A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. Johannesburg, December 2014. / Industrial units cannot operate without failure forever. When the operation of a unit deviates from industrial standards, it is considered to have failed. The time from the moment a unit enters service until it fails is its lifetime. Within reliability and often in life data analysis in general, lifetime is the event of interest. For highly reliable units, accelerated life testing is required to obtain lifetime data quickly. Accelerated tests where failure is not instantaneous, but the end point of an underlying degradation process are considered. Failure during testing occurs when the performance of the unit falls to some specified threshold value such that the unit fails to meet industrial specifications though it has some residual functionality (degraded failure) or decreases to a critical failure level so that the unit cannot perform its function to any degree (critical failure). This problem formulation satisfies the random signs property, a notable competing risks formulation originally developed in maintenance studies but extended to accelerated testing here. Since degraded and critical failures are linked through the degradation process, the open problem of modelling dependent competing risks is discussed. A copula model is assumed and expert opinion is used to estimate the copula. Observed occurrences of degraded and critical failure times are interpreted as times when the degradation process first crosses failure thresholds and are therefore postulated to be distributed as inverse Gaussian. Based on the estimated copula, a use-level unit lifetime distribution is extrapolated from test data. Reliability metrics from the extrapolated use-level unit lifetime distribution are found to differ slightly with respect to different degrees of stochastic dependence between the risks. Consequently, a degree of dependence between the risks that is believed to be realistic to admit is considered an important factor when estimating the use-level unit lifetime distribution from test data. Keywords: Lifetime; Accelerated testing; Competing risks; Copula; First passage time.

Orientador: Marcos Antonio Correa / Resumo: O ácido p-cumárico (APC) é um composto fenólico não flavonóide que apresenta segurança e eficácia bem descritas na ciência dos alimentos devido suas propriedades antioxidante, antitumoral, anti-inflamatória, antimicrobiana e por apresentar baixa toxicidade oral. Essas propriedades são pouco exploradas em produtos para cuidados com a pele. O objetivo do presente estudo foi avaliar de forma in vitro a segurança e a eficácia do APC e incorporá-lo em emulsão cosmética óleo em água (O/A). Nossos estudos in vitro e alternativos ao uso de animais foram conduzidos para verificar a citotoxicidade do APC em células de queratinócitos (HaCat) e fibroblastos humanos (HDFa), o potencial de irritação ocular (HET-CAM) e a atividade antimicrobiana em diferentes cepas. Emulsões contendo APC foram submetidas ao estudo de estabilidade e de liberação, retenção e permeação cutâneas. Resultados: o IC50 do APC em células HaCat e HDFa foi 693,57 e 2.814,75 μg/mL, respectivamente. Além disso 100 μg de APC foram levemente tóxicos em membrana corioalantóica de ovo embrionado. As concentrações bactericidas mínimas em cepas de E. coli, S. aureus, P. aeruginosa e S. epidermidis, foram 3.000 μg/mL, 1.875 μg/mL, 3.750 μg/mL e 3.750 μg/mL, respectivamente. Emulsões contendo diferentes concentrações de APC foram estáveis durante o período de estabilidade acelerada. Após 12 horas 91,08 ± 0,03% do APC foi liberado da formulação e após 24 horas, 0,52 ± 0,18% e 0,94 ± 0,37% ficaram retidos no estrato córneo e na e... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: p-Coumaric acid (PCA) is a non flavonoid phenolic compound whose safety and efficacy widely described in food science papers due to antioxidant, antitumor, anti inflammatory properties, and low oral toxicity. These characteristics are poorly or no described when PCA is added to skin care products. The aim of the present study was to evaluate the safety and efficacy of PCA through in vitro assays, and then add it in oil in water cosmetic emulsion (O/W). Our in vitro trials, without animal use were conducted to predict PCA´s cytotoxicity in HaCat and HDFa cells, ophthalmic irritation potential, and antibacterial activity against differents strains. Emulsions with PCA has been tested to predict shelf life, dermal absorption, and dermal retention. Results: PCA´s IC50 in HaCat and HDFa cells was 693.57 and 2,814.75 μg.mL-1, respectively. In addition 100 μg of APC were slightly toxic in chorioallantoic membrane assay. The minimum bactericidal concentrations against E. coli, S. aureus, P. aeruginosa and S. epidermidis strains were 3,000 μg.mL-1, 1,875 μg.mL-1, 3,750 μg.mL-1, and 3,750 μg.mL-1 , respectively. Emulsions containing 0.04%, 0.06%, 0.08% and 0.10% of PCA were stable during self life testing for ninety days. After 12 hours 91.08 ± 0.03% of PCA was released of the emultion, and after 24 hours 0.52 ± 0.18% and 0.94 ± 0.37%, were present in stratum corneum and epidermis/dermis, respectively. Our findings indicate that PCA concentrations would be effective and safe to use in c... (Complete abstract click electronic access below) / Mestre

