Predictive Maintenance – Industrial Boilers
Consulting
Data Science
Predictive Maintenance – Industrial Boilers
Consulting
Data Science
AI-powered predictive maintenance solution for industrial boilers, combining IIoT data acquisition, cloud analytics, and intelligent alerting.
Yamasoft provided end-to-end technical and business consulting for the design and implementation of a predictive maintenance solution for industrial boilers. The engagement covered IIoT architecture, data acquisition over TCP Modbus, cloud-based data processing, and the application of AI models for predictive analytics. By combining real-time monitoring, historical data analysis, and intelligent alerting, the solution enables early detection of potential failures and optimized maintenance planning.
The client at a glance
| Location
Germany
| Industry
Manufacturing
| Employees
13.8K
| Annual revenue (2024)
€4.4B
What Was The Challenge?
Industrial boiler systems generate large volumes of operational data, but traditional monitoring approaches rely on static thresholds and reactive maintenance. The customer needed to collect and process more than 500 data points per boiler over TCP Modbus while ensuring reliable, secure, and scalable data transmission. Without predictive capabilities, equipment failures could lead to unplanned downtime, increased operational costs, and safety risks. The challenge was to transform raw IIoT data into actionable insights that support proactive maintenance and informed operational decisions.
How Did We Solve It?
Yamasoft consulted the customer about the design of a cloud-based predictive maintenance solution that continuously monitors industrial boilers through automated IIoT data collection. Using AI-powered analytics, the system evaluates more than 500 data points, detects anomalies, and predicts potential failures before critical thresholds are reached. Advanced alerting and notification mechanisms provide timely insights to maintenance teams, enabling proactive interventions. Through full project consulting and delivery—including integration, configuration, and deployment—Yamasoft helped the customer reduce risk, improve reliability, and shift from reactive to predictive maintenance.