Reliability Analysis Model Research Articles

비동질 정시중단 자료를 활용한 수리 가능 장비의 베이지안 신뢰도 분석 모델 연구

Purpose: This study formulates the Bayesian reliability analysis model using type I censored failure data from heterogeneous repairable systems.BRMethods: The failure of products employing varying methods for different usage environments is typically statistically uneven. Consequently, heterogeneity is difficult to reflect as a factor in the proposed model. Heterogeneity causes events to be distributed; hence, it is regarded as a frailty. This study incorporates the foregoing factors into the previous power law model and devises a reliability analysis model that can be updated using periodically collected data by Bayes’ theorem.BRResults: The sensitivity and characteristics of the parameters in the proposed model are confirmed through mathematical simulations. Moreover, two case studies demonstrate the validity of the model.BRConclusion: This study is expected to be utilized as a reference for the long-term analysis of high-value products (such as weapon systems) requiring continual update and tracking reliability throughout their lifecycle.

스포츠센터의 상사 · 부하의 LMX와 조직몰입, 조직신뢰 및 조직시민행동의 구조적 관계

This study has a main purpose that closely examines the structural relationship among leader-member exchange, organizational commitment, organizational trust and organizational citizenship behavior in sports center. In order to achieve it, the sample from employees were accumulated by using convenience sampling that chose sports center in Seoul. The samples were 300 people. and we excluded unsuitable sheet like that were decided as untrustful one and an omission and unclear. So the final samples were 283 people. On the basis of that, The statistical techniques, spss 24.0 and amos 24.0 program have been used for the analysis as per research purpose. The statistical analysis used in the research for a data analysis includes frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structure equation model analysis. The research has drawn the following conclusions, based on the above mentioned research method and its procedures:BR First, The leader-member exchange factors influences the organizational commitment.BR Second, The leader-member exchange influences the organizational trust.BR Third, The organizational commitment influences the organizational citizenship behavior.BR Fourth, The organizational trust influences theorganizational citizenship behavior.

Identifying the Most Probable Human Errors Influencing Maritime Safety

In the traditional and extended shipboard operation human reliability analysis (SOHRA) model, the error-producing condition (EPC) is critical. The weight and proportion of each EPC in one specific task are often determined by the experts’ judgments, including most of the modified versions. Due to this subjectivity, the result and recommended safety measures may not be as accurate as they should be. This study attempts to narrow the gap by proposing a novel approach, a combination of SOHRA, entropy weight method, and the TOPSIS model. The entropy weight and TOPSIS method are employed to decide the weight of each EPC based on the foundation of the SOHRA model. A cargo-loading operation from a container ship is analyzed to verify this model. The results suggest that the entropy-weighted TOPSIS method can effectively determine the weights of EPCs, and the eight most probable human errors are identified.

A comparative study for parameter estimation of the Weibull distribution in a small sample size: An application to spring fatigue failure data

The Weibull distribution is the most widely applied model in reliability analysis. The main objective of this paper is to present a simple method called the minimum discrepancy method that is applicable to both complete and censored data for the parameter estimation of the Weibull distribution and a detailed comparison in a small sample size of thirteen methods in terms of several criteria by a simulation study. Additionally, parameter estimation methods are applied to the spring fatigue failure data. By extensive simulations and comparisons, the generalized least square 1, the weighted least square 1, the weighted Maximum likelihood estimation and the minimum discrepancy method are recommended for parameter estimation with small samples.

The development of logic-probabilistic reliability model of the main electrical scheme

The issues of construction and analysis of the topological model in reliability analysis of main electric schemes connections in power plants and substations are considered in this article. The multi-matrix method for reliability analysis is proposed in this article for different electric schemes: two operating systems of built-up wires and one bypass system of built-up wires; two operating systems of built-up wires; one operating system of built-up wires and one bypass system of built-up wires by the obtaining multi-states. The main conclusions were made on the further direction of research.

An Intelligent Electronic Fuse for Selective Isolation of Faulty Switching Cells in Power Electronic Converter Legs to Guarantee Continuous Operation

This article proposes a novel device designated as an intelligent electronic fuse (iFuse) intended to be connected in series with any current-bidirectional voltage-unidirectional active switch present in a power converter. The iFuse duty is to selectively isolate its series-associated switch from the rest of the converter circuit immediately after detecting that this switch has failed in short circuit. Nonetheless, it maintains the reverse (free-wheeling) current path originally offered by the failed switch. The failure detection is typically performed when the failed switch causes a shoot-through event. Therefore, the iFuse is able to block large currents. The iFuse allows increasing the power-converter fault tolerance and reliability with regard to switch short-circuit failures (SCFs), as in converters featuring switches in parallel, redundant legs, and multilevel neutral-point-clamped topologies. The reliability model analysis of a two-level converter leg with two parallel switches per position reveals that its reliability can be increased up to four times when an iFuse is implemented in series with each switch. The iFuse device feasibility and good performance are verified through experimental tests, proving that it can detect and isolate the associated-switch failure in 6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> , while stopping short-circuit currents of up to 1 kA without incurring in harmful di / dt values.

