About the Customer:
An international group of steel and mining companies with USD 9 billion in revenues.
- More effective quality management system and corresponding production maintenance tool is needed. It’s better to predict the defects in production or malfunctioning of the equipment on a base of statistics and current production data, rather than just wait for the real fail
- Incomplete, insufficient historical and current data or its poor quality not allowed customer’s analysts to build effective predictions and modeling.
- Additional time and efforts were spent for the cleansing and enrichment of the needed data before our data scientists started the predictive modeling
- Established advanced analytics infrastructure and customized models for the quality prediction in casting stainless steel slabs
- Built visually rich reports on the probability of slab defects based on the product parameters (steel grade and gauge of sheets)
- Reduced a number of defects, which potentially result in additional 250-300 of steel sheets per month for separate kind of steel grade
- Decreased costs for defects detection
- Improved decision-making and the manufacturing efficiency
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