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Predictive Quality Models and Advanced Analytics Reduce Production Defects and Expenses

Client: Large Group of Steel & Mining Companies
Industry: Manufacturing
Location: Ukraine
Size: 60,000+ employees

Our customer

An international group of steel and mining companies with USD 9 billion revenues.

Business Challenge

  • Working on the development of predictive quality models, our data scientists faced the problem of poor quality of exported data (incomplete, insufficient, etc.) needed for training a model.
  • Additional time and efforts were spent for cleansing and preparing data for predictive modelling.

How we helped

  • 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)

Business Value

  • 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

Technologies

  • SAP Predictive Analytics
  • SAP HANA
  • SAP Data Services
  • SAP BI
  • SAP ERP

Download Case Study in PDF format