No description available.

The goal of service life prediction is to accurately predict the useful lifetime of a coating system in a typical service environment. Field testing is the most true-to-life form of service life testing but requires long exposure times, often not quick enough to readily aid redesign in the product development cycle. As an alternative, accelerated weathering chambers are used to speed up coating failure in a laboratory setting. These devices do indeed accelerate failure but often produce failure modes that are not seen in actual service or produce material rankings that are not reproducible. This work explores the principle of cumulative stressor damage for an exterior architectural coating being exposed to outdoor conditions in San Luis Obispo, California, as well as an accelerated UV/moisture protocol. The accelerated UV/moisture protocol is executed first by ASTM D4587, and then by creating a custom exposure test cycle based on locally observed weather. Comparison of failure mode and quantification of failure is determined by gloss and spectral reflectance measurements. Finally, acceleration factor determination for the new SLO-in-a-box protocol is outlined, with a discussion of preliminary results.

Yes / Variable-displacement vane oil pumps are increasingly employed in automotive powertrains for their efficiency benefits through reduced losses. However, confirming long life reliability of a new commodity based on limited data available from product development tests and early field experience is a significant challenge, which is addressed by the work presented in this paper. The approach presented combines physical examination of pumps returned from tests, with analysis of damage factors for pump wear progression, and an analysis of functional parameters for the powertrain system focused on the cause effect linkages across the systems hierarchy. The metrology results from physical measurements of used parts provide useful insights for the wear progression and the expected service performance of the pump. The paper also expands towards a data driven approach based on ECU data analysis that could provide a pathway towards the development of online health monitoring and diagnostics of the oil pumps. / Research project: “Intelligent Personalised Powertrain Health Care”, funded by Jaguar Land Rover.

This study was aimed at exploring data analysis techniques for generating accurate estimates of the loss in quality of fresh fruits, vegetables and cut flowers in chilled supply chains based on data from advanced sensors. It was motivated by the recent interest in the application of advanced sensors, by emerging concepts in quality controlled logistics, and by the desire to minimise quality losses during transport and storage of the produce. Cut roses were used in this work although the findings will also be applicable to other produce. The literature has reported that whilst temperature was considered to be the most critical post-harvest factor, others such as growing conditions could also be important in the senescence of cut roses. Kinetic modelling was the most commonly used modelling approach for shelf life predictions of foods and perishable produce, but not for estimating vase life (VL) of cut flowers, and so this was explored in this work along with multiple linear regression (MLR) and partial least squares (PLS). As the senescence of cut roses is not fully understood, kinetic modelling could not be implemented directly. Consequently, a novel technique, called Kinetic Linear System (KLS), was developed based on kinetic modelling principles. Simulation studies of shelf life predictions for tomatoes, mushrooms, seasoned soybean sprouts, cooked shrimps and other seafood products showed that the KLS models could effectively replace the kinetic ones. With respect to VL predictions KLS, PLS and MLR were investigated for data analysis from an in-house experiment with cut roses from Cookes Rose Farm (Jersey). The analysis concluded that when the initial and final VLs were available for model calibration, effective estimates of the post-harvest loss in VL of cut roses could be obtained using the post-harvest temperature. Otherwise, when the initial VLs were not available, such effective estimates could not be obtained. Moreover, pre-harvest conditions were shown to correlate with the VL loss but the correlation was too weak to produce or improve an effective estimate of the loss. The results showed that KLS performance was the best while PLS one could be acceptable; but MLR performance was not adequate. In another experiment, boxes of cut roses were transported from a Kenyan farm to a UK distribution centre. Using KLS and PLS techniques, the analysis showed that the growing temperature could be used to obtain effective estimates of the VLs at the farm, at the distribution centre and also the in-transit loss. Further, using post-harvest temperature would lead to a smaller error for the VL at the distribution centre and the VL loss. Nevertheless, the estimates of the VL loss may not be useful practically due to the excessive relative prediction error. Overall, although PLS had a slightly smaller prediction error, KLS worked effectively in many cases where PLS failed, it could handle constraints while PLS could not.In conclusion, KLS and PLS can be used to generate effective estimates of the post-harvest VL loss of cut roses based on post-harvest temperature stresses recorded by advanced sensors. However, the estimates may not be useful practically due to significant relative errors. Alternatively, pre-harvest temperature could be used although it may lead to slightly higher errors. Although PLS had slightly smaller errors KLS was more robust and flexible. Further work is recommended in the objective evaluations of product quality, alternative non-linear techniques and dynamic decision support system.

