Machine Health Monitoring is complex, frequently changes, and is critical to driving uptime. Navigating the machine health complexity is where the convergence of Technology and People is most important. AI and Advanced Analytics play a part to empowering people, but it isn’t a magic wand. Smart, focused problem solvers who can work with the AI outputs to get actual results in the plant is where the magic happens.

The presentation addresses the root cause of machine failure, technical advancements enabling vital insights, the importance of where people and technology converge, and two real-world examples that share actionable insights to drive continuous improvement.

Takeaways

1. Predictive maintenance is not enough. Only a comprehensive solution can address the complex operational and machine health problems plaguing industry.
2. Catching failures is only the beginning. The true value comes from addressing blind spots in your operations – not catching failures.
3. The Right Data, Right Analysis, and Right Action lead to meaningful insights to make informed decisions.

Jeremy Frank grew up in Pittsburgh, Pennsylvania and developed an early passion for investigating machine health failures through his father’s forensic work with black hawk helicopter crashes. While pursuing his PHD at Penn State University, he started KCF Technologies with Professor Emeritus Gary Koopman and another Penn State researcher. The company focus is to research, develop, and deploy innovative technologies, creating ruggedized commercial products that optimize manufacturing processes. Frank is passionate about advancing American innovation and promotes a culture of entrepreneurship to drive the economy and elevate workers. His goal for KCF Technologies is to reach zero unexpected downtime, zero waste, and zero injuries by 2030 in the industrial and manufacturing sectors.