A non-probabilistic convex polyhedron model for reliability analysis of structures with multiple failure modes and correlated uncertainties based on limited data

A non-probabilistic convex polyhedron model for reliability analysis of structures with multiple failure modes and correlated uncertainties based on limited data

A double-loop relevant vector machine-based system reliability analysis method with Meta-IS idea and active learning strategy

This paper proposes a double-loop relevant vector machine (RVM) model for system reliability analysis. To reduce the computational load, an adaptive RVM is constructed, which is built by minority initial samples and K-folds clustering. The candidate sample pool constructed by this rough adaptive RVM model improves the computational efficiency. Based on the idea of active learning, another adaptive RVM is established. By combining two adaptive RVMs, the proposed model has the advantages of both active learning and importance sampling, which is called DLRVM. In this model, the failure probability is expressed as a product of the augmented failure probability and the correction factor. From the characteristics of RVM, this model under the Bayesian framework has significant generalization ability which avoids the limitations of many machine learning models. The accuracy and high efficiency are verified via four academic examples and an implicit engineering problem. The results also indicate that RVM is appropriate for system reliability analysis.

Development and Validation of Creative and Critical Thinking Competency Diagnostic Scale Using Item Response Theory

The purpose of this study is to develop and validate a diagnostic scale in the form of a written test from which creative and critical thinking (two key competencies at university) can be objectively measured.The research method consisted of 40 questions, modified and supplemented to suit the undergraduate students of I University, from the TOCT questionnaire. This survey had been verified for its validity by education professionals. It was used in a preliminary test in January 2021, and narrowed down to 20 questions. Furthermore, in October 2021 the official test was conducted on 93 students enrolled in the ‘Logical Thinking’course for the unit of Thinking Education as a basic subject to verify the validity of the diagnostic scale developed in the preliminary test. This diagnostic scale comprises objective multiple choice questions with 5 possible answers in the areas of comprehensive understanding, creative composition, objective evaluation, and problem-solving. This study used a two-parameter logistic model of descriptive statistics, correlation analysis, reliability analysis, and item response theory to examine the correction rate, independence, reliability and question characteristics.The results of the study showed the following: First, the average score of the participants in the study displayed a low correction rate (46.3%) of 9.26 out of 20. Second, the result of the correlation analysis displayed a rather low positive (+) correlation analysis between comprehensive understanding and problem-solving between creative composition and problem-solving, as well as between creative composition and objective evaluation. However, the correlation coefficient was less than 0.4, which indicated that there is no multi-collinearity. Third, the result of the reliability analysis displayed a very low reliability due to a relatively small number of questions having a suitable item difficulty in each sub-category. Fourth, the result of the item difficulty analysis displayed 8 easy questions, 5 moderately difficult questions and 7 difficult questions. Fifth, the result of item discrimination analysis showed that there were 4 questions with item discrimination, and 6 questions with high discrimination, whereas 10 questions had no item discrimination. Based on these study results, the limitations and implications inherent in the creative and critical thinking diagnostic scale were discussed.

Multi-State Reliability Analysis Based on General Wiener Degradation Process and Random Shock

A multi-state reliability analysis model suffering from a dependent competing failure process is developed in this study, where the soft failure is described by general nonlinearity random effect. Wiener degradation process with measurement error and the hard failure is caused by random shock. Considering that the shock process not only may cause abrupt damage but also can accelerate degradation, there are some correlations between soft failure and hard failure. Based on the proposed new model, the multi-state functions are obtained under the cumulative shock model and the extreme shock model, and the system state probabilities are given under the different degradation state points. The fatigue cracks growth data example and MEMS oscillator example are given to demonstrate the proposed new model. At last, some sensitivity analyses are given to illustrate the influence of parameters on the state probability and the system reliability.

