Journal articles: 'Model of reliability assessment'

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Rebba, Ramesh, and Sankaran Mahadevan. "Computational methods for model reliability assessment." Reliability Engineering & System Safety 93, no. 8 (August 2008): 1197–207. http://dx.doi.org/10.1016/j.ress.2007.08.001.

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Alsharqawi, Mohammed, Tarek Zayed, Laya Parvizsedghy, Ahmed Senouci, and Hassan Al-Derham. "Reliability Assessment Model for Water Distribution Networks." Journal of Pipeline Systems Engineering and Practice 11, no. 2 (May 2020): 04019059. http://dx.doi.org/10.1061/(asce)ps.1949-1204.0000442.

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Perkin, Samuel, Arne Brufladt Svendsen, Trond Tollefsen, Ingrid Honve, Iris Baldursdottir, Hlynur Stefansson, Ragnar Kristjansson, and Pall Jensson. "Modelling weather dependence in online reliability assessment of power systems." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 231, no. 4 (March 13, 2017): 364–72. http://dx.doi.org/10.1177/1748006x17694951.

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Probabilistic reliability assessment of power systems is an ongoing field of research, particularly in the development of tools to model the probability of exogenous threats and their potential consequences. This paper describes the application of a weather-dependent failure rate model to a region of the Icelandic transmission system, using 10 years of weather data and overhead line fault records. The studied failure rate model is compared with a constant failure rate model, in terms of variability and how well the models perform in a blind test over a 2 year period in reflecting the occurrence of outages. The weather-dependent and constant failure rate models are used as input to a state-of-the-art risk assessment tool to determine the sensitivity of such software to weather-dependent threats. The results show the importance of weather-dependent contingency probabilities in risk estimation, and in quantitative assessment of maintenance activities. The results also demonstrate that inclusion of weather dependence in power system reliability assessments affects the overall distribution of risk as a positively skewed distribution, with high-risk periods occurring at low frequency.

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Zhang, Bin, Dong Dong Yu, and Peng Su. "In Service Beam Bridge Reliability Assessment." Advanced Materials Research 838-841 (November 2013): 1034–41. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.1034.

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In order to evaluate the reliability of existing bridges ,based on maximum value of the load and model of probability calculation of resistance attenuation, according to the data of the bridge which actually collected, and by using the ADINA finite element software to build the finite element model of considering the damage detection of beam bridge. The component and system failure criteria are determined on the basis of the bridge load-bearing characteristics.The Time-dependent reliability of the system by using the probability calculation model for assessing the maximum value of the load and resistance attenuation can be obtained. The result shows Changes in the process of reliability prediction of bridge , the correctness of reliability calculation model be verified; the correctness of the ADINA model be validated; Also confirmed the feasibility of prediction model; to obtain the main influencing factors of reliability of existing bridges.

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DONG, Yun-Wei, Guang-Ren WANG, Fan ZHANG, and Lei GAO. "Reliability Analysis and Assessment Tool for AADL Model." Journal of Software 22, no. 6 (June 24, 2011): 1252–66. http://dx.doi.org/10.3724/sp.j.1001.2011.04014.

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Slot, René M. M., John D. Sørensen, Bruno Sudret, Lasse Svenningsen, and Morten L. Thøgersen. "Surrogate model uncertainty in wind turbine reliability assessment." Renewable Energy 151 (May 2020): 1150–62. http://dx.doi.org/10.1016/j.renene.2019.11.101.

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Castañeda, G. A. Pérez, J.-F. Aubry, and N. Brinzei. "Stochastic hybrid automata model for dynamic reliability assessment." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 225, no. 1 (March 2011): 28–41. http://dx.doi.org/10.1177/1748006xjrr312.

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Huang, Jiale, Fei Xiao, and Yang Zhang. "Reliability Evaluation of Pavement Life-Cycle Assessment Model." Modelling and Simulation in Engineering 2018 (October 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/4172519.

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Inventory reliability of the life-cycle assessment (LCA) model highly depends on the data quality and normally exhibits significant uncertainty. A rigorous statistical methodology was established to capture and quantify the inherent uncertainties linked to the results of the LCA model. Two sources of uncertainty, data quality and model, were identified. The former was captured by converting the deterministic value to probability density function using beta distribution according to the evaluation matrix of data quality; the latter was assessed by prescribing variation interval through defining uncertainty factor. The functional equivalent pavement structures were designed, and the corresponding energy consumption and CO2 emission were calculated by the LCA model. A 10% variation was observed for the LCA results and within 30-year analysis span, at the 95% confidence level, and environmental burdens of cement pavement are higher than those of asphalt pavements while the comparison between the two asphalt pavements is not significant statistically. Therefore, the established statistical methodology is capable of capturing the uncertainty of the LCA model and quantifying the reliability the LCA results.

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Gandhi, Parul, Mohammad Zubair Khan, Ravi Kumar Sharma, Omar H. Alhazmi, Surbhi Bhatia, and Chinmay Chakraborty. "Software Reliability Assessment Using Hybrid Neuro-Fuzzy Model." Computer Systems Science and Engineering 41, no. 3 (2022): 891–902. http://dx.doi.org/10.32604/csse.2022.019943.

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Hoduń, Piotr, and Michał Borecki. "Reliability Assessment of MV Power Connections." Energies 14, no. 21 (October 23, 2021): 6965. http://dx.doi.org/10.3390/en14216965.

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This article presents an analysis of the reliability of the power grid using data on the failure rate of the medium voltage (MV) power grid from the last five years. The analysis of the state of the power grid was based on the data provided by the grid operator. The purpose of this article is to analyze the reliability assessment of the medium voltage (MV) power connections using various analytical methods, a simulation model and reliability indicators. The analysis was performed based on the defined categories of power outages in terms of their duration. This made it possible to determine the energy quality indicators in a selected power grid. Then, a more complex analysis was carried out to assess the convergence of the applied analytical models of reliability assessment with the actual results obtained for the power grid. Moreover, using ANSYS Multiphysics, a numerical model of the cable head was developed to analyze the processes taking place in this element of the power grid for various exploitation cases.

