What percentage of manufacturing organizations already use digital twin? When did they adopt it? What do they use it for? This article answers these questions and more. Read More
In this infographic, discover how manufacturing teams can build toward alignment and eliminate internal misunderstandings, disconnects, and departmental silos. Read More
Improving lifetime value of a fusion powerplant using a physics-based digital twin. Assystem is an international engineering and digital services group focused on low-carbon projects that accelerate the transition to clean energy. Assystem is committed to the development of decarbonized electricity (fusion energy, renewables and electricity grids) and clean hydrogen. The Assystem team wanted to leverage the expensive design models to create a digital twin by inputting the sensor data that was livestreamed from the plant, which helps engineers understand the plant’s structural integrity and further optimize inspection and maintenance schedules.
As a key to growth in the coffee machine industry, innovation has always been a core pillar of Gruppo Cimbali’s company philosophy. Investing in the research and development of high-performance machines is a strategic decision, and Gruppo Cimbali is proud to be recognized as one of the first companies in the sector to expand into telemetry, Internet of Things (IoT), and Wi-Fi connected machines. To continue to deliver on its innovation promise, the company now applies digital twins – utilizing Altair Activate® – to their development processes enabling it to design better products, shorten development times, and increase energy efficiency.
Sheet Metal Forming has different and wide industrial applications (Automotive, White Goods, Aeronautic, etc....). In the metal forming industry, the simulation of processes and the resulting material behavior is of high importance. Important process parameters (e.g., material flow, temperature range, force required), as well as the resulting material characteristics (e.g., strength, residual stress, temperature resistance), can be supported using FEA to replace costly and uneconomical practical tests. The re-use of knowledge gained from these FEA simulations in combination with data provided by different sensors is the next step towards the implementation of a Digital Twin. Its integration into the IT architecture of a digital factory is inevitable to increase the efficiency and environmental sustainability of processes and products in manufacturing. Therefore the presented project relies on Reduced Order Models in use of Machine Learning approaches as well as an IoT-based dashboard for the combined visualization of actual data and derived KPIs. As a result, the implemented solution enables significant improvement of capabilities in the considered context.
Digital twins help organizations optimize product performance, gain visibility into the in-service life of a product, know when and where to perform predictive maintenance, and how to extend a product’s remaining useful life (RUL). The Altair digital twin integration platform blends physics- and data-driven twins to support optimization throughout the products lifecycle. We take a complete, open, and flexible approach that enables your digital transformation vision on your terms.