Predictive optimisation: AVEVA integration for efficient maintenance in industry
problems
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.
Objectives
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.
Results
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
+30%
Improvement in product quality by
+40%
Sector
- Industry.
- Any sector where machinery is used in the production process.
Technologies used
AVEVA
RapidMiner
CSV
Microsoft SQL Server
