Abstract
There exists a considerable literature on reliability growth modelling. Recently somecommon models have been extended to encompass innovation. They assume the time of aninnovation is known and that there is a coincidental improvement in performance. However,despite such developments, it remains that most models do not fully address the engineeringconcerns as they do not capture the underlying physical processes and they tend to beoptimistic about ensuing performance. This paper aims to address these issues by specifyinga general framework for reliability growth that supports more effective modelling. Further,we develop a strategy for using such models proactively during development to facilitatemeaningful improvements in reliability performance.
| Original language | English |
|---|---|
| Pages (from-to) | 11-24 |
| Number of pages | 13 |
| Journal | Annals of Operations Research |
| Volume | 91 |
| DOIs | |
| Publication status | Published - 1999 |
Keywords
- reliability growth
- innovation
- data analysis
- Bayesian statistics
- importance measures
- Monte Carlo Markov chains
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Cite this
Ansell, J. I., Walls, L. A., & Quigley, J. L. (1999). Achieving growth in reliability. Annals of Operations Research, 91, 11-24. https://doi.org/10.1023/A:1018985303897