Pumps and Syste ms, July 2009
Editor's Note: This is the second article in a series about machinery health, to read the previous article, click here.
Potential to Failure (P-F) curves graphically display the failure time cycle and measurement techniques that can be used to detect asset failures prior to reaching the asset incurring functional failure. Proactive strategies should focus on managing assets high on the P-F curve, or early (P1 to P5) in the failure cycle (Figure 1). The ability to detect failures early in development allows top quartile performers to proactively manage their maintenance programs by understanding the health of their assets. Many companies, however, find it difficult to operate proactively and continually react to assets that reach functional failure with little or no warning.
Figure 1. Understanding the Potential to Functional Failure (P-F) Curve
Understanding Asset Criticality and the Impact on Maintenance Strategies
All assets do not have the same failure consequences. Understanding how failure affects an asset is essential to defining strategies to mitigate the impact.
First, understand that asset failures can impact various aspects of a business, including safety, environment, regulatory compliance, product quality, production and operations and maintenance costs. Understanding what is important to the business can help in prioritizing and weighting the impact of failure. For example, a failure that results in a safety incident or death should be regarded as more critical than a failure that results in a poor quality product. While both are important to understand and mitigate, addressing the safety impact takes precedence. In companies that are physical asset intensive, top performers assign a weighted value to the areas of failure impact and develop comprehensive rankings of asset criticalities. Top performers use this knowledge to apply appropriate failure mitigation strategies.
Figure 2
Figure 2 shows an example of a distribution of assets (%) by criticality and what asset strategies (see below) might be applied. Understanding asset criticality and business goals is key to applying the right strategy.
Maintenance Strategies
Reliability Centered Maintenance (RCM ) is a systematic, disciplined process to ensure safety and mission compliance. RCM defines system boundaries and identifies system functions, functional failures and likely failure modes for equipment and structures in a specific operating context. Because it is a time- and resource-intensive process, the application of RCM is typically applied only to the top 15 percent (defined as part of the strategy) of the highly critical and critical assets.
Development of complete Failure Modes and Effects Analysis (FMEAs) is applied to about 55 percent of the assets, specifically those in the mid to low level criticalities. This technique applies unique FMEAs for each asset. Developing FMEAs require less time and resources to complete than applying RCM, yet drive the mitigation and controls to address the asset failure modes.
The application of FMEA or asset class specific predefined maintenance templates is a strategy that can be applied to about 25 percent of the assets, primarily those identified as having low critically.
Run-to-failure (RTF) strategies are typically applied to the bottom 5 percent of the assets in terms of criticality, primarily those where it is acceptable for failures to occur without prior warning. The most cost-effective approach in these cases is to simply replace and not maintain the asset.
The percentages above and in Figure 2 are based on experience and will ultimately depend on the specific criticality based maintenance strategy.
Condition Monitoring Methodologies
Choosing the most effective asset failure mitigation strategy will come from the application of RCM, FMEA, templates and RTF strategies. Using these results to drive the right Condition Monitoring (CM) and Predictive Maintenance (PdM) technologies is key to understanding asset health and essential to optimizing return on investment. Companies that are physical asset intensive should strive to have the correct mix of preventive, predictive, proactive and run-to-failure maintenance strategies (Figure 3) for managing their assets.
Figure 3
The appropriate CM/PdM strategy will vary depending on the failure mode and how long it takes a failure to manifest itself from detection to functional failure , which is known as the failure cycle. The failure cycle is graphically displayed on the asset's P-F curve (Figure 1). CM programs can be as basic as collecting and analyzing periodic oil samples or monitoring process variables (pressure, flow, etc.) available for the asset.
While these approaches may be sufficient for some assets, certain failure modes require additional data and less time between collection intervals to detect changes in condition and to proactively manage and possibly prevent the failure. For some failure modes, periodic data collection (in intervals ranging from once a week to once every six months, based upon the failure cycle) can detect failures with sufficient time to plan the required maintenance. Individual failure modes, failure consequences, failure detectability and the lead time in predicting functional failure help in determining whether to use continuous online, scanning, or portable data collection frequencies and methodologies.
Under maintaining or under-instrumenting a highly critical asset might ensure lower planned costs, but may also result in poor reliability, high reactive maintenance (RM) costs, poor asset performance and unacceptably high overall risk to the business. Conversely, over maintaining or over-instrumenting a non-critical asset will incur higher-than-necessary planned costs compared to the level of risk reduction that can be achieved. The optimum level of investment targets the right assets with the right mix of planned maintenance, resources and technology, thereby reducing asset risk to a tolerable level at manageable planned costs. Optimizing strategy over time (dotted lines) will result in the right risk reduction while balancing costs (Figure 4).
Figure 4
Typically, highly critical and many critical assets need more frequent sampling and require an on-line system. On-line systems sample data continuously and often offer automated relays and shut down systems or automated alarms to address failures with low failure cycles and high failure consequences. In addition to these traditional on-line API 670 compliant protection systems, scanning systems (including both traditional wired and newer wireless scanning) can be applied to assets that are critical, mid-level,
