Industry of the future
Anticipating the evolution of systems life cycles to reinforce industry performance.
Industry’s digital transformation brings new challenges in product design, as well as service and system design, particularly in their production and their life cycle monitoring. IRT SystemX’s objective is to accompany industries towards a circular economy, thus limiting the consumption of resources and energy, while ensuring their productivity.
R & D activities carried out with partners to accompany industries towards a circular economy
- Capitalize on data generated throughout the life cycle to enable the analysis, forecasting and anticipation of behavioural anomalies in products, processes and equipment, allowing therefore an optimized, sober and robust design.
- Digitize processes and standardize exchanges through collaborative platforms for the extended enterprise.
- Connect the physical and virtual worlds by collecting operational data in real time so as to develop digital twins. The objective is to make the best use of products, equipment and infrastructure and to automate and remotely control production or testing processes.
Examples of use cases
- Continuity of the digital chain and collaborative engineering for the workshop of the future and its supply chain in the extended enterprise.
- Detection of heterogeneous weak signals from Internet of Things (IoT) networks for prescriptive maintenance.
- Modelling and optimization of predictive maintenance policies for complex systems.
- Optimization of large multi-physical models and improvement of design margins.
- Evaluation of the performance of cyber-physical systems in the design phase and choice of organic architectures.
- Management of additive manufacturing via machine learning.
Technologies
- Additive manufacturing
- Modelling, simulation and numerical engineering
- Digital model
- Supercomputers
Ongoing R&D projects:
- AMC, Agility and Design Margins
- CAB, Cockpit and Bidirectional Assistant
- CDF, Manufacturing Directive Design
- HSA, Simulation/machine learning hybrid modelling
- I(SC)², Collaborative Systems Engineering of Complex Systems
- MPO, Predictive Maintenance and Optmization
- S2C, Systems Safety & Continuity
- TOP, Topology Optimization Platform
- WAS, Wire Additive manufacturing process Simulation
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