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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

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Modeling reliabilty growth in the product design process

Krasich, M. and Quigley, J.L. and Walls, L.A. (2004) Modeling reliabilty growth in the product design process. Proceedings of the Annual Reliability and Maintainability Symposium. pp. 424-430.

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Relying on reliability growth testing to improve system design is not always cost effective and certainly not efficient. Instead, it is important to design in reliability. This requires models to estimate reliability growth in the design and to assess whether goal reliability will be achieved within the target timescale. While many models have been developed for analysis of reliability growth in test, there has been less attention given to reliability growth in design. This paper proposes and compares two models - one motivated by the practical engineering process (the modified power law) and the other by extending the reasoning of statistical reliability growth modeling (the modified IBM). The commonalities and differences between these models are explored through an assessment of their logic and an application. We conclude that the choice of model depends on the growth process being modeled. Key drivers are the type of system design and the project management of the growth process. When the design activities are well understood and project workloads can be managed evenly, leading to predictable and equally spaced modifications each of which having a similar effect on the reliability of the item, then the modified power law is a more appropriate model. On the other hand, the modified IBM is more appropriate for more uncertain situations, where the reliability improvement of a design is driven by the removal of faults, which are yet unknown and only through further investigation of the design, these can be identified. These situations have less predictable workloads and fewer modifications are likely later on in the project.