The world’s best mathematics at the tip of everyone’s fingers to solve their product design challenges
We strive to make cutting-edge mathematics, modern software practices and high-performance computing work for you.
Rafinex’s algorithm products include advanced topics such as stochastic topology optimization for designing robust, reliable and safe components in high-performance industries. These robust designs are fit for reality and remain safe even during off-design situations.
A suite of manufacturability analyses help engineers at the earliest design phase to avoid difficult-to-manufacture features and remove late-stage redesigns, thus accelerating time-to-market and drastically reducing costs.
Customized optimization algorithms for composite materials and hybrid structures, which include manufacturability constraints, assist our customers to create innovative products.
We are dedicated to creating advanced numerical models which account for real-life variability using uncertainty quantification methods, allowing safe and profitable usage by everyone in engineering and design.
We are partnering with Rafinex because they are an extremely effective and results-driven software company. The combination of ModuleWorks CAD/CAM technology and Rafinex advanced optimisation algorithms builds an effective bridge between the worlds of engineering design optimisation and manufacturing.Lothar Glasmacher, Head of Additive and Process Technologies, ModuleWorks GmbH
Rafinex is proud to be part of this ambitious endeavor in Luxembourg: MeluXina!Our resident FNR Fellow Dr. Martin Řehoř will be among the first to push the boundaries of the new EURO HPC supercomputer which ranks among the TOP25 hardware globally. Martin’s research interests focus on the development of preconditioning strategies for state-of-the-art non-Newtonian flow solvers in the context of [...]
It’s time for another workout we agreed, so we let loose our optimiser on the tracks running one more extremely short turnaround to get the ECU (‘Electric Control Unit’) into better shape.We unleashed more of the algorithm’s potential to leverage the design space by dropping the various manufacturing constraints. But we were adamant in that we expected unmatched performance of [...]