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Kolarik, William J., Jeffrey C. Woldstad, and Shuxia Lu. "Real-Time Human Performance Reliability Assessment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (July 2000): 843–46. http://dx.doi.org/10.1177/154193120004402290.

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This paper describes a real-time conditional human reliability model constructed to predict the likelihood of human performance metrics exceeding critical boundaries in a future time interval. The model is implemented by collecting real-time data from selected performance measures, modeling and forecasting these measures, and then converting the forecast results into reliability measures. To demonstrate the feasibility of the proposed model, a prototype software package has been developed and tested for a simple movement task.

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Yin, Zong Run, Dong Su, and Jun Shan Li. "A Novelty Model for Reliability Assessment of Complex System." Applied Mechanics and Materials 571-572 (June 2014): 118–23. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.118.

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Aiming at the difficulty in reliability assessment of complex system. A novelty model based on Bayesian method and GO methodology is proposed. Bayesian method is adopted for multi-source information fusion to build the component reliability model, and then GO methodology is utilized to integrate the component reliability parameters and form the reliability model of the system. At last, an instance of reliability assessment for complex electronic equipment is given to show the effectiveness of the model. Result shows that, this method take advantage of Bayesian method and GO methodology, it provide useful reference for relative applications.

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Maevsky, D. A., O. V. Naidenko, E. J. Maevskaya, O. V. Strelzov, and A. A. Naidenko. "RESEARCH OF ACCURACY OF SOFTWARE SOFTWARE RELIABILITY ASSESSMENT." ELECTRICAL AND COMPUTER SYSTEMS 33, no. 108 (November 30, 2020): 17–25. http://dx.doi.org/10.15276/eltecs.32.108.2020.2.

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The aim of the work is to establish the presence or absence of dependence of the accuracy of reliability assessment on the programming language and software reliability model. To this end, software reliability modeling was performed using the main reliability models, such as: Dzhelinsky-Moranda, non- uniform Poisson process (Gela-Okumoto), Schneide-Windows, Musa, Weibul model, S-Shaped model, Du- ena, geometric model of Moranda, Musa-Okumoto. The existence of the problem of choosing a reliability model, which is due to their large number, is noted. It is shown that the problem of choosing a model has not yet been resolved. For research, we selected time series for defect detection in 40 software systems writ- ten in various programming languages: JavaScript, Ruby, Python, Objective-C, C ++, Scala, C #, PHP, C, Java, Rust, ActionScript. The data source for the specified time series is the Internet resource Github.com. Modeling was carried out using specialized software developed by the authors. The simulation accuracy was estimated as the mean-squared deviation of the calculated cumulative defect detection curve from the real one. The dependence of the accuracy of software reliability assessment on the programming language and reliability model is given. Recommendations are given on choosing a model for a software system de- pending on the programming language. It is concluded that there is no one universal model that with ac- ceptable accuracy would allow us to evaluate the reliability of a software system, regardless of the pro- gramming language in which it was written.

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Stanley, Leanne M., and Michael C. Edwards. "Reliability and Model Fit." Educational and Psychological Measurement 76, no. 6 (July 11, 2016): 976–85. http://dx.doi.org/10.1177/0013164416638900.

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The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the reliability of scores and the fit of a corresponding measurement model to be either acceptable or unacceptable for a given situation, but these are not the only possible outcomes. This article focuses on situations in which model fit is deemed acceptable, but reliability is not. Data were simulated based on the item characteristics of the PROMIS (Patient Reported Outcomes Measurement Information System) anxiety item bank and analyzed using methods from classical test theory, factor analysis, and item response theory. Analytic techniques from different psychometric traditions were used to illustrate that reliability and model fit are distinct, and that disagreement among indices of reliability and model fit may provide important information bearing on a particular validity argument, independent of the data analytic techniques chosen for a particular research application. We conclude by discussing the important information gleaned from the assessment of reliability and model fit.

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Xu, Xingjian, Tian Ban, and Yuehua Li. "SPLM: A Flexible and Accurate Reliability Assessment Model for Logic Circuits." Journal of Circuits, Systems and Computers 28, no. 02 (November 12, 2018): 1950032. http://dx.doi.org/10.1142/s0218126619500324.

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Reliability evaluation by using probabilistic computational models has become an important research field in modern digital designs. Based on the profound understanding of different reliability evaluation methods, this paper proposes a universal model for signal probability and reliability analysis of logic circuits. The proposed Signal Probability Level Matrix (SPLM) provides us with the reliability and signal probability of the entire circuit as well as individual outputs. We can deal with SPLM very flexibly depending on different applications and design constraints. The accuracy and efficiency of the proposed model have been proved and verified by representative circuits in literatures. Furthermore, the proposed model is particularly useful in reliability assessment in cascade-structure circuits such as ripple carry adders.

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Yang, Seungho, Afnan Ahmad, Peter Y. Park, Gunho Sohn, and Jeremy Krygsman. "Public Transit Service Reliability Assessment using Two-Fluid Model." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (March 18, 2020): 89–100. http://dx.doi.org/10.1177/0361198119896783.

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This study introduces a traffic flow theory-based reliability indicator to evaluate the inter-city public transit service. The two-fluid theory parameter n that measures the road networks’ resilience to changing traffic is used as a new reliability indicator of public bus service. We compared the performance of the new indicator with the three existing reliability indicators, including on-time performance, with a total of 52 different GO Bus routes to ascertain the usability of the new indicator. The GO Bus service is an inter-city bus service operated by Metrolinx in the Greater Toronto and Hamilton areas in Ontario, Canada. We used 1 month of GO Bus GPS data collected in July 2017 to estimate various public transit reliability indictors. We also investigated the relationship between reliability indicators and selected roadway network characteristics, such as route length, freeway ratio, intersection density along a route, and so forth. The study applied a series of statistical analyses, including principal component analysis, correlation analysis, and z-test using Fisher’s z transformation. The results showed that the proposed two-fluid indicator n can be used as a supplementary reliability indicator for assessing road networks’ resilience in regards to changing traffic flow conditions. The new indicator provided additional insights for inter-city bus service operators for initiating communication with roadway governing agencies for the purpose of improving road networks to further improve public transit service reliability.

