45 research outputs found

    The safety case and the lessons learned for the reliability and maintainability case

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    This paper examine the safety case and the lessons learned for the reliability and maintainability case

    A Condition-Based Maintenance Model for Assets with Accelerated Deterioration Due to Fault Propagation

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    Complex industrial assets such as power transformers are subject to accelerated deterioration when one of its constituent component malfunctions, affecting the condition of other components, which is a phenomenon called fault propagation. In this paper, we present a novel approach for optimizing condition-based maintenance policies for such assets by modelling their deterioration as a multiple dependent deterioration path process. The aim of the policy is to replace the malfunctioned component and mitigate accelerated deterioration at minimal impact to the business. The maintenance model provides guidance on determining inspection and maintenance strategies to optimize asset availability and operational cost.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/TR.2015.243913

    Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections

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    In this paper, we develop a maintenance model for systems subjected to multiple correlated degradation processes, where a multivariate stochastic process is used to model the degradation processes, and the covariance matrix is employed to describe the interactions among the processes. The system is considered failed when any of its degradation features hits the pre-specified threshold. Due to the dormancy of degradation-based failures, inspection is implemented to detect the hidden failures. The failed systems are replaced upon inspection. We assume an imperfect inspection, in such a way that a failure can only be detected with a specific probability. Based on the degradation processes, system reliability is evaluated to serve as the foundation, followed by a maintenance model to reduce the economic losses. We provide theoretical boundaries of the cost-optimal inspection intervals, which are then integrated into the optimisation algorithm to relieve the computational burden. Finally, a fatigue crack propagation process is employed as an example to illustrate the effectiveness and robustness of the developed maintenance policy. Numerical results imply that the inspection inaccuracy contributes significantly to the operating cost and it is suggested that more effort should be paid to improve the inspection accuracy

    A review on maintenance optimization

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    To this day, continuous developments of technical systems and increasing reliance on equipment have resulted in a growing importance of effective maintenance activities. During the last couple of decades, a substantial amount of research has been carried out on this topic. In this study we review more than two hundred papers on maintenance modeling and optimization that have appeared in the period 2001 to 2018. We begin by describing terms commonly used in the modeling process. Then, in our classification, we first distinguish single-unit and multi-unit systems. Further sub-classification follows, based on the state space of the deterioration process modeled. Other features that we discuss in this review are discrete and continuous condition monitoring, inspection, replacement, repair, and the various types of dependencies that may exist between units within systems. We end with the main developments during the review period and with potential future research directions

    A generalised semi-Markov reliability model.

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    The thesis reviews the history and literature of reliability theory. The implicit assumptions of the basic reliability model are identified and their potential for generalisation investigated. A generalised model of reliability is constructed, in which components and systems can take any values in an ordered discrete or continuous state-space representing various levels of partial operation. For the discrete state-space case, the enumeration of suitable system structure functions is discussed, and related to the problem posed by Dedekind in 1897 on the cardinality of the free distributive lattice. Some numerical enumerations are evaluated, and several recursive bounds are derived. In the special case of the usual dichotomic reliability model, a new upper bound is shown to be superior to the best explicit and non-asymptotic upper bound previously derived. The relationship of structure functions to event networks is also examined. Some specific results for the state probabilities of components with small numbers of states are derived. Discrete and continuous examples of the generalised model of reliability are investigated, and properties of the model are derived. Various forms of independence between components are shown to be equivalent, but this equivalence does not completely generalise to the property of zero-covariance. Alternative forms of series and parallel connections are compared, together with the effects of replacement. Multiple time scales are incorporated into the formulation. The above generalised reliability model is subsequently specialised and extended so as to study the optimal tuning of partially operating components. Simple drift and catastrophic failure mechanisms are considered. Explicit and graphical solutions are derived, together with several bounds. The optimal retuning of such units is also studied and bounds are again obtained, together with some explicit solutions

