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2013 | Buch

Generalized Logit-Based Proportional Hazards Models and Their Applications in Survival and Reliability Analyses Kapitel lesen Erstes Kapitel lesen

Stochastic Reliability and Maintenance Modeling

Essays in Honor of Professor Shunji Osaki on his 70th Birthday

herausgegeben von: Tadashi Dohi, Toshio Nakagawa

Verlag: Springer London

Buchreihe : Springer Series in Reliability Engineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

In honor of the work of Professor Shunji Osaki, Stochastic Reliability and Maintenance Modeling provides a comprehensive study of the legacy of and ongoing research in stochastic reliability and maintenance modeling. Including associated application areas such as dependable computing, performance evaluation, software engineering, communication engineering, distinguished researchers review and build on the contributions over the last four decades by Professor Shunji Osaki.

Fundamental yet significant research results are presented and discussed clearly alongside new ideas and topics on stochastic reliability and maintenance modeling to inspire future research. Across 15 chapters readers gain the knowledge and understanding to apply reliability and maintenance theory to computer and communication systems. Stochastic Reliability and Maintenance Modeling is ideal for graduate students and researchers in reliability engineering, and workers, managers and engineers engaged in computer, maintenance and management works.

Inhaltsverzeichnis

Frontmatter
Generalized Logit-Based Proportional Hazards Models and Their Applications in Survival and Reliability Analyses
Abstract
We introduce a flexible family of generalized logit-based regression models for survival and reliability analyses. We present its parametric as well as its semiparametric versions. The method of maximum likelihood and the partial likelihood approach are applied to estimate the parameters of the parametric and semiparametric models, respectively. This new family of models is illustrated with male laryngeal cancer data and compared with Cox regression.
N. Balakrishnan, M. C. Pardo, M. L. Avendaño
Design of Reliability Test Plans: An Overview
Abstract
Reliability prediction of new components, products, and systems is a difficult task due to the lack of well-designed test plans that yield “useful” information during the test and due to the stochastic nature of the normal operating conditions. The accuracy of the reliability prediction has a major effect on the warranty cost and repair and maintenance strategies. Therefore, it is important to design efficient test plans. In this chapter, we present an overview of reliability testing with emphasis on accelerated testing and address issues associated with the design of optimal test plans, stress application methods, and reliability prediction models. We further discuss the concept of equivalence of test plans and how it could be used for test time reduction. Finally, we present accelerated degradation modeling and the design of accelerated degradation test plans.
E. A. Elsayed
Maintenance Outsourcing: Issues and Challenges
Abstract
All products and systems are unreliable in the sense that they degrade and fail. Corrective maintenance (CM) restores a failed item to an operational state and effective preventive maintenance (PM) reduces the likelihood of failure. These maintenance actions can be done either in-house or can be outsourced to an external agent. We focus on the maintenance being outsourced and look at the issues involved from the perspectives of the owner of the asset and the agent providing the maintenance service.
D. N. P. Murthy, N. Jack, U. Kumar
Warranty/Maintenance: On Modeling Non-zero Rectification Times
Abstract
This chapter revisits modelling of warranty/maintenance costs under the assumption that both, the warranty repairs and the maintenance actions, require non-negligible completion time. We provide an intuition on this topic by summarising our previous results, as well as the published work of other authors. We closely examine a case study that provides an excellent motivation for extending the research in this area. Also, again assuming non-negligible repair and maintenance times, we propose a simulation model for the expected warranty costs that integrates the concepts of reliability improvement and warranty. We conclude with a discussion on new directions for future research.
Stefanka Chukova, Yu Hayakawa
Repair-Time Limit Replacement Policies
Abstract
This article concerns repair-limit replacement problems and review the existing stochastic models in which repair times are random variables. If a system fails, we should decide whether we repair the failed system (repair option) or replace it by new one (replacement option with a lead time). We classify the existing repair-time limit models based on available information amount of repair times (perfect, partial, and no information), repair type (perfect and imperfect repair), and objective functions (expected cost and profit with and without discounting). We summarize the modeling assumptions and explain how to obtain the optimal repair-limit replacement policies. Finally, we propose some interesting topics for future studies.
Won Young Yun, Naoto Kaio
Repair Strategies in an Uncertain Environment: Stochastic Game Approach
Abstract
This chapter deals with Repair strategies for stand-by equipment which maximises the time until failure when there is a vital need for the equipment, and it is unable to respond. We model conflict situations where the operating environment is controlled by an opponent. We develop stochastic game models to determine the form of the optimal Maintenance/Repair policy under these conditions and present numerical examples.
Y.-H. Kim, Lyn C. Thomas
Maintenance Modeling and Policies
Abstract
The systems used in production, transportation services, and communication services constitute the majority part of not only industrial activities but also our daily life. Most of them have many units or components with various structure that will degrade with time or usage, and even suffer from a sudden failure due to the random shocks. For some systems, such as military systems, aircrafts, and nuclear power plants, they are of great importance and cannot afford to any failure. A machine in industrial plant failing to work properly will interpret the whole production assembly line and cost a large amount of capital and labor, while the failure of the aircraft will endanger the life of all the passengers. Therefore, maintenance on these systems is necessary due to the two aspects: (1) prolong the service life of the products; (2) improve the system reliability to avoid unnecessary failure.
Yaping Wang, Hoang Pham
Reliability of Systems Subjected to Imperfect Fault Coverage