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Wawrzyński, Wojciech, Mariusz Zieja, Justyna Tomaszewska, and Mariusz Michalski. "Reliability Assessment of Aircraft Commutators." Energies 14, no. 21 (November 6, 2021): 7404. http://dx.doi.org/10.3390/en14217404.

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The article describes the method of predicting the reliability and durability of an aircraft commutator, which is a primary source of electric energy in helicopters. Tests were conducted for 10 starter-generators. From this research it follows that the technical condition of brushes and bearings has a significant impact on the reliability of starter-generators. The reliability of starter-generators was determined based on the method consisting of two stages that was adopted: the first stage involved determining the density function of changes in diagnostic parameter depending on the operating time, but the second stage included the assessment of the reliability of bearings of the starter-generator taking into account the real flight profile. The first stage of the adopted method consisted of defining the dynamic model of changing the length of the starter-generator’s brush, which became the probabilistic model. Subsequently, based on differential equations, Fokker–Planck partial differential equation was derived, which describes the process of increasing the brush wear in a probabilistic way. This method enables the prediction of the residual durability of the helicopter’s starter-generator due to the change in a diagnostic parameter which is the wear of brushes during starter-generator operation. The second stage of this method allows determining the durability of starter-generator’s bearings building upon the average helicopter’s flight profile. Owing to the difficulty in measuring the wear of bearings, the relation between the durability of bearings and the temperature of surroundings can be applied by replacing the flight altitude with temperature. The reliability of the helicopter’s starter-generator was determined based on the serial-type reliability structure.

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HAYASHIDA, SHIHO, SHINJI INOUE, and SHIGERU YAMADA. "SOFTWARE RELIABILITY ASSESSMENT USING EXPONENTIAL-TYPE CHANGE-POINT HAZARD RATE MODELS." International Journal of Reliability, Quality and Safety Engineering 21, no. 04 (August 2014): 1450019. http://dx.doi.org/10.1142/s0218539314500193.

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We discuss software hazard rate modeling with a change of testing-environment and a software reliability assessment method based on the proposed software hazard rate models. A software hazard rate model is known as one of the important and useful mathematical models for describing the software failure-occurrence phenomenon and conducting quantitative software reliability assessment. Taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment because it is said that such approach enables us to conduct more plausible software reliability assessment reflecting the actual testing-environment. Especially in this paper, we develop exponential-type software hazard rate models with effect of change-point and a software reliability assessment method based on our models. Finally, we show numerical examples for our models and results of model comparisons with existing software hazard rate models by using actual data.

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Fujimoto, Yukio, Akio Ideguchi, and Mitsumasa Iwata. "Reliability Assessment for Deteriorating Structure by Markov Chain Model." Journal of the Society of Naval Architects of Japan 1989, no. 166 (1989): 303–14. http://dx.doi.org/10.2534/jjasnaoe1968.1989.166_303.

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Piasecki, Michał, and Krystyna Barbara Kostyrko. "Indoor environmental quality assessment, part 2: Model reliability analysis." Journal of Building Physics 42, no. 3 (February 5, 2018): 288–315. http://dx.doi.org/10.1177/1744259118754391.

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Indoor environmental quality index involves a set of indoor environmental quality sub-components, provides an assessment of building user comfort and satisfaction and may be used as a tool to support the design of energy-efficient buildings. Unfortunately, the unknown reliability of the indoor environmental quality model is a recognized barrier for its wider practical use. In this article, a preliminary reliability test for the indoor environmental quality model is presented, providing a correct evaluation of the measurement data results and a step-by-step guide to the expression of its uncertainty. The uncertainty based on the physical parameters is first analyzed and then corrected by considering the impacts of the instability of the physical parameters. In the end, all sources of uncertainty are recognized, including uncertainties introduced by the probability distribution of panel sensory tests. A procedure for detecting internal incongruity in the indoor environmental quality model structure is also provided, and a criterion for elimination of this syndrome is proposed. Finally, in standardized indoor environment, the estimated uncertainty of the IEQindex is presented to be no less than ±17%.

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CHIANG, Shen, Yasuto TACHIKAWA, and Kaoru TAKARA. "A PSEUDO VALIDATION ALGORITHM FOR HYDROLOGICAL MODEL RELIABILITY ASSESSMENT." PROCEEDINGS OF HYDRAULIC ENGINEERING 50 (2006): 103–8. http://dx.doi.org/10.2208/prohe.50.103.

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Luzhaeva, E. M., E. N. Yagovkina, and T. Yu Freze. "THE MODEL OF QUANTITATIVE ASSESSMENT OF TECHNICAL SYSTEM RELIABILITY." Vektor nauki Tol'yattinskogo gosudarstvennogo universiteta, no. 2 (2016): 35–39. http://dx.doi.org/10.18323/2073-5073-2016-2-35-39.

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Usynin, Aleksander. "Model-Fitting Approaches to Reliability Assessment and Prognostic Problems." Journal of Pattern Recognition Research 1, no. 1 (2006): 32–36. http://dx.doi.org/10.13176/11.7.

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Ettlinger, Andreas, and Hans Neuner. "Assessment of inner reliability in the Gauss-Helmert model." Journal of Applied Geodesy 14, no. 1 (January 28, 2020): 13–28. http://dx.doi.org/10.1515/jag-2019-0013.