    Markov and Semi-markov Chains, Processes, Systems and Emerging Related Fields

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    This book covers a broad range of research results in the field of Markov and Semi-Markov chains, processes, systems and related emerging fields. The authors of the included research papers are well-known researchers in their field. The book presents the state-of-the-art and ideas for further research for theorists in the fields. Nonetheless, it also provides straightforwardly applicable results for diverse areas of practitioners

    Reliability and Condition-Based Maintenance Analysis of Deteriorating Systems Subject to Generalized Mixed Shock Model

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    For successful commercialization of evolving devices (e.g., micro-electro-mechanical systems, and biomedical devices), there must be new research focusing on reliability models and analysis tools that can assist manufacturing and maintenance of these devices. These advanced systems may experience multiple failure processes that compete against each other. Two major failure processes are identified to be deteriorating or degradation processes (e.g., wear, fatigue, erosion, corrosion) and random shocks. When these failure processes are dependent, it is a challenging problem to predict reliability of complex systems. This research aims to develop reliability models by exploring new aspects of dependency between competing risks of degradation-based and shock-based failure considering a generalized mixed shock model, and to develop new and effective condition-based maintenance policies based on the developed reliability models. In this research, different aspects of dependency are explored to accurately estimate the reliability of complex systems. When the degradation rate is accelerated as a result of withstanding a particular shock pattern, we develop reliability models with a changing degradation rate for four different shock patterns. When the hard failure threshold reduces due to changes in degradation, we investigate reliability models considering the dependence of the hard failure threshold on the degradation level for two different scenarios. More generally, when the degradation rate and the hard failure threshold can simultaneously transition multiple times, we propose a rich reliability model for a new generalized mixed shock model that is a combination of extreme shock model, δ-shock model and run shock model. This general assumption reflects complex behaviors associated with modern systems and structures that experience multiple sources of external shocks. Based on the developed reliability models, we introduce new condition-based maintenance strategies by including various maintenance actions (e.g., corrective replacement, preventive replacement, and imperfect repair) to minimize the expected long-run average maintenance cost rate. The decisions for maintenance actions are made based on the health condition of systems that can be observed through periodic inspection. The reliability and maintenance models developed in this research can provide timely and effective tools for decision-makers in manufacturing to economically optimize operational decisions for improving reliability, quality and productivity.Industrial Engineering, Department o

    Condition-based maintenance for systems with aging and cumulative damage based on proportional hazards model

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    This paper develops a condition-based maintenance (CBM) policy for systems subject to aging and cumulative damage. The cumulative damage is modeled by a continuous degradation process. Different from previous studies which assume that the system fails when the degradation level exceeds a specific threshold, this paper argues that the degradation itself does not directly lead to system failure, but increases the failure risk of the system. Proportional hazards model (PHM) is employed to characterize the joint effect of aging and cumulative damage. CBM models are developed for two cases: one assumes that the distribution parameters of the degradation process are known in advance, while the other assumes that the parameters are unknown and need to be estimated during system operation. In the first case, an optimal maintenance policy is obtained by minimizing the long-run cost rate. For the case with unknown parameters, periodic inspection is adopted to monitor the degradation level of the system and update the distribution parameters. A case study of Asphalt Plug Joint in UK bridge system is employed to illustrate the maintenance policy.The work described in this paper was partially supported by a theme-based project grant (T32-101/15-R) of University Grants Council, and a Key Project (71532008) supported by National Natural Science Foundation of China

    Modèles de fiabilité et de maintenance prédictive de systèmes sujets à des défaillances interactives

