How AI is optimizing factory maintenance – Part 1

By Spencer Acain

When operating a factory, one of the major goals is to minimize issues, downtime, or anything else outside the status quo and ensure smooth operation. However, this is easier said than done, as all machines require maintenance and must contend with unforeseen failures. Predictive maintenance is emerging as a powerful tool that leverages AI and machine learning to better understand when and where maintenance is required to minimize downtime and preemptively handle issues before they become catastrophic.

In this episode, host Spencer Acain is joined by Dr. James Loach, Head of Research for Senseye Predictive Maintenance, to explore the unique approach Senseye is taking to the problem of keeping factories running as smoothly as possible.

In this episode you will learn:

  • What is Senseye (2:40)
  • Senseye as a decision support system (4:30)
  • How AI brings flexibility and scalability to predictive maintenance (11:04)
  • Monitoring operations vs. looking for failures (13:13)
James Loach

James Loach

Head of Research for Senseye Predictive Maintenance

Spencer Acain

Spencer Acain

Technical Writer for Global Marketing at Siemens Digital Industries Software

AI Spectrum Podcast

AI Spectrum

This podcast features discussions around the importance of AI and ML in today’s industrial world.

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This article first appeared on the Siemens Digital Industries Software blog at https://blogs.sw.siemens.com/podcasts/ai-spectrum/how-ai-is-optimizing-factory-maintenance-part-1/