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Cassantec

We know when machines fail!

What is the problem you are solving?
Operating industrial equipment requires decisions about the future under uncertainty (e.g. maintenance scheduling, asset management, operating strategies). The information basis for these future-oriented decisions is usually slim to non-existent. Hence, operators have to rely on experience, gut feeling and simple heuristics. The resulting decisions are not optimal, leading to high risk and cost as well as suboptimal plant availability. Cassantec clsoes that information gap by answering the decision-makers' "when"-questions. Explicit prognoses quantify when to expect which malfunction to occur with which probability over a time horizon of weeks to months, in certain cases even years. The financial benefit of using the better information from Cassantec Prognostics is in the millions, e.g. ~ EUR 35M for a 1.5 GW coal-fired power plant, through lower maintenance cost and higher plant availability.

What is unique about your solution?
Based on advanced AI data analytics, Cassantec Prognostics calculates when to expect which malfunction with which probability. Other than our competition from Predictive Analytics, we don’t only give early warnings, but provide actual explicit timelines until malfunction.
These features cannot be provided by competing technologies currently offered in the fields of asset performance management (APM) and predictive maintenance (PdM). Industrial asset manufacturing, operations and maintenance is predominantly following the paradigm of Mechanical and Electrical Engineering, with deterministic, rule-based approaches, often leveraged by deterministic physical models. Cassantec’s advanced prognostic capabilities however are based on stochastic process modeling and analysis provided through Industrial Engineering and Operations Research. Data-driven machine learning capabilities are based on the latest progresses in Artificial Intelligence and Data Mining.