What can physics teach us about machine health in manufacturing? Joining us today to unpack this question is Mica Rubinson, a physicist with a PhD from the Weizmann Institute of Science. She currently serves as the algorithms lead for Augury, a company providing AI-driven insights into machines, processes, and operations in manufacturing. We sit down to discuss her transition from physics and neuroscience to working in AI, and how her background has informed her understanding of complex systems and improving machine health algorithms.
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Mica shares the methods behind Augury’s fault testing processes, why they use the highest quality data available, how in-house experts help them filter their data reliably, and their approach to communicating with customers. Our conversation also explores the balance between edge computing and cloud computing, and why both are necessary for optimal performance and monitoring.
Key Points From This Episode:
“We look for better ways to adjust our algorithms and also develop new ones for all kinds of faults that could happen in the machines catching events that are trickier to catch, and for that we need highest quality data.” — Mica Rubinson [0:08:20]
“At Aubrey, we have internal vibration analysts that are experts in their field. They go through very rigorous training process. There are international standards to how you do vibration analysis, and we have them in-house.” — Mica Rubinson [0:09:07]
“[It’s] really helpful for us to have [these] in-house experts. We have massive amounts of records – signal recordings from 10 years of machine monitoring. Thanks to these experts [in] labeling, we can filter out a lot of noisy parts of this data.” — Mica Rubinson [0:10:32]
“We quantify [our services] for the customer as their ROI [and] how much they saved by using Augury. You had this [issue, and] we avoided this downtime. [We show] how much does it translates eventually [into] money that you saved.” — Mica Rubinson [0:22:28]
Links Mentioned in Today’s Episode:
Augury
Weizmann Institute of Science