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[en] This paper considers the design of life-test sampling plans based on failure-censored accelerated life tests. The lifetime distribution of products is assumed to be Weibull with a scale parameter that is a log linear function of a (possibly transformed) stress. Two levels of stress higher than the use condition stress, high and low, are used. Sampling plans with equal expected test times at high and low test stresses which satisfy the producer's and consumer's risk requirements and minimize the asymptotic variance of the test statistic used to decide lot acceptability are obtained. The properties of the proposed life-test sampling plans are investigated
[en] In some environments, components might not always fail fully, but can degrade, and there can be multiple stages of degradation. In such cases, the efficiency of the system may decrease. After a certain stage of degradation the efficiency of the system may decrease to an unacceptable limit and can be considered as a total failure. However, the system can fail randomly from any stage. and can be repaired. Further, the repair action cannot bring the system to the good stage, but can make it operational and the failure rate of the system will, therefore, remain the same as before the failure. In this study, we present a model for predicting the reliability, availability, mean life time, and mean time to first failure of multistage degraded systems with partial repairs. In the analysis, state dependent transition rates for the degradation process, as well as repair processes, are considered. A numerical example is provided to illustrate the results
[en] This paper develops two component-level control-limit preventive maintenance (PM) policies for systems subject to the joint effect of partial recovery PM acts (imperfect PM acts) and variable operational conditions, and investigates the properties of the proposed policies. The extended proportional hazards model (EPHM) is used to model the system failure likelihood influenced by both factors. Several numerical experiments are conducted for policy property analysis, using real lifetime and operational condition data and typical characterization of imperfect PM acts and maintenance durations. The experimental results demonstrate the necessity of considering both factors when they do exist, characterize the joint effect of the two factors on the performance of an optimized PM policy, and explore the influence of the loading sequence of time-varying operational conditions on the performance of an optimized PM policy. The proposed policies extend the applicability of PM optimization techniques.
[en] Since the Second World War, the philosophy behind the quality systems of industries and service companies has evolved to embrace the whole life cycle of the product, system or service. In this evolution process, quality has become a strategic factor in the survival of entreprises. The first steps in trying to establish quality systems were taken for the armed forces, followed by space, aeronautical and nuclear projects, whose products were more and more complex and sophisticated. These systems were established by means of quality plans or programmes, and their basic objective was to guarantee a high safety level for the user and/or the general population. In later years, the main concern was to reach a determined quality level not only in one phase of the product life, but in the complete life cycle of the final product. Today a new goal is established and pursued: better quality of the product, service or system life cycle at a lower cost. Methods of improving the quality of systems and processes are the subject of numerous initiatives and studies, to better availability and maintainability of complex equipment or installations, with an extended useful life and greater requirements. Experience in the performance of complex projects shows that a higher quality may be obtained through designing a comprehensive quality plan which pays special attention to information management and modifications of the original design. Obtaining a high reliability level for an installation (equipment, systems, etc), increasing its availability and rationalizing its maintenance may be little less than fanciful without a deep knowledge of the installation, of its activities and its current status in day-to-day operation, which shows the importance of truthful information available to operators and corresponding exactly to their needs. In this frame of mind, a quality plan comprising a configuration management system of information and documents constitutes the basic support tool for logistics in the design, engineering, fabrication, erection, operation, maintenance, etc of complex installations. In view of the above, we may say that commonly defined and generally accepted objectives for Concurrent Engineering and Computer-Aided Logistics Support (CALS) must be met with the support of efficient installation configuration management and effective implementation of global quality plans
[en] This paper investigates the preventive age replacement policy (ARP) for a system subject to random failures. Unlike most maintenance models in the literature, our model considers a system that is exploited under different operating environments each characterized by its own degree of severity. The system lifetimes follow a different distribution depending on the environment it is operating under. Furthermore, the system lifetimes distribution is assumed unknown and therefore estimated from field reliability data. The reliability of the system is calculated using two kernel estimators. This method offers the advantage of non-parametric estimation methods and completely determined by two parameters, namely the smoothing parameter and the kernel function. First, a probability maintenance cost model is derived and conditions under which an optimal preventive maintenance age exists are provided. Then, a statistical maintenance cost model is developed using two kernel estimators. The impact of the variability of the kernel smoothing parameter on the cost model is also investigated. Numerical experiments are provided to illustrate the proposed approach. Results obtained demonstrate the accuracy of the proposed statistical maintenance cost model. - Highlights: • A stochastically deteriorating system under different operating environments is considered. • Probability and statistical maintenance optimization models are proposed. • Theoretical maintenance optimality conditions are derived. • The assumption according to which time to failure distribution is known is relaxed. • Two kernel estimators are implemented. Results demonstrate the accuracy of the approach.
[en] Methods of calculation of thermal processes of the isolating materials are considered, in problems of nondestructive diagnostics of the main and distributive power stations. Theoretical justification of calculation of thermal processes of the multilayered isolating structure was given. On the basis of the analysis of results of operation, service life, physical processes of “ageing” and use of diagnostic parameters of the isolating structure characteristics of resistance of the equipment to refusal are offered. Time of refusal and a residual service life allow to predict using of dependences of refusal resistance. (paper)
[en] The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings