Finanzauto incorporates maintenance systems and reduces costs by incorporating J1939 communication protocols
+55%
Reduction of additional expenses
x2
Optimization and efficiency in maintenance
Client
Official distributor of Caterpillar in Spain, global leader in earthmoving machinery and energy solutions.Finanzauto seeks to optimize the monitoring of its engines and generators through the implementation of an intelligent platform that integrates advanced communication with its industrial assets, ensuring efficiency, reliability, and reduced operational costs.
Challenge
Implement a centralized system capable of monitoring all engines distributed across their generators, integrating J1939 communication protocols to enable direct asset connection to Dragsa via a CAN network.The goal was to reduce costs associated with the use of additional hardware for data collection without compromising reliability or monitoring quality.
Problem
- High dependence on intermediary equipment: Communication between the engines and control systems required additional devices, increasing installation and maintenance costs.
- Lack of integration of standard protocols: The absence of the J1939 protocol hindered direct communication with the engines, limiting traceability and monitoring efficiency.
- Difficulty interpreting operational data: Existing systems could not natively process the information generated by the engines, reducing analysis capabilities and fault prediction.
- High operational costs: Frequent maintenance needs and limited digitalization increased operational expenses and slowed incident detection.
Solution
How we do it?
The integration of Dragsa was carried out as an advanced monitoring platform with native support for the J1939 protocol, enabling direct communication with generators through the CAN network.- Full integration without additional hardware: Dragsa interprets and digitalizes engine data without requiring modifications on the client’s side, optimizing installation and reducing costs.
- Intelligent and predictive monitoring: The platform processes operational data in real time, enabling early detection of issues and prediction of mechanical failures.
- Advanced data and alarm management: Data export systems, interactive control panels, and a customizable alarm manager were incorporated, ensuring more agile and precise supervision.
Results
Significant reduction in installation and maintenance costs. Increased early detection of errors and potential engine failures.Optimization of predictive maintenance, reducing unplanned downtime.
Complete digitalization of the monitoring system with access to dynamic, configurable dashboards.
Greater operational efficiency and comprehensive control over energy assets.