Pourquoi les manufacturiers devraient avoir recourt à des jumeaux numériques (article en anglais)

Although not a new technology, digital twins – virtual representations of real-world objects or systems – are crucial in bolstering the Fourth Industrial Revolution. Ranging in scale from a car to a city, constant real-time data and feedback loops ensure digital twins are accurate virtual representations. This allows manufacturers to use them and learn as if they are testing in the real world.

Currently, manufacturers take advantage of digital twins for a wide variety of purposes with the most common focusing on improving the production process or sustainability. Production digital twins can improve manufacturing through cost savings and improved efficiency. These often have positive yet overlooked side effects. The newly efficient operations tend to reduce energy and water consumption, waste and emissions, leading to a smaller environmental footprint. Similarly, while not the primary goal, sustainability-focused digital twins can lead to cost savings and improve efficiency.

Viewing production digital twins and sustainability-focused digital twins as separate entities is a missed opportunity for manufacturers. Failing to incorporate all aspects of production creates an incomplete model. As digital twins mature, manufacturers should incorporate production and sustainability metrics into a single digital twin to obtain the full benefits of the model.

What is a digital twin?

A digital twin can be described as an information mirror model or an exact 3D virtual representation of real-world systems. Digital twins often simulate how a “twin” will fare in a wide range of scenarios, identify operation bottlenecks and compare expected results with real-time production.

Digital twins receive data from various sensors monitoring the real-world twin. In a manufacturing setting, for example, sensors can measure a wide range of information, such as performance outputs (number of holes drilled, energy consumed and so forth) or environmental information (weather conditions, for example). This information is then analysed with the help of machine learning and artificial intelligence (AI).


Pour lire l'article complet : https://www.weforum.org/agenda/2023/05/digital-twins-manufacturing-sustainability/

Retour à la liste des nouvelles