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2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)最新文献

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A new NHPP model for modeling failure process with S-shaped mean cumulative function 基于s型平均累积函数的失效过程NHPP模型
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050152
R. Jiang
{"title":"A new NHPP model for modeling failure process with S-shaped mean cumulative function","authors":"R. Jiang","doi":"10.1109/ICRMS.2016.8050152","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050152","url":null,"abstract":"The mean cumulative function (MCF) characterizes the failure behavior of a repairable system. Typical model for modeling failure process is the power-law model. It is only applicable for the situations where the empirical MCF is concave or convex. In practical applications, the empirical MCF can be S-shaped. The intensity function associated with an S-shaped MCF is unimodal. The unimodal failure intensity results from interaction between aging and maintenance improvement. In the literature, few models are available for representing the failure process with unimodal failure intensity. In this paper, we present such a model. The model has three parameters and its expression is relatively simple. A regression method is developed to help determine whether the model is appropriate for modeling a given set of data and obtain the initial estimates of the model parameters. The maximum likelihood method is used to obtain the final parameter estimates. Two real-world examples are included to illustrate the appropriateness and usefulness of the proposed model and the parameter estimation method.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124014818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Regional importance analysis under multiple failure modes 多失效模式下的区域重要性分析
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050053
Baoyu Li, Lei Cheng, Leigang Zhang, Yao Wang, Xiongqing Yu
{"title":"Regional importance analysis under multiple failure modes","authors":"Baoyu Li, Lei Cheng, Leigang Zhang, Yao Wang, Xiongqing Yu","doi":"10.1109/ICRMS.2016.8050053","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050053","url":null,"abstract":"For structural system with multiple failure modes extensively present in engineering practice, two regional mode importance measures are proposed on the basis of the existing mode importance measures, i.e., the regional mode importance measure based on failure probability and the regional mode importance measure based on sample mean of output response. Compared with the existing global mode importance measures, the proposed regional importance measures can not only provide the inter-mode importance information, but also reflect the effects of different regions of input variables on the importance of a single mode or a group of modes, thus providing useful information to improve and optimize the reliability model. Numerical and engineering examples are used to demonstrate the feasibility and rationality of the proposed indices.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115450292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of MTBF evaluation methods for small sample sizes 小样本MTBF评价方法分析
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050042
Hongsheng Pan, Anwei Sheng, Zhuojian Wang, Xinmin Han
{"title":"Analysis of MTBF evaluation methods for small sample sizes","authors":"Hongsheng Pan, Anwei Sheng, Zhuojian Wang, Xinmin Han","doi":"10.1109/ICRMS.2016.8050042","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050042","url":null,"abstract":"The accurate estimation of Mean Time Between Failures (MTBF) may be necessary under small sample size conditions and can be difficult. This article proposes combinations of two methods to calculate the cumulative probability using hierarchical Bayesian estimation and the mean rank order method, and two approaches to estimate parameters of the Weibull distribution using the ε-support vector regression (ε-SVR) and least square method. The relative error of these methods against a simulation are used to measure the accuracy of the parameter estimation where, according to the definition of MTBF, the expectation of the Weibull distribution is taken as the estimated value of MTBF. The article suggests approaches for further research in the reliability of aviation equipment.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122069717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
New forecasting method of closing time for aerospace relay in storage accelerated degradation testing 航天继电器贮存加速退化试验合闸时间预测新方法
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050118
Zhao-Bin Wang, Sai Fu, Shang Shang, Wenhua Chen
