Analytics by RMG
The functionality of the devices and the associated higher complexity increase with each generation of devices. At the same time users‘ expertise is dwindling. The willingness to keep the number of experienced employees available is decreasing. When new positions are filled, there is a growing gap in experience in dealing with the various devices.
Probably the strongest requirement to the measuring devices is the security of their availability, ideally paired with an early warning if there is a need for interaction with the devices or even for service calls. It can be assumed that the devices operate within the limits (or better) permitted by calibration law.
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The AI-Analytics approach consists in recognizing errors or limits. The algorithm is constantly working on its own improvement. Learning is just as important for the skills of AI-Analytics as the „training“. This is decisive for the level to which the system can develop.
The AI system Drift-Monitor is based on such an AI algorithm and is used to monitor the status of devices of the types ultrasonic gas meters and process gas chromatographs. The goal is to notice upcoming changes and deteriorations as early as possible, even before the error limits are exceeded.
The display of the implicit status using traffic light logic for each individual device on the control room terminal is transmitted by the Drift-Monitor every time the status changes. The AI system Drift-Monitor is available as on-premises (on site) or as a cloud installation. The definition of on-premises refers to the use of the company's own servers and its own IT environment. However, if the variant “Software as a Service” (cloud model) is chosen, the data is kept on the provider's system. The cloud solution has advantages in terms of maintenance and operational responsibility. The AI algorithm can also learn from error cases that occur at other customers, although the data is strictly separated. Only the algorithm learns. All aspects of the privacy policy are followed.
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Analytics by RMG
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