Research, conducted in collaboration with a leading aerospace manufacturer, aimed to facilitate learning in order to improve the reliability of engineering systems during their development phase. In particular, the processes and mathematical models used during reliability growth testing were investigated to assess how they might be better used to support this improvement. This required both soft and hard OR approaches to be adopted. For example, information flows were mapped and reengineered in order to provide a basis for more effective data collection and feed-back to decision-makers. A new mathematical model that combines failure data with engineering judgement was developed to estimate reliability growth. The paper presents a case study describing the problem, the modelling conducted, the recommendations made and the actions implemented. The ways in which the researchers and the manufacturer learnt to improve both the modelling and the reliability growth testing process are reflected upon.
- decision support