Reliability Availability Eng Trivedi Bobbio

2020

Reliability and Availability are key attributes of technical systems. Methods of quantifying these attributes are thus essential during all phases of system lifecycle. Data (measurement)-driven methods are suitable for components or subsystems but, for the system as a whole, model-driven methods are more desirable. Simulative solution or analyticnumeric solution of the models are two major alternatives. In this tutorial, we explore model-driven methods with analytic-numeric solution. Non-state-space, state space, hierarchical and fixed-point iterative methods are explored using real-world examples. Challenges faced by such modeling endeavors and potential solutions are described as also one of the software packages used for such modeling exercises.

RBD, FTA, Markov, Boolean , Monte Carlo simulation are the most common approaches to System Reliability Modeling. Fact is that all of them are in use. This already proves that each one has its own advantage and disadvantage. If there was one with advantages only over the other, all others would disappear. Comparing Monte Carlo simulation with all the others as a group of analytical methods was treated by Ajit Kumar Verma and others () Regarding the analytical methods , it is common practice , in the literature covering System Reliability Modeling , to justify the selection of a specific method. Man Cheol Kim and Poong Hyun Seong [] dealing with nuclear protection system recognize FTA as the most advantageous model. The same method is preferred by Rongrong Yu1 and others [] for multi-input and mul-ti-output, systems with large quantity of components, W.E. Smith and others chose Markov chains in there Server Availability study [] Bennets [] indicates that RBD has its advantages in relatively simple systems, but for complex systems the use of a conditional probability result (Bayes theorem) will be required. He advocates an alternative method : to treat the whole problem as if it were Boolean. Is it accidental that safety problems prefer FTA , Server Availability vote for Markov and very complex system advocate Boolean methods? The paper deals with the above question. It reveals the logic behind the listed preferences .

[1988] The Eighteenth International Symposium on Fault-Tolerant Computing. Digest of Papers

Many real-life systems are typically involved in sequence-dependent failure behaviors. Such systems can be modeled by dynamic fault trees (DFTs) with priority AND gates, in which the occurrence of the top events depends on not only combinations of basic events but also their failure sequences. To the author's knowledge, the existing methods for reliability assessment of DFTs with priority AND gates are mainly Markov-state-space-based, inclusion-exclusion-based, Monte Carlo simulation-based, or sequential binary decision diagram-based approaches. Unfortunately, all these methods have their shortcomings. They either suffer the problem of state space explosion or are restricted to exponential components time-to-failure distributions or need a long computation time to obtain a solution with a high accuracy. In this article, a novel method based on dynamic binary decision tree (DBDT) is first proposed. To build the DBDT model of a given DFT, we present an adapted format of the traditional Shannon's decomposition theorem. Considering that the chosen variable index has a great effect on the final scale of disjoint calculable cut sequences generated from a built DBDT, which to some extent determines the computational efficiency of the proposed method, some heuristic branching rules are presented. To validate our proposed method, a case study is analyzed. The results indicate that the proposed method is reasonable and efficient.

International journal of engineering research and technology, 2020

Markov model provides great flexibility in modelling the timing of events. Markov analysis is a method of analysis that can be applied to both repairable and nonrepairable types of systems. In this paper, Markov modelling technique is used to compute the reliability for non-repairable system and defined the mean time to failure of non-repairable systems with different failure rates. This technique is also used to compute the steady-state availability for repairable systems and to derived the mean time between failure of repairable systems with different failure rates and repair rates. Keywords— Markov model; Repairable and Non-repairable systems; MTTF; MTBF; Failure rate; Repair rate; Reliability; INTRODUCTION Markov analysis is the mathematical abstractions to model simple or complex concepts in quite easily computable form. The Markov analysis is also considered powerful modelling and analysis tool in solving reliability tribulations. Markov analysis is a tool for modelling comple...

Computers & Mathematics with Applications, 2012

Quality standards impose increasingly stringent requirements and constraints on quality of service attributes and measures. As a consequence, aspects, phenomena, and behaviors, hitherto approximated or neglected, have to be taken into account in quantitative assessment in order to provide adequate measures satisfying smaller and smaller confidence intervals and tolerances. With specific regards to reliability and availability, this means that interferences and dependencies involving the components of a system can no longer be neglected. Therefore, in order to support such a trend, specific techniques and tools are required to adequately deal with dynamic aspects in reliability and availability assessment.

Journal of Mathematics and Informatics, 2017

In this paper, is to permit the system reliability analysts/managers/engineers/ practitioners to conduct RAM analysis of the system which may help them to model, analyze and predict the behavior of industrial systems in a more realistic and consistent manner. Markovian approach is used to model the system behavior. For carrying out study, Root Cause Analysis (RCA) of the subsystems is carried out and transition diagrams for various subsystems are drawn and differential equations associated with them are formulated. After obtaining the steady state solution the corresponding values of reliability and maintainability are estimated at different mission times. With RAM analysis of the system key performance metrics such as Mean Time between Failure (MTBF), Mean time to Repair Time (MTTR) and System availability values are ascertained.

2007

This paper shows how recent revolutionary Bayesian Network (BN) algorithms can be used to model very complex reliability problems in a simple unified way. The algorithms work for socalled hybrid BNs, which are BNs that can contain a mixture of both discrete and continuous variables. Such hybrid BNs enable us to model failure times and reliability together. The approach allows a compact representation of the event-dependent failure behaviours characteristic of fault-tolerant systems, avoiding the state space explosion problem of t he Markov Chain based approaches. The BN framework presented is able to solve any configuration of static and dynamic gates with general time-to-failure distributions, without using numerical integration techniques or simulation methods. Unlike other approaches (which tend to be restricted to using exponential distributions) we can use as input any parametric or empirical failure rate distribution. The approach offers a powerful framework for analysts and decision makers to successfully perform robust reliability assessment. Sensitivity, uncertainty, diagnosis analysis, common cause failures, and warranty analysis can also be easily performed within this framework.

Annals of Nuclear Energy, 2020

Non-functional requirements are essentially important and play vital role for applications ranging from safety-critical systems (SCS) to simple gaming applications to ensure their quality. SCS demands not only for safe and reliable systems but systems those remain safe and available while under attacks. Availability analysis approaches include, but are not limited to cluster technique, Markov based chain models, Reliability Block Diagrams (RBD), Fault Tree Analysis (FTA) and Flow Network. The classical approaches fail to account for the comprehensive and accurate analysis of the diverse characteristics such as temporal behavior of systems, uncertainty in system behavior and failure data, functional dependencies among components and multiple failure modes for components or systems. This paper presents a novel approach for the availability analysis of a Digital Feed Water Control System (DFWCS) of nuclear power plant, which considers the maintenance and repair of the main-steam safety valves. The approach will be useful when no operational profile data is available for that. The system has been modeled using Stochastic Petri Net capturing all the system requirements along with the partial failures of its subsystems and common-cause failures and analyzed using TimeNet tool. The proposed methodology proves to be efficient and overcomes the limitations of the traditional approaches and the Markov model approach as it computes the state-transition probabilities, rather than assuming or qualitatively assessing it.

2019

A thesis submitted in partial fulfilment of the requirements for the degree of