The risks of applying qualitative reliability prediction methods: a case study

The fast technological innovation of the past decades contributed to an increasing complexity in products. This increased product complexity together with four different business drivers (time, profitability, functionality and quality) have an important influence on the reliability strategies used within companies. New methods are necessary to predict reliability in product design. In current business processes qualitative reliability prediction methods are often applied to estimate the reliability risks present in products and processes. An example of a popular qualitative reliability prediction method is the so-called failure mode and effects analysis (FMEA). Many successful implementations of the FMEA method are described in literature from various professional fields. On the other hand, several setbacks of the traditional FMEA approach are described in literature. Most of these drawbacks result from the qualitative analysis approach. Nevertheless, the FMEA reliability prediction method is probably the most implemented method in practice. Present-day companies do not seem to take notice of the drawbacks of qualitative reliability prediction methods as described in literature. A convincing reason for this is the fact that no proven alternatives exist for these qualitative methods. Therefore the goal of this paper is to illustrate the risks of applying qualitative reliability prediction methods in practice and make suggestions for improving the application of these methods. This illustration is based on a complete reliability prediction approach named ROMDA. This ROMDA approach adopts FMEA to predict product reliability and will be presented in the second section. Subsequently this ROMDA approach is applied in a practical situation after which the reliability predictions are evaluated. Based on this evaluation, general conclusions and recommendations are described in order to improve the application of qualitative reliability prediction methods in practice