The goal from day one was clear: build the definitive source of industrial reliability knowledge, and open it up to empower teams everywhere to shift from reactive troubleshooting to proactive control.
The Library of Machine Malfunctions and Changing the Factory-Worker Relationship
Artem Kroupenev, VP of Strategy | Augury
Tell us about yourself and your role with Augury.
As VP of Strategy at Augury, I thrive at the intersection of technology, manufacturing, and business transformation. My role is about connecting Augury’s pioneering machine health technologies with the needs and ambitions of manufacturers worldwide. By listening closely to our customers and analyzing the manufacturing landscape, I help shape our vision, guide product direction, and ensure we're always delivering impactful solutions—solutions that not only prevent downtime, but also help production leaders unlock new sources of value across their operations.
Tell us about the library of machine malfunctions? How did this idea come about and why did you decide to publish this?
From the very beginning at Augury, we recognized that bringing AI—and specifically machine learning—to industrial diagnostics would demand something unprecedented: a vast, highly accurate dataset of real machine readings from operating factories. Vibration analysis had a strong theoretical foundation and some established standards, but those standards simply weren’t robust enough to deliver accurate diagnostics across the diverse reality of thousands of machine types and use cases found in manufacturing environments.
We started our journey with a handheld data collection device, immersing ourselves in the real world of frontline maintenance. Once we amassed a critical mass of machine recordings, we transitioned towards a continuous monitoring solution. That evolution made us the industry leader and enabled us to scale our coverage to over a thousand factories and hundreds of thousands of machine components worldwide.
Today, this effort has grown into the world's largest and most comprehensive library of real machine recordings: over 600 million machine hours, more than 460 trillion samples, with multiple neural networks trained on this data. These models now deliver diagnostics with over 99.9% accuracy across a wide range of equipment. And this isn’t static—the library grows exponentially as we add new asset types, expand into more use cases, and ingest ever-richer forms of machine data. The goal from day one was clear: build the definitive source of industrial reliability knowledge, and open it up to empower teams everywhere to shift from reactive troubleshooting to proactive control.
Many manufacturing leaders conflate AI adoption with AI impact. How do you measure whether AI is truly driving business outcomes versus just being deployed?
AI’s real impact in manufacturing isn’t measured by how many systems are deployed—it’s about the transformation that shows up on the bottom line and across teams. At Augury, we insist on evidence, not anecdotes. Our recently published TEI study confirms it: manufacturers using our platform see a 3x-20x ROI, reduce unplanned downtime by up to 90%, boost overall equipment effectiveness (OEE) by up to 30%, and shrink their maintenance budget by as much as 40%. These aren’t projections—they’re validated outcomes from hundreds of sites and millions of machine hours.
Just as important as the financial impact is what it unlocks for the people who keep factories running. When reliability becomes a strategic advantage and teams leave reactive firefighting behind, you see the real cultural shift: higher engagement, smarter collaboration, and pride in keeping production flowing. That’s how AI moves from tech hype to operational excellence.
You talk about changing the factory-worker relationship—how does predictive maintenance shift the role of maintenance teams on the shop floor?
Predictive maintenance radically transforms the day-to-day reality for maintenance and reliability professionals. Instead of spending their days responding to crises and breakdowns, technicians and engineers become strategic partners—anticipating issues before they escalate, planning repairs proactively, and focusing on improving plant reliability and efficiency. This shift means less “firefighting,” less stress, and more time spent optimizing processes and mentoring teams. Ultimately, it’s about empowering people with actionable insights so their work isn’t just about fixing what’s broken, but about elevating the entire manufacturing operation.
Your 2025 State of Production Health report shows that 96% of manufacturing leaders expect supply chain disruptions to increase in the next year—how does machine health and predictive health help manufacturers build resilience in this uncertain environment?
Resilience begins with visibility and foresight. Real-time machine health data gives manufacturers the ability to spot emerging risks early, understand true production capacity, and plan around potential bottlenecks. Predictive analytics let teams get ahead of problems—protecting delivery commitments and keeping lines running even as external shocks hit. In an age of uncertainty, machine health isn’t just a technical feature; it’s a critical lever for turning unpredictable challenges into manageable risks and maintaining trust with customers, suppliers, and executive stakeholders.
Manufacturers appear optimistic despite fears of tariffs, recession, and labor shortages. From your vantage point, what explains this confidence?
Leading manufacturers have built a reputation for resilience—they adapt quickly, innovate under pressure, and aren’t afraid to transform legacy processes. The recent surge in digital tools and data-driven decision-making means leaders now have far greater visibility and control than ever before. This optimism is grounded in the results we’re seeing every day: teams using technology to become more agile and prepared, outperforming uncertainty rather than being paralyzed by it. It’s not just hope—it’s confidence born of real, sustained success.
How does Augury envision integrating generative and agentic AI into its solutions to provide even more predictive foresight?
Augury’s Agentic AIroadmap is focused on systems that go beyond detecting and diagnosing issues, and move towards deep insights into asset strategy and guiding entire maintenance and reliability workflows. By combining generative AI’s contextual explanation and communication skills with agentic models that orchestrate workflows, we’re now delivering reliable foresight and seamless execution at every level of plant operations.
Artem Kroupenev is VP Strategy at Augury, where he oversees Augury’s AI-based machine health, performance, and digital transformation solutions. He has over 12 years of experience in technology, product, innovation, and business development and has co-founded enterprise companies in Israel, New York, and West Africa.
Artem holds and BA and MA from IDC Herzliya in Israel.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
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