Industry 4.0 is a revolutionary movement that has provided increasingly interconnecting components to the industrial sector through the use of technology. Among the several tools that emerged from industry 4.0, one has been calling the attention due to its revolutionary outcome: The Digital Twin technology, which has been used in industry to raise productivity by planning and optimizing the process of collecting and analyzing data through a continuous flow of data coming from a real asset and being sent to a digital replica.
This technology has in its essence the main pillars from the Fourth Industrial Revolution, being digitized, decentralized, modular, and allowing real-time operation to get the most customizable and optimized outcomes.
Read: All concepts of Industry 4.0 that anyone in the industrial sector should know. Click here to access
The Digital Twin was originally designed by Michael Grieves in 2002, to be used in the Project Life-cycle Management (PLM). Even though the Digital Twin is still being used in this area, other industries have also discovered the value delivered by this technology to the improvement of their process and operations. Here we have two examples of industries that are using Digital Twin:
- NASA in the research for aircraft conditions predictions on a launch environment
- Healthcare system, with researchers pointing to Digital Twins as the medicine of the future – a fully personalized healthcare.
Digital Twin levels according to the ability to exchange data:
Digital Twin can be used in many branches of activities, the technology has a lot of different concepts surrounding it, and from all these definitions, researches from the Fraunhofer Austria Research GmbH, separate them from the level of integration of the Digital Twin. All of them have in common the digital representation of an existing asset, and the differential in the definition is the ability to exchange data. That being said, these are the 3 main models:
- Digital Model: The Digital Model doesn’t automate data exchange from the physical to the digital model. All the data exchange is done manually, furthermore, no change in the state of the physical or digital model has direct consequences in both of them.
- Digital Shadow: Differently from the Digital Model, it has an automatic flow of data from the physical to the digital shadow. A change in the physical object can interfere with the digital.
- Digital Twin: There’s a flow of data between the physical asset and the digital and vice versa. As the Digital Shadow, the physical can control the digital, but also the digital interfere in the physical. This constant flow fully integrated is what makes a Digital Twin.
What results can this technology deliver?
Although the majority of articles and papers use the term Digital Twin, only 18% of them really follow the definition. The adoption of this revolutionary technology in manufacturing can increase the effectiveness of an operation, offering lots of benefits. Based on these parameters, Vidya is part of this 18% who manufacture a real Digital Twin. Using our software the following results could be achieved:
- Work orders based on statistical assumptions;
- 100% control of productivity of the team in real-time;
- Increase of 50% in the maintenance and execution of team productivity;
- Identify the impact of changes in the productivity system;
- 30% reduction of people in the field;
- Evaluation of machine conditions based on descriptive methods and machine learning algorithms;
- 30% reduction on time for acquiring information.
We managed to reach all these results combining engineering data, 3D models, technical drawings, and databooks, generated until the fourth phase of the PLM. Those complex and rich databases didn’t get to the operational phase in the handover of the project, and as such, the operator usually isn’t able to take advantage of the results of all these data if not correctly displayed.
We connect these phases through a cloud-based tool that works along with IoT (Internet of Things) sensors, and tablets used on the field. This way it’s possible to identify and gather valuable data from the material, degradation state, and TAGS of assets in real-time with inputs made on the software platform, improving inspection and maintenance activities.
Vidya’s Digital Twin Software is the junction of the engineering data with the continuous flow of data between the physical model to the digital one and vice versa. It happens thanks to the communication through inputs made from field inspections utilizing a tablet or other sources as IoT sensors into the digital twin, and outputs calculated by machine learning technology, applied with a predictive algorithm.
By doing it, you’ll have the ability to control, manage, and predict asset integrity status, inspection and maintenance operations, according to the life-cycle of the material. It is a major improvement of the industrial process that can save up to 25% of the maintenance budget.
Do you want to know more about our results and how our Digital Twin Platform works?
Download our Digital Twin Portfolio: https://vidyatec.com/forms/technology-portfolio/