Research

Reliable Design

At the RMO research group, our reliable design approach focuses on the development of computational tools for design under uncertainties as well as the implementation of these tools in industrial applications. The main research challenge includes avoiding a conservative and overdimensioned design using traditional empirical safety factors. Instead, a probabilistic framework is applied taking into account uncertainties with a true-to-nature representation of the stochasticity in loading, material and design parameters.

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Reliable Materials

To ensure reliable materials, we focus on multiscale material analysis and prediction of i.e. defect size and distributions, phase transformations and grain size evolutions during additive manufacturing, welding and sintering. Herein, advanced simulation tools are employed, and a key aspect is to find trade-off between computation time and the level of detail of simulation model. In our research, we combine simulations at different scales with data-driven models to ease the computational burden of multiscale material modelling.

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Reliable Manufacturing

Our research in reliable manufacturing focuses on failure prevention at two different scales. i) Product scale, including predicting product performance and quality through detailed analysis and control of the manufacturing process. ii) Production scale, encompassing production planning with emphasizes on resilience to unforseen events.

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Multidisciplinary Optimization

At the RMO research group, we develop mathematical algorithms for integrating reliability assessment and uncertainty analysis into multidisciplinary optimization. Our aim is to employ a holistic decision supports system integrating reliability, product liftetime and sustainability constraints.

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