2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)最新文献

{"title":"Reliability growth model in early design stages","authors":"J. Juskowiak, V. Schweizer, M. Stohrer, B. Bertsche","doi":"10.1109/RAMS.2013.6517687","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517687","url":null,"abstract":"In this paper, a new model for reliability growth planning in product development as well as a derived potential for its optimization are proposed. Unlike current models which do not have the ability to edit previous input data and thereby update the planning curve, the S-Planning-Curve (SPL), is proposed. Additionally, the SPL test results can be integrated as well. A delay before the beginning of the first test is also taken into account. The use of this integral approach and integration of known models, such as the continuous power law, make the SPL a powerful tool in product development. In addition the computer-based application can be easily used in practice. Because of its flexibility, the SPL model has advantages in different cases compared to the Modified Power Law and the modified IBM-Rosner Model. At the beginning of new complex products, it takes time to analyze the system thoroughly. Consequently this characteristic is implemented by the SPL. Furthermore, a delay time can be used to setup a test station. On the other hand, the SPL allows a response to a discrepancy between the actual and planned reliability at development time.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130323491","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 predictions - continued reliance on a misleading approach","authors":"C. Jais, B. Werner, D. Das","doi":"10.1109/RAMS.2013.6517751","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517751","url":null,"abstract":"Reliability prediction methodologies, especially those centered on Military Handbook (MIL-HDBK) 217 and its progeny are highly controversial in their application. The use of reliability predictions in the design and operation of military applications have been in existence since the 1950's. Various textbooks, articles, and workshops have provided insight on the pros and cons of these prediction methodologies. Recent research shows that these methods have produced highly inaccurate results when compared to actual test data for a number of military programs. These inaccuracies promote poor programmatic and design decisions, and often lead to reliability problems later in development. Major reasons for handbook prediction inaccuracies include but are not limited to: 1) The handbook database cannot keep pace with the rapid advances in the electronic industry. 2) Only a small portion of the overall system failure rate is addressed 3) Prediction methodologies rely soley on simple heuristics rather than considering sound engineering design principles. Rather than rely on inaccurate handbook methodologies, a reliability assessment methodology is recommended. The reliability assessment methodology includes utilizing reliability data from comparable systems, historical test data, and leveraging subject-matter-expert input. System developers then apply fault-tree analysis (or similar analyses) to identify weaknesses in the system design. The elements of the fault tree are assessed against well-defined criteria to determine where additional testing and design for reliability efforts are needed. This assessment methodology becomes a tool for reliability engineers, and ultimately program managers, to manage the risk of their reliability program early in the design phase when information is limted to: 1) The handbook database cannot keep pace with the rapid advances in the electronic industry. 2) Only a small portion of the overall system failure rate is addressed 3) Prediction methodologies rely solely on simple heuristics rather than considering sound engineering design principles.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132348164","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":"Improved software reliability by application of scorecard reviews","authors":"D. Bernreuther, T. Pohland","doi":"10.1109/RAMS.2013.6517767","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517767","url":null,"abstract":"To support development of more reliable software, AMSAA has developed a software reliability scorecard offered free of charge to department of defense employees and their contractors. The scorecard methodology provides a structured and transparent approach to assess and improve software reliability practices. AMSAA's new software reliability scorecard assesses seven key areas of software development and sustainment: Program Management, Requirements Management, Design Capabilities, System Design, Design for Reliability, (Customer) Test & Acceptance, and Fielding & Sustainment. Across the categories a total of 57 specific elements are examined. The scorecard evaluates the risk being taken in each of the key areas separately and also assesses the overall risk of the effort. The instrument captures the rationale for the assessment score given and identifies them along with recommendations for reducing individual risks.