2020 Annual Reliability and Maintainability Symposium (RAMS)最新文献

{"title":"How Do Systems Fail?","authors":"B. O’Halloran, Douglas L. Van Bossuyt","doi":"10.1109/RAMS48030.2020.9153715","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153715","url":null,"abstract":"Summary & ConclusionsModern systems are changing quickly and becoming more complex through increased connectivity, smaller packaging, higher performance requirements, more components, the inclusion of complex software and Artificial Intelligence (AI), and much more. The following are high-level challenges that arise in many modern systems. The first is the distribution of the system, which are both physical (e.g., power grids) and digital (e.g., air traffic control, transportation networks). With highly distributed system, the vulnerability from the environment becomes significant. The second challenge is the implementation of new technology where examples include driverless vehicles and Boeing’s 787 Dreamliner. Occasionally implementing new technology doesn’t lend well to their intended purpose as observed by the Supersonic Transport (SST) aircrafts for commercial flights such as Concorde [1] and the Tupolev Tu-144 [2]. This industry suffered a major crash, Air France Flight 4590, that killed 109 passengers and crew and led to the ultimate demise of the industry [3]. The result of these design challenges is the need for improved methods to identify, assess, and mitigate off-nominal behavior. While all industries seek to create safe and reliability systems, their failures continue to splash across the news with surprising regularity. The examples are nearly endless. Across 63 years (1957–2019) there have been 402 mission failures in the spaceflight industry including satellites, manned spacecrafts, rockets, etc. As a subset of these missions, the manned spaceflight industry has seen 118 failures with a total of 262 deaths [4]; there have been 5 manned flight incidents where 19 astronauts died, 8 training or testing incidents where 11 astronauts died, 35 incidents where a total of 232 non-astronauts died (e.g., civilians, employees, etc.), and 70 incidents (35 flight and 35 training or testing) where no deaths occurred. Beyond the 402 mission failures, there have also been 118 Satellite launch failures [4]. Since the introduction of the commercial airline industry in 1918, there have been a reported 154,984 deaths [3]. Since 1970, there have been 11,634 accidents. Even more alarming is that the annual death rate hasn’t decreased much with time. The death rate per year between 1970–2018 is 1722 and between 1990–2018 is 1337. While this has reduced, a large number of accidents continue to cause a large number of deaths in this industry. According to [5], there have been 25 major dam failures, 16 of which have occurred in the last 50 years. The nuclear power industry has observed over 100 failures, several of which have resulted mitigations exceeding a billion US dollars. It is important to note that systems fail with regularity regardless of the system’s type, purpose, or age, the industry that the system belongs, or the era in which it was designed and built. The continued increase in what we demand from our systems has always trumped the practitio","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133415634","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":"Automatic Generation of RAMS Analyses from Model-based Functional Descriptions using UML State Machines","authors":"Christof Kaukewitsch, Henrik Papist, M. Zeller, M. Rothfelder","doi":"10.1109/RAMS48030.2020.9153667","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153667","url":null,"abstract":"SUMMARY & CONCLUSIONSIn today’s industrial practice, safety, reliability or availability artifacts such as fault trees, Markov models or FMEAs are mainly created manually by experts, often distinctively decoupled from systems engineering activities. Significant efforts, costs and timely requirements are involved to conduct the required analyses. In this paper, we describe a novel integrated model-based approach of systems engineering and dependability analyses. The behavior of system components is specified by UML state machines determining intended/correct and undesired/faulty behavior. Based on this information, our approach automatically generates different dependability analyses in the form of fault trees. Hence, alternative system layouts can easily be evaluated. The same applies for simple variations of the logical input-output relations of logical units such as controllers. We illustrate the feasibility of our approach with the help of simple examples using a prototypical implementation of the presented concepts.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124063512","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":"Fast Iterative Design Optimization for Reliability Vibration Tests in Automotive","authors":"M. Bonato","doi":"10.1109/RAMS48030.2020.9153601","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153601","url":null,"abstract":"Summary & ConclusionsThe development of an engine-cooling module (ECM) for an European carmaker faced a major blocking point. The stalemate concerned the design of the suspension rubbers separating the engine-cooling radiator (the ECM carrier) from the chassis. The development of an engine-cooling module (ECM) for an European carmaker faced a major blocking point. The stalemate concerned the design of the suspension rubbers separating the engine-cooling radiator (the ECM carrier) from the chassis. From the one hand, the damping rubbers had to be soft, in order to be compliant with noise, vibration & harshness (NVH) criteria – acoustic noise and vibration transmitted to the cabin. On the other hand, their softness would provoke such high amplitude response during shaker tests that the module carrier (the radiator) would fail at the early stage of vibration testing – a leakage was observed after 10 hours of the targeted 90 hours duration. New rubbers, designed for durability purposes, would fail to meet the NVH criteria. The project development team went through a double-faced dilemma: how to design rubbers with an acceptable trade-off between NVH and durability of the engine-cooling radiator, and how to find a quick and efficient way to validate the design in order to be compliant with vibration validation tests. Together with the customer, our company (automotive tier-1 supplier) established an iterative design optimization of the damping rubbers, based on the simultaneous feedback from the acoustic response and the durability predictions. The goal was to develop a strategy permitting a quick an effective criteria for damage estimation for each design proposed.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127871513","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":"Transitioning a Reliability/Sustainment Model into a Digital Twin","authors":"Alastair Moubray, Philip A. Bedard, J. Miro, Robert Stukes","doi":"10.1109/RAMS48030.2020.9153589","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153589","url":null,"abstract":"Complex weapon systems, such as the Navy’s family of shipboard Active Electronically Steered Array (AESA) radars, present unique challenges to effectively model, plan, and optimize for high reliability and low support costs.