ASTRIIS offers the AStrion platform, a predictive maintenance software for rotating machinery. It uses advanced signal processing and spectral analysis to detect potential defects up to eight months in advance, improving industrial uptime and reducing maintenance costs.
Funding
Funding not disclosed
Founders
Product
Problem
Rotating machinery failures can lead to significant operational downtime and increased maintenance costs. Traditional maintenance approaches often rely on scheduled interventions or reactive repairs, which are inefficient and can result in unexpected equipment failures.
Solution
ASTRIIS provides the AStrion platform, a predictive maintenance software designed for rotating machinery. Leveraging advanced signal processing and spectral analysis, AStrion identifies potential defects up to eight months before they cause failure. This proactive approach enhances industrial process availability and contributes to reducing carbon footprints by optimizing maintenance schedules and preventing catastrophic failures. The system operates effectively without requiring historical data, offering immediate insights upon deployment.
Target Audience
The primary target audience includes industrial sectors that rely on rotating machinery, such as energy, manufacturing, and transportation, seeking to improve operational uptime and reduce maintenance expenditures.
Features
- Advanced signal processing and spectral analysis for defect detection in rotating machinery.
- Identifies faults up to 8 months prior to failure by analyzing the full frequency band.
- Utilizes AI-driven algorithms to categorize and characterize alarms based on physical indicators.
- Extracts non-stationarities and validates sensor data for enhanced reliability.
- Analyzes fine frequency bands for high-resolution defect identification.
- Tracks the evolution of fundamental frequencies and their harmonics.
- Operates without the need for historical datasets, enabling immediate deployment.
- Integrates with standard market sensors for data acquisition.