2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)最新文献

{"title":"Accelerated reliability demonstration and assurance test design","authors":"M. Krasich","doi":"10.1109/RAMS.2010.5448027","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448027","url":null,"abstract":"This paper, shows how the fixed duration and reliability assurance tests, time and cost prohibitive in the past, can be accelerate to achieve two fold advantage: to determine item (product) reliability as it is related to its actual use stresses, and to considerable shorten the test time, to accommodate reasonable cost and tight program schedules. While traditional tests of this type were modeled mathematically to produce the measure of reliability as MTBF with the assumption of all failure rates being constant, there is little or no guidance on what the environmental and operational stresses need to be applied during the test.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127307895","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":"Modeling and quantification of aging systems for maintenance optimization","authors":"W. Lair, R. Ziani, S. Mercier, M. Roussignol","doi":"10.1109/RAMS.2010.5448074","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448074","url":null,"abstract":"To conclude, this method quickly gives us reliability quantities that allow us to find an optimal maintenance. The methodology can be used for many systems. However the limitations are the number of aging components and the system complexity. Indeed, the computational time increases with those two parameters. In the future, we will try to apply this method with more complex systems and keep the computational time low. Focus will also be put on the determination of importance and sensibility indicators, in order to be able to identify the essential components of the systems, from the maintenance optimization point of view.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703752","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":"Reliability estimation for one-shot systems with zero component test failures","authors":"Huairui Guo, S. Honecker, A. Mettas, D. Ogden","doi":"10.1109/RAMS.2010.5448016","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448016","url":null,"abstract":"Te for one-shot systems such as missiles and rockets are very expensive. In order to design an efficient test plan to demonstrate the required reliability in the final system test, system reliability should be studied in advance. Before the final system tests, many subsystem level tests usually have already been conducted by customers and manufacturers. Therefore, the system reliability can be estimated using the information obtained from these tests before the final system test. Due to the highly reliable nature of one-shot systems, it is very unlikely to observe many failures, even at the subsystem level tests. To accurately estimate the system reliability with few failures or even without failures is very challenging. A lot of research has been done on how to estimate the system reliability and its confidence intervals from its subsystem test data. However, most of them require failures at the sub-level tests. When there are no failures, these methods do not work. In this paper, a flexible and practical method is designed to estimate the system reliability and its confidence bounds when there are few or no failures during the subsystem tests. This method can be applied to series, parallel and complex systems. The estimated system reliability information is then used to design an efficient test plan for the final system reliability demonstration test. A case study shows that the proposed method is very efficient and accurate when compared with existing methods and simulation results.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"51 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114059126","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":"Applying discrete event modeling in the real world","authors":"J. Owens, Arthur S. Miller, D. Deans","doi":"10.1109/RAMS.2010.5448012","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448012","url":null,"abstract":"There are many facets and features to applying the processes of reliability, availability, and maintainability (RAM) engineering during the lifecycle of a system. None are more important than the methodical, intentional application of modeling and simulation upfront in the design of a system to ensure that requirements are met. This paper presents and discusses solutions that demonstrate the practical application of complex modeling and how this process applies practically using real-world examples such as chemical manufacturing plants and space-borne systems. Many large manufacturing or development organizations are driven by costs of development and real-time maintenance and not seeking long term value by planning a system to be more reliable, and thus creating value by reducing cost of operation and ownership. RAM Simulation and Modeling is a process employed by RAM engineers for predicting performance of a system in order to drive value through reliability gap analysis, and project development as examples. The authors will demonstrate, through practical examples, how application of the RAM modeling has been applied to create maximum value to both Government entities and commercial companies alike. Modeling and simulation have been employed throughout all phases of the lifecycle of new system development (new plant designs, existing facilities improvements, integrated site design, spacecraft development, and maintenance task analysis) and have delivered value in the form of lower cost of operation, improved availability of the system, and value to corporate bottom lines. The authors will also demonstrate how reliability engineers have successfully provided value to design teams by helping them identify failure modes and mitigate them, thus improving the systems that they support.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128660672","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":"Optimal replacement of safety-critical aircraft parts with utilization uncertainties","authors":"Peng Wang, T. Jin","doi":"10.1109/RAMS.2010.5447966","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5447966","url":null,"abstract":"Two maintenance optimization programs have been proposed to find the optimum lifetime limits of turbine wheels, a safety-critical component in the aircraft engine. The deterministic model enables us to quickly calculate the optimum replacement time provided that the accurate cumulative operating hours are available for the critical components. When the component operating hours involve utilization uncertainties, the stochastic model has been demonstrated as an effective method in terms of finding the optimum age-based replace time. The result is accurate as compared to the solutions form Monte Carlo simulations.