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AbstractIn this contribution, the minimum detectable bias (MDB) as well as the statistical tests to identify disturbed observations are introduced for the Gauss-Helmert model. Especially, if the observations are uncorrelated, these quantities will have the same structure as in the Gauss-Markov model, where the redundancy numbers play a key role. All the derivations are based on one-dimensional and additive observation errors respectively offsets which are modeled as additional parameters to be estimated. The formulas to compute these additional parameters with the corresponding variances are also derived in this contribution. The numerical examples of plane fitting and yaw computation show, that the MDB is also in the GHM an appropriate measure to analyze the ability of an implemented least-squares algorithm to detect if outliers are present. Two sources negatively influencing detectability are identified: columns close to the zero vector in the observation matrix B and sub-optimal configuration in the design matrix A. Even if these issues can be excluded, it can be difficult to identify the correct observation as being erroneous. Therefore, the correlation coefficients between two test values are derived and analyzed. Together with the MDB these correlation coefficients are an useful tool to assess the inner reliability – and therefore the detection and identification of outliers – in the Gauss-Helmert model.

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Yu, D. C., T. C. Nguyen, and P. Haddawy. "Bayesian network model for reliability assessment of power systems." IEEE Transactions on Power Systems 14, no. 2 (May 1999): 426–32. http://dx.doi.org/10.1109/59.761860.

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Sudjianto, Agus, Lokesh Juneja, Hari Agrawal, and Mahesh Vora. "Computer Aided Reliability and Robustness Assessment." International Journal of Reliability, Quality and Safety Engineering 05, no. 02 (June 1998): 181–93. http://dx.doi.org/10.1142/s0218539398000182.

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The competitive pressure to shorten product development time has necessitated the automotive industry to rely more on Computer Aided Engineering (CAE) for analyzing and proving product reliability and robustness. The challenge of this approach is the incorporation of product variability, due to manufacturing and customer usage variations in the analysis, requires a massive computation process which may be prohibitive even with today's advanced computers. In this paper, we demonstrate the use of an efficient computational procedure based on optimal Latin Hypercube Sampling (LHS) and a "cheap-to-compute" nonlinear surrogate model using Multivariate Adaptive Regression Splines (MARS) to emulate a computationally intensive complex CAE model. The result of the analysis is the identification of sensitivity of design parameters, in addition to a computationally affordable reliability assessment. Fatigue life durability of automotive shock tower is presented as an example to demonstrate the methodology.

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Troy, R., and R. Moawad. "Assessment of Software Reliability Models." IEEE Transactions on Software Engineering SE-11, no. 9 (September 1985): 839–49. http://dx.doi.org/10.1109/tse.1985.232543.

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Bahrudin, Bahrudin, and Kumaidi Kumaidi. "MODEL ASESMEN MUSABAQAH TILAWAH AL-QURAN (MTQ) CABANG TILAWAH." Jurnal Penelitian dan Evaluasi Pendidikan 18, no. 2 (December 1, 2014): 153–67. http://dx.doi.org/10.21831/pep.v18i2.2858.

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Penelitian ini bertujuan untuk mengembangkan model penilaian MTQ Cabang Tilawah, karena model penilaian yang selama ini digunakan dalam MTQ tidak sesuai dengan teori asesmen. Jenis penelitian ini adalah research and development, yang dimulai dengan research dan diteruskan dengan pengembangan model. Research dilakukan untuk memperoleh informasi mengenai kelemahan-kelemahan model penilaian MTQ Cabang Tilawah yang digunakan selama ini dan aspek-aspek yang mendukung perlunya dilakukan pengembangan model penilaian tersebut. Pengembangan model mengacu pada prosedur Borg & Gall (1983), yang dilakukan melalui tiga tahap, yaitu: pra-pengembangan, pengembangan, dan diseminasi. Hasil penelitian menunjukkan bahwa model penilaian yang dikembangkan dalam penelitian ini layak digunakan dalam penilaian MTQ Cabang Tilawah. Penilaian tentang kelayakan tersebut didasarkan pada validitas dan reliabilitas instrumen yang digunakan dalam uji coba. Dari analisis rasional mengenai isi instrumen yang dilakukan oleh sejumlah pakar diperoleh penilaian bahwa instrumen-instrumen penilaian yang dikembangkan dalam penelitian ini adalah valid. Kemudian dari estimasi reliabilitas skor gabungan hasil uji coba diperoleh koefisien reliabilitas sebesar 0,96. sehingga hasil penilaian yang dikembangkan dalam penelitian ini adalah reliabel. Kata kunci: MTQ, asesmen, tajwid, fasih, suara, irama ______________________________________________________________ AN ASSESSMENT MODEL OF MUSABAQAH TILAWAH AL-QURAN (MTQ) OF THE TILAWAH SECTIONAbstract This study aims to develop a model of an assessment of MTQ of the tilawah section because the assessment of MTQ that has been applied so far is not relevant to assessment theories. This was a research and development study, started with research and continued with developing a model. The research was conducted to obtain information about weaknesses of the model of the assessment of MTQ of the tilawah section having been applied so far and aspects supporting the needs for developing an assessment model. The model development referred to the procedure by Borg & Gall (1983), consisting of three steps, i.e.: pre-development, development, and dissemination. The results of the study show that the assessment model developed in the study is appropriate to be applied in the assessment of MTQ of the tilawah section. The evaluation of the appropriateness is based on the validity and reliability of the instruments in the tryout. From the analysis of the rationale of the instrument contents done by several experts, the instruments developed in the study are considered valid. Based on the estimation of the reliability of the combined scores from the tryout, the reliability coefficient is 0.96, the assessment instruments developed in the study are reliable.Keywords: MTQ, assessment, tajwid, fashahah, voice, rhythm

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Wang, Zhi Ming, and Jian Guo Yang. "Reliability Assessment of Numerical Control Machine Tools Using Weibull Mixture Models." Advanced Materials Research 181-182 (January 2011): 161–65. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.161.

