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The issue of VMEA is to finalize Input selection to define KPIV. Starting from the inputs selected with the Causes/effects matrix, the VMEA fits into the detail of each variable.


This is the tool that makes the link between the measure phase and the analysis phase. It applies a last filter on the Input is thus to define the KPIV of our procesus.

Step 1: Evaluate Input

For each Input output from the cause-effect matrix, they are evaluated according to 3 factors:

  • severity: Its impact on the customer in the event that the KPIV has a failure. The score is the same as that identified in the development of the cause-effect matrix.
  • probability of occurrence: The probability of the failure occurring.
  • level of detectability: The level of failure detection.


For the evaluation, use a scoring scale of 1 to 10 as the FMEA.

Step 2: Interpret the results and identify the KPIV

The objective here is to finalise the identification of KPIV. For this:

  1. Identify Final score = Severity * Occurence * Detectability
  2. Classify scores in A, B, C or D
  3. Interpret the scores according to the following table:
> 200AThese Input are the process KPIVs that will be studied in the Analysis phase.
26 to 199BIf the severity level is between 7 and 10, set them as KPIV.

If the probability of occurrence is 9 or 10, set them as KPIV.
1 to 25CPut these Inputs under control.


The VMEA is built on the same principle as the FMEA. Nevertheless, there are still some differences:

Only applies to the KPIV of the process being studied.Applies to all types of data and variables.
Only used in the context of a DMAIC project.Used when we want to identify failure modes: product / process design ...
Focuses only on a scope and an identified process.Used on a process in its entirety.


B. Bergman, J. De Mare, S. Loren, T. Svensson (2009)-Robust Design Methodology for reliability

P. Johannesson, M. Speckert (2014)-Guide to load analysis for durability in vehicle engineering

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