Predictive maintenance outperforms reactive and preventive strategies, with the U.S. Department of Energy reporting savings of 30-40% over reactive approaches and 8-12% over preventive ones. Machine learning and vibration analysis are reshaping how these programs scale, while a certified analyst skills shortage creates a pressing barrier to market growth.
The benefits of a predictive program originate from the fact that it is a strategy driven by data such as vibration, ultrasound, temperature, electrical, and other measurements. This data ultimately drives informed decisions such as figuring out the specific repair required to fix a machine or timing the repair appropriately to minimize the risk of catastrophic failure. As such, some of the barriers to the success of a predictive program revolve around the challenges associated with acquiring and managing the vast amounts of information as well as processing or analyzing the information into accurate and actionable results. Not only that, but the industry will face a serious skills shortage if it is to solely use the traditional human-based analysis to keep up with the rising demand for predictive maintenance solutions. Time constraints associated with training proficient human analysts will hinder market growth. More about 7 Business Reasons to Develop a Predictive Maintenance Program
How Do Analysts Train Machine Learning Models?
Skilled vibration analysts train machine learning models through supervised learning, a process in which labeled datasets teach computers to identify specific fault signatures. Faults such as shaft misalignment, resonance, imbalance, looseness, and bearing wear each produce unique data signatures. By labeling thousands of datasets with the faults they represent, professional analysts supply the input data that algorithms need to classify defects independently.
How Does Big Data Help Vibration Analysts?
Big data analytics give vibration analysts machine-by-machine insights that simplified ISO 10816 limit tables cannot provide. Mechanical equipment spans countless types, including chillers, compressors, turbines, fans, and pumps, each with sub-types, drive configurations, and installation-specific variables that affect vibrational behavior. A large compiled database covering the full spectrum of machine designs allows analysts to adjust their techniques at a granular level rather than applying blanket standards.
What Is the Vibration Analyst Skills Shortage?
The predictive maintenance industry faces a structural skills shortage because analyst certification requires substantial field experience. The Vibration Institute, an ANSI-accredited certifying body, requires a minimum of 6 months of experience for Category I certification and 60 months for Category IV. Because experience cannot be accelerated, time constraints on training proficient human analysts directly limit how fast the predictive maintenance market can grow.
The latest market research estimates that the predictive maintenance market will experience compound annualized growth of 28.4% over the next five years. It is easy to see that the time and training constraints alone prevent human analysts from being capable of keeping up with this demand. A new analyst who begins training today will not be proficient in advanced analysis for at least 3 to 5 years. Meanwhile, the market will have more than tripled in size. Advancements in automated diagnostics are an absolute requirement for enabling the predictive maintenance industry to keep up.
Conclusion
Not only will fusing the diagnostic capabilities of machines and humans enable unprecedented levels of both accuracy and autonomy, it will be absolutely required in order to overcome timing bottlenecks associated with training and certification. Increased automation in diagnostics will act as a backwind for vibration analysts, enabling them to focus more time and attention on the machines with the most severe problems.
The insights gained by taking a big data approach to analysis will improve result quality and analyst skill level. These advancements are breaking down the cost and skill barriers that hinder the implementation of successful predictive maintenance programs. Facilities will have greater access to predictive maintenance, and they will therefore be able to achieve the highest levels of operational excellence and equipment reliability.
The article was written by Brandon Blatter, a certified ISO Category III vibration analyst with 10 years of experience performing centralized analysis on rotating equipment such as chillers, fans, pumps, compressors, gearboxes, etc.
