Digital twins, we’re talking about virtual cloning now?
Technological advances continue to advance at a frantic pace, paving the way for increasingly innovative and transformative concepts. Among these, the "digital twins" are emerging as a promising digital revolution.
What it is, how they work, their interest and their implementation, with a focus on concrete cases in progress.
What is a digital twin?
A digital twin is a virtual representation of an object, a system or even a real process. It is essentially a digital copy, fed by real-time data from the entity it represents. Whether it’s a manufactured product, a building, or even an entire city, the digital twin offers faithful virtual reproduction, allowing constant monitoring and in-depth analysis.
How do it works?
Digital twins work through a combination of technologies such as the Internet of Things (IoT), artificial intelligence (AI), and 3D modeling. Sensors embedded in real objects collect data in real time, which is then transferred to the digital twin.
AI analyzes this data, allowing the digital twin to accurately reflect the current state of its physical counterpart.
Digital twins start by collecting data from sensors embedded in the real objects they represent. These sensors collect information such as environmental conditions, performance, movements, etc.
Then, the collected data is then transmitted in real time to the digital twin, usually via technologies such as the Internet of Things (IoT) or dedicated communication systems.
Once the data is received, the digital twin uses 3D modeling techniques to create an accurate virtual representation of the real object. This modeling can be complex, ranging from simple reproductions to highly detailed models.
AI comes into play to analyze data from the digital twin. This analysis can include trend detection, prediction of future performance, scenario simulation, and even decision-making based on intelligent algorithms.
The digital twin provides real-time feedback on the state of the real object. This feedback can be used to make informed decisions, optimize performance, prevent breakdowns, and facilitate long-term planning.
Objectives of Digital Twins:
One of the main goals of digital twins is to optimize the performance of real objects. This can include improving operational efficiency, reducing downtime and optimizing processes.
Problem Prevention: By monitoring real-time and analyzing data, digital twins aim to prevent potential problems before they become critical. This allows predictive maintenance and reduced costs associated with unplanned outages.
Digital twins are also used to simulate various scenarios, allowing companies to test potential changes, anticipate consequences and adjust strategies accordingly.
And what does it say in terms of costs? By optimizing operations, preventing outages and facilitating planning, digital twins help reduce operational and maintenance costs.
By providing an accurate virtual representation of reality, digital twins improve decision-making by allowing stakeholders to have a complete and updated view of the situation.
They also promote continuous innovation by offering a virtual field to test new ideas, concepts and technologies, without risking negative impacts on the real world.
The interest of the Digital Twins to summarize?
The interest of digital twins lies in their ability to improve decision-making, operational efficiency and the prevention of potential problems. By monitoring in real time, companies can anticipate failures, optimize performance, and reduce maintenance costs. This applies to various sectors such as manufacturing, logistics, healthcare, and even urban planning.
What is the link with VR and immersive learning?
Digital twins share a natural affinity with virtual reality (VR) and immersive learning, creating a bridge between the virtual world and the real world. VR offers an immersive platform that allows users to interact directly with the digital twins, making the experience more visual, interactive and engaging.
By combining digital twins with VR, professionals can virtually enter simulated environments that faithfully reproduce real-life situations. For example, in the field of health education, surgeons can perform complex procedures in a virtual environment based on anatomical digital twins.
Immersive learning associated with digital twins allows for more interactive training. Users can virtually manipulate objects, simulate processes and receive real-time feedback, enhancing hands-on learning.
Professionals can use VR to virtually navigate through digital twins, viewing operations and processes in an immersive way. This facilitates understanding of complex systems and identifies ways to optimize performance.
The combination of digital twins and VR also facilitates remote collaboration. Geographically dispersed teams can virtually connect to shared digital twins, enabling real-time collaboration for complex projects.
VR provides a personalized learning experience by allowing learners to explore digital twins at their own pace. This promotes a better understanding of complex concepts and stimulates engagement. The integration of digital twins with VR and immersive learning opens new perspectives for exploration, learning and innovation. This synergy creates an environment where the boundary between virtual and real is blurred, paving the way for innovative applications in training, simulation and in-depth understanding of complex systems.
Examples of Digital Twins projects ?
In Europe, the adoption of digital twins is booming. From manufacturing companies to utilities, many entities are exploring the benefits of digital twins.
In France, the National Directorate of Digital Uses works in partnership with ENSAM, CESI and CEA on an innovative project to develop and use digital twins as part of the training of engineers: the JENII project (Immersive and Interactive Digital Teaching Twins).
This project, led by the CNAM, allows researchers and learners to experiment and train themselves face-to-face and remotely, in their field, through immersive experiences (virtual reality).
Cnam’s Chimie-pharma and Agroalimentaire teaching team is the first to have paved the way for digital twins and is currently closely followed by the automotive, aerospace and nuclear sectors.
Other examples 👇
Aerospace Industry
Predictive Maintenance: In aerospace maintenance, digital twins help predict potential component failures, enabling proactive maintenance planning and minimizing downtime.
Industrial Manufacturing
Production Line Optimization: Digital twins are used to create virtual factory replicas, allowing managers to simulate and optimize production processes to maximize efficiency.
Quality Control: Digital twins are used to compare real products with their virtual models, facilitating early defect detection and ensuring high quality standards.
Health
Assisted Surgery: In medicine, digital twins are used to create accurate models of organs or body parts, allowing surgeons to simulate complex procedures before actually performing them.
Patient Tracking: Digital twins facilitate real-time patient tracking, allowing healthcare professionals to make decisions based on accurate and up-to-date data.
Energy
Power Grid Management: Digital twins can model power grids, enabling intelligent power distribution management, rapid fault identification and efficient integration of renewable energy.
Facility Maintenance: In the field of energy, digital twins are used for real-time monitoring of facilities, allowing predictive maintenance and maximizing the life of equipment.
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