Chalk & Talk Data Science – The health score of an equipment in blind failure prediction
Comparison of anomaly detection models in an industrial context
Application to non-cyclic datasets
Sensor fault detection using machine learning applied on acoustic test bench
Amiral Technologies present its collaboration with Airbus Aircraft on the detection of failures and the use of a dictionary of failures to identify failures seen on a test bench.
Benchmark: comparison of failure prediction models
The prediction of industrial equipment failures connected in blind mode is based on algorithms for detecting anomalies or new features on raw or transformed time series data.
Version 2.2 of DiagFit is now available!
Indeed, in the field, industrial use cases are very varied and many of them do not follow cycles or regular cyclical processes, and therefore require treatment with differently optimized algorithms and feature generators. Mention may be made, for example, of vacuum pumps which only operate when the vacuum must be made and this over a period […]
Predictive maintenance: what is blind failure prediction?
Predictive maintenance in the industry Predictive maintenance “is the asset management practice of repairing an asset or piece of equipment before it fails based on data received about it” (source, IBM). This practice aims to rationalize costs, maintain operational stability and increase profitability by limiting unwanted stoppages. Many companies offer predictive maintenance solutions for industry and position themselves […]
Monitor your industrial equipment in real time and generate a high return on investment
Unplanned downtime is the weak link in the industrial sector. When production lines and machines stop working, manufacturers lose money. These downtimes lead to costly maintenance times. They can be avoided if the machines are monitored in real time. Predictive maintenance can eliminate maintenance overhead by allowing crews to perform maintenance on the fly to […]
How does predictive maintenance have a positive impact on the environment?
Predictive maintenance and its positive impact on the environment New emblem of the industry 4.0, predictive maintenance is a powerful factor of economic performance, but also of environmental performance. Find out how the predictive maintenance market fits brilliantly into the ecological transition. Predictive maintenance is a modern approach to maintenance, based on anticipating breakdowns using […]
Why are Amiral Technologies’ unsupervised learning solutions so powerful?
What is unsupervised learning? Unsupervised Learning is used when no historical data is available that involves past faulty behavior and/or aging progression. Therefore, Unsupervised Learning is mandatory to design data-based alarm system and aging monitoring algorithms in the majority of industrial situations. This is at least true in the current state of data availability and labelling. […]
Understanding DiagFit #2 : a cyclic example
In the previous article, we saw how to recognize a problem containing cyclic data. Now we are going to deal with a concrete case of a problem containing cyclic data. We will use our feature generation software designed for cyclic problems, and observe what gains such a feature generator brings when used in combination with […]
