Michael DeMaria with Fluke Reliability The Industrial Talk Podcast with Scott MacKenzie

Industrial Talk is onsite at Xcelerate 24 and talking to Michael DeMaria, Director, Product Management with Fluke Reliability about "Azima, Vibration AI - 30+ years of historical vibration data".

Scott MacKenzie and Michael DeMaria discussed the importance of predictive maintenance in the industrial sector, highlighting challenges in vibration analysis and the integration of AI. Michael emphasized the role of Azima's vibration analysis software in identifying patterns and faults in industrial machinery, while Scott MacKenzie stressed the critical nature of predictive maintenance and the need for timely decision-making. Both speakers emphasized the importance of simplifying data collection and integrating AI to improve machine health and efficiency. Later, Michael de Maria joined the conversation and highlighted the need for persistence logic and ethical considerations in automation. The speakers discussed the potential of predictive analytics in reducing downtime and the importance of a balanced approach combining AI and human analysis to mitigate risks and ensure effective predictive maintenance.

Action Items
[ ] Interested customers should reach out to Michael de Maria at Azima to learn more about their vibration monitoring solutions.
[ ] Scott will provide Michael's contact information on the industrial talk website so listeners can connect with him.
[ ] Michael will continue engaging with customers to help them optimize asset maintenance using Azima's software and expertise. (Michael DeMaria) [Throughout]
Outline
Industrial maintenance and predictive analytics.
Product manager for Azima shares insights on industrial innovation.
Michael describes their experience working on aircraft carriers and nuclear power plants, highlighting their background in plant operations and maintenance.
Michael discusses their work in developing an automated diagnostic system for vibration analysis, focusing on how the software identifies patterns and faults, and prioritizes actions to mitigate them.
Simplifying vibration analysis for industrial machines to improve efficiency and reduce downtime.
Michael discussed the importance of vibration analysis in predicting machine failure, highlighting the potential for machines to fail quickly without proper maintenance.
Michael and Scott discussed the genesis of vibration analysis, with Speaker 2 explaining how the method was initially unknowingly developed in the 70s and 80s.
Developing a data collection system for non-analysts to quickly capture and send data to analysts geographically diverse.
Michael discusses managing spare parts inventory, highlighting the importance of predicting faults and ordering parts in advance.
Michael trends the development of faults and plans for repairs to minimize downtime and optimize maintenance cycles.
Using AI to analyze vibration data in aircraft maintenance.
Michael emphasizes safety and preparation in maintenance, while Scott MacKenzie highlights data-driven decision-making and human analysis.
Data lake with 100 trillion data points and analyst commentary enables more informed problem-solving and reporting.
Michael: AI can analyze vibration data, but human validation is crucial (12 words)
Human component in AI-driven vibration analysis is important (14 words)
AI and data collection, potential risks and benefits.
Scott MacKenzie: AI tool leverages human knowledge, skills, and directs to right data (0:16:34)
Michael: AI captures data, but uncertainty on what to do with it (0:17:03)
Michael argues that more data doesn't always equal better results.
Using AI in vibration analysis for predictive maintenance.
Michael discusses the importance of AI in predictive maintenance, highlighting its ability to analyze large amounts of data and identify potential issues before they become major problems.
Michael emphasizes the need for human oversight in vibration analysis, as AI can only provide so much insight and may overstate or...