Reducing Production Defects with Predictive Quality Models

Predictive Quality Models and Advanced Analytics Reduce Production Defects and Expenses

Large Group of Steel & Mining Companies

Location:

Ukraine

Industry:

Manufacturing

Employees:

60,000+

About the Customer:

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

Business Challenge

  • 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
Predictive Quality Models and Advanced Analytics Reduce Production Defects and Expenses - Case Image

Solution

  • 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)

Technologies

SAP ERP logo
SAP ERP
SAP HANA logo
SAP HANA
SAP Predictive Analytics  logo
SAP Predictive Analytics
and many others

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

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