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SMEs can also make good use of a Digital Twin

Digital twins seem well suited for use in the manufacturing industry and could even bring about a revolution there in the form of more efficient production and better maintenance. But how do you deploy this technology as an SME? The knowledge and insights needed to invest in twins are often lacking. Teade Punter, however, sees plenty of possibilities and opportunities for the digital twin in SMEs.

A digital twin is the digital version of a physical asset, a system, an object or process, or in other words an asset: something worth collecting data on. With a twin, a digital representation of the real asset is created, by using the data from the asset's sensors. The real asset and the virtual asset are identical. If something changes in the physical asset, it is also the same in the twin.
Digital twinning is very similar to simulation in that it also imitates reality. Digital twinning adds an element to this, namely a continuous connection between the virtual and the real world. The digital representation is the real system, which makes it possible to directly see the system status and to control it via the actuators of the asset.
A digital twin can be used to develop new assets, as is done in aerospace, which is also where the concept originated. This article takes the digital twin as a derivative of existing assets, as developed in the manufacturing industry.

Making a digital twin

A digital twin is created by collecting data about the asset. This data comes from the sensors of the asset and is visualized with the twin. Therefore, twin development starts with the data structure of the asset. In Industry 4.0, methods such as RAMI4.0 and Asset Administration Shell (AAS) are propagated for this purpose. Some companies are already picking this up, others are more cautious. In addition to the data structure, it is often also important to look at the behavior of the asset. This might include "agents" that perform specific tasks of the asset, such as keeping track of inventory. Behavior of the asset requires modeling, a description of the states, with the conditions under which it occurs.

Three phases

For the development and application of digital twins, three phases are recognized: data logging, asset mapping, and asset-model integration.

Data logging forms the basis of every twin development: the data is collected via (IoT) sensors. For many companies, this is often already a big step, which should therefore not be underestimated.

Imaging the asset (virtualizing) may only look at the appearance and shape of the asset to depict it as real as possible in 3D, for example. Imaging is also about modeling. It involves looking at aspects of the asset that are relevant to its application, such as the maintenance or use of the asset or specific agent tasks. To make a model as real as possible, multiple aspects of the asset will need to be included. On the other hand, it is desirable to constrain the number of aspects in the model, so that the model is more powerful and clear. The image result is a 'digital model'. If the data exchange between asset and model is highly automated, it is referred to as a 'digital shadow'.
An asset can also be looked at from different perspectives. In the manufacturing industry, the plant and machine perspective often plays a role. From the factory perspective, this may involve the integration of several machines, for example, and the logistical workflow of the products may be examined. The machine perspective then has a more limited scope, and there the quality of products may be the focus of the twin.
Asset and model integration involves the complete integration of the physical and virtual asset where data and control are aligned. This is the step from digital shadow to digital twin. In this phase the twin is made synchronous with the real asset. Once this has been realized, control from the digital twin can regulate the physical asset.

Smart Industry Twin

An asset can also be looked at from different perspectives. In the manufacturing industry, the plant and machine perspective often plays a role. From the factory perspective, this may involve the integration of several machines, for example, and the logistical workflow of the products may be examined. The machine perspective then has a more limited scope, and there the quality of products may be the focus of the twin.

Motivations for SMEs

A digital twin can be developed for a variety of reasons. For SMEs, the following are possible motivations for starting a twin.

Because the twin is a copy of the real system, it can serve as a remote monitoring tool for companies that have machines at customers' premises. Thanks to the digital twin, a service operator can immediately see if there are any problems at one of its customers. In this way, maintenance can be carried out more efficiently and possibly also better informed.

 Twin can also be developed to collect data on machine parts or machine usage to recognize patterns. In this way, for example, the wear of parts can be predicted and their replacement scheduled without having to interrupt the manufacturing process at undesirable times: so-called predictive maintenance.

The twin can also be used to collect data. The data logging phase is then done from the digital twin. Data is collected about (simulated) situations in which you don't want to, or can't, bring the real machine in because it would break down or pose a danger to employees.

Yet another motivation is to allow multiple people to work on the machine simultaneously by having them work with a twin and thus train the real machine.

Finally, a motivation can be to align the assets of different companies. Companies can thus form a chain of assets, where machine information is exchanged and machines can hook up to each other, creating new forms of cooperation.

Investment

With digital twinning, the manufacturing industry is digitizing. Besides the opportunities, as described above, and risks such as security and IT dependence, twinning should be seen as an investment. Of course it is important to determine beforehand why the twin is being developed. A cost-benefit analysis can help here. However, the benefits of digital twins cannot be fully predicted before the actual twin implementation, because twinning also changes the view on the possibilities with the assets, machines and processes. Digital twinning is thus primarily a decision for companies with an eye for and confidence in a digital future.

Author: Teade Punter is a lecturer in High Tech Embedded Software (HTES) and a leading lecturer in Fontys Centre of Expertise High Tech Systems and Materials (HTSM).

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Fontys

Fontys Expertise Center High Tech Systems and Materials (HTSM) connects Fontys students and researchers with high-tech companies in the Brainport area.

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