Digitalized Production planning for Induction hardening

Induction hardening is a fast and energy efficient surface hardening method for steel components, where only the material volume to be hardened is heated by induction and subsequently shower quenched. The component will thus gain increased wear- and fatigue strength.

Today, industrial production planning for induction hardening is solely done by experienced-based trial-and-error. Hence, the purpose of this project is to introduce a more digitized method for production planning, which enables rapid implementation of robust processes for new products and new materials.

The project is organized into three work packages, two of which deal with sub-challenges: 
AP1: to introduce engineering use of finite element analysis (FEA).
AP2: to quantify the input material and then use this data for FEA (AP1) and artificial neural networks (ANN).
AP3: contains the implementation plan, in addition to a pilot study on how to use ANN to connect digitized production data (material, process and performance).