The industry currently leads the way in the development of new Use Cases within the Industrial Internet of Things, commonly denominated IIoT. The massive influx and consolidation of intelligent objects, i.e. sensors connected between each other and also with the data centres in the cloud, offers a great potential for producing and operating in more efficient ways. In this evolution, the technology that appears to be at the forefront is the so-called digital twin.
A digital twin is a replica of an IoT product that includes all its components, physical as well as digital, plus all the dynamics and interaction between them. This permits the analysis of an object in real time from a computer and without physically monitoring it.
This technology requires important investments, and thus, its adoption has so far been limited to leading industries, with examples from the machine and tool industry, manufacturers of heating equipment, engines, vehicles, etc. Despite this, according to Gartner, almost 50% of the companies that are implementing IoT already employs or are planning to create a digital twin. Also, the next generation networks, 5G, with its promises of super-fast connectivity and low latency, can only contribute to the development of new products or business models based on this innovative technology.
Use Cases
The technology that the digital twin is based on was originally developed by the NASA, due to their need to know the status of and remotely control their space shuttles.
When creating a digital replica it is possible to obtain immediate feedback from the current activity, which again enables precise corrections. The digital twins will show particularly useful in operations and maintenance of connected machines and equipment that are generating large volumes of data. For example, they may help to prevent downtime via early detection of anomalies and preventive maintenance. Also, they could be valuable in the identification of possible improvements with regards to how to most efficiently employ a certain machine or equipment.
Let’s imagine the case of a high precision machine, where minimum variations in its design or manufacturing may have important consequences. With the digital twin it will be possible to create prototypes and virtually “try” these before they are passed on to production, a phase that may also be controlled in real time. In the case of the same equipment for different industries and environments, you could create two or more versions of the digital twin. This would enable working on quality assurance and performance optimisation on the same equipment but with distinct uses or environments. When it comes to operations, processes could be optimised via advanced data analytics in real time, which could also lead to future improvements of the design itself.
IT Considerations
Various factors play an important role in the creation of new products and services based on the digital twin technology. This includes IoT, the nature of data to be channelled into the system, and advanced data analytics aided by artificial intelligence (AI). The data generated by the physical products are sent to the cloud via IoT, where AI enables the identification of patterns and the creation of models of behaviour, detection of possible deviations, prevention of issues and downtime, performance improvements, automatically management of optimal product configurations according to use, the prediction of future events, etc. For all this to work you first have to decide on which data to employ, often from different sources and in various formats, and normalise it for analysis in real time. It becomes clear that an adequate IT architecture is vital in order to assure the basis for a successful project. Thus our recommendation is that expert consultants are involved from the beginning of the process.
This article was first published in Spanish ComunicacionesHoy in September 2018
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