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"1082 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133178834","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":"Design Interface - The nexus of engineering and product support","authors":"P. Dallosta, T. A. Simcik","doi":"10.1109/RAMS.2013.6517688","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517688","url":null,"abstract":"The paper defines the Design Interface process by which system design characteristics of Reliability and Maintainability are analyzed and trade studies conducted to influence the design to meet operational and sustainment requirements. Given that the total cost of Reliability may account for as much as 60% of a system's life Cycle Cost [1], emphasis on reducing the impact of Reliability related cost drivers during the early phases of product development is an imperative for the Program Management, Systems Engineering and Product Support communities.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133069461","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":"Practical Bayesian methods for determining device failure rates from zero-failure data","authors":"M. V. Bremerman","doi":"10.1109/RAMS.2013.6517734","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517734","url":null,"abstract":"This paper presents several practical methods that can be used to supplement classical reliability prediction techniques typically used to calculate electronic system failure rates. These methodologies employ Bayesian data analysis techniques utilizing available field reliability data and accelerated life test (ALT) results. Methodologies include the Clopper-Pearson method which has been shown in the literature to be a special case of the Bayesian method. The Clopper-Pearson lower one-sided confidence bound equation is solved in terms of reliability and allows for the derivation of a failure rate point estimate when no credible prior information is available and zero failures have occurred in the field. When lower level test data such as accelerated life test results (informative prior) are available, a gamma-exponential conjugate model can be used to derive the failure rate from the resulting posterior distribution over a range of credibility intervals using the GAMMAINV Excel function. An example of application in the context of the space industry is presented where the failure rate for a power hybrid device was derived using real accelerated life test results and zero-failure on-orbit data collected from multiple space payloads.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122832710","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 assessment of IGBT modules modeled as systems with correlated components","authors":"E. Kostandyan, J. Sørensen","doi":"10.1109/RAMS.2013.6517663","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517663","url":null,"abstract":"System modeling of electrical components for Wind Turbine (WT) applications is an important part for the overall WT reliability assessment. The presented approach is an approximate method for Insulated Gate Bipolar Transistor (IGBT) reliability estimation, modeled based on the parallel system configuration. The estimated system reliability by the proposed method is a conservative estimate. Application of the suggested method could be extended for reliability estimation of systems composing of welding joints, bolts, bearings, etc. The reliability model incorporates the correlation between the components in the reliability estimation though limit state functions and mechanical (failure-effect) correlations. The model is based on a physics of failure approach and a linear accumulated damage rule. To account model parameter variabilities, the First Order Reliability Method (FORM) technique was applied for the systems failure functions estimation. It is desired to compare the results with the true system failure function, which is possible to estimate using simulation techniques. Theoretical model development should be applied for the further research. One of the directions for it might be modeling the system based on the Sequential Order Statistics, by considering the failure of the minimum (weakest component) at each loading level. The proposed idea to represent the system by the independent components could also be used for modeling reliability by Sequential Order Statistics.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121061991","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":"System level reliability analyses and predictions in a varying stress environment","authors":"D. Johnson, D. Coit, R. Kosaka, K. Megow","doi":"10.1109/RAMS.2013.6517617","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517617","url":null,"abstract":"New flexible methods have been developed to predict reliability and estimate failure time distribution parameters for equipment and systems that are to be exposed to more stressful and diverse usage conditions in the future. Decades ago, the design reference mission for steam catapults and arresting gear on aircraft carriers was quite simple. The design engineers of these systems had a good understanding of the loads and added factors of safety to be cautious. Move ahead to the present, the mixture of aircraft has changed drastically, sortie rate has increased and so has the kinetic energy imparted to these critical systems. This has led to a need to develop a more generalized and flexible reliability predictive tool. This tool can be described as a stress-sensitive Weibull distribution. The entire process is outlined for this innovative technique. It includes the options for several methods of analysis. The base model is a Weibull distribution based solely on failure data without modifications. The first method is also a Weibull distribution, but the Weibull scale parameter is modified by a stress ratio, using end speed and the aircraft weight. The second method uses mean and standard deviation of end speed and aircraft weight to modify the Weibull scale parameter. These scale parameter modifiers are calculated based on an assumed general log-linear model and maximum likelihood estimation tools. The third method decouples any correlation that may exist between aircraft weight and end speed by binning aircraft launches into groups and calculating their proportion of the total. Once evaluated, these methods are able to extrapolate future failures at different levels of stress all across these critical systems.