Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/77753
Title: Some contributions to maintenance and accelerated degradation test under complex failure process
Authors: CHEN LIANGPENG
Keywords: reliability, life cycle, maintenance, degradation, stochastic process, testing
Issue Date: 20-Jan-2014
Source: CHEN LIANGPENG (2014-01-20). Some contributions to maintenance and accelerated degradation test under complex failure process. ScholarBank@NUS Repository.
Abstract: This thesis investigates several practical issues in maintenance and accelerated degradation testing (ADT), which are two important techniques implemented in the product/system's life cycle reliability engineering. First off, the statistical analysis of repairable systems provides useful tools to characterize and predict the system failure behaviour. In view of the widely observed bathtub type failure rate and intensity during the system lifetime, we propose a flexible superposed piecewise constant intensity model, which also takes into consideration the possible substantial changes/shifts due to rectifications/reliability growth at failures or other time epochs. Next, we broaden the context to consider repairable production systems, and derive an optimal bivariate maintenance policy to achieve the cost efficiency. Utilizing the modern monitoring technology, the condition-based maintenance is facilitated in recent years, we propose a competing risk model to incorporate both soft failure due to natural degradation and traumatic failure due to random shocks. We then analyse the system reliability and obtain a periodic inspection schedule with degradation-threshold based preventive maintenance. While maintenance is normally performed when the product is deployed to the field use, ADT is carried out in design and verification phase before the mass production. Note that the underlying degradation of some devices in practice cannot be well described by the existing models in ADT literature, we propose the implementation of an inverse Gaussian process. Optimal testing plans are derived to achieve good statistical precision in estimating the product's important reliability index, such as the life percentile. Finally, we pay attention to the practical ADT planning considering the estimation bias incurred due to the heterogeneity of field conditions.
URI: http://scholarbank.nus.edu.sg/handle/10635/77753
Appears in Collections:Ph.D Theses (Open)

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