In this thesis, vibration induced fatigue life analysis of axial leaded Tantalum &amp / Aluminum capacitors, PDIP and SM capacitors mounted on the printed circuit boards are performed. This approach requires the finite element model, material properties and dynamic characteristics of the PCB. The young modulus of the PCB material is obtained from 3 point bending tests, resonance frequencies are obtained from modal tests and transmissibility&amp / #8217 / s of the PCB are obtained from transmissibility tests which are used as fatigue analysis inputs. Step Stress Tests are performed to obtain failure times of the tested electronic components which are also used as the numerical fatigue analysis inputs. Consecutively, fatigue analysis of a sample PCB used in military systems is aimed since it is important to compare the calculated fatigue damage to estimated life limits in order to determine which component(s), if necessary, must be moved to positions of lower damage . For this purpose, power PCB of the power distribution unit used in Leopard 1 battle tank is examined. Numerical fatigue analysis coupled with accelerated life test whose profile is convenient to military platforms is performed. Furthermore, the effects of eccobond and silicone on the fatigue life of the components are also surveyed since these techniques are common in electronic packaging. In addition, mean-time-to-failure values are obtained for the tested components by using Weibull distribution. Finally, sensitivity analysis is performed to indicate the effect of certain parameters on the fatigue life of a sample axial leaded capacitor.

ABSTRACT VIBRATION FATIGUE ANALYSIS OF EQUIPMENTS USED IN AEROSPACE AYKAN, Murat M.Sc., Department of Mechanical Engineering Supervisor: Assoc. Prof. Dr. F. Suat KADIOgLU Co-Supervisor: Assoc. Prof. Dr. Mehmet &Ccedil / ELiK June 2005, 123 Pages Metal Fatigue of dynamically loaded structures is a very common phenomenon in engineering practice. As the loading is dynamic one cannot neglect the dynamics of the structure. When the loading frequency has a wide bandwidth then there is high probability that the resonance frequencies of the structure will be excited. When this happens then one cannot assume that the structures response to the loading will remain linear in the frequency domain. Thus to overcome such situations frequency domain fatigue analysis methods exist which include the dynamics of the structure. In this thesis, a Helicopters Self-Defensive System&rsquo / s Chaff/Flare Dispenser Bracket is analyzed by Vibration Fatigue Method as a part of an ASELSAN project. To obtain the loading (boundary conditions), operational flight tests with accelerometers were performed. The obtained acceleration versus time signals are analyzed and converted to Power Spectral Densities (PSD), which are functions of frequency. In order to obtain the stresses for fatigue analysis, a finite element model of the bracket has been created. The dynamics of the finite element model was verified by performing experimental modal tests on a prototype. From the verified model, stress transfer functions have been obtained and combined with the loading PSD&rsquo / s to get the response stress PSD&rsquo / s. The fatigue analysis results are verified by accelerated life tests on the prototype. Also in this study, the effect of single axis shaker testing for fatigue on the specimen is obtained.

