Digital Twins: The quintessence of Industry 4.0

Date 7/10/2020
Category IoT

The fourth industrial revolution is already a reality and, its arrival is starred by several actors who have come to stay in our daily lives. While Big Data, IoT and machine learning have made the headlines in the international technology press, in recent years a technology that brings together all the previous ones has been growing cautiously but significantly. I am talking about Digital Twins and their appearance in the industry, as it will change forever the way production processes are understood.

Digital Twins are one of the key technologies of Industry 4.0. It should taken into account that this industrial revolution involves much more than a single technological dimension. It has to do with new business models, risk prevention or operational efficiency. Thanks to the Digital Twins we can achieve these objectives through a real solution that takes advantage of all the potential provided by the other leading technologies of Industry 4.0.

But, what truly are digital twins and how do they work?

A Digital Twin is a virtual replica of a physical asset or system that simulates the behaviour of its real counterpart in order to monitor it to analyse its behaviour in certain situations and improve its effectiveness.

The model is normally in the cloud and can therefore be monitored and controlled remotely from any location.

The key of this technology is the interconnection generated between both physical and virtual worlds, as digital twins make it possible to have an exact representation of what is happening in their physical counterpart. To achieve this, data capture systems and a cloud system are necessary– we will discuss later.

So how can this technology help me transform my industry?

If we focus on the industrial world, thanks to the application of digital twins, there are 4 determining areas that will experience a revolution.

  • Design: when working on the design of a new product, a number of strategic decisions must be taken, such as the choice of materials or components, which will significantly affect the final result of the product. The need to know the behaviour of the product in the future has been solved so far through simulations and table-based definitions of design parameters. But now, thanks to the implementation of the Digital Twins, I can have a virtual version of my product, receive data from this asset in real time, and predict its behaviour without tables; which makes the design process much more agile and effective.
  • Maintenance: elements deteriorates over time and it is very difficult to measure and predict when and where a system or product will fail. Thanks to the use of digital twins, we can achieve through continuous monitoring, a much more realistic evolution of the variables that affect to the deterioration of our assets. Based on simulations, we will be able to predict what is going to happen and generate databases in real time to receive warnings before there is a problem.
  • Monitoring: In industry, assets are quite often distributed in a decentralised way, even in different geographical areas, which makes their monitoring difficult. What we will achieve with the application of digital twins in this area is to unify these assets, centralising them and being able to automate their monitoring management.
  • Operation: having the digital twin of a machine provides a real time analysis of its behaviour. This information optimizes its operation. By knowing the operating parameters, we will receive recommendations and advices in case any of them should be modified, which will considerably increase the efficiency of processes. This application will make operations more dynamic by modifying them in real time.

The Digital Twins cycle

To make the process of turning the physical world into a digital one happen, we must follow some steps or actions that make up what we have called the Digital Twin cycle.

  1. Information capture systems: these are sensors that capture environmental and operational information from the physical world.
  2. Information intake: combination of data sources to obtain information of the asset. Industrial systems such as MES, ERP, SCADA, CAD are included.
  3. Integration: all elements are unified through communication systems between the different data sources in a scalable and flexible environment: CLOUD.
  4. Intelligent and automatic analytics: It is necessary to apply intelligent and automatic models of information processing able to generate real time responses.
  5. Execution of the response through actions: The actions identified by the management system have to come back to the world through alerts, adjustment of variables, etc.

To sum up, sensors installed in the physical asset are used to capture operational and environmental data on a continuous basis. This dynamic data is transmitted to the cloud where it is enhanced with static data, such as the physical asset's engineering specification data. The combined data is then used as input to a statistical or engineering model in the cloud, and is analysed in real time to generate information that returns to the physical asset to monitor its ongoing operation, completing the loop of comment as shown below:

Components needed to deploy digital twins in our industry

In order to deploy any Digital Twin system, we will need a number of elements that match the main components of the Internet of Things:

  • Sensors: origin of the data of the physical asset. It is necessary to integrate a series of sensors that allow the generation of the digital twin of the asset according to the variables of interest.
  • Communications: system to link the physical and digital worlds. Depending on the application, it will be a determinant in terms of consumption, latency, etc.
  • Platform: software for information intake, analysis and management. New data sources coming from ERP and MES, among others, can be integrated here.

How can I start generating my digital twin process?

The first step would be to determine why, what my digitalisation objectives are and why I want to obtain information from a digital twin in my production plant. Some of the reasons that lead me to begin this process of implementing Digital Twins in my industry may be applying an improvement, increasing the efficiency of my processes or solving a coordination problem.

Thus, it is very interesting to experiment, in other words, to make a test without modifying any system to experiment with simulated data. By taking data from operational parameters, I can generate simulations to know if I would have managed to find out what I was looking for.

The next step would be connecting the equipment in a non-invasive way, without influencing the operational dynamics that I already have. At Integra, we conceive the IoT as a technology that adds value to a system through an extra non-invasive layer, without the need to replace PLCS, Mesh systems or other existing elements.

Once the equipment is connected, it is time to contextualize, add the detail and visualization layer that will test me if I really manage to apply that improvement I am looking for through my system.

After the previous step, we will have to apply the operational changes in the database so that decisions are taken automatically. This step will provide the system with intelligence that will subsequently help me make predictions and business decisions.

Finally, once we have validated why and how, we have to think about scaling. We can scale the same problem that has been solved into many other areas of the company or assets. This is what is really going to allow me to have a completely digitalised Industry 4.0 with centralised management through digital twins.

Now that you know how much Digital Twins can bring to your industry, what are you waiting for to make it a true Industry 4.0? At Integra, we have a great expertise in digitalization projects and we can help you with everything you need.

If you want to discover much more about this world of digital twins, do not hesitate to download the webinar of my colleague Gabriel Garcia through the following link.

Authors

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María Mateo

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