Predictive optimisation: AVEVA integration for efficient maintenance in industry


The customer is faced with unplanned machine downtime during the production process and high maintenance costs (machine damage and low energy efficiency).
With this project, the customer wanted to reduce and avoid unplanned downtime in their factory as much as possible.
Our solution with the implementation of the AVEVA system is based on maintenance prediction and centralised tag management to strengthen the operability and extend the service life of the equipment.


Reduce unplanned downtime

Optimising the operability and extending the life of critical equipment

Centralised data management

Strengthening the overall efficiency of the factory

Project procedure

1. Initial phase

Critical equipment is identified and key parameters are defined. 

3. Testing phase

The accuracy of the system is validated and adjustments are made to thresholds and algorithms.

2. Implementation phase

AVEVA is configured for real-time monitoring and predictive algorithms are developed. Tags are integrated into AVEVA for efficient connectivity.


The result is a fully operational, centrally managed, real-time system with informed and proactive decision making in the industrial environment.

Reduction of machinery maintenance costs by


Improvement in product quality by



  1. Industry.
  2. Any sector where machinery is used in the production process.

Technologies used




Microsoft SQL Server

Other use cases

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