry and sector. This proliferation means that traditional maintenance models requiring engineers to have easy physical access to real-world devices and systems are often no longer viable. As such, the need for an alternative management model is growing, which is where “digital twin” AI technology has enormous potential for any enterprise doing business through connected devices. This report looks at the benefits companies can gain from digital twin technology, the options available on the market to take advantage of it, where digital twins are already in use, and what some industries stand to lose by ignoring this AI trend.
A digital twin is a software simulation of a real-world object or system created with AI technologies that include machine learning, deep learning, video and image analytics, and augmented/virtual reality (AR/VR). A digital twin can make remote sites accessible and observable, ensure compliance and productivity in remote locations (e.g., construction sites or deep-sea oil rigs), enable predictive maintenance of complex hardware, help design smart city programs, maintain commercial connected devices, and help track, model, and predict online consumer behavior (see Exhibit 1). This could be especially useful for manufacturing and utilities firms distributing their sites and operations ever-more widely across the globe, and consumer-facing firms catering to an ever-younger demographic of users who transact largely through mobile devices.
The IoT, or internet of things, isn’t just relevant to manufacturing firms. Consider things like phone sensors, Fitbits, smart speakers, and smart home hardware. By now, the IoT is an opportunity for businesses of all stripes to communicate more effectively with customers, predict their clients’ needs, and keep their operations running smoothly. To do this, however, maintaining a comprehensive, real-time overview of a vast network of IoT devices and systems is paramount. Enter digital twins.
Exhibit 1: Potential benefits of digital twin technology in industry
Digital twins are becoming an imperative in an IoT-saturated world
Digital twins are virtual simulations of real-world assets. To enable generation of a digital twin, a real-world asset must have either an embedded connection to the cloud or have a sensor attached to it retroactively to enable such connectivity, converting it to a smart or IoT asset. These can be objects—like a wearable device, a smart TV, or a piece of heavy machinery—or a system—like a social media platform.Pairing and simulation technologies—precursors to digital twins—have been around for decades. NASA’s efforts to model how its equipment would function in space and then design it to eliminate preventable errors pioneered this technology. The modern term “digital twins” was coined in 2002 by Michael Grieves at the University of Michigan, but has only become an applied reality in the past few years due to the major technological advances and changing commercial circumstances outlined below.
These factors have led to a boom in digital twin awareness and adoption and growing demand for affordable simulations. A growing number of vendors are now capitalizing on this demand. We’ll take a look at some in this report.
There is by now a wide array of digital twin offerings to suit your enterprise’s needs
The digital twin market is still nascent and in flux, with active vendors dividing along both industry and approach lines. Some vendors, particularly smaller players, take a more targeted approach and develop productized digital twins for specific verticals, while established older vendors tend to take a platform approach, enabling enterprises across a wide range of industries to compile their own simulations to reach a broader market. Here are several standout digital twin solution vendors from both small and large players:
Exhibit 2: SWIM.AI’s digital twin framework
Source: SWIM.AI (HFS screenshot)
Veerum. Canadian IoT startup Veerum, founded in 2014, offers a Digital Twin platform for improving cost efficiency and project management for capital projects. The projects include large-scale undertakings such as oil and gas exploration or infrastructure construction. Unusually, Veerum largely deploys and leverages data inputs from its own IoT hardware rather than plugging into clients’ devices. Using hardware including drones, lasers, and ground robots, the platform creates a digital simulation of a site and updates it daily, enabling clients to track how their project is progressing against original design specifications (see Exhibit 3). The goal is to catch inefficiencies or errors early to avoid these problems escalating and becoming more expensive to resolve further down the line, as well as track materials use and other project factors on a more granular scale. Veerum is a participant in GE’s Zone Startups Calgary accelerator and has major clients including Cenovus Energy.
Exhibit 3: Veerum’s digital twin technology
Source: Veerum (YouTube screenshot)
Digital twins can give your enterprise a more holistic view of its operations
Historically, investing in such simulations only made fiscal sense to enterprises dealing with remote physical sites such as deep-sea oil rigs, spacecraft, and out-of-the-way construction projects. Their demand was driven by the need to be able to prevent system failures where human engineers wouldn’t be able to intervene easily, or at all. However, this is now changing. Some of the world’s most complex and mission-critical systems are no longer purely physical. For some businesses, being able to gauge consumer behavior on a social media platform could make the difference between a good and a bad financial quarter. Or, being able to predict a flaw in a smart fridge or thermostat could vastly improve customer satisfaction and brand loyalty in an economy where customer experience standards are being set very high by high-tech giants like Amazon.
Regardless of whether a digital twin relates to a physical asset or a digital one, the key benefits of the technology boil down to the following points:
Fundamentally, these benefits boil down to a holistic overview of their operations and systems, which becomes an invaluable advantage as the ecosystem of smart devices attached to an enterprise’s operations grows exponentially.
On the flip side of this coin, companies that neglect to view their expanding ecosystem of connected devices – whether these belong to the enterprise itself, or to its customers – as invaluable new sources of data collection and competitive insights, stand to fall behind in an increasingly data-driven market. As we’ve seen, there are plenty of varied options to help enterprises begin leveraging the information the IoT ecosystem provides, and little excuse not have them on their radars.
Bottom line: Digital twins will become essential to enterprises’ management of their assets—cross this bridge now or regret it later
The facts are clear and undeniable. The IoT is growing around enterprises and beyond their control, driven as much by their customers’ connected device purchases as it is by their decision to use these devices in their operations. Further, operations are becoming more globalized, increasing the distance between an enterprise’s nervous center and its peripheral assets. Both factors make the need for technology that can provide a holistic, real-time, and highly accurate overview of an enterprise’s entire asset ecosystem essential. This is where the leaps and bounds that have been made in the past decade in AI are making a tangible impact and making helpmeets like digital twins possible. Digital twins were once the turf of heavy industry and the exclusive right of very well-funded scientific organizations, but this is no longer the case. With offerings from players from IBM to SWIM.AI now on the market, enterprises have little excuse not to, at the very least, investigate this technology. What it comes down to is this: start looking to digital twins to control your IoT ecosystem, before it starts controlling you.