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Unlimited machine uptime – the AI advantage in machine monitoring

An effective and efficient maintenance strategy should prevent unplanned equipment downtime while also limiting the expense of planned interventions. With access to the right information, it's possible to direct maintenance only where it's necessary, thus preventing downtime and limiting maintenance costs.


Unplanned downtime presents significant costs to producers. 20% of total production costs are associated with downtime and inefficiencies. Machine failures alone lower global productivity by 10%. Every single hour of unplanned downtime can incur enormous expenses—in the automotive sector a one-hour breakdown costs about €2.5 million.


At the same time, maintenance to prevent downtime is also a significant cost, accounting for 15-40% of production costs. As preferable as maintenance costs are to the alternative—no production—managing maintenance costs is critical to managing overall production costs.


This session provides a valuable contribution to the AI Manufacturing conference, addressing some of the most urgent topics of our time, including AI, productivity, and operating costs.


Maintenance professionals, manufacturers, engineers, and anyone else interested in the implementation of AI in manufacturing, will learn how data analysis and forecasting work within an AI-assisted predictive maintenance solution to prevent unplanned downtime and reduce maintenance costs. This draws from real-world examples of the solution in use on rotating equipment in multiple industries.


Attendees will also learn:

  • How vibration frequency spectrums indicate machine faults

  • How AI can use that information to estimate the remaining useful life of a machine

  • How machine learning can deliver machine diagnostics


Speakers

Luke Stockburger

AiSight

Project Manager

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