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This document discuss the use case of SAP HANA combined with SAP Visual enterprise to control Maintenance cost of a Mining Companies.

Why it is necessary to control Maintenance Cost?

Mining is a capital intensive industry. As an average, capital costs represent more than 40 per cent of total mining costs. Cutting cost through an optimized used of this fixed capital is definitely easier than optimizing the efficiency of labor.

The ultimate objective of the maintenance function is to provide competitive advantage by increasing the efficiency of maintenance actions and increasing reliability and availability of equipment through effective strategies, planning and continuous improvement. High levels of equipment reliability and availability improve product quality and delivery performance, reduce asset intensity, and also reduce direct operational and maintenance costs.

To achieve excellence in maintenance requires the following:

  1. Maintenance goals and objectives set to suit the business
  2. A strategy to achieve those goals and objectives
  3. A system to measure and manage the maintenance function
  4. The right resources

(See the attached file)

What is Predictive Maintenance?

Predictive maintenance is a holistic way of maintenance of all the assets. It helps to determine the condition of all available equipment in order to predict when maintenance should be performed. This approach offers cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted.

The main value of Predicted Maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures. The key is "the right information in the right time". By knowing which equipment needs maintenance, maintenance work can be better planned (spare parts, people etc.) and what would have been "unplanned stops" are transformed to shorter and fewer "planned stops", thus increasing plant availability. Other advantages include increased equipment lifetime, increased plant safety, fewer accidents with negative impact on environment, and optimised spare parts handling.


Despite of collecting rich data, decision-making frequently remains reactive rather than predictive. Many mining companies still have only limited visibility into key performance metrics and struggle to track indicators such as mine contractor activity, costs associated with operations and maintenance and ore movements at different stages of the production cycle.

With SAP HANA, It will be possible to push data from operational systems like SCADA, PLM etc  into the HANA database, and perform real-time analysis to detect and trigger repair or schedule maintenance. This will benefit in following ways:

  • Reduction of maintenance costs due to predictive analysis capabilities ensures that maintenance is only performed when warranted
  • Increased Operational efficiency due to increased equipment availability thereby reduction in Cost of production.
  • Increase in Planned Maintenance will improve production planning and provide better control over Cash Flow.

How SAP Visual Enterprise can be used in Predictive Maintenance?

SAP Visual Enterprise Viewer works in 3D  with SAP Visual Enterprise you could use the capabilities to see 3D data in a dashboard for supply chain analysis, engineering performance, and factory workflows.

Combined with SAP HANA it allows you to better view of your analytics data by allowing 3D view of your equipment so that it will be possible to understand you data more meaningful analysis of your data. (Please visit you tube video link reference point no 4 for a demo on how it works)



To know more about SAP HANA visit following link


To Know more about SAP Visual Enterprise visit following link:


Please Note:-

Although I have tried to verify all the correctness of contents given in this document.Please let me know if there is any errors or misstatements or any exaggeration  from my side regarding SAP HANA or SAP visual Enterprise or otherwise.Any suggestions on how can i improve this article are warmly welcomed.

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