Peran Stakeholder sebagai Aktor Kebijakan Pemberdayaan Kelompok Perempuan “Sepakat” melalui Potensi Lokal di Kabupaten Aceh Barat Daya

In Aceh Barat Daya District, this essay examines the role of stakeholders as players in empowering the women's group "Agreed" through regional potential. This study employs a case study methodology and a qualitative research design. Data was gathered by observation, interviews, and documentation. Triangulation validity, reliability, and interactive analysis models were then used to analyze the data. The study's findings demonstrate that stakeholders have played a significant role as policy actors for empowerment programs since the implementation of the Participatory Missile Appraisal (PRA) and Participation Assessment Plan (MPA) processes, which prioritize community involvement. supported by the application of the ideas of corporate development, institutional development, and human development. However, it is clear from the existence of unresolved business issues like seasonal business, the lack of specialized training and enrichment of product innovation for groups, as well as the inability to organize businesses, that the needs of the "Agreed" women's group have not been met in practice as expected. So, solid cooperation between policy actors is needed in carrying out empowerment and more efforts to evaluate implementation to assess the level of success of the program being implemented

Data-driven reduced order model and simplicial homology global optimization for reliability analysis and application

A novel framework of reliability analysis was developed in this study to consider the uncertainty of geomaterials and geological conditions by combining the reduced-order model (ROM), reliability analysis, and numerical model. The reliability method was used to determine the reliability index using the simplicial homology global optimization (SHGO) based on the ROM. The developed method was verified and illustrated using three numerical examples and a simple slope. The limit state curve in all three numerical examples was in excellent agreement with the actual curve. The reliability index and failure probability were also in excellent agreement with those of the actual limit state function using the first-order reliability method (FORM) and Monte Carlo simulation, respectively, indicating that the ROM method can present the limit state function well. The results showed that the developed method is feasible and effective for reliability analysis of geotechnical and geological engineering problems with a complex, nonlinear, and implicit limit state function. Furthermore, the developed method is effective, efficient, and accurate for reliability analysis. It provides an excellent way to approximate the limit state function to avoid the time-consuming numerical model in a practical engineering system.

The development of coronaphobia scale and psychometric effect among UAE people

The effects of the COVID-19 pandemic on mental health are likely to worsen as the epidemic progresses and will last long even after the pandemic has passed. The present study developed a coronaphobia scale during the pandemic to measure its psychological effects such as fear, anxiety, and depression in the majority of the cases in the United Arab Emirates (UAE). It is a 35-item scale that measures anxiety symptoms connected with COVID-19 and may be used to identify people who require mental health treatment. Based on 618 adults, the reliability and validity of these items were appropriate. The scales were distributed via social media using a Google form. Internal consistency, reliability analysis, and structural equation models, particularly confirmatory factor analysis, were carried out. The elevated scores on the coronaphobia scale were associated with social phobia, anxiety, stress, and depression. The coronaphobia score distinguishes well between those with and without dysfunctional anxiety (85% specificity and 90% sensitivity). These results support the coronaphobia scale as a valid and effective tool for clinical practice and research.

Optimum preventive maintenance strategy for turbine based on reliability analysis and mathematical modeling

Optimum preventive maintenance strategy for turbine based on reliability analysis and mathematical modeling

A combined shear strength reduction and surrogate model method for efficient reliability analysis of slopes

Surrogate models are often used to alleviate extensive computational burden for slope reliability analysis. How to efficiently train a surrogate model with high precision is always a nontrivial task. This paper proposes a novel method, which combines the shear strength reduction (SSR) technique, the surrogate model and the adaptive pool-based sampling strategy for efficient slope reliability analysis. The surrogate model is used to replace the time-consuming slope stability model in simulation-based reliability analysis, while the SSR technique coupled with an adaptive pool-based sampling strategy is innovatively adopted to search for the most informative samples to train the surrogate model, which can improve the computational efficiency significantly. Further, an expanded sampling method is suggested to improve the local prediction of surrogate model in other design space, enabling an efficient evaluation of the slope failure probability corresponding to different threshold safety factors. The main feature of the proposed method is that it takes advantage of SSR technique to efficiently generate training samples in the region of interest. Several slope examples are analyzed to validate the accuracy, computational efficiency as well as the applicability of the proposed method. The results show that proposed method outperforms other approaches in computational efficiency and can give accurate estimation of slope failure probability as well.

New success likelihood index model for large group human reliability analysis considering noncooperative behaviors and social network

Human reliability analysis (HRA) is a systematic method to qualitatively and quantitatively assess and analyze potential human errors for enhancing the safety and reliability of complex socio-technical systems. As a representative HRA approach, the success likelihood index method (SLIM) has been widely applied to quantify the effects of performance shaping factors on human performance and derive the human error probabilities of operational tasks. The influence quantification of performance shaping factors mainly relies on experts’ subjective judgments, where conflict opinions inevitably exist because of their different knowledge and experiences. Besides, the current SLIM studies often involved a small group of experts and assumed them to be independent, which is insufficient to tackle increasingly complicated HRA problems. In this article, a large group SLIM model is developed to calculate the human error probabilities of operational tasks considering experts’ noncooperative behaviors and social relations. Specifically, a large group of experts are included to provide task state assessments under complex uncertain linguistic environment, and clustered into subgroups based on a social network analysis. Then a consensus reaching process is performed to tackle the noncooperative behaviors of experts to obtain a consensus human error probability estimation. Finally, a case study of cargo loading process is provided to illustrate the practicality and effectiveness of the proposed large group SLIM model.