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129035221","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":"Designing a system to manage field reliability","authors":"G. Sarakakis, N. Lassar, S. Chowdhury","doi":"10.1109/RAMS.2013.6517722","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517722","url":null,"abstract":"In this paper we describe a customized system to manage field reliability, from inception to implementation. We provide the reasoning to pursue such a project, the objectives we set up front, and the challenges we faced. We created a web-based system that allows centralized management of field reliability, including systematic risk scoring and prioritization, facilitated problem resolution, automated reporting, integrated actions and document management and automated flow of issues into lessons learned. The system aims to capture the often scattered reliability knowledge that resides in emails and spreadsheets, and organize this knowledge in web-based relational database. A key part of the system is the integration of risk scoring, facilitated 8D, document and actions management, and lessons learned. This creates a reliability knowledge database that can be used to improve reliability over product life cycles and prevents re-occurrence of the same problem in future products. We hope that other organizations can benefit from the ideas presented in this paper and advance their level of sophistication in terms of managing field reliability.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116039693","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 Bayesian approach to online system health monitoring","authors":"Masoud Pourali, A. Mosleh","doi":"10.1109/RAMS.2013.6517716","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517716","url":null,"abstract":"This paper introduces a new online system health monitoring methodology utilizing Bayesian Belief Networks. The developed methodology enables inference with limited number of monitoring points optimally placed to obtain information on functional states of components, subsystems, and relevant physical parameters affecting the reliability of elements of the system. The approach integrates physics of failure modes when available with traditional reliability data (e.g., failures and demands) and is (1) capable of assessing current state of a system's health and probabilistic assessment of the remaining life of the system (prognosis), and (2) through appropriate data processing and interpretation can point to elements of the system that have caused or are likely to result in system failure or degradation (diagnosis). Continuous health assessment is made possible through the application of dynamic BBNs. The proposed methodology is designed to answer important questions such as how to infer the health of a system based on limited number of monitoring points at certain subsystems (“upward” inference); how to infer the health of a subsystem or component based on knowledge of the health of the main system (“downward” inference); and how to infer the health of a subsystem based on knowledge of the health of other subsystems (“distributed” inference). The methodology and algorithms are demonstrated through an example.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117158111","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 engineering efforts at U.S. Army Armaments Research Development and Engineering Center","authors":"M. Downes, L. P. Nguyen","doi":"10.1109/RAMS.2013.6517703","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517703","url":null,"abstract":"To achieve the goals of meeting Warfighters' requirements and maximizing reliability, Armament design engineers and program managers must pursue a scalable, tailorable and flexible reliability engineering program prior to Department of Defense (DoD) Milestone B. Milestone B is the point at which a recommendation is made regarding continuation of an acquisition program into the Engineering and Manufacturing Development (EMD) phase. Early reliability engineering influence provides more time efficiency and minimizes redesign and retest that would result from unforeseen requirements ambiguity and test failures later in the acquisition process. The U.S. Army Armaments Research, Development and Engineering Center (ARDEC) Quality Engineering and System Assurance Directorate's “Design for Reliability Process” provides a systematic procedure for planning and performing reliability engineering for new munitions, weapons and fire control systems. This paper presents the basis for the design for reliability process and tools that have been proven instrumental in designing in the reliability of armaments throughout the acquisition life cycle. While designing in reliability is expected to be more cost effective during sustainment and operational life cycle phases, a well-executed reliability engineering program will also minimize technical, performance, schedule and cost risks in the materiel solution, technology, and product development acquisition phases.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114206664","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}