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.

Executive Summary

Goal: Make accurate data-based predictions to identify production defects and equipment malfunctioning.

Solution: Predictive analytics infrastructure and models for quality prediction.

Benefits: The client now has access to an insight-driven analytics solution that predicts quality in stainless steel slab casting and generates reports on defect probability.

Services delivered: Predictive Analytics & Advanced Analytics development.

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

Business Challenge

  • The client needed a more effective quality management system and corresponding production maintenance tool. It’s better to predict the defects in production or equipment malfunctions based on statistics and current production data rather than simply waiting for the real failures.
  • Incomplete, insufficient, or poor-quality historical and current data prevented the client’s analysts from making effective predictions and modeling.
  • Additional time and effort were spent on cleansing and enriching the needed data before our data scientists started the predictive modeling.

Solution

  • Established advanced analytics infrastructure and customized models for quality prediction in casting stainless steel slabs.
  • Built visually rich reports on the probability of slab defects based on the product parameters, such as steel grade and gauge of sheets.

Technologies

SAP ERP logo
SAP ERP
SAP HANA logo
SAP HANA
SAP Predictive Analytics  logo
SAP Predictive Analytics

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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