Reliability of products is here regarded with respect to failure avoidance rather than probability of failure. To avoid failures,we emphasize variation and suggest some powerful tools for handling failures due to variation. Thus, instead of technicalcalculation of probabilities from data that usually are too weak for correct results, we emphasize the statistical thinking thatputs the designers focus on the critical product functions.Making the design insensitive to unavoidable variation is called robust design and is handled by (i) identification andclassification of variation, (ii) design of experiments to find robust solutions, and (iii) statistically based estimations of propersafety margins.Extensions of the classical failure mode and effect analysis (FMEA) are presented. The first extension consists of identifyingfailure modes caused by variation in the traditional bottom–up FMEA analysis. The second variation mode and effect analysis(VMEA) is a top–down analysis, taking the product characteristics as a starting point and analyzing how sensitive thesecharacteristics are to variation.In cases when there is sufficient detailed information of potential failure causes, the VMEA can be applied in its mostadvanced mode, the probabilistic VMEA. Variation is then measured as statistical standard deviations, and sensitivities aremeasured as partial derivatives. This method gives the opportunity to dimension tolerances and safety margins to avoidfailures caused by both unavoidable variation and lack of knowledge regarding failure processes