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Weibull distribution is one of the most widely used model in reliability analysis of NC machine tools. In order to assess the reliability of NC machine tool, Generalized Expectation Maximization (GEM) algorithm is used to estimate parameters of mixture Weibull models. Akaike information criterion (AIC) and Bayesian information criterion (BIC) are used as comprehensive criteria to select the number of subpopulations of mixture models. The results show that mixture models are more suitable to assess reliability of NC machine tools than that of single model. Root mean square errors (RMSE) of mixture models reduce by 87.5% than that of single model. Reliability evaluation results of machine tool, such as MTBF etc., are given.

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Yang, Zhaojun, Xiaoxu Li, Chuanhai Chen, Hongxun Zhao, Dingyu Yang, Jinyan Guo, and Wei Luo. "Reliability assessment of the spindle systems with a competing risk model." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 2 (April 23, 2018): 226–34. http://dx.doi.org/10.1177/1748006x18770343.

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Traditional reliability assessment of spindle systems of machine tools suffers from long testing time and high cost. Accelerated life testing is an alternative that overcomes the shortcomings of traditional reliability testing. In a life testing, identification of critical factors of service life and an accurate model are important. Based on the characteristic analysis and engineering experience, four reliability factors, which are the average power of spindle systems, the number of tool changing, the number of spindles restarting and environment temperature, are selected as accelerating environment variables. An accelerated failure time model is used to describe the inverse relationship between the variables and reliability for the catastrophic failure mode and the degradation failure mode separately. Then a competing risk model is built by considering competing risks of two modes. Parametric reliability models are proposed to capture the statistical independency and dependency separately, in which the Gumbel–Hougaard copula function is used to establish the joint cumulative distribution for dependency. Thereby the hypothesis testing is developed to determine the failure modes dependency. The reliability sensitivity of each environment variable is analyzed. Finally, the proposed model is illustrated with a real field case study.

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INOUE, SHINJI, YUKI NAKAGAWA, and SHIGERU YAMADA. "OPTIMAL SOFTWARE SHIPPING TIME ESTIMATION BASED ON A CHANGE-POINT HAZARD RATE MODEL." International Journal of Reliability, Quality and Safety Engineering 21, no. 02 (April 2014): 1450007. http://dx.doi.org/10.1142/s0218539314500077.

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Software failure-occurrence or the fault-detection phenomenon is changed notably in an actual testing phase or an operational phase due to the changes of factors influencing the software reliability growth process. Taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment because it is said that such approach enables us to conduct more plausible software reliability assessment reflecting an actual testing-environment. We develop a framework for developing software hazard rate models with effect of change-point, and discuss change-point detection methods for applying our model to quantitative software reliability assessment. Additionally, we discuss an optimal software release problem for estimating optimal shipping time with the effect of the change as one of the application problems of our model in software project management. Finally, we show numerical examples for software reliability assessment and our optimal software release policy based on our change-point model by using actual data.

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Zhao, Chun Hong, Lian Guang Liu, Zi Fa Liu, and Ying Chen. "Reliability Assessment of Wind Power System Considering Multi-Objective Models." Advanced Materials Research 608-609 (December 2012): 742–47. http://dx.doi.org/10.4028/www.scientific.net/amr.608-609.742.

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The integration of wind farms has a significant impact on the power system reliability. An appropriate model used to assess wind power system reliability is needed. Establishing multi-objective models (wind speed model, wind turbine generator output model and wind farm equivalent model) and based on the non-sequential Monte Carlo simulation method to calculate risk indicators is a viable method for quantitatively assessing the reliability of power system including wind farms. The IEEE-RTS 79 test system and a 300MW wind farm are taken as example.The calculation resluts show that using the multi-objective models can improve accuracy and reduce error; the higher average wind speed obtains the better system reliabitity accordingly.

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Kurian, V. John, Shuen Shyan Goh, Mohamed Mubarak Abdul Wahab, and Mohd Shahir Liew. "Reliability Assessment Model for Aging Jacket Structures in Malaysian Waters." Applied Mechanics and Materials 567 (June 2014): 283–88. http://dx.doi.org/10.4028/www.scientific.net/amm.567.283.

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As the world is progressing towards deeper water technology, jacket platform still remains as an important production structure for oil and gas in Malaysian shallow water regions. Besides the discovery of new oil and gas, enhanced oil recovery (EOR) allows more oil to be extracted from the old fields. As a result, service life of existing fixed jacket platforms need to be extended. The overall reliability of aged platform has to be reevaluated in order to monitor the integrity of the structure, and to prevent unexpected failures. Reserve Strength Ratio (RSR) is a widely adopted measure to quantify the ultimate strength of a structure. However, structural strength alone is inadequate to express a structure's reliability. Reliability is best defined as the probability that the extreme load will not exceed the ultimate strength of a structure. It can be expressed either in probability of failure or reliability index, which is the inverse normalized form of probability of failure. This paper presents the study of existing jacket platforms in Malaysia's three oil and gas operating regions. Relationship between probability of failure, reliability index and RSR has been formed to provide a simple reliability assessment model of jacket structure in Malaysia water regions.

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ORMANDJIEVA, OLGA, MANAR ABU TALIB, and ALAIN ABRAN. "RELIABILITY MODEL FOR COMPONENT-BASED SYSTEMS IN COSMIC (A CASE STUDY)." International Journal of Software Engineering and Knowledge Engineering 18, no. 04 (June 2008): 515–39. http://dx.doi.org/10.1142/s0218194008003763.

