How to use predictive maintenance strategies to become a rock star in your facility

With predictive maintenance and a CMMS, maintenance managers can nurture their teams by shaping a less stressful, less reactive day-to-day environment, making them rock stars within their own facility or plant. Instead of responding to one emergency after another in a seemingly random and uncontrolled manner, now days and even weeks can be planned down to the hour.

Predictive maintenance directly monitors the condition and performance of assets during normal operation to reduce the likelihood of failures. It attempts to keep costs low by reducing the frequency of maintenance tasks, mitigating unplanned breakdowns and eliminating unnecessary preventive maintenance.

While it evaluates the condition of equipment by performing periodic or continuous (online) equipment condition monitoring, most predictive maintenance is performed while equipment is operating normally to minimize the disruption of everyday operations. This maintenance strategy leverages the principles of statistical process control to determine when maintenance tasks will be needed in the future.

Shifting to a condition-based, predictive maintenance strategy allows asset histories to be tracked and empowers maintenance teams to make more strategic decisions. It also allows them to prioritize work orders efficiently to make sure the right type of maintenance is performed on the right asset at the right time.

A properly established CMMS is critical in this effort, as it allows maintenance managers to report key performance indicators (KPIs) to upper management that reflect a specific maintenance program’s the return on investment (ROI), as well as the overall costs of unplanned downtime and corrective maintenance.

For more information, read our technical article on how tracking key performance indicators drives more effective maintenance. And check out our infographic to learn more about leveraging predictive strategies to best benefit your maintenance team’s operations.

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