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Texts: Silja Eisto, Maria Latokartano, Metsä Group Photos: Ingimage, Montinutra, Metsä Group
Metsä Board Äänekoski harnesses artificial intelligence Metsä Board Äänekoski has started to use AI-based root cause analysis for visual defects to improve board quality and vision-based condition monitoring for tail threading ropes to decrease unplanned shutdowns. In cases of visual defects on paperboard, technology reduces time needed to locate the origin of process disturbances. Camera techno- logy on the board machine is constantly monitoring the paper- board’s quality. If a visual defect is observed, AI-based root cause analysis commences. The AI analyses 10,000 machine parameters, taking into account process delays to locate the origin of the visual defect. AI-technology has been adopted to avoid unplanned shut- downs caused by breaking of the tail threading ropes. A total of 12 cameras are connected to the AI-based machine vision system, which constantly monitors tail threading ropes. The AI-based machine vi- sion analyses video material, and when the risk of tail threading rope breaking is high, the operators are alerted. This enables the opera- tors to do a controlled replacement of the tail threading rope and avoid unplanned machine downtime.
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