Technology > Background
The empirical basis of our technology:
The computational solution underlying our technology is fed by two sets of asset data:
- A set of asset-specific historical condition and process data, typically including thermal, vibration, and lubricant analysis results. If condition data is insufficient or not archived at all, we may be able to provide comparable condition data from identical asset models.
- A complete set of up-to-date condition and process data downloaded from the asset. Condition data updates are necessary for automated updates of the Prognostic Report.
The explicit remaining useful life (RUL) prognostics provided by our Prognostic Report allow effective evaluation and optimization of maintenance schedules, triggering a next generation of prognostic maintenance capabilities. Our computational solution allows numerous additional simulations, sensitivity analyses, and statistical tests to ascertain the robustness of our diagnostic insight, prognostic foresight, and recommendations.
What is the basis of our technology?
Our proprietary protected, technology rests on 3 pillars:
- A prognostic computational solution. This solution is based on a novel and unique combination of established best-practice approaches, tools, and techniques from operations research, artificial intelligence, and data mining, all validated in industrial applications. In particular, the solution combines advanced Markovian and Bayesian techniques to determine condition parameter trends, malfunction risk profiles, and remaining useful life (RUL) of critical industrial assets.
- A structured and validated configuration process. This process allows us to adjust and apply our computational solution to critical industrial assets, related malfunction scenarios, and available condition and process data of different asset operators in our target industries.
- A convenient and operator-oriented operational integration of our Prognostic Report. This includes in particular an automated data download and transfer capability, which continuously or periodically transfers the specified condition and process data from the asset's condition sensors and process data logs to our prognostic software. This minimizes the operational effort for operators, and helps to focus on the pure content of the Prognostic Report provided.
Cassantec's proprietary technology rests on three pillars, allowing application of a computational solution fed by asset-specific empirical data through an initial configuration process and an eventual operational integration. Through this integration, our reporting solution yields a strong set of unique, differentiating features: It supports an end-to-end solution linking condition monitoring to maintenance scheduling and asset management, providing explicit quantitative relationships between condition parameters and malfunction risk.