The five partners EFD (Norway), SSAB, Outokumpu, and University of Oulu (Finland), and WIAS (Germany) propose an EID programme on Mathematics and Materials Science for Steel Production and Manufacturing, where eight PhD projects are jointly carried out, providing a unique interdisciplinary and inter-sectorial training opportunity. The research is focussed on three major topics - induction heating, phase transformations in steel alloys, ladle stirring. Two theses concern hardening: one is the hardening of helical and bevel gears by an optimized single or multi-frequency approach and the other is a novel idea about the hardening of the inner surface of pipes. Two of the theses are related to induction heating applications in the production of high-frequency welded pipes and for pre- and post-heating in the thermal cutting of steel plates. Two theses are concerned with phase transformations during steel production and the final two theses are related to secondary metallurgy in the ladle, optimal alloying strategies and an inverse problem related to stirring efficiency. Despite the fact that most theses projects deal with established processes, they are not fully understood nor fully controllable from a quality point of view. Improved and optimized process control requires quantitative mathematical modelling, simulation and optimization of the complex thermal cycles and thermal gradients experienced by the processed material. Such models require an understanding of the behaviour of the materials from a materials science and phase transformations perspective. Tailored industrial on-site trainings, customized courses in physical modelling and testing of steels as well as numerical simulation of induction heating and flow phenomena combined with scientific research in carefully selected topics on the interface of materials science and applied mathematics will provide the early stage researchers with excellent qualifications to pursue a career in academia or industry.

The process industry is continuously looking for new ways to improve resource efficiency due to high dependence on resources (energy, raw materials and utilities). In large scale production even small changes in using raw materials and in energy can significantly improve process efficiency. The MORSE approach is to adopt new software tools for model-based predictive control, multi-criterial through process optimisation and quality management with overall process coordination. The application of these new software tools will lead to process improvements - reducing the use of raw material and energy while increasing the high quality and production rates. The Morse project aims to further develop and to integrate a set of software tools that have partly already been validated in different process steps in steel industries. These software prototype tools and models were developed and evaluated by six R&D partners of the consortium in collaboration with three process industry partners. With the enhanced Morse tools companies of the process industry will be enabled to optimise the use of raw materials and energy by coordinated prediction and control of resource input and product quality along the entire process route from raw material and energy intake to customer delivery. The mission of the Morse project is to develop model-based, predictive raw material and energy optimisation tools for the whole process route. This approach will be demonstrated in steel industry, to increase yield and product quality in production of high-strength carbon steels, stainless steels and cast steels.