FORFING PRESS
Remote predictive maintenance for hydraulic power units
THE NEED _
Our client offers turnkey hydraulic machine and component manufacturing with comprehensive solutions for its customers, from the design of their equipment by the engineering department to manufacturing, assembly, testing, and commissioning. They carry out the entire process, working in sectors such as steel, oil and gas, naval, and hydraulic energy. In an industrial environment involving a product with such high performance and technical and performance specifications, monitoring the equipment for optimal performance is key. The main objectives of the project are the monitoring of two 6kTn forging presses with more than 300 measurement variables for monitoring machine status, process operating data, and data analysis for the deployment of predictive maintenance ranges.
THE ADVANTAGES _
- Detailed 24/7 monitoring of operating parameters and machine status
- Maintain a database of operating variables and facility status to train predictive models.
- Exponential improvement in the responsiveness of technical support services.
- Possibility to develop predictive maintenance plans that generate recurring revenue by establishing long-term relationships.
THE SOLUTION _
In collaboration with the technical department of our client, a joint analysis of the operation signals and sensors of the hydraulic unit was defined. Additional sensors were specified and installed. The data capture strategy, industrial protocols, and telemetry platform were defined, including the installation of a sensor data server. An independent 3G connectivity solution was analyzed and deployed. The functionalities for remote monitoring of the unit were defined: real-time monitoring of the industrial pumps and the entire unit, alarm tracking for each pump and the group, and automatic generation of operation reports for each pump and the entire system. Finally, the predictive models were defined and implemented to monitor the health of each pump, as well as the recommendation model for the next service date.
MONITORING _
A joint strategy was defined for the analysis of signals and sensors of the hydraulic unit, including the installation of additional sensors to ensure coverage of critical variables. The data capture architecture was designed, selecting the appropriate industrial protocols and deploying a dedicated telemetry platform. To ensure secure and autonomous connectivity, an independent 3G communication solution was implemented, separate from the plant’s main system. Additionally, a local server was installed for the acquisition and storage of field sensor data.
REMOTE SERVICE __
Within the remote service layer, real-time monitoring of each pump and the entire hydraulic unit was enabled. The system allows for visualization of the operational status, detailed tracking of individual and collective alarms, and automatic generation of performance reports for each pump and at the global level. These features enable the client’s maintenance team to access the system status from any location, facilitating quick and well-informed interventions.
INTELLIGENCE __
Finally, predictive maintenance models have been developed and implemented to estimate the health status of each pump individually. By analyzing both historical and real-time critical variables, the models can anticipate potential failures and calculate the recommended date for the next intervention, enabling efficient maintenance planning. This intelligence layer represents a qualitative leap in lifecycle management, transforming operational data into actionable decisions.
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