Intelligent predictive maintenance platform for Finanzauto’s marine engines
Company
Finanzauto, the official Caterpillar distributor in Spain and a global leader in earthmoving machinery and power solutions, sought to evolve its previous digitalization project. Previously, Surcontrol had digitized their engines and generators through direct J1939 communication and advanced monitoring.
The current objective was to anticipate failures, detect anomalous behavior in real time, and manage the full maintenance cycle predictively and in a unified way.
Challenge
Develop an advanced system combining automatic analysis, configurable rules, and predictive models to detect operational anomalies in marine engines.
The platform needed to identify periods of stable operation, compare them with new operating cycles, and issue intelligent alarms whenever significant variations occurred.
Problem
- Reactive maintenance: Engines were only serviced after reaching fixed usage milestones, without considering actual operational behavior.
- Difficulty predicting early failures: Early anomalies, such as increased RPMs or deviations in critical parameters, were not detected in time.
- Lack of a unified system: Manual alarms, schedules, and inspections were scattered across different tools and channels.
- No visual customization: Finanzauto required a platform aligned with its visual identity to offer it to its own users.
Solution
How we do it?
Surcontrol developed a complete predictive maintenance platform based on intelligent analysis of real engine data and centralized operational management.
- Advanced anomaly detection: The system identifies stable operating periods, compares them automatically, and generates alerts when unusual deviations occur.
- Predictive alarms based on actual behavior: Notifications are not solely based on hours of use—they respond to RPM spikes, abnormal parameters, or early indicators of wear.
- Optimal operation models: The platform evaluates current engine behavior against manufacturer reference curves to detect progressive degradation.
- Manual and automatic analysis modes: Technicians can configure specific rules or allow the system to detect anomalies autonomously.
- Custom branding and theme editor: A visual manager was developed so Finanzauto can adapt colors, logos, and overall platform style without altering the software.
- Integrated CMMS: A centralized management module shows active alarms, completed inspections, upcoming tasks, maintenance history, and complete engine cycle planning.
Results
- Early detection of failures and degradation before affecting performance
- Maintenance based on actual usage rather than preset hours
- Automatic and predictive analysis of engine behavior
- Customizable platform with Finanzauto branding
- Unified system for managing alarms, tasks, and inspections
- Increased operational reliability and reduced downtime