Predictive maintenance

By taking into account measurements of the state of the equipment, maintenance work can be better planned (spare parts, people, etc.)

Time-based maintenance is labor intensive, ineffective in identifying problems that develop between scheduled inspections, and therefore is not cost-effective.

In today's dynamic landscape of service maintenance, prolonged repair processes present a significant challenge for organizations striving to maintain operational excellence.

Extended downtime, increased Mean Time to Repair (MTTR), and production losses not only affect profitability but also disrupt service continuity and diminish customer satisfaction.

When properly implemented, it provides companies with a tool for achieving lowest asset net present costs for a given level of performance and risk.

In 2010, the mining company Boliden, implemented a combined Distributed Control System and predictive maintenance solution integrated with the plant computerized maintenance management system on an object to object level, transferring equipment data using protocols like Highway Addressable Remote Transducer Protocol, IEC61850 and OLE for process control.

To evaluate equipment condition, predictive maintenance utilizes nondestructive testing technologies such as infrared, acoustic (partial discharge and airborne ultrasonic), corona detection, vibration analysis, sound level measurements, oil analysis, and other specific online tests.

But despite such capabilities, not even the most sophisticated equipment successfully predicts developing problems unless the operator understands and applies the basics of vibration analysis.

[9] In certain situations, strong background noise interferences from several competing sources may mask the signal of interest and hinder the industrial applicability of vibration sensors.

Consequently, motor current signature analysis (MCSA) is a non-intrusive alternative to vibration measurement which has the potential to monitor faults from both electrical and mechanical systems.

Changes in these friction and stress waves can suggest deteriorating conditions much earlier than technologies such as vibration or oil analysis.

Infrared monitoring and analysis has the widest range of application (from high- to low-speed equipment), and it can be effective for spotting both mechanical and electrical failures; some consider it to currently be the most cost-effective technology.

[12] It allows for the automation of data collection and analysis tasks, providing round the clock condition monitoring and warnings about faults as they develop.