Abstract
Due to imperfect fault coverage, the reliability of redundant systems cannot be enhanced unlimitedly with the increase of redundancy. Many works have been done on the reliability modeling and optimization of systems subjected to imperfect fault coverage. The methodologies adopted mainly include combinatorial approach, ordered binary decision diagram and universal generating function. Depending on the type of fault tolerant techniques used, there are mainly three kinds of fault coverage models: (1) element level coverage (ELC). (2) fault level coverage (FLC). and (3) performance-dependent coverage (PDC). This chapter reviews the literatures on the reliability of systems subjected to imperfect fault coverage and shows an extended work.
G. Levitin, S. H. Ng, R. Peng, M. Xie
Replacement and Maintenance Policies of Devices: A Review
Abstract
In this chapter, we discuss the contributions of the author to replacement and maintenance of devices. Some related works are also discussed.
Mohamed Abdel-Hameed
Dynamical Systems with Semi-Markovian Perturbations and Their Use in Structural Reliability
Abstract
The aim of this chapter is to present dynamical systems evolving in continuous-time and perturbed by semi-Markov processes (SMP). We investigate both probabilistic modeling and statistical estimation of such models. This work was initially developed in order to study cracking problems for the confinement device in nuclear power plants, where a jump Markov process was used as the perturbing process. The new key element here is the use of SMPs instead of Markov ones for the randomization of the system. Several numerical illustrations in reliability are investigated, accompanied with guidelines for a practical numerical implementation.
Julien Chiquet, Nikolaos Limnios
Customer-Perceived Software Reliability Predictions: Beyond Defect Prediction Models
Abstract
In this chapter, we propose a procedure for implementing customer-perceived software reliability predictions, which address customer’s concern about service-impacting outages and system stability. Data requirements are clearly defined in terms of test defects and field outages to ensure a good data collection process. We incorporate the effect of operational profile to demonstrate the changes in defect find rate from internal tests through precutover test and in-service operation. A software reliability growth model is a necessary key step, but not sufficient for addressing customer-perceived reliability measures. The proposed approach is a result of in-depth investigations of test defect data and field outage data over many years. It has been successfully demonstrated with actual field data and applied to a variety of software development projects.
Kazu Okumoto
Recent Developments in Software Reliability Modeling and its Applications
Abstract
Management technologies for improving software reliability are very important for software total quality management (TQM). The quality characteristics of software reliability are that computer systems can continue to operate regularly without the occurrence of failures on software systems. In this chapter, we describe several recent developments in software reliability modeling and its applications as quantitative techniques for software quality/reliability measurement and assessment. That is, a quality engineering analysis of human factors affecting software reliability during the design review phase, which is the upper stream of software development, and software reliability growth models based on stochastic differential equations (SDEs) and discrete calculus during the testing-phase, which is the lower one, are discussed. Finally, we discuss quality-oriented software management analysis by applying the multivariate analysis method and the existing software reliability growth models to actual process monitoring data.
Shigeru Yamada
Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Ungrouped Failure Time Data
Abstract
This chapter presents computation procedures for maximum likelihood estimates (MLEs) of software reliability models (SRMs) based on nonhomogeneous Poisson processes (NHPPs). The idea behind our methods is to regard usual failure time data as incomplete data. This leads to quite simple computation procedures for NHPP-based SRMs based on the EM (expectation–maximization) algorithm, and these algorithms overcome a problem arising in practical use of SRMs. In this chapter, we discuss the algorithms for 10 types of NHPP-based SRMs. Numerical examples show that the proposed EM algorithms help us to reduce computational efforts in the parameter estimation of NHPP-based SRMs.
Hiroyuki Okamura, Tadashi Dohi
Closed-Form Approach for Epistemic Uncertainty Propagation in Analytic Models
Abstract
System dependability or performance is often studied using stochastic models. These models capture the natural uncertainty in the system being studied, known as aleatory uncertainty. Randomness in events of interest like times to failure/recovery of components, ability to detect failures, ability to perform recovery action, inter-arrival time, service time, etc., are taken into account in the models, by means of their distributions. The models are usually solved at fixed parameter values. However, the model input parameter values have uncertainty associated with them as they are derived either from a finite number of observations (from lifetime determining experiments or field data) or are based upon expert guesses. This uncertainty in model input parameter values, known as epistemic uncertainty, is not normally taken into account by the stochastic aleatory model.
Kesari Mishra, Kishor S. Trivedi
Generational Garbage Collection Policies
Abstract
In the computer science community, the technique of garbage collection [5] is an automatic process of memory recycling, which refers to those objects in the memory no longer referenced by programs are called garbage and should be thrown away. A garbage collector determines which objects are garbage and makes the heap space occupied by such garbage available again for the subsequent new objects. Garbage collection plays an important role in Java’s security strategy, however, it adds a large overhead that can deteriorate the program performances. From related studies which are summarized in [5], a garbage collector spends between 25 and 40 percent of execution time of programs for its work in general, and delays caused by such garbage collection are obtrusive.
Xufeng Zhao, Syouji Nakamura, Cunhua Qian
Metadaten
Titel
Stochastic Reliability and Maintenance Modeling
herausgegeben von
Tadashi Dohi
Toshio Nakagawa
Copyright-Jahr
2013
Verlag
Springer London
Electronic ISBN
978-1-4471-4971-2
Print ISBN
978-1-4471-4970-5
DOI
https://doi.org/10.1007/978-1-4471-4971-2

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