2009 Annual Reliability and Maintainability Symposium最新文献

{"title":"Probabilistic risk assessment for decision making during spacecraft operations","authors":"L. Meshkat","doi":"10.1109/RAMS.2009.4914665","DOIUrl":"https://doi.org/10.1109/RAMS.2009.4914665","url":null,"abstract":"Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods.","PeriodicalId":201787,"journal":{"name":"2009 Annual Reliability and Maintainability Symposium","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134312921","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}

{"title":"Development of reliability program standard GEIA-STD-0009","authors":"M. Cushing, E. A. Long, M. Hockenberry","doi":"10.1109/RAMS.2009.4914692","DOIUrl":"https://doi.org/10.1109/RAMS.2009.4914692","url":null,"abstract":"Until recently, Military Standard 785 [1] was the primary reliability program standard used by the US Department of Defense (DoD). MIL-STD-785 consisted of a menu of tasks that program managers could select from in order to construct a reliability program for a specific acquisition. Many systems subjected to operational field testing by the DoD failed to demonstrate their reliability requirements. MIL-STD-785 was cancelled in 1998 after two industry standards were developed as alternatives: IEEE 1332 [2] and SAE JA1000 [3]. The requirements set forth in both IEEE 1332 and SAE JA1000 are very concise and consist primarily of statements of three objectives. Many systems still fail to demonstrate their reliability requirements during operational field testing as depicted in Figure 1 [4].","PeriodicalId":201787,"journal":{"name":"2009 Annual Reliability and Maintainability Symposium","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117340209","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}

{"title":"Bayesian methods for evaluating discrete reliability growth","authors":"J. Hall, A. Mosleh","doi":"10.1109/rams.2010.5448026","DOIUrl":"https://doi.org/10.1109/rams.2010.5448026","url":null,"abstract":"Bayesian estimation procedures are derived herein that may be utilized to evaluate reliability growth of discrete systems, such as guns, rockets, missile systems, torpedoes, etc. One of the advantages of these Bayesian procedures is that they directly quantify the epistemic uncertainties in model parameters (i.e., the shape parameters of the beta distribution), as well as six reliability growth metrics of basic interest to program management. These metrics include: (1) the initial system reliability; (2) the projected reliability following failure mode mitigation; (3) reliability growth potential (i.e., the theoretical upper-limit on reliability achieved by finding and fixing all failure modes via a specified level of fix effectiveness); (4) the expected number of failure modes observed during testing; (5) the probability of observing a new failure mode; and (6) the fraction of the initial system probability of failure associated with failure modes for which program management is aware. These metrics [18] give reliability practitioners the means to estimate the reliability of discrete systems undergoing development, address model goodness-of-fit concerns, quantify programmatic risk, and assess system maturity. Analytical results are presented to obtain Bayes' estimates of the beta shape parameters under a delayed corrective action strategy (i.e., when corrective actions are installed on system prototypes at the end of the current test phase). A Monte Carlo simulation approach is given for constructing uncertainty distributions on each of the aforementioned reliability growth management metrics. Bayesian probability limits for inference on interval estimation are obtained in the usual manner (i.e., via desired percentiles of the uncertainty distributions). These uncertainty distributions are found to be approximated very well by beta and/or Gaussian random variables. These methods are illustrated by simple numerical examples. In particular Bayes' estimates the beta shape parameters are obtained from a small dataset, and compared against the true parameter values. Bayesian epistemic uncertainty distributions are also constructed for the reliability growth management metrics via the proposed Monte Carlo approach. This methodology is useful to program managers and reliability practitioners that wish to quantitatively assess the reliability growth program of one-shot systems developed under a delayed corrective action strategy.","PeriodicalId":201787,"journal":{"name":"2009 Annual Reliability and Maintainability Symposium","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126613503","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}