The high cost of developing new steels is a consequence of poor simulation capabilities, forcing the developers to adapt trial-and-error. Ferritico provides machine learning based prediction software, enabling prediction of steel mechanical and thermodynamical process properties and reducing time-to-market and cost for developing and optimizing steel.
Finite Element Method (FEM) software helps steel application designers simulate the mechanical performance of steels in their final assembly and hence, to chose what steel to use. Ferritico simulates extended steel data sets to be consumed by FEM software which implies improved FEM simulations and less trial-and-error during design.
Ferritico develops machine learning models for steel manufacturing processes, enabling process optimization and eventually automation capabilities. The models combine generic steel prediction models with customized models considering local process environment variables
Steel components are post-processed, e.g. to improve look-and-feel characteristics and durability, e.g. heat treatment and surface plating to manage corrosion. Ferritico provides simulation of post-processing effects to avoid expensive trial-and-error.