{"title":"New forecasting method of closing time for aerospace relay in storage accelerated degradation testing","authors":"Zhao-Bin Wang, Sai Fu, Shang Shang, Wenhua Chen","doi":"10.1109/ICRMS.2016.8050118","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050118","url":null,"abstract":"Space relays are affected by many nonlinear elements during storage, and the reason for predicting time series is to achieve nonlinear mapping. Combining artificial neural networks and grey system theory, we built a grey artificial neural network (GANN) model. The model effectively combined the characteristics of artificial-neural-network nonlinear adaptability and the characteristics of grey theory weakening data sequence volatility integration. We predicted the degradation value of the closing time of measured data in a relay accelerated storage test by using a variety of grey models and GANN models. By comparing several forecasting methods, the results showed the proposed grey neural network model has higher precision and is more accurate than a single grey model. The method also provides new ideas and methods for the life prediction of relay storage acceleration tests.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132528807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Fault location method of complex software based on community mining 基于群体挖掘的复杂软件故障定位方法
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050150
Rui Li, Minyan Lu, Qian Ye
{"title":"Fault location method of complex software based on community mining","authors":"Rui Li, Minyan Lu, Qian Ye","doi":"10.1109/ICRMS.2016.8050150","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050150","url":null,"abstract":"The explosion by amount of codes as well as the swelling logic complexity have stifled the performance of the traditional fault-location methods since the resource adopted during this process is unacceptable. Under such a situation, a scheme to locate the faults in complex software more effectively has been proposed in this paper based on networks community theory. First, on the base of establishing the dependency network of every module in software, dependency relationships between various community blocks can be obtained by applying clustering algorithms to mine the community structure. Second, with status reports generated by monitoring-codes planted into the center node of every community, we can distinguish whether communities work in a normal way, thus the fault searching area can be shrunk smaller by repeating the steps above. Third, once the searching area has been shrunk to several modules, the traditional methods like Tarantula is eligible for finding the fault since the number of suspected codes has been compressed to an acceptable level. At last, the experiment by applying the method we come up has been conducted and the statistic has been collected as well as analyzed to compare with the main-trend solutions, during which the speed superiorities and acceptable accuracy of our method have been confirmed.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131578535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reliability degradation monitoring of CNC machine tools based on the SPC method with the Metropolis-Hastings algorithm 基于Metropolis-Hastings算法的SPC方法的数控机床可靠性退化监测
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050081
Xuejiao Du, Fei Chen, Zhaojun Yang, Binbin Xu, Weizheng Chen, Xiaoxu Li
{"title":"Reliability degradation monitoring of CNC machine tools based on the SPC method with the Metropolis-Hastings algorithm","authors":"Xuejiao Du, Fei Chen, Zhaojun Yang, Binbin Xu, Weizheng Chen, Xiaoxu Li","doi":"10.1109/ICRMS.2016.8050081","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050081","url":null,"abstract":"After the random failure period, CNC machine tools will enter the wear-out failure period as a result of abrasion, fatigue and aging. Therefore, it is extremely important to monitor the changing trend of operation state and thus to construct rational maintenance policy or determine when to scrap it. In this paper, the mean time between failures (MTBF) is chosen to be the characteristic variable of reliability degradation and is estimated from a Weibull process model. A statistical process control (SPC) chart is then developed using the Metropolis-Hastings (MH) algorithm for condition monitoring. The availability and sensitivity of the proposed method are illustrated through analyzing the field data of a CNC machining center.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133863879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A reliability optimization allocation method for multifunctional systems using new hybrid particle swarm optimization 基于混合粒子群算法的多功能系统可靠性优化分配方法
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050064
Qihai Liang, Hai-ping Dong, X. Yi, Bin Qin, Xiaoyu Yang
{"title":"A reliability optimization allocation method for multifunctional systems using new hybrid particle swarm optimization","authors":"Qihai Liang, Hai-ping Dong, X. Yi, Bin Qin, Xiaoyu Yang","doi":"10.1109/ICRMS.2016.8050064","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050064","url":null,"abstract":"A reliability optimization allocation method for multifunctional systems using Hybrid Particle Swarm Optimization (HPSO) is proposed in this paper. First, researchers established a mathematical model for system reliability optimization allocation with the constraints of multi-function failure rates. Then, the HPSO was used to solve the optimization allocation model for multifunctional systems. Finally, researchers used an integrated transmission device with five functions as an example. They allocated reliability indexes of five functions by the method proposed in this paper. The result was compared with the results of basic Particle Swarm Optimization (PSO) and the result of Genetic Algorithm (GA). This comparison showed that the method proposed in this paper has a more powerful search capability, higher solving precision, fewer required parameters, better engineering adaptability and operability, and provides a new method of reliability allocation for complex systems with multiple functions.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133725741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