The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the same end-goals as Reliability Centered Maintenance (RCM). RCM was first introduced to the aircraft industry in an attempt to bridge the gap between the empirically-driven and theory-driven approaches to establishing optimal maintenance policies. Under RCM, qualitative processes that enable the prioritizing of functions based on the criticality and influence would be combined with mathematical modeling to obtain the optimal maintenance policies. Where this thesis work deviates from RCM is its proposal to directly apply quantitative processes to model the reliability measures in optimal maintenance problem. First, Monte Carlo (MC) simulation, in conjunction with a pre-determined Design of Experiments (DOE) table, can be used as a numerical means of obtaining the corresponding discrete simulated outcomes of the reliability measures based on the combination of decision variables (e.g., periodic preventive maintenance interval, trigger age for opportunistic maintenance, etc.). These discrete simulation results can then be regressed as Response Surface Equations (RSEs) with respect to the decision variables. Such an approach to represent the reliability measures with continuous surrogate functions (i.e., the RSEs) not only enables the application of the numerical optimization technique to solve for optimal maintenance policies, but also obviates the need to make mathematical assumptions or impose over-simplifications on the structure of a multi-unit system for the sake of mathematical tractability. The applicability of the proposed methodology to a real-world optimal maintenance problem is showcased through its application to a Time Limited Dispatch (TLD) of Full Authority Digital Engine Control (FADEC) system. In broader terms, this proof-of-concept exercise can be described as a constrained optimization problem, whose objective is to identify the optimal system inspection interval that guarantees a certain level of availability for a multi-unit system. A variety of reputable numerical techniques were used to model the problem as accurately as possible, including algorithms for the MC simulation, imperfect maintenance model from quasi renewal processes, repair time simulation, and state transition rules. Variance Reduction Techniques (VRTs) were also used in an effort to enhance MC simulation efficiency. After accurate MC simulation results are obtained, the RSEs are generated based on the goodness-of-fit measure to yield as parsimonious model as possible to construct the optimization problem. Under the assumption of constant failure rate for lifetime distributions, the inspection interval from the proposed methodology was found to be consistent with the one from the common approach used in industry that leverages Continuous Time Markov Chain (CTMC). While the latter does not consider maintenance cost settings, the proposed methodology enables an operator to consider different types of maintenance cost settings, e.g., inspection cost, system corrective maintenance cost, etc., to result in more flexible maintenance policies. When the proposed methodology was applied to the same TLD of FADEC example, but under the more generalized assumption of strictly Increasing Failure Rate (IFR) for lifetime distribution, it was shown to successfully capture component wear-out, as well as the economic dependencies among the system components.

We consider the problem of estimating the failure stresses of bundles (i.e. the tensile forces that destroy the bundles), constructed of several statisti-cally similar fibres, given a particular kind of censored data. Each bundle consists of several fibres which have their own independent identically dis-tributed failure stresses, and where the force applied on a bundle at any moment is distributed equally between the unbroken fibres in the bundle. A bundle with these properties is an example of an equal load-sharing sys-tem, often referred to as the Daniels failure model. The testing of several bundles generates a special kind of censored data, which is complexly struc-tured. Strongly consistent non-parametric estimators of the distribution laws of bundles are obtained by applying the theory of martingales, and by using the observed data. It is proved that random sampling, with replace-ment from the statistical data related to each tested bundle, can be used to obtain asymptotically correct estimators for the distribution functions of deviations of non-parametric estimators from true values. In the case when the failure stresses of the fibres are described by a Weibull distribution, we obtain strongly consistent parametric maximum likelihood estimators of the distribution functions of failure stresses of bundles, by using the complexly structured data. Numerical examples illustrate the behavior of the obtained estimators.

No description available.

No description available.

No description available.

The objective of the proposed research is to develop statistical algorithms for controlling failure trends through targeted maintenance of at-risk components. The at-risk components are identified via chronological history and diagnostic data, if available. Utility systems include many thousands (possibly millions) of components with many of them having already exceeded their design lives. Unfortunately, neither the budget nor manufacturing resources exist to allow for the immediate replacement of all these components. On the other hand, the utility cannot tolerate a decrease in reliability or the associated increased costs. To combat this problem, an overall maintenance model has been developed that utilizes all the available historical information (failure rates and population sizes) and diagnostic tools (real-time conditions of each component) to generate a maintenance plan. This plan must be capable of delivering the needed reliability improvements while remaining economical. It consists of three facets each of which addresses one of the critical asset management issues: * Failure Prediction Facet - Statistical algorithm for predicting future failure trends and estimating required numbers of corrective actions to alter these failure trends to desirable levels. Provides planning guidance and expected future performance of the system. * Diagnostic Facet - Development of diagnostic data and techniques for assessing the accuracy and validity of that data. Provides the true effectiveness of the different diagnostic tools that are available. * Economics Facet - Stochastic model of economic benefits that may be obtained from diagnostic directed maintenance programs. Provides the cost model that may be used for budgeting purposes. These facets function together to generate a diagnostic directed maintenance plan whose goal is to provide the best available guidance for maximizing the gains in reliability for the budgetary limits utility engineers must operate within.