<p>The built environment usually constitutes a very importantpart of the real capital of a nation and the constructionsector represents more than 10% of the yearly Gross NationalProduct of the industrialised world. The importance of goodplanning of all construction, where the service life of thework is considered, is of great interest and an importantaspect in sustainability considerations. The need for increasedknowledge about degradation of materials, for structuredmethodology, and for working tools for those involved in theplanning process, has resulted in an extensive effort inpre-normative research and standardisation regarding thisfield.</p><p>This thesis presents a discussion on service life planningand the role of the Factor Method in such a work, andespecially, discussion of modification and development of themethodology. In the design process, the need to evaluate theservice life of products is great, and this is a formidableproblem to solve, as the results will depend on both materialproperties and the environment in which the material is placedor used. A practical solution has to be based on a goodknowledge in the field, but also on a sound working strategy,to ensure that different design scenarios can be compared in astandardised or structured way. The Factor Method is apromising working tool for such an evaluation and comparison,but is as such, still more of a methodology, than a method.Examples of the use of the methodology are still very limitedand the method as such, is much discussed by researchers.However, its future will depend on how practical it will be toapply in use. The method is useful to estimate the service lifeof products, based on a known reference service life and anumber of modifying factors that will depend on the conditiondifferences between the specific project and the referencein-use conditions. The required precision of such a methodologyis discussed, especially in the light of inherent distributionin material properties and the fact that often the consequencesof failure are very limited. In such cases, the standardisedFactor Method is considered to be of great use and should giveparties involved a good means for working in a structured andsystematic way.</p>

<p>The built environment usually constitutes a very important part of the real capital of a nation, and the construction sector represents more than 10% of the yearly Gross National Product of the industrialised world. Good planning of all construction is important, and consideration of the service life of the work is of great interest and is a significant aspect of sustainability considerations. The need for more knowledge about degradation of materials, for structured methodology, and for working tools for those involved in the planning process, has resulted in an extensive effort in pre-normative research and standardisation regarding this field.</p><p>This thesis presents a discussion on service life planning and the role of the Factor Method in such work, and especially, discussion of modification and development of the methodology. In the design process, the need to evaluate the service life of products is a great challenge, as the results will depend on both material properties and the environment in which the material is placed or used. A practical solution has to be based on a good knowledge in the field, but also on a sound working strategy, to ensure that different design scenarios can be compared in a standardised or structured way. The Factor Method is a promising working tool for such an evaluation and comparison, but is as such, still more of a methodology, than a method. Examples of the use of the methodology are still very limited, and the method as such, is much discussed by researchers. However, its future will depend upon how practical it will be to apply in use. The method is useful to estimate the service life of products, based on a known reference service life and a number of modifying factors. These factors in turn depend on the conditional differences between the specific project and the reference, in-use conditions. This thesis discusses the required precision of such a methodology, especially in light of inherent distributions in material properties, and the fact that the consequences of failure are often very limited. In such cases, the standardised Factor Method is considered to be quite useful, and should give the parties involved a good means for working in a structured and systematic way. </p>

