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The purpose of this paper is to highlight the need for degradation data in order to improve the reliability and the mean residual life estimation of a specific item of equipment and to adapt the preventive maintenance tasks accordingly.

An initial reliability model which uses a degradation-based reliability model that is built from the collection of hitting times of a failure threshold. The proposed maintenance model is based on the cost/availability criterion. The estimation of both reliability and optimum time for preventive maintenance are updated with all new degradation data that are collected during operating time.

An improvement for the occurrences of maintenance tasks which minimizes the mean cost per unit of time and increases the availability.

Inspection tasks to measure the degradation level should be realized at least one time for each item of equipment at a specific time determined by the proposed methodology.

The introduction of a criterion which helps the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation level of a specific item of equipment.

The purpose of this paper is to propose new importance measures for degrading components based on Shapley value, which can provide answers about how important players are to the whole cooperative game and what payoff each player can reasonably expect.

The proposed importance measure characterizes how a specific degrading component contributes to the degradation of system reliability by using Shapley value. Degradation models are also introduced to assess the reliability of degrading components. The reliability of system consisting independent degrading components is obtained by using structure functions, while reliability of system comprising correlated degrading components is evaluated with a multivariate distribution.

The ranking of degrading components according to the newly developed importance measure depends on the degradation parameters of components, system structure and parameters characterizing the association of components.

Considering the fact that reliability degradation of engineering systems and equipment are often attributed to the degradation of a particular or set of components that are characterized by degrading features. This paper proposes new importance measures for degrading components based on Shapley value to reflect the responsibility of each degrading component for the deterioration of system reliability. The results are also able to give timely feedback of the expected contribution of each degrading component to system reliability degradation.

The purpose of this paper is the reliability analysis for systems with dependent gamma degradation process and Weibull failure time.

Consider a life testing experiment in which a sample of n devices starts to operate at t=0 and the data are available on failure time and failure-evolving process on each individual, called in some contents wear or degradation. Ignoring the between performance characteristics dependency structure may lead us to different reliability estimations, while the dependency justly exists. In previous research, dependency between the degradation process and hard failure time has been studied in limited detail (special closed form expression). Thereafter, the dependency between two degradation processes with the same structure (gamma process) in a system is considered using the copula function.

The results indicate that ignoring the dependency structure may lead us to different reliability estimations while the dependency justly exists.

This study gives some contributions that evaluate reliability metrics with more than one failure mechanism that may not be independent and possibly follow a different distribution function. The authors have used the copula function as a basis to develop a proposal model and analysis methods. In addition, the authors discussed the identifiability of the copula. Finally, simulation data were used to review the suggested approach.

The purpose of this paper is to develop and test models explaining the unsatisfactory innovation activity of Russian firms and the main obstacles to innovation cluster development.

Based on statistical analysis and the results of a pilot survey of 192 local businessmen, followed by imitation modeling analysis, the study tests hypotheses regarding the impact of unsatisfactory institutional environments, including weak property rights protection, on innovation cluster development in Russia.

The analysis shows that the impact of adverse factors on innovation activities of cluster members is crucial, and estimates to what extent the negative factors' influence should be reduced to prevent cluster degradation processes.

The models provide a number of sensitivity tests of the parameters; however, data from clusters with different levels of support and protection need to be obtained. Government experiments could be conducted to test the models and find ranges of optimal parameters for cluster development. Short of this, examination of actual data from different cluster in similar environments would allow estimated of optimal strategies for support. Longitudinal data can also help determine the actual cause and effect of successful innovation cluster development.

The paper provides managerial implications for organizations involved in innovation clusters, which can be used to improve cluster members' performance and collaborative innovation activities by means of creating acceptable institutional environments.

The paper provides evidence of the connection between collaborative activities of clustering organizations in Russia and their performance caused by expectations concerning institutional conditions on the macro level in Russia.

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

A generalized distribution with wide range of skewness and elongation will be suitable for the data mining and compatible for the misspecification of the distribution. Hence, the purpose of this paper is to present a distribution-based approach for estimating degradation reliability considering these conditions.

Tukey’s g-and-h distribution with the quantile expression is introduced to fit the degradation paths of the population over time. The Newton–Raphson algorithm is used to approximately evaluate the reliability. Simulation verification for parameter estimation with particle swarm optimization (PSO) is carried out. The effectiveness and validity of the proposed approach for degradation reliability is verified by the two-stage verification and the comparison with others’ work.

Simulation studies have proved the effectiveness of PSO in the parameter estimation. Two degradation datasets of GaAs laser devices and crack growth are performed by the proposed approach. The results show that it can well match the initial failure time and be more compatible than the normal distribution and the Weibull distribution.

