Scope of Application
Cosmino ConditionMonitor monitors and displays process data which is received in real time by systems and sensors. Cosmino informs the competent employee in case of a violation of individually configurable limits. This minimises downtimes and repair costs and optimises the production process.
The analysis of the recorded data on disruptive factors is also taken as a basis for the transition from purely reactionary maintenance to preventive measures. Moving closer to the ideal maintenance time prevents failures of machines and tools or identifies them more quickly.
Along with the traditional use of process parameters, there is an increasing demand for predictive analyses (advanced analytics). Large and partly unsummarised amount of data are required for Big Data. As the so-called “data lake”, databases are used which are optimised for efficient storage and quick access (e.g. time series databases). Specific applications such as predictive maintenance, smart manufacturing or anomaly detection can then be started through individual “machine learning algorithms”.
A portion of the recorded process parameters is also relevant for traceability.