The huge landfills from solid waste generated by the massive utilisation of different products from domestic sources are badly affecting the environment. About 70% of the solid municipal waste, two thirds of which comprises of household waste, is dumped as landflll all over the world. For efficient product lifecycle management via upgrade, maintenance, reuse, refurbishment, and reclamation of components etc., storage of product related information throughout its lifecycle is indispensable. Efficient use of information technology integrated with product design can enable products to manage themselves in a semiautomatic and intelligent manner. It means that products themselves should contain informationú that what to do with them when they are of no use. More advanced products may locate themselves and communicate with their recyclers through internet or some other communication technology. In this regard, different types of technologies have been investigated. These technologies are broadly classified as passive embedded information devices and active embedded information devices. Methods of automatic identification in combination with information technology can act as passive Embedded Information Devices (EID) to make products intelligent enough in order to manage associated information throughout their life cycles. Barcodes, Radio Frequency Identification tags, and a new technology called i-button technology were investigated as possible candidates for passive EIDs. The ibutton technology from the perspective of product lifecycle management is presented for the very first time in the literature. Experiments demonstrated that RFID and i-button technologies have potential to store not only the static but dynamic data up to some extent, such as small maintenance logs. As passive EIDs are unable to store the sensory data and detailed maintenance logs regarding a product, therefore, in addition to these demonstrators for passive EIDs, an advanced active EID demonstrator for lifecycle management of products with high functional complexity is also presented. Initially, the idea is presented as smart EID system that r~cords the sensory data of a refrigerator compressor and stores the detailed maintenance logs into the product itself. However, this idea is extended as intelligent EID that is implemented on a gearbox in order to predict the gearbox lifetime under an accelerated life test. This involves developmen,t of a novel on-chip life prediction algorithm to predict the gearbox lifetime under accelerated life testing scenario. The algorithm involves a combination of artificial neural networks and an appropriate reliability distribution. Results of accelerated life testing, simulation for the choice of appropriate reliability distribution and the life prediction algorithm are presented. Bi-directional communication software that is developed in order to retrieve lifecycle data from the intelligent EID and to keep intelligent EID updated is also explained. Overall, embedded information devices can be proposed as a good solution to support a sustainable approach to lifecycle management.

Micro-milling represents a versatile and fast manufacturing process suitable for production of fully 3D micro-components. Such components are demanded for a vast number of industrial applications including safety systems, environmental sensors, personalized medical devices or micro-lenses and mirrors. The ability of micro-milling to process a wide range of materials makes it one of the best candidates to take a leading position in micromanufacturing. However, so far it does not seem to happen. By discussion with various industrialists, low predictability of micro-milling process was identified as the major limiting factor. This is mainly because of strong effects of the tool tolerances and process uncertainties on machining performance. Although, these issues are well known, they are not reflected by the current modelling methods used in micro-milling. Therefore, the research presented in this thesis mainly concentrates on development of a method allowing a prediction of the tool life in manner of tool breakage probability. Another important criterion which must be fulfilled is the method applicability to industrial applications. This means that the method must give sufficiently accurate prediction in reasonable time with minimum effort and interactions with day-to-day manufacturing process. The criteria listed above led to development of a new method based on analytically/numerical modelling techniques combined with an analysis of real tool variations and process uncertainty. Although, the method is presented in a relatively basic form, without considering some of the important factors, it shows high potential for industrial applications. Possibility of further implementation of additional factors is also discussed in this thesis. Additionally, some of the modelling techniques presented in this thesis are assumed to be suitable for application during designing of micro end-mills. Therefore, in the last part of this thesis is presented a systematic methodology for designing of micro end-mills. This method is based on knowledge and experience gained during this research.

