Conference article

Probabilistic Variation Mode and Effect Analysis

Pär Johannesson
Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Sweden

Thomas Svensson
SP Technical Research Institute of Sweden

Leif Samuelsson
Volvo Aero Corporation, Sweden

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Published in: 10th QMOD Conference. Quality Management and Organiqatinal Development. Our Dreams of Excellence; 18-20 June; 2007 in Helsingborg; Sweden

Linköping Electronic Conference Proceedings 26:6, p.

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Published: 2008-02-15


ISSN: 1650-3686 (print), 1650-3740 (online)


An important goal of engineering design is to get a reliable system; structure or component. One such well-established method is FMEA (Failure Mode and Effect Analysis); where the aim is to identify possible failure modes and evaluate their effect. A general design philosophy; within robust design; is to make designs that avoid failure modes as much as possible; see e.g. (Davis; 2006). Further; it is important that the design is robust against different sources of unavoidable variation. A general methodology called VMEA (Variation Mode and Effect Analysis) has been developed in order to deal with this problem; see (Johansson; et al.; 2006) and (Chakhunashvili; et al.; 2006). The VMEA is split into three different levels; 1) basic VMEA; in the early design stage; when we only have vague knowledge about the variation; and the goal is to compare different design concepts; 2) advanced VMEA; further in the design process when we can better judge the sources of variation; and 3) probabilistic VMEA; in the later design stages where we have more detailed information about the structure and the sources of variation; and the goal is to be able to asses the reliability.

This paper treats the third level; the probabilistic VMEA; and we suggest a simple model; also used in (Svensson; 1997); for assessing the total uncertainty in a fatigue life prediction; where we consider different sources of variation; as well as statistical uncertainties and model uncertainties.


Probabilistic VMEA; fatigue life; life prediction; safety factor


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