J. Collier, John Crane, Atlanta, Georgia (U.S.)
In today’s fast-paced industrial landscape, the pressure to maximize efficiency, minimize downtime and ensure the safety of operations has never been greater. Traditional maintenance models—such as corrective maintenance, which address issues only after a failure, or time-based maintenance built on fixed schedules and routine checks—are rapidly giving way to more dynamic and intelligent approaches.
At the forefront of this evolution is condition-based matinenance (CBM), a strategy that leverages real-time data and advanced analytics to both prevent equipment failures before they occur and verify an asset’s ongoing suitability for further service. While CBM is sometimes referred to as predictive maintenance, it is important to note that CBM does not predict failures. Rather, it identifies known precursors to failure, allowing engineers to take action to prevent issues before they arise. This approach improves efficiency, reduces downtime and enhances operational safety.
A modern and effective CBM system is built upon an optimized combination of data collection methods, such as fixed sensors, route-based handheld data collection, oil sampling and engineering inspections. Viewed holistically, these methods provide critical insight for early fault detection and smarter resource deployment. When used together, they enable operators to make informed decisions and respond swiftly to emerging risks with real-time insights.
The role of advanced sensors in CBM. The ability to accurately and rapidly assess the health of critical equipment sets the stage for an effective CBM program. This is made possible by the latest generation of industrial sensors that have transformed the way data is collected.
Modern sensors are capable of capturing a vast array of parameters. With unprecedented precision and speed, operators can monitor everything from vibration, temperature and pressure, to acoustic emissions and more. These devices are not only more sensitive than their predecessors but also more robust and able to operate reliably in harsh industrial environments. The result is a continuous stream of high-fidelity data that provides a real-time snapshot of equipment health.
For example, the author’s company’s innovative monitoring technologya is an advanced industrial monitoring solution that enables real-time measurement of key machine health parameters such as flow, pressure, power consumption, temperature and vibration. Designed to integrate seamlessly into existing infrastructure, the monitoring technology provides high fidelity data directly from rotating equipment, helping operators detect anomalies early and respond before performance is compromised. Its robust construction and flexible connectivity make it well suited to harsh environments, ensuring reliable insights under demanding operating conditions.
The importance of rapid, high-precision data collection cannot be overstated. Early detection of anomalies such as subtle changes in vibration patterns or temperature spikes enables onsite maintenance teams to intervene before minor issues escalate into major failures. This proactive approach not only extends the lifespan of assets but also helps avoid costly, unscheduled shutdowns.
With CBM, decision-makers are empowered to act swiftly and confidently with real insights. By integrating sensor data into centralized monitoring platforms, organizations can visualize trends, set tailored alerts and prioritize maintenance tasks based on actual need rather than arbitrary timelines.
Human expertise. Advanced tools and analytics are indispensable and have had an immense impact on industrial growth. The most successful CBM programs are those that seamlessly integrate these tools and analytics with the expertise of seasoned professionals.
Instead of viewing sensors and analytics as replacements for human judgment, leading organizations recognize them as powerful tools that enhance and inform decision-making.
Strategies for combining sensor data with human analysis include regular cross-functional reviews, where maintenance engineers and data analysts collaborate to interpret findings and develop action plans. Operators can also utilize advanced diagnostic platforms that are configured to flag anomalies for human review, ensuring that critical decisions are always made with the benefit of both data and experience.
For example, a mid-sized chemical processing facility in Texas (U.S.) implemented this cross-functional approach after experiencing repeated bearing failures on a critical agitator. By using handheld spectrometers during weekly inspections, the team identified early oil degradation and contamination patterns that traditional scheduling would have missed. They then introduced routine oil analysis to monitor metal particles and viscosity changes, which revealed misalignment in the gear assembly. With this insight, maintenance teams performed targeted adjustments, extended oil change intervals by 40% and avoided an unplanned shutdown, saving the business an estimated $180,000/yr in downtime and repair costs.
Benefits of a comprehensive CBM strategy. The advantages of a well-executed CBM strategy extend beyond monitoring the condition of the equipment. Such a strategy also helps identify the root causes of failure and eventually save organizations time and money. This targeted, yet far-reaching approach, minimizes the risk of catastrophic breakdowns and extends the useful life of critical assets. It is well documented that addressing early faults or defects positively impacts the overall reliability of systems.
Minimizing equipment downtime is another key benefit. With early fault detection and timely interventions, maintenance activities can be scheduled during planned outages or low-demand periods, reducing the impact on production. This not only boosts operational efficiency but also enhances reliability.
Risk exposure and maintenance costs are also significantly reduced. By avoiding unnecessary repairs and replacements, organizations can allocate resources more effectively, reduce cash held in inventory and achieve a better return on investment. Most importantly, CBM contributes to a safer working environment by preventing hazardous failures, reducing unnecessary work and ensuring that equipment operates within safe parameters.
What’s next? As industries continue to embrace digital transformation, CBM stands out as a cornerstone of modern asset condition management. The ability to monitor, analyze and act on real-time data is revolutionizing maintenance practices, delivering tangible benefits in efficiency, reliability and safety.
Looking ahead, the evolution of CBM will be driven by ongoing advancements in sensor technology, data analytics and artificial intelligence. However, the human element remains critical to its foundation.
For organizations seeking to future-proof their operations, now is the time to invest in not only CBM technologies but also in the integration of relevant intelligence, cultivating a workforce of skilled professionals capable of interpreting data and making informed decisions and selecting the right expert partner to support their CBM journey. HP
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John Crane’s Sense® Monitor
Jerry Collier is the Senior Director, North America for John Crane. He is a versatile leader with a proven record of improving the customer experience in the automation and rotating equipment arena.