Skip to main content

Performed within MCP DMCD

The metal-cutting industry faces a quick shift of its market because of altered manufacturing demands and novel societal regulations. To operate in a time of such rapid changes, Sandvik Coromant and Seco Tools have adopted an approach based on digitalisation and smart ma- terials design, which can be done by machine-learning algorithms exploring a digitalised materials database.

SeRC is engaged in a common research programme with the companies, with the goal to reduce the time it takes to develop novel materials from the current 10–15 years to 5–6 years. The SeRC approach implements machine-learning strategies

in search for hard materials, building on quantum-mechanics calculations with density-functional methodology, devel- oping guiding concepts to classify the full materials dataset (big data) into regularised subsets in which machine learning can be utilised to learn hardness.

We use large-scale computer simulations as well as novel calculation and data-man- agement methodologies together with new data infrastructure. With an extensive database utilised by machine learning, we can also handle the challenge that hardness is not the only property required for an efficient cutting tool. Proposed materials are synthesised and carefully characterised in state-of-the-art experiments. Moreover, in collaboration with the companies, we provide industrial verification of their cut- ting-tool performance.

The work has generated both significant insights and new and upgraded products, beneficial in end-user cutting applications. A synergy is that the increased competi- tiveness of the partaking industry Sandvik Cormant and Seco Tools has societal relevance in acting on globalisation and changing demographics.

On the general level, the main impact of our research is a paradigm shift within materials development. We are turning predictive theoretical search into a nat- ural first step of the design process. The project yields scientific breakthroughs and overcomes multiple technological barriers to enable innovation and strengthen the competitiveness of Swedish industry.