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129160672","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":"Two recommendations for the acquisition and growth of reliable systems","authors":"D. Nicholls, P. Lein","doi":"10.1109/RAMS.2010.5448040","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448040","url":null,"abstract":"This paper presents two recommendations for improving the acquisition and growth of reliable systems that support the intent of DoDI 5000.02 and ANSI/GEIA-STD-0009: ● During the proposal evaluation and selection process, use a metric based on a Historical Observed Reliability Ratio (HOR-R, pronounced “horror”) of the potential supplier's predicted or assessed reliability measure to its observed field reliability value. ◯ Consistent HOR-R values of less than or equal to 1.0 provide confidence that the supplier has a repeatable process for translating its prediction/assessment methodology of choice into correlated field experience that meets or is better than the reliability requirement, representing limited reliability and life cycle cost risk to the customer. ◯ HOR-R values greater than 1.0 indicate potential risk to the customer, in that the supplier has not demonstrated an ability to achieve reliability requirements in the field based on its prediction/assessment techniques, implying increased reliability and life cycle cost risk. ◯ Inability of a supplier to provide any HOR-R value based on past performance represents an unknown level of reliability and life cycle cost risk to the customer. ◯ Any reliability prediction or assessment technique can be used, e.g., empirical handbooks, physics-of-failure (PoF), etc., since the effectiveness of the metric is not based on the ability of the approach to generate a “suitable” number. ◯ The metric can be applied to requirements based on Mean Time Between Failure (MTBF), Mean Time to Failure (MTTF), Reliability (R(t)), Operational Availability (Ao), etc. ● Extend the definition of reliability growth A-Mode and B-Mode failures [1, 2] to include classifications of “Unanticipated Failure Mode” and “Unexpected Failure Mode”. ◯ The larger the percent contribution of Unanticipated Failure Modes to Total Failure Modes, the less robust the Design for Reliability (DFR) process is in proactively identifying failure modes prior to testing. Corrective action is based on an evaluation of current DFR analyses, modeling and simulation processes to improve their ability to identify failure modes. ◯ The larger the percent contribution of Unexpected Failure Modes to Total Failure Modes, the less effective the DFR process is in mitigating known failure modes. Corrective action is to improve reliability design practices, rules, procedures, etc., to more effectively mitigate identified failure modes prior to test. These two recommendations, and the corrective actions they initiate, provide benchmarks to improve both the effectiveness of acquisitions in reliability and life cycle cost risk avoidance, and the ability of DFR activities to proactively identify and mitigate failure modes prior to their more costly discovery during testing or field use.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121773193","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":"Integrated risk sensitivity study for Lunar Surface Systems","authors":"S. Go, D. Mathias, H. Nejad","doi":"10.1109/RAMS.2010.5448002","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448002","url":null,"abstract":"This paper illustrates an innovative approach to assessing the reliability of conceptual Lunar Surface Systems architectures using an integrated analysis model. The integrated model represents systems, dependencies, and interactions to develop risk-based reliability requirements that balance functional characteristics, needs, demands, and constraints to achieve availability goals. The model utilizes “availability” metrics based on first-order descriptions of the architecture to begin providing reliability impacts even before much design detail exists. Sensitivity analyses are performed to identify key risk parameters and find “knees” in the curve for establishment of system architecture- and element-level requirements.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132038654","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":"A multi-objective memetic algorithm for RBDO and robust design","authors":"Xiaotian Zhuang, R. Pan","doi":"10.1109/RAMS.2010.5447967","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5447967","url":null,"abstract":"In this paper, the requirement of robust design is explained first. An equivalent criterion based on percentile difference is evaluated as the performance variation. To maintain the design feasibility under variations, reliability constraints are considered. Then a multi-objective optimization problem, integrating robust design and reliability, is discussed. The performance variation and performance measure are simultaneously minimized.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726875","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":"Risk Informed Design modeling process & design team - Analyst interaction","authors":"C. Mattenberger","doi":"10.1109/RAMS.2010.5447997","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5447997","url":null,"abstract":"As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. The Altair design team was able to overcome these challenges by employing a process of Risk Informed Design utilizing the Valador Reliability Tool [1] (VRT). This tool is able to quickly and accurately produce estimates of the risk of Loss of Mission (LOM) and Loss of Crew (LOC) per mission and provide insight to the designers as to how their decisions will impact overall mission success. The VRT employs a method or risk assessment that is unlike traditional PRA as it effectively engages the designers in the model building process and as a result of this increased Designer - Analyst interaction both the quality of the design and the quality of the PRA model is increased.","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132750491","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":"Field failure rate may not be what you think","authors":"J. McLinn, D. Rand","doi":"10.1109/RAMS.2010.5448011","DOIUrl":"https://doi.org/10.1109/RAMS.2010.5448011","url":null,"abstract":"Ramp up, commercialization or roll-out are all common terms for one stage of a project when it goes from a low level production rate to a high rate. During this time, it is common for new problems to arise and the time to failure remain unknown. When shipping systems without operating time clocks or serialization, only the quantities shipped and quantities replaced are known. Weibull modeling generated from such roll-out data can easily be misleading. This paper will show some common errors with these model attempts that can be avoided. The roll-out process itself is part of the problem. Often, this is a hurried phase of limited time that is followed by a longer and fairly steady production rate. Even when ramping with a constant failure rate situation, it takes more than six months for the Weibull model data to settle down and look constant. Add a second failure mode, one that occurs in addition to the constant failure rate and the result is a complex Weibull curve that doesn't reflect either mode well. This easily happens when the operating environment varies from customer to customer. Several examples will make this graphically clear. Lastly, some conclusions are presented and some suggestions that will help separate failure modes during the ramp up. These suggestions will help obtain better estimates for planning warranty costs and determining repair support necessary. The problem described is real; examples from the disk drive industry are cited where ramp up and multiple failure modes are intertwined [1, 2, 3].","PeriodicalId":299782,"journal":{"name":"2010 Proceedings - Annual Reliability and Maintainability Symposium (RAMS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116442156","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}