대학 운동선수들의 은퇴불안, 진로결정 자기효능감, 진로준비행동의 관계

Objectives The purposes of this study were to investigate the structural relationship model of retirement anxiety, career decision-making self-efficacy and career preparation behavior of athletes in college. Methods The participants of this study consisted using of 415 athletes who were more than 18 years old with more than 3 years experience of competition. They were assessed by retirement anxiety scale, career decision-making self-efficacy scale and career preparation behavior scale. The evaluation questionnaires were modified to reflect the circumstances in Korea and underwent a validity test prior to translation. The data were conducted by descriptive statistics, confirmatory factor analysis, reliability analysis, correlation analysis, and structure equation modelling. Results First, retirement anxiety had no a influence on career decision-making self-efficacy. Second, retirement anxiety had a positive influence on career preparation behavior. Third, career decision-making self-efficacy had a positively influence on career preparation behavior. Conclusions The result of this study suggests the need of developing programs and providing necessary support aimed at improving college athletes' decision-making self-efficacy and career preparation behavior through career counseling and education.

스포츠 지도자의 감정노동과 직무소진, 프리젠티즘의 관계 연구

The purpose of this study is to investigate the relationship among emotional labor, job burnout, and presentism of sports leaders. The study subjects used data from 173 sports leaders working in Gyeonggi-do using the convenient sampling method. For data processing and analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis were performed using the SPSS 22.0 program and AMOS 22.0 program. Based on the derived results, the following conclusions were obtained. First, surface behavior and internal behavior, which are sub-factors of emotional labor of sports leaders, had a significant effect on job burnout. Surface behavior was identified as an antecedent variable to increase job burnout, and internal behavior was confirmed as an antecedent variable to lower job burnout. Second, surface behavior and internal behavior, which are sub-factors of emotional labor of sports leaders, had a significant effect on presentism. Surface behavior was identified as an antecedent variable to increase presentism, and internal behavior was identified as a antecedent variable to lower presentism. Third, job burnout had a significant effect on presentism. It was confirmed that job burnout plays a key role as a variable to increase presentism. Therefore, in order to lower presentism, it is necessary to come up with a way to lower job burnout.

Structural Reliability Analysis by Using Non-Probabilistic Multi-Cluster Ellipsoidal Model.

Uncertainties are normally unavoidable in engineering practice, which should be taken into account in the structural design and optimization so as to reduce the relevant risks. Yet, the probabilistic models of the uncertainties are often unavailable in the problems due to the lack of samples, and the precision of the conventional non-probabilistic models are not satisfactory when the samples are of multi-cluster distribution. In view of this, an improved method by using a non-probabilistic multi-cluster ellipsoidal model (multi-CEM) for the critical structural reliability analysis is proposed in this paper, which describes the samples in a more accurate and compact way and helps to acquire more satisfactory reliability analysis results. Firstly, a Gaussian mixture model (GMM) is built for the multi-cluster samples with performing expectation maximization (EM) algorithm, based on which the multi-CEM can be constructed. In the structural reliability analysis, two cases, respectively, considering whether the components of the multi-CEM are intersected or not are researched in detail. The non-probabilistic reliability (NPR) indexes for each component of the multi-CEM are computed using the Hasofer–Lind–Rackwitz–Fiessler (HL-RF) algorithm, and then the multidimensional volume ratios of the safe domain to the whole uncertainty domain are computed based on these indexes, indicating the structural NPR. In the end, two numerical examples and a practical application are conducted and analyzed to testify the effectiveness of the method.

Probabilistic model for determining the failure time of steel-to-timber connections with multiple dowel-type fasteners exposed to fire

There is a lack of knowledge on the structural reliability of dowel-type connections exposed to fire. The objective of this paper is to propose a model for the structural reliability analysis of steel-to-timber connections with multiple dowel-type fasteners two shear planes exposed to standard fire to determine the failure time probabilistically. A thermomechanical model was developed in two uncoupled phases. The phase to calculate the temperature field was based on the finite element method, while the phase to calculate the load carrying capacity was based on Johansen's theory, modified to consider the influence of temperature on the materials thermomechanical properties. The model error was calculated for the failure time of the connections. The structural reliability analysis of the failure time was carried out using Monte Carlo simulations. The analysis indicated that modes I and II, which are influenced by the solicitation rate and the relation between thickness of timber member and dowel diameter, have the largest probability to occur. The structural reliability analysis provided the mean and the 5th and 20th percentiles failure times of probability distributions for 25 connections. A sensitivity analysis through Sobol’ indices showed that the model error is the random variable with the higher relative importance.