Failure Modes and Effects Analysis (FMEA) is integral to reliability, quality and safety programs in a wide variety of industries. It’s a collaborative cross-functional methodology that aims to anticipate and address potential failures in products, processes or services before they happen.
FMEA teams assess the risk of potential failures in order to prioritize design improvements, control plans, test plans and other proactive mitigation strategies.
This article examines commonly used qualitative risk assessment methods in FMEAs, including traditional Risk Priority Number (RPN) or criticality (SxO) metrics as well as Action Priority (AP) ranking tables.
A note on quantitative risk assessment methods
In addition to the widely used qualitative risk assessment methods discussed here, there is also a long history of quantitative approaches that consider the component’s estimated failure rate or other factors. Some of these are described in public standards, such as MIL-STD-1629A, and may also have been designed/adapted by local analysis teams.
Most qualitative risk assessment methods commonly used with FMEAs require the analysis team to use past experience and engineering judgment to rate each potential problem according to at least two rating scales:
Many approaches also use a third scale:
These rating scales typically range from 1 to 10 (or 1 to 5), with the higher number representing the higher seriousness or risk. For example, a potential failure cause with a very low likelihood of detection may be rated 10 on the detection scale.
The specific labels, descriptions and/or criteria are typically customized by analysis teams to fit the products or processes they are analyzing. As an example, the following table shows a truncated 10-point Occurrence scale that could be used in product development for vehicle components.
The traditional Risk Priority Number (RPN) method assigns and multiplies all three ratings for each potential failure cause identified in the FMEA.
RPN = Severity x Occurrence x Detection
An alternative method, sometimes called “qualitative criticality” or “SxO” or “SO,” uses only two of the ratings.
SxO = Severity x Occurrence
The calculated metrics can then be used to evaluate the relative risk of potential failures in order to prioritize design improvements and other mitigations that may be effective.
Typically, thresholds for High, Medium, and Low risk will be defined, and a class of risk will be assigned to every failure cause. For example, consider a failure cause with S=10, O=4 and D=2. Its RPN would be 10x4x2 = 80. If we define RPN >100 as High risk and RPN<50 as Low risk and everything in between as Medium, we would assign a Medium risk to this failure cause. This helps separate failure causes into different bins of risk.
It’s important to remember that qualitative risk metrics are relative to a particular FMEA performed with a common set of rating scales and an analysis team that strives to make consistent rating assignments for all identified issues.
RPNs or SxOs can be compared to other metrics in the same FMEA but may not be comparable to metrics in another analysis.
Also, the RPN value that is calculated weights each score equally, which may not always be proper. Take for instance a failure cause with the scores S=7, O=4 and D=4. This has an RPN = 112, and by our earlier thresholds that categorizes it as High risk.
Is it really appropriate that this cause should be addressed before the cause we calculated earlier, with an RPN = 80? If the SOD scores are weighted equally, then yes – but typically severity is seen as more important than occurrence or detection, and failure causes associated with safety or regulatory concerns, as the severity of 10 in the first cause would indicate, should receive higher priority even with lower RPN values.
As a supplement or alternative to RPNs and SxOs, many FMEA programs have developed risk ranking tables to assist with the decision-making process. These tables typically identify whether action is required based on some combination of Severity, Occurrence, and/or Detection.
ReliaSoft’s XFMEA software was an early promoter of this approach and has provided flexible support for configurable risk ranking logic since Version 5 (released in 2010).
Recent versions of both the AIAG-VDA and SAE J1739 FMEA standards (published in 2019 and 2021) now also provide sample ranking tables that FMEA teams can adapt to fit their particular needs.
Going back to the earlier example, our first cause had the score S = 10, O = 4, and D = 2. Using the truncated table below, we would assign an action priority of High. The second cause, with the higher RPN but lower severity score (S = 7, O = 4, D = 4), would be assigned a priority of Medium. This implicitly slants the risk ranking towards failure causes that have more severe consequences for the end user, which aligns better with how FMEAs are typically performed.
Although FMEAs may contain only a single calculated risk metric for each potential failure cause, it is much more common for analysis teams to calculate both “initial” and “revised” metrics.
For the revised risk assessment, the analysis team assigns a second set of Severity, Occurrence and Detection ratings for each potential failure cause, either after the actions are completed or based on the expectation that they will be completed.
This provides an indication of the effectiveness of improvement activities and may also be used to evaluate the value to the organization of performing the FMEA.
As an example, the following image shows a partial FMEA worksheet in the ReliaSoft Cloud web-based software with both initial and revised RPNs and action priorities (APs).
If the FMEA team uses a commonly agreed logic to assign potential failure causes to different risk levels (aka “action priorities”) such as High, Medium or Low, they can also visualize a risk profile like the example shown next.
In this dashboard tile generated in the ReliaSoft Cloud software, the FMEA team has identified 28 potential failure causes for the design, with 21% initially assessed as high priority and reduced to 0% through implementation of assigned actions.
When both initial and revised RPNs have been assigned, the percent reduction in RPN can also be calculated as follows:
% reduction in RPN = (RPNi – RPNr) / RPNi
For example, if the initial ratings for a potential problem are S = 7, O = 8 and D = 5 and the revised ratings are S = 7, O = 6 and D = 4, then the percent reduction in RPN from initial to revised is (280-168)/280, or 40%.
A risk matrix (sometimes also called “qualitative criticality matrix”) provides another way to use these ratings to prioritize potential problems.
As shown in the following example, this type of matrix usually displays the Occurrence scale vertically and the Severity scale horizontally.
FMEA teams can then choose how to prioritize the potential failures that fall into each cell of the matrix.
With any or all of the qualitative risk assessment techniques discussed here, and as new approaches continue to evolve over time, an effective FMEA software tool can help to facilitate, streamline and turbocharge the efforts of FMEAs teams, as well as product managers and other groups throughout your organization that rely on this type of valuable product failure knowledge.
HBK ReliaSoft has 20+ years of expertise with FMEA software, training and consulting.
XFMEA is a desktop solution that has been widely used since 2003.
ReliaSoft Cloud is a web-based (Software-as-a-Service) SaaS product initially released in November 2024.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
This will bring together HBM, Brüel & Kjær, nCode, ReliaSoft, and Discom brands, helping you innovate faster for a cleaner, healthier, and more productive world.
