Features

INTEGNANCE TR addresses key challenges in plant operations—uncertain failure occurence timing, inconsistent sensor data formats, high downtime due to reactive maintenance and so on by leveraging AI-based failure prediction and centralized data management.

1. AI-driven failure prediction: Generates individual prediction model(s) for each machine to accurately identify failure occurence timing and optimize maintenance schedules
2. Sensor-diagnostic data integration: Collects and analyzes diverse time-series data (vibration, temperature, sound, etc.) using machine learning, converting raw measurement data into actionable insights
3. Web-based centralized monitoring: Enables unified management of rotating equipment with easy browser access at anytime and from anywhere
4. Automated notifications: Screens high-risk equipment and sends alerts to maintenance personnel via email or SNS for prioritization
5. Integration with INTEGNANCE VR: Visualizes analysis results and sensor data in VR, enabling collaborative maintenance planning with partner companies
6. One-stop service: INTEGNANCE TR offers a comprehensive solution, covering everything from sensor selection and on-site installation to AI algorithm development and application deployment for the client—all in a single, integrated service.

Details

INTEGNANCE TR improves plant reliability and availability by shifting from reactive to predictive maintenance mode. It uses AI algorithms to detect early signs of failure across multiple rotating machines, regardless of sensor type. The platform supports remote monitoring, standardizes inspection workflows, and connects with INTEGNANCE VR for immersive visualization and collaborative decision-making. Maintenance recommendations and alerts are automatically generated based on risk screening, reducing downtime and optimizing resource allocation.

Achievements and examples

JGC has implemented INTEGNANCE TR at an oil refinery in Japan. The system is currently monitoring 800 pieces of rotating equipment at the site.

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