RotoAI provides AI‑powered predictive maintenance solutions that keep industrial machinery operating smoothly. Their platform combines vibration monitoring, digital twin and rotordynamic modeling, and FEM/CFD simulations to anticipate failures and reduce downtime, while also offering fatigue testing and custom test‑setup design.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial machinery often suffers unexpected failures due to wear, imbalance, or rotordynamic issues, leading to costly unplanned downtime and shortened equipment life. Traditional maintenance relies on scheduled inspections or reactive repairs, which do not provide early warning of emerging faults.
Solution
RotoAI delivers an AI‑driven predictive maintenance platform that continuously monitors machine health and forecasts failures before they occur. The system fuses real‑time vibration data with physics‑based digital twins and rotordynamic models to generate accurate degradation predictions. Integrated FEM and CFD simulations enrich the digital twin with detailed stress and fluid‑flow analyses, enabling precise identification of fatigue hotspots. Users receive actionable maintenance recommendations through a unified dashboard, allowing them to schedule interventions proactively and extend asset lifespan. The platform also supports custom test‑setup design and provides training modules for rotordynamic analysis, ensuring that maintenance teams can adopt the technology effectively.
Target Audience
Primary customers are maintenance engineers and reliability teams in heavy‑industry sectors such as aerospace, power generation, oil & gas, and large‑scale manufacturing, as well as OEMs seeking to embed predictive analytics into their equipment.
Features
- AI algorithms that analyze vibration signals to predict component failures and estimate remaining useful life
- Physics‑based digital twin creation that incorporates rotordynamic modeling for each piece of equipment
- FEM and CFD simulation tools embedded in the platform to assess structural stress and fluid dynamics
- Automated fatigue testing workflows that generate data for model calibration and validation
- Design and renovation services for custom test rigs and monitoring setups
- Integrated condition monitoring suite with real‑time alerts and trend visualizations
- Training modules for rotordynamic analysis, vibration diagnostics, and predictive maintenance best practices