Harnessing P-F Curves for Improved Asset Reliability

The P-F curve, short for "Potential-Failure curve," is a powerful tool used in maintenance management to assess the condition of assets and predict their failure.

This graph visually represents the relationship between the time of failure and the condition of an asset.

The P-F curve is a useful tool for predicting when an asset is likely to fail to help maintenance professionals proactively schedule preventive maintenance, prioritize critical assets, and improve overall reliability.

Understanding the P-F Curve

The P-F curve provides essential insights into asset behavior and potential failures. Here's how you read a P-F curve:

1. Shape of the Curve: The shape of the curve indicates the type of failure an asset is susceptible to. A long-tailed curve signifies failure due to gradual wear and tear, while a short-tailed curve suggests failure resulting from sudden events.
2. Slope of the Curve: The slope of the curve reflects the rate of deterioration. A steep slope indicates rapid degradation, while a shallow slope indicates slower deterioration over time.
3. Curve Position: The position of the curve along the x-axis offers insights into the asset's expected lifetime. Assets with long lifetimes exhibit curves that start at high values on the y-axis and gradually decline. Conversely, assets with shorter lifetimes display curves that start at low values on the y-axis and sharply rise.

How to calculate a P-F curve?

There are several methods for calculating a P-F curve. The two most commonly used methods are degradation analysis and failure data analysis methods.

Degradation analysis

This method involves collecting data on an asset's performance degradation over time. For instance, by measuring the thickness of a pipe periodically, maintenance professionals can assess its degradation.

Various techniques like visual inspections, vibration analysis, or ultrasonic testing can provide valuable degradation data.

Let's consider a pipe with an initial thickness of 10 mm and a current thickness of 8 mm after 5 years.

The degradation rate would be (10 - 8) / 5 = 0.4 mm/year.

Reading the curve: The degradation analysis curve will plot the asset's performance condition on the y-axis against time on the x-axis. The curve will depict a gradual decline in the asset's condition over time.

Failure data analysis

This method utilizes data on previous asset failures. By analyzing maintenance records, warranty claims, or field reports, maintenance professionals can determine the relationship between an asset's age and its probability of failure.

Suppose a machine has experienced 4 failures in a total operating time of 1,000 hours. The failure probability would be 4 / 1000 = 0.004.

Reading the curve: The failure data analysis curve will plot the asset's failure probability on the y-axis against its age on the x-axis. The curve will show the likelihood of failure increasing with the asset's age.

P-F curves are valuable for predicting asset failures and improving asset reliability.

A deep understanding of the benefits and limitations of P-F curves will help you utilize the P-F curve fully to improve the performance of your assets.

Benefits of using a P-F curve

The utilization of P-F curves offers several advantages to improve equipment reliability, including:

1. Risk identification: P-F curves assist in identifying assets at risk of failure. Maintenance professionals can mitigate downtime and associated costs by prioritizing maintenance activities for these critical assets.
2. Failure prediction: The P-F curve enables accurate prediction of an asset's failure timeframe. This information allows for proactive scheduling of preventive maintenance, reducing unexpected breakdowns, and ensuring continuous operations.
3. Reliability improvement: Examining the P-F curve, maintenance professionals can identify and address the root causes of failures, thus enhancing asset reliability.

Some reliability insights you can get from a P-F curve

• The shape of the curve can indicate the type of failure: A curve with a long tail indicates that the asset is likely to fail due to wear and tear, while a curve with a short tail indicates that the asset is likely to fail due to a sudden event.
• The slope of the curve can indicate the rate of deterioration: A steep slope indicates that the asset is deteriorating quickly, while a shallow slope indicates that the asset is deteriorating slowly.
• The location of the curve on the x-axis can indicate the expected lifetime of the asset: An asset with a long expected lifetime will have a curve starting at a high value on the y-axis and slowly decreasing over time. An asset with a short expected lifetime will have a curve that starts at a low value on the y-axis and then quickly increases over time.

Practical applications of P-F curve

Let's consider practical applications of P-F curves in various industries:

1. Manufacturing: A manufacturer of electric motors can use P-F curves to identify motors at risk of failure. By prioritizing maintenance for these motors, costly downtime can be avoided.
2. Transportation: P-F curves can predict aircraft maintenance needs, helping transportation companies schedule maintenance during off-peak hours and minimizing service disruptions.
3. Power plants: Power plants can employ P-F curves to identify equipment at risk of failure. Prioritizing maintenance activities for such equipment prevents costly outages.

While it is a useful tool, the P-F curve doesn't paint the complete picture of equipment reliability.

Limitations of P-F curves

Despite their benefits, P-F curves have limitations.

First, P-F curves are based on historical data. If the operating conditions of an asset change, the P-F curve may no longer be accurate.

Second, P-F curves are only as good as the data that they are based on. The P-F curve may also be inaccurate if the data is incomplete or inaccurate.

To maximize the effectiveness of P-F curves, consider the following tips:

1. Use as much historical data as possible to calculate the P-F curve. The more data you have, the more accurate the curve will be.
2. Be sure to consider all of the factors that can affect asset failure when calculating the P-F curve. These factors may include environmental conditions, operating conditions, and maintenance practices.
3. Use the P-F curve to identify assets that are at risk of failure and prioritize maintenance activities for these to avoid unplanned downtimes.
4. Use the P-F curve to predict when an asset is likely to fail. Schedule preventive maintenance for these assets to avoid failures.
5. Continue to monitor asset performance and update the P-F curve as needed. This will ensure that the P-F curve is always accurate and up-to-date.

Improving asset reliability in your facilities

Implementing P-F curves, along with diligent data collection and analysis, empowers organizations to make informed decisions, minimize downtime, and enhance operational efficiency.

Of course, manually keeping track of data and ensuring data accuracy is not practical, especially for enterprises with large asset portfolios.

You'll need facilities management software that provides a centralized repository for asset data, as well as tools for data analysis and reporting.

Facilio allows users to track asset performance over time, which can be used to identify trends and patterns that may indicate an impending failure.

It also provides tools for estimating the remaining useful life of assets, which can be used to schedule maintenance activities and avoid costly unplanned outages.

In addition to tracking asset performance, Facilio also allows users to collect failure data, which can be used to create P-F curves and predict the probability of failure for assets.

It's better not just because it is intelligent and acts in real-time but also because:

• It creates P-F curves much more accurately than any manual methods or legacy tools that do not work in real time.
• It helps improve facility safety by identifying assets at risk of failure and helps take steps to mitigate those risks.
• Since it can detect potential problems much in advance, it enables you to be proactive with maintenance, repairs, and replacements to reduce costs associated with asset failures.  

Facilio's cloud-based Connected CMMS makes it easy to collect and analyze data, and its reporting tools make it easy to communicate the results of your analysis to stakeholders too!

Get in touch and learn how Facilio can help you improve asset reliability and achieve operational excellence in your facilities!