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Software component technology has a substantial impact on modern IT evolution. The benefits of this technology, such as reusability, complexity management, time and effort reduction, and increased productivity, have been key drivers of its adoption by industry. One of the main issues in building component-based systems is the reliability of the composed functionality of the assembled components. This paper proposes a reliability assessment model based on the architectural configuration of a component-based system and the reliability of the individual components, which is usage- or testing-independent. The goal of this research is to improve the reliability assessment process for large software component-based systems over time, and to compare alternative component-based system design solutions prior to implementation. The novelty of the proposed reliability assessment model lies in the evaluation of the component reliability from its behavior specifications, and of the system reliability from its topology; the reliability assessment is performed in the context of the implementation-independent ISO/IEC 19761:2003 International Standard on the COSMIC method chosen to provide the component's behavior specifications. In essence, each component of the system is modeled by a discrete time Markov chain behavior based on its behavior specifications with extended-state machines. Then, a probabilistic analysis by means of Markov chains is performed to analyze any uncertainty in the component's behavior. Our hypothesis states that the less uncertainty there is in the component's behavior, the greater the reliability of the component. The system reliability assessment is derived from a typical component-based system architecture with composite reliability structures, which may include the composition of the serial reliability structures, the parallel reliability structures and the p-out-of-n reliability structures. The approach of assessing component-based system reliability in the COSMIC context is illustrated with the railroad crossing case study.

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You, Weizhen, Alexandre Saidi, Abdel-malek Zine, and Mohamed Ichchou. "Mechanical Reliability Assessment by Ensemble Learning." Vehicles 2, no. 1 (February 14, 2020): 126–41. http://dx.doi.org/10.3390/vehicles2010007.

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Reliability assessment plays a significant role in mechanical design and improvement processes. Uncertainties in structural properties as well as those in the stochatic excitations have made reliability analysis more difficult to apply. In fact, reliability evaluations involve estimations of the so-called conditional failure probability (CFP) that can be seen as a regression problem taking the structural uncertainties as input and the CFPs as output. As powerful ensemble learning methods in a machine learning (ML) domain, random forest (RF), and its variants Gradient boosting (GB), Extra-trees (ETs) always show good performance in handling non-parametric regressions. However, no systematic studies of such methods in mechanical reliability are found in the current published research. Another more complex ensemble method, i.e., Stacking (Stacked Generalization), tries to build the regression model hierarchically, resulting in a meta-learner induced from various base learners. This research aims to build a framework that integrates ensemble learning theories in mechanical reliability estimations and explore their performances on different complexities of structures. In numerical simulations, the proposed methods are tested based on different ensemble models and their performances are compared and analyzed from different perspectives. The simulation results show that, with much less analysis of structural samples, the ensemble learning methods achieve highly comparable estimations with those by direct Monte Carlo simulation (MCS).

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Gong, Min, Serkan Eryilmaz, and Min Xie. "Reliability assessment of system under a generalized cumulative shock model." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 1 (August 3, 2019): 129–37. http://dx.doi.org/10.1177/1748006x19864831.

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Reliability assessment of system suffering from random shocks is attracting a great deal of attention in recent years. Excluding internal factors such as aging and wear-out, external shocks which lead to sudden changes in the system operation environment are also important causes of system failure. Therefore, efficiently modeling the reliability of such system is an important applied problem. A variety of shock models are developed to model the inter-arrival time between shocks and magnitude of shocks. In a cumulative shock model, the system fails when the cumulative magnitude of damage caused by shocks exceed a threshold. Nevertheless, in the existing literatures, only the magnitude is taken into consideration, while the source of shocks is usually neglected. Using the same distribution to model the magnitude of shocks from different sources is too critical in real practice. To this end, considering a system subject to random shocks from various sources with different probabilities, we develop a generalized cumulative shock model in this article. We use phase-type distribution to model the variables, which is highly versatile to be used for modeling quantitative features of random phenomenon. We will discuss the reliability characteristics of such system in some detail and give some clear expressions under the one-dimensional case. Numerical example for illustration is also provided along with a summary.

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Okunev, Alexander V., Anastasia A. Ivanova, and Alexander A. Philipiev. "Assessment of performance reliability of transformers." Innotrans, no. 3 (2020): 50–53. http://dx.doi.org/10.20291/2311-164x-2020-3-50-53.

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Increase of freight traffic resulted in increased loads on traction substations and, respectively, in increase of their equipment failure risks. In the context of maintaining the required voltage level and power quality, which determine appropriate values in reliability for traction substation transformers, the article looks upon solving the problem of determination of reliability essential parameters. A proposed calculation model makes it possible to simplify the choice of electrical apparatus for uninterrupted power supply of electric rolling stock traction.

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Jiang, Wen, Ye Xia Cheng, and Ye Jian Cheng. "Research on Reliability Assessment of Power System with Wind Farms." Advanced Materials Research 608-609 (December 2012): 588–91. http://dx.doi.org/10.4028/www.scientific.net/amr.608-609.588.

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Due to randomness and fluctuation of wind speed, reliability of power system will be affected severely with increasing wind energy injected into power grid. In order to evaluate the effect on reliability of power system with wind farms, the author considers feature of time-sequential and self-correlation of wind speeds and builds an auto-regressive and moving average (ARMA) model to forecast wind speeds. Combining with state models of conventional generating units, transmission lines and transformers, a time-sequential Monte Carlo simulation reliability model is proposed to do reliability assessment of composite generation and transmission system with wind farm. IEEE-RTS test system is introduced to prove the proposed model. Analysis and comparison of results show that reliability can be improved clearly after integration of wind farm.

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Prihatini, Septimar, Djemari Mardapi, and Sutrisno Sutrisno. "PENGEMBANGAN MODEL PENILAIAN AKHLAK PESERTA DIDIK MADRASAH ALIYAH." Jurnal Penelitian dan Evaluasi Pendidikan 17, no. 2 (December 15, 2013): 347–68. http://dx.doi.org/10.21831/pep.v17i2.1705.

