In this interview, FUCHS Smart Services and KCF Technologies discuss how lubrication-centered maintenance and machine health monitoring are reshaping industrial reliability. By combining lubrication expertise with real-time data and predictive maintenance technology, manufacturers are finding new ways to reduce unplanned downtime, extend asset life, and improve operational performance.
What does lubrication-centered maintenance look like on the plant floor?
Paul Bokrossy, FUCHS:
Lubrication-centered maintenance is really about shifting lubrication from a background task into a core driver of equipment reliability. A large portion of mechanical failures in things like bearings, gearboxes, and hydraulic systems actually begin with lubrication issues, so it plays a much more central role than many plants realize.
On the plant floor, what this looks like in practice is focusing on getting the fundamentals right every time. That means ensuring the correct lubricant is selected, applied in the right amount, and used at the right time. It also means moving away from fixed calendar-based thinking and instead paying attention to how the lubricant condition is changing over time so you can respond when it starts to degrade. And finally, it means taking contamination control seriously, because contamination is one of the primary reasons lubricants fail in the first place. When those three areas are consistently managed, lubrication becomes a structured reliability process rather than a reactive maintenance task.
What gaps exist in traditional predictive maintenance approaches?
Jeremy Frank, KCF Technologies:
One of the challenges with traditional predictive maintenance is that it often focuses on predicting when a machine will fail, rather than understanding why that failure is happening in the first place. In reality, machines are rarely just “failing on their own.” They are being gradually degraded by their operating conditions and maintenance practices over time.
When we look at the data across a very large population of industrial assets, we consistently see that those contributing factors tend to fall into machine operating conditions on one side, and maintenance practices on the other. Within maintenance practices, lubrication consistently stands out as one of the most significant and often overlooked drivers of failure.
Lubrication-related issues show up in many forms, including contamination, incorrect lubricant selection, improper application, and degradation driven by temperature and operating stress. These issues are extremely common, yet they are often not fully visible until you connect machine health data with lubrication expertise.
That is where the combination of machine health monitoring and lubrication knowledge becomes so powerful. It allows you not just to see that a problem is developing, but to understand what is actually causing it and how to correct it.
Can you share an example where machine health monitoring and lubrication analysis worked together?
Jeremy Frank, KCF Technologies:
One of the early examples in our partnership involved a manufacturer of critical railcar components with a range of rotating equipment including grinders, compressors, motors, and blowers.
In this case, our machine health monitoring system detected an emerging issue on a grinder gearbox and provided enough early warning for the customer to take the machine offline in a controlled way. That prevented an unplanned failure, but it didn’t yet explain why the issue was occurring.
From there, working together with FUCHS Smart Services, we performed an oil analysis that showed elevated wear metals and early signs of lubricant degradation. That immediately shifted the conversation from a mechanical failure to a lubrication-driven issue.
Paul Bokrossy, FUCHS:
From a lubrication standpoint, we typically see failures come down to either the wrong lubricant being used for the application, or gaps in lubrication management practices such as contamination control, filtration, or how the lubricant is maintained over time.
In this case, the oil analysis made it clear that the lubricant was no longer in a healthy state. Wear metals were increasing and the fluid properties were beginning to change, which meant it could no longer adequately protect the gearbox.
By addressing that directly, we were able to move the customer into a more suitable lubricant solution that matched the actual operating conditions of the equipment. That not only resolved the immediate issue but also improved the overall reliability of the system and helped extend maintenance intervals.
When you combine machine health data with lubrication expertise in this way, you can move from simply reacting to failures to actually addressing the root cause and improving long-term performance.
How do plants begin integrating lubrication strategy with machine health monitoring?
Jeremy Frank, KCF Technologies:
In most cases, this kind of integration does not happen all at once. It typically starts from one of two directions.
Some organizations begin with lubrication, where a site lubrication audit is used to establish best practices and bring consistency to how lubricants are selected and managed. That foundation then helps determine where machine health monitoring will have the greatest impact.
Others begin with machine health monitoring already in place. In those environments, the data often highlights broader reliability issues, and very quickly lubrication emerges as a key contributing factor. You start to see how operating conditions like vibration and temperature can accelerate lubricant degradation, which naturally leads back to lubrication strategy and expertise.
In both cases, the end result is the same. You bring lubrication intelligence and machine health data together so you can make more informed, connected decisions about equipment reliability.
What is the business impact of combining lubrication expertise with machine health data?
Paul Bokrossy, FUCHS:
One of the most important outcomes of this integration is that it allows us to validate the impact of lubrication improvements in a way that wasn’t possible before. When a better lubrication solution is implemented, we can now connect that directly to machine health data and see how the equipment responds over time.
That validation matters because it demonstrates that the lubrication strategy is not just improving performance in theory, but is actually paying for itself in practice. You see it reflected in longer asset life, fewer preventive maintenance activities, reduced lubricant consumption, and lower waste generation.
More importantly, it creates a continuous feedback loop where lubrication decisions are directly tied to measurable equipment performance.
What does the future look like for lubrication and machine health integration?
Jeremy Frank, KCF Technologies:
When equipment is properly lubricated, aligned, and maintained, it can operate at a very high level for a long time. The challenge is that many of the factors that shorten asset life are preventable.
What we consistently see is that when lubrication issues and machine health signals are addressed together, the improvement in reliability can be substantial. In many cases, organizations see dramatic reductions in unplanned downtime and significant extensions in asset life.
The real opportunity is in connecting these two domains. When lubrication data and machine health data are integrated, you move from reacting to failures toward understanding and preventing them at the source.
A New Model for Industrial Reliability
This collaboration between FUCHS Smart Services and KCF Technologies represents a shift in how industrial reliability is managed. By combining lubrication-centered maintenance with machine health monitoring and predictive analytics, manufacturers can move beyond isolated maintenance practices and toward a fully integrated reliability strategy that improves performance, reduces downtime, and extends asset life.
To learn more about how an integrated lubrication and machine health approach can improve reliability in your operation, connect with FUCHS Smart Services or KCF Technologies to start the conversation.
Dr. Jeremy Frank
Dr. Jeremy Frank, CEO of KCF Technologies, is a distinguished figure in industrial innovation, originally from Pittsburgh, PA, where his early involvement in his father’s business analyzing workplace accidents sparked a lifelong pursuit of machinery safety and efficiency. A Penn State alumnus with a PhD in Mechanical Engineering, Jeremy was deeply influenced by Dr. Gary Koopmann, leading to the co-founding of KCF Technologies in 2000. Under his leadership, KCF has pioneered advancements in wireless vibration sensing and machine health monitoring.
Today, the company is a global leader in predictive maintenance, monitoring over 80,000 machines across numerous industries, driven by Jeremy’s vision of eradicating unplanned downtime and enhancing industrial safety.
Paul Bokrossy
Paul Bokrossy is Director of Business Development for Smart Services at FUCHS Lubricants, where he helps industrial organizations improve reliability, optimize asset performance, and reduce total cost of ownership through integrated lubrication and machine health strategies. A Chemical Engineer by training, Paul began his career in the process control industry, spending 10 years helping manufacturers understand and manage the leading indicators that drive operational performance and business outcomes.
For the past 28 years, Paul has applied those same process control principles to fluid condition management, working with industrial organizations to implement on-site programs that proactively monitor and control the factors that impact equipment reliability and lubricant life. His expertise spans Reliability-Centered Lubrication, oil analysis, condition monitoring, and the integration of machine health platforms, helping maintenance and reliability teams leverage data-driven insights to improve uptime, extend asset life, and transition from reactive maintenance to predictive reliability strategies.
