No / This paper presents a framework for life prediction modelling and illustrates it with a case study of a plastic automotive component subjected to competing failure mechanisms: wear, leading to a soft failure-degradation of functional performance, and fatigue, leading to loss of function through fracture of a main sub-component. The paper focuses on developing a life prediction model for the fatigue failure mechanism. Structural and kinematic analysis of the component was conducted to identify a suitable substitute load characteristic for the failure mechanism. The aim is to develop an approximate model using limited testing data and when a baseline stress-life model is not available. The issues highlighted by the case study are generic to development of life models for non-critical automotive components, thus providing potentially wide scope for practical application of the approach.

Investment decisions on electric power networks have developed to balance network functionality and cost efficiency by analyzing the main risks associated with network operation. Ageing infrastructures, like large power transformers in particular, aggravate the stress of management, because the failure of a power transformer could cause power supply interruption, network reliability reduction, large economic losses and also environment impacts. Transformer asset management is therefore aimed to develop a cost-efficient replacement strategy to get the most usage of transformers. The main objective of this thesis is to understand how UK National Grid transformer assets failure trend can be used, as the engineering evidence to help make financial decisions related to transformer replacements. The studies in this thesis are implemented via two main approaches. First statistical analyses methods are undertaken. This approach is realized to be non-optimal, because the transformer failure mechanism at the normal operation stage is different from that when transformers are aged. Secondly, the transformer physical ageing model is used to estimate thermal lifetimes under the ageing failure mechanism. In conjunction with the random hazard rate obtained by statistical analyses, the actual National Grid transformer population failure hazard with service age is derived. Statistical analyses are carried out based on the ages of National Grid failed and in-service transformers. Transformer lifetime data are fitted into various distribution models by the least square estimator (LSE) and maximum likelihood estimator (MLE). Statistics are however powerless to suggest the population future failure trend due to their intrinsic limitations. National Grid operational experience actually indicates a stable and low value of the random failure hazard rate during the transformer early operation ages. The engineering knowledge however suggests an ageing failure mechanism exists which corresponds to an increasing hazard in the future. Transformer lifetime under ageing failure mechanism is conservatively indicated by its thermal end-of-life corresponding to a specific level of insulation paper mechanical strength. By analyzing National Grid scrapped transformers’ lowest degree of polymerization (DP), these transformers are estimated to have deteriorated at different rates and their thermal lifetimes distribute over a wide age range. The limited number of scrapped transformers cannot adequately indicate the ageing status of the whole population. A transformer’s thermal lifetime is determined by its loading condition, thermal design characteristics and installation site ambient temperature. However, these input data are usually incomplete for an individual transformer.A simplified approach is developed to predict the National Grid in-service transformer’s thermal lifetime by using information from scrapped transformers. The in-service transformer population thermal hazard curve under ageing failure mechanism can thus be obtained.Due to the independent effect from transformer random failure mechanism and ageing failure mechanism, the National Grid transformer population actual failure hazard curve with age is therefore derived as the superposition of the random failure hazard and the thermal hazard. Transformer asset managers are concerned about the knee point age, since aged transformer assets threaten network reliability and the transformer replacement strategy needs to be implemented effectively.

The prospect of reducing environmental impacts is a key driver for the research and development (R&D) of new forest products. Life cycle assessment (LCA) is often used for assessing the environmental impact of such products, e.g. for the purpose of guiding R&D. The aim of this thesis is to improve the methods and practices of LCA work carried out in the R&D of forest products. Six research questions were formulated from research needs identified in LCA work in five technical inter-organisational R&D projects. These projects also provided contexts for the case studies that were used to address the research questions. The main contributions of the research are as follows: Regarding the planning of LCA work in inter-organisational R&D projects, the research identified four characteristics that appear to be important to consider when selecting the roles of LCAs in such projects: (i) the project’s potential influence on environmental impacts, (ii) the degrees of freedom available for the technical direction of the project, (iii) the project’s potential to provide required input to the LCA, and (iv) access to relevant audiences for the LCA results. Regarding the modelling of future forest product systems, it was found that (i) it is important to capture uncertainties related to the technologies of end-of-life processes, the location of processes and the occurrence of land use change; and (ii) the choice of method for handling multi-functionality can strongly influence results in LCAs of forest products, particularly in consequential studies and in studies of relatively small co-product flows. Regarding the assessment of environmental impacts of particular relevance for forest products, it was found that using established climate impact assessment practices can cause LCA practitioners to miss environmental hot-spots and make erroneous conclusions about the performance of forest products vis-à-vis non-forest alternatives, particularly in studies aimed at short-term impact mitigation. Also, a new approach for inventorying water cycle alterations was developed, which made it possible to capture catchment-scale effects of forestry never captured before. To connect the LCA results to global challenges, a procedure was proposed for translating the planetary boundaries into absolute product-scale targets for impact reduction, e.g. to be used for evaluating interventions for product improvements or for managing trade-offs between impact categories.