A FMEA (Failure Modes and Effects Analysis)  is a large effort. Here are three (3) simple steps to help improve your FMEA. We add some hints that makes this process easier.

With any FMEA, the language we choose and record can make or break the analysis. Within the same language. we all interpret words differently. Without the proper use of words, some failure modes can be misleading when read by others. All is not lost.There are a few simple rules of thumb to follow. This will allow for better FMEA results.

Read on to learn how!

STEP ONE: Develop a Consistent Failure Modes Description

Why is it important to be descriptive? First, others who read your FMEA need to be able to understand it. Follow this simple THREE (3) part naming  convention. It will help you to develop consistent and repeatable ways to describe each failure.

Part Causing Failure (Object) / Failure mode (Adjective) / due to / Failure Cause (Why)

Bearing seized due to lack of lubrication.

Impellor worn due to ingress of particles.

STEP TWO: Development of the Failure Characteristics

Not all tasks are the same. In order to select the correct logical decision, we must understand the failure characteristics. If prior failure data or history exists, we can use it.  This is typically done using statistical distributions. The most commonly used is called the Weibull distribution.

Through Years of experience in developing scheduled maintenance programs we have learned how more efficient programs can be developed. This is done through the use of logical decision processes. These logical decision processes are actually decision trees. We use these trees to select tasks. These tasks comprise the maintenance program. Learn more about our easy to use our Maintenance Task Selection Software.

When creating a Weibull model, two technical parameters are required. The Eta or characteristic life and the Beta shape factor are needed. These two parameters tell us how the failure mode will behave. With an applicable maintenance task we hope to manage to an acceptable level of risk.

Consider as a simple example compare the  failure modes below.

  1. Bearing failure due to end of life/wear
  2. Bearing seized due to lack of lubrication (after initial lubrication at installation)

The estimate Eta (characteristic life) value of a well maintained bearing should be 10 yrs. Often bearing L10 life is rated in revolutions of the bearing, at a specified load. The second failure mode the scenario is different. Here we will assume the bearing was correctly installed, and lubricated. Subsequently it was not lubricated as specified by the manufacture. Hence,  it fails in 1 yr due to the lack of lubrication. Review of the Beta (shape factor) value is different for each failure mode (end of life vs. lack of lubrication). The Beta value should near or equal 1 for a well lubricated, and in correctly loaded bearing. Such a bearing will  achieve its stated L10 life.

The second failure mode description is well detailed. This makes it easy to understand. The first adjective we find is ‘seized’. The final part of the statement is‘lack of lubrication’. This then describes why the failure mode occurred. Because of a lubrication issue, the wear out of the bearing is faster than the L10 life.  This is due to the lubrication reaching its end of useful life.  So we use a Beta value of 4.

Failure Mode

Eta

Beta

Bearing failure

10 yrs

1

Bearing seized due to lack of lubrication

1 yr

4

STEP THREE: Determining the Applicable Maintenance Task.

A maintenance task is said to be applicable if,  the task is capable of improving on the reliability that would exist if the task was not performed..

There are 4 basic scheduled maintenance task types we can chose from.

  1. Scheduled inspection of an item at regular intervals to find potential failures.
  2. Scheduled Rework of an item at or before some specified age limit.
  3. Scheduled discard of an item(or one of its parts) at or before some specified life limit.
  4. Scheduled inspection of a hidden-function to find functional failures.

When determining maintenance activities , the beta parameter plays a very important role. Beta helps determine which types of tasks might be applicable. We use different Beta for different failure modes. We don’t have to do this the hard way. Visit here to learn more about the easy way. Download a FREE trial: 

The beta value of 4 suggests that the end of life is predictable. In fact it follows a typical wear out or end of life behavior. In this scenario, the end of life of the bearing lubricant. A bearing with old lubrication causes the bearing to seize. The applicable task would thus be a Type 2 task. You would select to rework the bearing lubrication at or before its specified life limit.

A beta parameter of 1 suggests that the failure is random. That means the component has the same probability of failure the first day it is installed as compared with; say the 1000th day. The failure is not predictable and a time based PM is not applicable. In these cases, Chose a Type 1 task. Inspect the bearing at regular intervals to find potential failures. Typically this is performed using a Vibration Analysis.

Neglecting for a moment the topic of SAFETY.  Maintenance decisions that do not affect safety should be based on a cost-benefit analysis. If however, SAFETY is affected then we must do more. If  an acceptable maintenance task cannot be found to reduce the risk to an acceptable level, then the only way to protect from failure would be to redesign the system. With this redesign we seek to remove that specific failure mode.

Need some help with your next FMEA or looking for more on this topic?

Check here in our Reliability Services Section.

In summary the use of language in FMEA to describe failure modes is very important, without datasets to support the failure mode estimating parameters can alter the outcomes of FMEA. It is important to consider the component (what failed), the mode of failure (an adjective) and the cause of the failure (the why) to gain real benefits from a FMEA, otherwise outcomes can be compromised and typically FMEA will not improve the equipment performance as intended.

 

About adatoo

Amir Datoo is an experienced Reliability Engineer currently based in the USA. He has worked extensively with major international companies to integrate their data and CMMS systems

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