Sandvik Coromant challenge: Dynamic recommendations within industrial metal cutting applications

Sandvik is a global, high-tech engineering group providing solutions that enhance productivity, profitability and sustainability for the manufacturing, mining, and infrastructure industries.

Sandvik Coromant is part of the business area Sandvik Manufacturing & Machining Solutions, and provides tools, tooling systems and services that optimize machining operations such as turning, milling, and drilling. These solutions are used in the metal cutting process and are typically found within industrial applications such as automotive, aerospace, and power generation. Services include, for example, logistic solutions and productivity improvement programs.

The challenge to solve

Cutting data recommendations are currently developed by testing a limited number of tools in certain applications. This limitation results in cutting data recommendations which are traditional and static, meaning that customers are not able to gain the full benefits of the tool’s potential.

We are looking to build cutting data recommendations that take into account data models from actual machining conditions and use data analysis and AI to enhance them for a new generation indexable milling tool concept. We are interested in exploring three cutting tool recommendations for customers:

1. Build a system that, with certain inputs, recommends cutting data for specific tools, situations & theoretical results
   Possibility of feeding back “real world" results, including detailed materials description which can be continuously fed into the system to enrich the data.
2. Build AI algorithms to review & recommend cutting data
   Decision-making based on comparisons from similar cutting conditions & the same material (with the possibility of adapting for fixturing and machine condition and evaluating recommendations).
3. Build a community that feels inspired to contribute with real-life data to support continuous product evolution
   Motivate sales resources and customers to actively participate in providing data for the model.

Are you interested in collaborating with us to find a solution?