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.
Introduction
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:
- Identify Final score = Severity * Occurence * Detectability
- Classify scores in A, B, C or D
- Interpret the scores according to the following table:
Score | Class | Interpretations |
---|---|---|
> 200 | A | These Input are the process KPIVs that will be studied in the Analysis phase. |
26 to 199 | B | If 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 25 | C | Put these Inputs under control. |
VMEA vs FMEA
The VMEA is built on the same principle as the FMEA. Nevertheless, there are still some differences:
VMEA | FMEA |
---|---|
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. |
Source
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