RawMatStat - Expert system for evaluating process data in the recycling of scrap metals

Important results from the project

A circular economy requires efficient recycling of materials to minimize resource consumption and process emissions. RAWMATSTAT aims to support scrap-based plants with follow-up on raw material, production practices and production. Today´s system gives the process management a good overview of the raw material analyses, deviation from steel recipes and the quality of the recipes. Additional functions will be added in future releases.

Expected long term effects

The information that RAWMATSTAT delivers is expected to lead to: - informed decisions about raw material purchases - high quality of input data for optimization of recipes with RAWMATMIX - good basis for decisions on optimization of recipes - good basis for follow-up of loading against charge recipes Eventually the increased precision is expected to lead to: - reduced raw material costs - reduced quality deficiency costs - reduced emissions (scope3) due to increased utilization of alloying substances in scrap

Approach and implementation

Seven areas for improvement were set up: Raw material knowledge, Recipe quality, Loading accuracy, Timing, Weight precision, Slag quality and Carbon Fotprint. All areas were studied and the first three were selected for implementation in the first version. A system was then created that allows both interactive ad hoc analysis of individual raw materials, recipes and products as well as generation of reports for a certain period of time where all raw materials, recipes and charges are analyzed in a way that areas for improvement are highlighted. System is now ready for verification.