SAP > Case Studies > Predictive Maintenance case-studies from Minerals Industry

Predictive Maintenance case-studies from Minerals Industry

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 Predictive Maintenance case-studies from Minerals Industry - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Enterprise Asset Management Systems (EAM)
  • Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
  • Mining
Applicable Functions
  • Maintenance
Use Cases
  • Predictive Maintenance
About The Customer
A large iron ore mining company in Australia
The Challenge

To develop a reliable and integrated asset management platform:

The objective of the platform was to support condition-based monitoring in order to keep in check the asset’s health, predict failure or breakdowns and ensure proactive maintenance decision-making on the basis of the historic data.

The Solution

The implementation of this method of proactive maintenance was done by Advisian through specific software installation and configurations for condition-based monitoring.

Advisian successfully completed successful integration of SAP PM (predictive maintenance) which is a functional module to manage equipment on the production floor.

They also developed a maintenance strategy for their clients, which helped them achieve health and performance monitoring for critical mine processing equipment.

Data Collected
Equipment Status,
Operational Impact
  • [Cost Reduction - Maintenance]

    The evident outcomes resulted in a cost efficient predictive maintenance approach

  • [Efficiency Improvement - OEE]

    A significant reduction of equipment downtime

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