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    RÉSUMÉ: L’interaction des défaillances est une thématique qui prend une ampleur considérable dans le monde de la recherche industrielle moderne. Les systèmes sont de plus en plus complexes et leurs fonctionnements et défaillances sur le long terme sont sujets à diverses sources d’influence internes et externes. Les actifs physiques en particulier sont soumis à l’impact du temps, de l’environnement et du rythme de leur utilisation. Connaître ces sources d’influence n’est pas suffisant car il importe de comprendre quelles sont les relations qui les lient afin de planifier de façon efficiente la maintenance des actifs. En effet, cette dernière peut s’avérer très couteuse et sa mauvaise planification peut conduire à l’utilisation de systèmes dangereux pouvant engendrer des évènements catastrophiques. La fiabilité est un vaste domaine. Elle propose une large panoplie de modèles mathématiques qui permettent de prédire le fonctionnement et les défaillances des actifs physiques. Ceci dit, les concepts des modèles les plus appliqués à ce jour se basent sur des hypothèses parfois simplistes et occultent bien souvent certaines relations de dépendances qui régissent un système. L’interaction des défaillances dans le cadre des dépendances stochastiques est abordée par de nombreux travaux de recherches. Par contre, la compréhension et l’implémentation de ces travaux demeurent un défi pour les spécialistes en maintenance qui ont besoin de modèles réalistes pour une maintenance préventive efficace. Cette thèse traite de la fiabilité et la maintenance prédictive des actifs physiques en exploitation et sujets à divers modes de défaillance interactifs. Elle établit avant tout l’importance d’accorder une attention particulière à l’interaction des défaillances dans le domaine de la fiabilité et de la maintenance. Dans une revue de littérature, les concepts et les méthodes de modélisation et d’optimisation en fiabilité et en maintenance préventive sont présentés. Les divers types de dépendances dans un système sont discutés. Un cas d’application, à savoir celui des ponceaux en béton, est proposé. Les travaux entrepris par la suite fournissent avant tout un cadre pour la modélisation de la fiabilité incluant l’interaction des défaillances. A cette fin, une étude comparative des modèles existants les plus pertinents est effectuée de points de vue conceptuel, méthodologique et applicatif. Le cadre étant défini, un modèle basé sur les chocs extrêmes et les chaînes de Markov est construit afin de valoriser le caractère séquentiel des défaillances interactives. Cette proposition est améliorée pour prendre en compte la dégradation du système. Une stratégie de maintenance prédictive est conséquemment développée. Toutes ces approches sont appliquées à un ensemble de ponceaux en béton observés sur plusieurs années. Cela permet d’expliquer les dépendances entre l’occurrence de déplacements et l’occurrence de fissures dans une structure. Tous ces concepts et résultats sont finalement discutés afin de déterminer des perspectives réalistes pour une étude approfondie de l’interactivité d’un point de vue fiabiliste et dans un but stratégique pour la planification de la maintenance.----------ABSTRACT: Failure interaction is a subject gaining growing attention in the world of modern industrial research. Systems are becoming increasingly complex. Their life cycles are subject to various internal and external influences. Physical assets in particular are impacted by time, environment and usage. Knowing these sources of influence is not enough. Indeed, it is important to understand the relationships between them in order to plan effectively for the maintenance of assets. Maintenance can be quite expensive. Thus, poor planning can lead to dangerous systems that could cause catastrophic events. Reliability engineering offers a wide range of mathematical models to predict failures. That being said, the concepts of the most widely applied models in the industry are often based on simplistic assumptions and tend to overlook certain dependencies within a system. Failure interaction in the context of stochastic dependencies is largely addressed in the literature. However, understanding and implementing the proposed approaches remains a challenge for maintenance specialists that need realistic models for efficient maintenance planning. This thesis focuses on the reliability and predictive maintenance of physical assets subject to interactive failure modes. First of all, it emphasizes the importance of paying particular attention to failure interaction. In a literature review, the concepts and methods for modeling and optimizing reliability and preventive maintenance are presented. The diverse dependencies in a system are discussed. A case study is proposed, namely concrete culverts. Subsequently, the research provides a framework for modeling reliability that integrates the interaction of failures. To this end, the most relevant models in the literature are comparatively studied from a conceptual, methodological and applicative point of view. In the defined framework, a model based on extreme shocks and Markov processes is built in order to represent the sequential nature of interactive failures. This approach is extended to take into account the natural degradation of a system. A predictive maintenance strategy is consequently developed. All these models are applied to a set of concrete culverts observed over several years. The dependences between the occurrence of displacements and the occurrence of cracks in a structure are explained through these approaches. Finally, these concepts and results are discussed in order to determine realistic perspectives for in-depth studies of the impact of failure interaction on reliability and for strategic maintenance plannin
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