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Condition-based monitoring promises industry revenue increase

By Max Burkhalter
March 15, 2022

The Internet of Things (IoT) has enabled predictive maintenance for many industries. The implementation of sensors designed to forecast potential equipment wear and tear in advance of malfunction has had a positive impact on the productivity levels of many businesses. Condition-based monitoring (CBM) is maximizing revenue potential by protecting industrial equipment from the downtime associated with repair.

Natural Evolution

Reactive maintenance involves waiting until a piece of equipment or machinery breaks down before repairing. The operational effectiveness of this method is quite low, with unpredictably long downtimes. Planned maintenance, while more predictable, still requires the downtime associated with regularly scheduled repairs. Predictive maintenance, heralded by the arrival of IoT powered sensors, collects real-time data from equipment to detect potential wear and tear well before operational fault. Thanks to advances in IoT technology, predictive maintenance is considered the optimal strategy for machine repair.

Condition monitoring, another name for predictive maintenance, enables profit for both the equipment manufacturers and the industries in which they operate. By alerting owners as to the need for proactive repairs based on data collected from IoT sensors, manufacturers can maximize profit by selling parts to happy customers who aren't reaching out when their equipment suddenly fails. In turn, the operators of the equipment can ensure production schedules aren't affected by malfunction by arranging repairs during off-production hours.

Tools of the trade

Among the most common condition-based monitoring tools, vibration analysis and vibration monitoring sensors measure changes in the amplitude, frequency, and intensity of reverberations on high-powered equipment. These finely tuned instruments detect the slightest changes in the tenor of a machine and communicate the associated data back to the manufacturer and owner. Studying vibration measurements enables the ability to diagnose imbalance, looseness, or misalignment. Oil analysis pertains to the testing of lubricants. By monitoring wear particles, water contamination, and viscosity, heavy machinery malfunctions attributed to the corrosion or contamination of fluids can be detected well in advance of failure.

Acoustic analysis measures changes in frequency to determine the potential of an equipment fault. Sonic measurement involves the use of a microphone and is a key indicator of lubrication variance. Ultrasonic analysis goes beyond human audio frequency recognition capabilities, and can filter out unnecessary audio tones, making it an essential addition to noisy manufacturing environments.

Perle powers industry

Perle industrial cellular routers are just one of the technologies designed to help relay the information captured by today's leading condition-based monitoring systems. Industrial cellular routers facilitate the transmission of data collected by sensors to central monitoring systems, offering real-time insights to transform isolated data into actionable big data.


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