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Predictive Maintenance

Predictive maintenance is a strategy in which the current condition of equipment is monitored and analyzed to be able to predict equipment failure before it occurs. The main objective of predictive maintenance is to optimize maintenance scheduling and minimize equipment downtime.

Predictive maintenance uses the data collected during monitoring to determine when performance degradation or failure is likely to occur, and the severity of the decline. This allows maintenance tasks to be performed in a more accurate and cost-effective manner based on real time equipment assessment.

While the prerequisites for an effective predictive maintenance program can vary based on the organization and equipment being used, careful planning and research to establish equipment baseline conditions is always key for any successful predictive maintenance program.

Advantages of Predictive Maintenance

The advantages of predictive maintenance are numerous and wide ranging. One of the most significant of which is a decrease in ongoing maintenance costs. Predictive maintenance eliminates much of the redundancy associated with traditional maintenance methods by customizing maintenance based on current conditions and performance. Reducing the time, labor, and parts associated with pre-defined maintenance schedules can reduce maintenance costs by 50% or more.

Predictive maintenance can also significantly reduce the frequency of unexpected equipment failures. A worn or defective component may present signals of degradation that could potentially evade a pre-set maintenance cycle. The monitoring and analysis inherent to predictive maintenance mitigates these circumstances by creating a proactive response loop. This can lead to longer equipment life, reduced troubleshooting, and more predictable capacity planning.

Spare parts inventories can also be reduced and streamlined through predictive maintenance. Rather than stocking a comprehensive inventory of parts to address both scheduled part replacement and unscheduled failures, more parts can be sourced on an “as-needed” basis, with the predictive feedback creating a lead time buffer for part replacement.

Historical data combined with the analytical horsepower of predictive maintenance also provides indirect advantages by creating leaner operations with more visibility into equipment performance over time. Service life and mean time between failures can be more accurately predicted thus enabling more systematic capital expenditure planning. Operator safety, efficiency, and morale can also be improved by avoiding potentially dangerous and disruptive catastrophic failures.

Studies have shown that predictive maintenance saves roughly 8% to 12% over preventive maintenance and up to 40% over reactive maintenance.

Predictive Maintenance Software

Predictive maintenance would not be possible without advanced software to gather, analyze, and store the appropriate data for each piece of equipment. A computerized maintenance management system (CMMS) is the engine behind this enhanced functionality.

Using algorithms that proactively identify trends, CMMS software can automatically generate alerts and work orders that ensure timely maintenance responses and minimize downtime risk. CMMS can add additional value as a centralized platform for maintenance history, work order management, parts inventory control, asset management, and report generation.

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Predictive Maintenance ROI (Return On Investment)

In addition to the reduction in maintenance costs, a reduction in equipment downtime of 40% or more coupled with an increase in productivity of up to 25% can facilitate a quick recoup of initial costs and an overall ROI averaging 10x across multiple industries.

Predictive maintenance, with the power to substantially reduce ongoing maintenance costs as well as prevent highly disruptive and costly downtime, can undoubtedly deliver a considerable return in a relatively short period of time.

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