Cast aluminum alloys are common in automotive and aerospace applications due to their high strength-to-density ratio. Fracture data for cast aluminum alloys, such as fatigue life, tensile strength and elongation, are heavily affected by the structural defects, such as pores and bifilms. There have been numerous studies in which either fatigue performance or tensile deformation were characterized and linked to casting defects. However, a comprehensive study that correlates tensile and fatigue properties has not been reported. The present study is motivated to fill this gap. The main objective of the investigation is to analyze the link between tensile and fatigue performance of commonly used cast aluminum alloys, and determine whether fatigue performance of cast aluminum alloys can be predicted. To accomplish this task, four research questions were developed: (i) how well do equations developed to account for mean stress effects perform in cast aluminum alloys, especially in datasets with various levels of structural quality, (ii) is the strong correlation between fatigue life and structural quality index obtained from tensile data reported for A206 alloy castings applicable to other aerospace and automotive casting alloys, (iii) how do methods to estimate high cycle fatigue from tensile data perform with aluminum castings, and (iv) can the axial fatigue performance of an A356-T6 casting be predicted from rotating beam fatigue data. Among the three mean stress correction models analyzed by using seven datasets from the literature, the one developed by Walker with an adjustable exponent has provided the best fit. It has been hypothesized that the adjustable Walker parameter is related to the structural quality index, QT, estimated from tensile data. Results have shown that there is indeed a strong correlation between QT and the Walker parameter. Moreover the parameters of the xvi Weibull distribution estimated from corrected data have been found to be strongly influenced by the mean stress correction method used. Tensile and fatigue life data for 319, D357 and B201 aluminum alloy castings reported in the literature have been reanalyzed by using a maximum likelihood method to estimate Basquin parameters in datasets with run-outs, Weibull statistics for censored data and mean stress correction. After converting tensile data to QT, a distinct relationship has been observed between the expected fatigue life and mean quality index for all alloys. Moreover, probability of survival in fatigue life has been found to be directly linked to the proportions of the quality index distributions in two different regions, providing further evidence about the strong relationship between elongation, i.e., structural quality, and fatigue performance [1]. Specimen geometry has been found to make the largest difference whereas the two aerospace alloys, B201 and D357, with distinctly different microstructures, have followed the same relationship, reinforcing the findings in the literature that fatigue life in aluminum castings is mainly determined by the size distribution and number density of structural defects. Six methods to predict fatigue life from tensile data have been compared by using data from the literature as well as the experimental A356 data developed in this study. Results have shown that none of the six methods provide reliable results. The consistently poor performance of the methods developed for steels and wrought alloys can be attributed to the major structural defects, namely bifilms, in aluminum castings. A new method to estimate the S-N curve from tensile data have been developed by using data for seventy-one S-N curves have been collected and Basquin parameters have been determined. Analysis showed that there is a strong relationship between QT and the Basquin exponent. xvii The Basquin parameters estimated by using the empirical relationships developed in the present study have provided better fits to the same datasets tested for the six methods. Hence the model developed in this study is proposed as the most reliable method to estimate high cycle fatigue properties. Finally, three methods to convert rotating bending fatigue test results to uniaxial fatigue data have been investigated by using the data developed in this study. Results have indicated that the method developed by Esin, in which both the fatigue life and alternating stress are corrected, provide the best estimate. Analyses of fracture surfaces of broken specimens via scanning electron microscopy have shown that tensile, axial fatigue and rotating beam fatigue properties are all strongly influenced by the same structural defects, confirming the validity of the approach taken in this study.

This work employs statistical and Bayesian techniques to analyze mathematical forward models with several sources of uncertainty. The forward models usually arise from phenomenological and physical phenomena and are expressed through regression-based models or partial differential equations (PDEs) associated with uncertain parameters and input data. One of the critical challenges in real-world applications is to quantify uncertainties of the unknown parameters using observations. To this purpose, methods based on the likelihood function, and Bayesian techniques constitute the two main statistical inferential approaches considered here. Two problems are studied in this thesis. The first problem is the prediction of fatigue life of metallic specimens. The second part is related to inverse problems in linear PDEs. Both problems require the inference of unknown parameters given certain measurements. We first estimate the parameters by means of the maximum likelihood approach. Next, we seek a more comprehensive Bayesian inference using analytical asymptotic approximations or computational techniques. In the fatigue life prediction, there are several plausible probabilistic stress-lifetime (S-N) models. These models are calibrated given uniaxial fatigue experiments. To generate accurate fatigue life predictions, competing S-N models are ranked according to several classical information-based measures. A different set of predictive information criteria is then used to compare the candidate Bayesian models. Moreover, we propose a spatial stochastic model to generalize S-N models to fatigue crack initiation in general geometries. The model is based on a spatial Poisson process with an intensity function that combines the S-N curves with an averaged effective stress that is computed from the solution of the linear elasticity equations.