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Tujuan penelitian ini adalah mengembangkan model penilaian akhlak peserta didik Madrasah Aliyah. Konstruk akhlak dikembangkan dengan pendekatan akhlak sebagai aspek afektif dan konsep religiousity dari Glock and Stark (1966). Penelitian pengembangan ini menggunakan metode lapor diri dan observasi tak langsung, melibatkan 291 siswa dan 26 guru dengan teknik purposive sampling. Pengujian kualitas instrumen meliputi: validasi tampang, isi, dan konstruk; reliabilitas (konsistensi internal dan reliabilitas interrater); dan uji stabilitas instrumen. Hasil pe-nelitian ini adalah: (1) Model penilaian akhlak terdiri dari model pengukuran dan sistem peni-laian. Instrumen tersusun melalui proses expert judgment, Focus Group Disscussion dan pengujian konstruk. (2) Hasil analisis faktor konfirmatori (CFA) berdasarkan data empirik menunjukkan bahwa konstruk akhlak peserta didik mencakup dimensi akhlak kepada Allah, akhlak kepada Nabi Muhammad SAW., akhlak kepada orangtua, akhlak kepada diri sendiri, akhlak kepada guru, akhlak kepada teman/tetangga/masyarakat, dan akhlak kepada lingkungan. (3) Instrumen mempunyai kehandalan internal antara 0,865 – 0,921 (tinggi) dan reliabilitas interater 0,866 (tinggi) dan koefisien Cohens’ Kappa 0,770 (sangat baik), serta stabilitas antara 0,715 sampai 0,858 (baik sampai sangat baik). (4) Sistem penilaian setelah disimulasikan dan dikonfirmasi menunjukkan 90 % kesesuaian dengan performansi akhlak siswa. Kata kunci: model penilaian, akhlak peserta didik, konstruk akhlak, instrumen ______________________________________________________________DEVELOPING A MODEL OF AN ASSESSMENT OF MADRASAH ALIYAH STUDENTS’ AKHLAK Abstract This study aims to develop a model of an assessment of Madrasah Aliyah students’ akhlak. The constructs of students’ akhlak are developed on the basis of the akhlak as affective domain and as a religiousity concept, adopting the ritualistic concept and consequences from Glock and Stark (1966). This research and development used self-report and indirect observations, involving 291 students and 26 teachers by using purposive sampling technique. The quality instrument testing consists of: validation process (face, content and construct), reliability (internal consistency and inter-rater reliability); and stability. The results of the study are as follows. (1) The model of an assessment of students’ akhlak includes a measurement model and an assessment system for students’ akhlak. The instrument is composed through the process of expert judgment, Focus Group Disscussion and testing constructs (2) The result of Confirmatory Factor Analysis (CFA) shows that constructs of students’ akhlak cover the dimensions of akhlak to Allah, Prophet Muhammad, parents, self, teachers, society, and environment. (3) The internal reliability of instrument ranges from 0.865 to 0.921 (high); the inter-rater reliability is 0.851 (high) by Product Moment Correlation and Cohens’ Kappa coefficient 0.770 (very good). Instruments stability levels ranging from being good to being very good (0.715 to 0.858). (4) the assessment system model after the simulation is confirmation yields an agreement of 90% with the respondents’ performances.Keywords: assessment model, students’ akhlak, akhlaks’ constructs, instrument

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Mathur, Nirbhay, Vijanth Sagayan Asirvadam, and Azrina Abd Aziz. "Mechanical Damage Assessment for Pneumatic Control Valves Based on a Statistical Reliability Model." Sensors 21, no. 10 (May 11, 2021): 3307. http://dx.doi.org/10.3390/s21103307.

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A reliability assessment is an important tool used for processing plants, since the facility consists of many loops and instruments attached and operated based on other availability; thus, a statistical model is needed to visualize the reliability of its operation. The paper focuses on the reliability assessment and prediction based on the existing statistical models, such as normal, log-normal, exponential, and Weibull distribution. This paper evaluates and visualizes the statistical reliability models optimized using MLE and considers the failure mode caused during a simulated process control operation. We simulated the failure of the control valve caused by stiction running with various flow rates using a pilot plant, which depicted the Weibull distribution as the best model to estimate the simulated process failure.

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He, Qing Chuan, Wen Hua Chen, Jun Pan, and Shi Jiao Wang. "Challenges in Reliability Assessment for Electronics." Advanced Materials Research 118-120 (June 2010): 419–23. http://dx.doi.org/10.4028/www.scientific.net/amr.118-120.419.

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There has been a growing interest in assessing the ongoing reliability of electronics and systems in order to predict failures and provide warning to avoid catastrophic failure. Methods based on prognostics and health management shows an enabling technology to assess the reliability of electronics and systems under its actual application conditions. However, many challenges in implementation of methods based on PHM still remain including: environmental and usage profiles for life-cycle loads, identification of failure mechanism, identification of failure PoF model, identification of parameters to be monitored, approaches to anomaly detection. These challenges were presented and discussed, and would be carried out by developing methodologies and techniques.

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KOHDA, TAKEHISA, and KOICHI INOUE. "SAFETY ASSESSMENT MODEL OF SOFTWARE FOR FAILURE DIAGNOSIS SYSTEMS." International Journal of Reliability, Quality and Safety Engineering 06, no. 01 (March 1999): 81–89. http://dx.doi.org/10.1142/s0218539399000097.

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The software for a failure diagnosis system can be represented in terms of production rules; the condition part represents a system failure condition and the conclusion part corresponds to a cause of the system failure or an appropriate protective action to be taken. This paper proposes a safety assessment model of the software to evaluate its contribution to the risk caused by the entire failure diagnosis system. The proposed risk criterion considers not only the reliability of hardware components of the failure diagnosis system, but also the reliability characteristics of the system to be monitored. Conventional verification and validation methods of rule-based systems assume that the software reliability can be achieved by maintaining the consistent relation between condition parts and conclusion parts. However, the risk criterion derived in this paper shows that the software for a failure diagnosis system cannot be optimized without considering these environmental factors.

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SCHNEIDEWIND, NORMAN. "APPLYING NEURAL NETWORKS TO SOFTWARE RELIABILITY ASSESSMENT." International Journal of Reliability, Quality and Safety Engineering 17, no. 04 (August 2010): 313–29. http://dx.doi.org/10.1142/s0218539310003834.

