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The EnCORE project focuses on developing advanced deep learning algorithms for predictive maintenance in manufacturing. By utilizing normal machine data, it aims to enhance prediction accuracy and reduce unplanned downtime, ultimately benefiting industries like Food & Beverage and Consumer Goods.
In the manufacturing sectors, the traditional planned maintenance approach is no longer viable, as it cannot cope with the ever-rising complexity of production systems.
This pressing problem hurts industry’s profitability, and unplanned downtime costs industrial manufacturers €43 billion per year.
This pressing problem has fuelled the growth of the predictive maintenance market.
Currently, predictive maintenance solutions employ typical machine learning approaches based on monolithic rule-based…
CORE INNOVATION AND TECHNOLOGY OE
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