An improved AGREE method with reliability mathematical model for complex system importance degree computation 基于可靠性数学模型的复杂系统重要度计算改进AGREE方法
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050166
Xin He, Yufeng Sun, Yaqiu Li
{"title":"An improved AGREE method with reliability mathematical model for complex system importance degree computation","authors":"Xin He, Yufeng Sun, Yaqiu Li","doi":"10.1109/ICRMS.2016.8050166","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050166","url":null,"abstract":"During the system design process, there are numerous factors that should be taken into account to incorporate reliability requirements into subsystems. The AGREE method is one of the most applicable methods to achieve system reliability allocation. However, when applied to some complex systems, this traditional method may become invalid. Firstly, the allocation results may become distorted and a computation method for the degree of importance is not proposed. Generally, this method can be only used for systems in series or parallel. To address these issues, the traditional AGREE allocation method needs to be modified. This paper proposes a novel degree computational method for complex system allocation whereby the traditional AGREE method is integrated with a mathematical model of system reliability. A framework for the new reliability allocation method is described. In practice, this novel method is used for the reliability allocation of a ship power system. A sensitivity analysis was conducted across several design requirements. The allocation results were verified, demonstrating the use in practical applications.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132714009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Reliability-centered optimal design method for flight vehicle control system 以可靠性为中心的飞行器控制系统优化设计方法
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050056
Shangping Kong, Hairui Zhang, X. Liao, Dongpao Hong
{"title":"Reliability-centered optimal design method for flight vehicle control system","authors":"Shangping Kong, Hairui Zhang, X. Liao, Dongpao Hong","doi":"10.1109/ICRMS.2016.8050056","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050056","url":null,"abstract":"With the dominant emergence of hi-tech and the great diversification of flight vehicle's mission requirements, a more reliable control system is needed to face the complex missions and environment. To meet these requirements, a reliability-centered optimal design method for flight vehicle control system is put forward by integrating the reliability analysis into function and performance design. An air based flight vehicle is taken as an application example to illustrate the design method. The mission profile is firstly analyzed based on the mission requirements and the function demands are proposed as the design constraints. Based on this, the failure mode and effect analysis (FMEA) method is introduced and used to identify the weak links in the system. According to the result of FMEA, an improved design scheme is proposed and proved to be effective in practice. It illustrates that the reliability-centered optimal design method can effectively improve the reliability level of the flight vehicle while ensuring that the functions and performance meet the requirements.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124770854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quality entropy model of the numerical control manufacturing process 数控制造过程的质量熵模型
2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS) Pub Date : 2016-10-01 DOI: 10.1109/ICRMS.2016.8050101
Yubing Huang, W. Dai, Yongjiao Chi, Yu Zhao
{"title":"Quality entropy model of the numerical control manufacturing process","authors":"Yubing Huang, W. Dai, Yongjiao Chi, Yu Zhao","doi":"10.1109/ICRMS.2016.8050101","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050101","url":null,"abstract":"During the numerical control manufacturing process, the operational path and process parameters were defined, however, the various kinds of manufacturing factors were still generating great uncertainties. In this paper, the quality entropy model of the manufacturing process is put for word to analyze the uncertainty factors on the products of NC machining. The entropy theory combined with information entropy and quality entropy concept was proposed to model the quality entropy of the manufacturing process. The manufacturing factors, including hardware equipment, operator, environment deviation and rejection rate which influence the product quality are given, and the criterion and method determining the corresponding uncertainty state are given, and the quality entropy algorithm of the manufacturing process and the influence degree of each uncertainty are given. And the case study is analyzed and the quality entropy of manufacturing process is calculated.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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