|Abstract:||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.