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Maximizing the P-F Interval with Predictive Maintenance

By Bryan Christiansen, Founder and CEO at Limble CMMS. This article appears in the November/December 2019 issue of Inspectioneering Journal.
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Introduction

Implementation of a successful Predictive Maintenance system requires a good working knowledge of the P-F Interval. Proper application of this principle allows for early detection of equipment anomalies, which lowers the maintenance burden and lessens the impact to operations. With the proliferation in industrial digitization, detecting problems before a failure occurs is easier today than ever before.

This article will introduce the P-F Interval and its importance in predictive maintenance, describe methods to detect failures early, and map out a path to begin an effective Predictive Maintenance program at your facility.

P-F Interval

First, let us understand the P-F Interval. In an old-fashioned maintenance model, the operations team ran the equipment until it failed. The maintenance team then reacted, repairing the equipment as soon as they could. As maintenance strategy became more preventive, tasks to check on equipment or replace parts were added on a periodic basis. This was an improvement, but it was difficult to optimize the timing of the tasks. The preventative maintenance (PM) task had to be performed before issues were to become failures. The cycle of PM-to-failure could vary widely; thus, the maintenance team could either overcommit to PMs, or risk failures.

The P-F Curve
Figure 1. The P-F Curve

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Posted by Sairaman Govindaraj on December 30, 2019
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