Tukey’s g-and-h distribution is first proposed to investigate the influence of the tail and the skewness on the degradation reliability. In addition, the parameters of the Tukey’s g-and-h distribution is estimated by PSO with root-mean-square error as the object function.

The importance of the adverse impacts of network degradation has stimulated substantial international research interest in transport network reliability, that is, the ability of degraded transport networks to cope with travel demand. Most of the recent research effort has focused on the reliability of urban passenger transport networks, in terms of the probability that the network will deliver a required standard of performance. This situation is characterised by high levels of congestion, a dense road network, and quantifiable probability of degradation of the network. Outside major urban centres, the situation is very different. The main dominant consideration in transport network infrastructure provision is accessibility - linking urban centres, providing regional coverage, and basic levels of accessibility for the non-urban community and economy. The network is sparse, congestion is not a significant issue, and access to essential community services and to markets is the major driving force underlying network development. In this context, the vulnerability of the network is perhaps more important than ‘reliability’. This paper develops the concept of network vulnerability. It begins by reviewing the current state of research into network reliability, then proposes extensions and adaptations to the reliability concepts that are more appropriate for strategic-level multi-modal transport systems. Several alternative definitions for vulnerability are proposed. The paper also discusses the development of algorithmic and visualisation tools that may be used to identify specific ‘weak spots’ in a network, where failure of some part of the transport infrastructure would have the most serious effects on access to specific locations and on overall system performance. Finally, the paper describes potential applications of network vulnerability concepts, and proposes directions for further research.

At the research and development stage of a product, the manufacturer usually faces the problem of selecting the most reliable design among several competing ones for some parts (or components) of the product in order to enhance the product's quality. It is a great challenge for the manufacturer if these completing designs are highly reliable, since there are few (or even no) failures can be obtained by using traditional life tests or accelerated life tests. In such cases, if there exist product characteristics whose degradation over time can be related to reliability, then collecting “degradation data” can provide information about product reliability. This paper proposes a systematic approach to the selection problem where the products' degradation paths satisfy Wiener processes. First, an intuitively appealing selection rule is proposed and, then, the optimal test plan is derived by using the criterion of minimizing the total experimental cost. The sample size, inspection frequency, and termination time needed by the selection rule for each of competing designs are computed by solving a nonlinear integer programming problem with a minimum probability of correct selection. Finally, an example is provided to illustrate the proposed method.

The purpose of this paper is to analyze the dependent competing failure reliability of harmonic drive (HD) with strength failure and degradation failure.

Based on life tests and stiffness degradation experiments, Wiener process is used to establish the accelerated performance degradation model of HD. Model parameter distribution is estimated by Bayesian inference and Markov Chain Monte Carlo (MCMC) and stiffness degradation failure samples are obtained by a three-step sampling method. Combined with strength failure samples of HD, copula function is used to describe the dependence between strength failure and stiffness degradation failure.

Strength failure occurred earlier than degradation failure under high level accelerated condition; degradation failure occurred earlier than strength failure under medium- or low-level accelerated condition. Gumbel copula is the optimum copula function for dependence modeling of strength failure and stiffness degradation failure. Dependent competing failure reliability of HD is larger than independent competing failure reliability.

The reliability evaluation method of dependent competing failure of HD with strength failure and degradation failure is first proposed. Performance degradation experiments during accelerated life test (ALT), step-down ALT and life test under rated condition are conducted for Wiener process based step-down accelerated performance degradation modeling.

Zero-failure reliability testing aims at demonstrating whether the product has achieved the desired reliability target with zero failure and high confidence level at a given time. Incorporating accelerated degradation testing in zero-failure reliability demonstration test (RDT) facilitates early failure in high reliability items developed within short period of time to be able to survive in fiercely competitive market. The paper aims to discuss these issues.

The triangular cyclic stress uses one test chamber thus saving experimental cost. The parameters in model are estimated using maximum likelihood methods. The optimum plan consists in finding out optimum number of cycles, optimum specimens, optimum stress change point(s) and optimum stress rates.

The optimum plan consists in finding out optimum number of cycles, optimum specimens, optimum stress change point(s) and optimum stress rates by minimizing asymptotic variance of estimate of quantile of the lifetime distribution at use condition subject to the constraint that total testing or experimental cost does not exceed a pre-specified budget. Confidence intervals of the design parameters have been obtained and sensitivity analysis carried out. The results of sensitivity analysis show that the plan is robust to small deviations from the true values of baseline parameters.

For some highly reliable products, even accelerated life testing yields little failure data of units in a feasible amount of time. In such cases accelerated degradation testing is carried out, wherein the failure termed as soft failure is defined in terms of performance characteristic of the product exceeding its critical (threshold) value.