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We adapt concepts from the field of neural networks to assess the reliability of software, employing cumulative failures, reliability, remaining failures, and time to failure metrics. In addition, the risk of not achieving reliability, remaining failure, and time to failure goals are assessed. The purpose of the assessment is to compare a criterion, derived from a neural network model, for estimating the parameters of software reliability metrics, with the method of maximum likelihood estimation. To our surprise the neural network method proved superior for all the reliability metrics that were assessed by virtue of yielding lower prediction error and risk. We also found that considerable adaptation of the neural network model was necessary to be meaningful for our application – only inputs, functions, neurons, weights, activation units, and outputs were required to characterize our application.

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Jiang, Wen, Zhi Hu, and Zheng Yan. "Reliability Assessment of Composite Generation and Transmission System with Wind Farms." Advanced Materials Research 347-353 (October 2011): 879–83. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.879.

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Wind energy will affect the reliability of power system for its randomness and fluctuation. In this paper, the steady state model for the asynchronous generator is established and wind farms are considered as special PQ buses during power flow calculation. Combining with state models of conventional generating units, transmission lines and transformers, a time-sequential Monte Carlo simulation based on wind farm reliability model is established to do reliability assessment of composite generation and transmission system with wind farm. Meanwhile, an optimal load shedding model is used to decrease shedding load. IEEE-RTS test system is used to prove the proposed method. Analysis and comparison of results show that reliability can be improved clearly after integration of wind farm.

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Yuniarto, Dwi, A’ang Subiyakto, Aedah Binti Abd. Rohman, and Reny Rian Marliana. "Assessment of Readiness and Usability of Information Systems Use." Jurnal Online Informatika 4, no. 1 (September 6, 2019): 1. http://dx.doi.org/10.15575/join.v4i1.256.

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The assessment of the use of information systems has been carried out by many researchers. This research was conducted in Private Universities in Indonesia, which currently involve many information systems in many ways, especially those related to the management of Higher Education, by measuring the readiness and usability of the use of information systems with models that I build from the integration of two models. The results of the measurement of this study were obtained from the distribution of questionnaires, there were 47% of respondents who filled 61-80% of the level of IS usage and 68% of respondents stated their readiness in the level of readiness to use IS. The stage consists of evaluating reflective measurement models and structural model assessments. Evaluating reflective measurement in evaluating internal consistency reliability using Composite Reliability, Reliability Indicator, Convergent Validity, and Discriminant Validity, finally concluded that the use of the Readiness and Usability integration model can be forwarded to a more complex research stage and can use the questionnaire.

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Lv, Cheng Cheng, Zong Zhan Gao, Feng Zhang, and Tong Feng Gao. "Non-Probabilistic Reliability Computation and Efficiency Assessment Based on Interval Model." Applied Mechanics and Materials 685 (October 2014): 646–50. http://dx.doi.org/10.4028/www.scientific.net/amm.685.646.

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A new interval non-probabilistic reliability method is proposed in this paper. The sampling control factor is introduced, which can regulate the distribution of the sampling domain structure. The efficiency of the reliability calculation is effectively improved. The numerical results prove that this method can effectively and feasibly improve the computational efficiency of structural reliability by changing the value in practical engineering calculations when is located at a suitable interval.

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Chou, P. H., K. N. Chiang, and Steven Y. Liang. "Reliability Assessment of Wafer Level Package using Artificial Neural Network Regression Model." Journal of Mechanics 35, no. 6 (November 14, 2019): 829–37. http://dx.doi.org/10.1017/jmech.2019.20.

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ABSTRACTFor electronic packaging structure, there are many design parameters that will affect its reliability performance, using experimental way to obtain the reliability result will take a considerable amount of time. Therefore, how to shorten the design time becomes a critical issue for new electronic packaging structure development. This research will combine artificial intelligence (AI) and simulation technology to assess the long-term reliability of wafer level packaging (WLP). A simulation technology using finite element method (FEM) with appropriate mechanics theories has been validated by multiple experiments will replace the experiment to create reliability results for different WLP structures. After a big WLP structure-reliability database created, this study will apply artificial neural network (ANN) theory to analyze this database and obtains a regression model for structure-reliability relationship of WLP. Once the regression model is established and validated, the WLP geometry, such as pad size, die and buffer layer thickness, and solder volume, etc. can be simply entered, and then the WLP reliability results can be immediately obtained through the ANN regression model.

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Álvarez, Miguel Ángel Navas, José Carpio Ibáñez, and Carlos Sancho de Mingo. "Reliability Assessment of Repairable Systems Using Simple Regression Models." International Journal of Mathematical, Engineering and Management Sciences 6, no. 1 (October 29, 2020): 180–92. http://dx.doi.org/10.33889/ijmems.2021.6.1.011.

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The statistical nature of failures in repairable systems does not have a behaviour similar to non-repairable systems. The statistical models developed for the study of the reliability of repairable systems mostly based on the application of stochastic processes. However, there is a group of prediction models for reliability based on time series analysis. Below are the results and conclusions of the application of simple regression models in the escalators Avante model (TNE), in order to assess their potential use by maintenance organizations.

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Храбатин, Роман Ігорович, Микола Миколайович Яцишин, Вікторія Валеріївна Бандура, and Любов Василівна Саманів. "Design of mathematical model for reliability assessment information processing system." Technology audit and production reserves 5, no. 1(13) (October 30, 2013): 32–36. http://dx.doi.org/10.15587/2312-8372.2013.18391.

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Chowdhury, Rajib, and B. N. Rao. "Assessment of high dimensional model representation techniques for reliability analysis." Probabilistic Engineering Mechanics 24, no. 1 (January 2009): 100–115. http://dx.doi.org/10.1016/j.probengmech.2008.02.001.

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Journal articles on the topic 'Model of reliability assessment'

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