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  • PREDICTIVE MAINTENANCE

    Predictive Maintenance helps the end-users to increase their assets’ availability and reliability in a new, innovative way and is the next move in asset maintenance when the typical reactive, condition-based or preventive maintenance routines are not sufficient and no longer cost-effective for organizations.

Extending an asset's availability and reliability with predictive maintenance

Today's primary challenge is not only to react to the asset failure but to foresee when the service needs to be done or when the failure is expected to appear. This preventive oriented maintenance strategy with early detection of asset conditions helps to save companies a lot of time and money.

The Predictive Maintenance solution enables the users to collect the wear, conditions and usage information, generate statistical and predictive models based on the gathered data and integrate the result into the asset maintenance process.
 

Layers of the Predictive Maintenance solution 

Our solutions offer a wide range of tools which make it possible to move an organization to the next level in the asset maintenance maturity model.

  • Analytics Layer
  • Reporting Layer
  • Integration Layer
     


Preventive Maintenance Solutions 

The Preventive Maintenance solution is built on the underlying platform IBM Preventive Maintenance and Quality and utilizes IBM’s software products like IBM SPSS, IBM iLOG, and IBM COGNOS BI and it can be can be integrated directly into Enterprise Asset Management system IBM Maximo.  

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BENEFITS OF PREDICTIVE MAINTENANCE

  • Reduced asset downtime (higher asset availability)
  • Optimised production processes due to the minimized risk of assets failure
  • Improved productivity of maintenance resources
  • Reduced cost of asset failure and overall cost of asset maintenance
  • Enhanced services for customers due to improved asset reliability

CONNECT WITH OUR SPECIALIST

Talk to one of our solution specialists and get a better sense of the scope of our work, timing, and our process.

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