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128938694","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":"Monte Carlo Simulation for Reliability","authors":"Rodney Benson, Darryl W. Kellner","doi":"10.1109/RAMS48030.2020.9153600","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153600","url":null,"abstract":"This paper provides an introduction to Monte Carlo simulation and its applicability to reliability engineering. It provides an example of how Monte Carlo simulation can be used to help answer questions regarding the length of time complex systems can operate in a degraded state before falling below performance thresholds, and how it can be used to assist in program development by comparing alternative designs. By developing a custom Monte Carlo model, various outputs can be provided to provide insights into how changes to the design affect the reliability of the system.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129189883","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":"Detailed Interface FMECA in a Large Aerospace System","authors":"Reinaldo Perez","doi":"10.1109/RAMS48030.2020.9153580","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153580","url":null,"abstract":"The generation of piece-part interface FMECA for a large aerospace system is addressed via the use of several preliminary constructs that greatly facilitate the process of generating the piece-part interface FMECA for a large system. The constructs of circuit data sheets, schematics, fault containment regions, and a new version of piece-part interface FMECA can all in unison help in the performance of the task. The piece-part interface FMECA is one of the most useful FMECA for analyzing failure modes at a system level if hardware failure modes are to be incorporated into an aerospace fault management system. This paper establishes that defining the fault containment regions and the generation of the piece-part interface FMECA from the fault containment regions provides a new and effective way in addressing failures in large systems.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129253735","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":"Effects Assessment for Requirements Faults of Safety Critical Software in Nuclear Industry","authors":"Boyuan Li, C. Smidts","doi":"10.1109/RAMS48030.2020.9153594","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153594","url":null,"abstract":"In a context where software has been pervasive in safety critical applications, trust in software safety is challenged by software complexity and lack of systematic methods to assess the effects of remaining faults. To expand the use of digital technology in the nuclear industry, systematic methods are required to assess the effects of remaining faults for software-based Instrumentation & Control (I& C) systems in safety critical applications. In this paper, the effects of the remaining requirements faults are assessed using a probability density function (PDF) of their hazard rates. A hazard-based effect analysis (HEA) method is developed to obtain the probability distribution of the hazard rates of a remaining requirements fault. The HEA method is applied to a Reactor Protection System (RPS) in the case study. The probability density functions for the introduced faults, detected faults and remaining faults in the requirements phase of the RPS system on the domain of hazard degree are obtained.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"432 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116006768","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":"Resilience in the Context of Nuclear Safety Engineering","authors":"R. Yan, S. Tolo, S. Dunnett, J. Andrews, E. Patelli","doi":"10.1109/RAMS48030.2020.9153717","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153717","url":null,"abstract":"SUMMARY & CONCLUSIONSThe safety and reliability of critical infrastructures is a key challenge in modern societies. This is all the more true when referring to the nuclear power industry, due to the rigid safety requirements on the one hand and the growing complexity of new systems on the other. The current study investigates the potential of a resilience engineering approach in dealing with current and future challenges in the context of nuclear reactor safety. The efficiency of several resilience metrics for capturing systems’ performance in the case of accidents are discussed, and a novel framework for resilience analysis of nuclear reactor is proposed. The overall aim of this work is to provide computational and theoretical tools for resilience evaluation, paving the way for its application in the nuclear industry.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115356118","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":"An Entropy-based Approach for Modeling Lithium-Ion Battery Capacity Fade","authors":"Alireza Namdari, Z. Li","doi":"10.1109/RAMS48030.2020.9153698","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153698","url":null,"abstract":"Batteries are key components of many electronic devices including instrumentations, vehicles, embedded systems, and medical devices. The malfunction of batteries may cause failure in operations of the entire system. Thus, the health management of the batteries, such as the determination of the operating conditions and replacement intervals, is essential in order to ensure the normal functioning and operations of the entire system. The battery health indicators built on effective health monitoring can be integrated into a prognostic model such that the batteries will be operating within the design limits to meet expected performance and safety requirements. Entropy, which originated as a concept in physics and thermodynamics, has been widely used to measure the regularities and uncover the uncertainties of stochastic processes. Different entropy measures have been introduced since Shannon presented the first definition of entropy, including Permutation entropy, Renyi entropy, Tsallis entropy, Approximate entropy, and Sample entropy. In this study, we assess various entropy measures of short voltage sequences of multiple lithium-ion batteries under different testing conditions. Then a Support Vector Machine (SVM) is employed to model the relationship between the battery capacities and various entropy measures of battery voltages. Numerical results reveal that the entropy measures are effective estimators of battery capacity loss and the proposed SVM-Entropy-based model is capable of predicting the battery capacity fade with high accuracies.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115714433","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":"Life Data Analysis with a Joint Probability Density Function","authors":"Umur Yenal, David Jimenez","doi":"10.1109/RAMS48030.2020.9153681","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153681","url":null,"abstract":"When assessing product life, the survival analysis is generally conducted in a time or usage domain. In certain instances, it is beneficial to investigate the impact of joint variables on product reliability, and in this case, the joint distribution of usage and time are considered. While it is simple to analyze unconditional probability density functions independently, the problem of statistical independence with random variables of usage and time arises. Usage is not independent of time, since usage contains information about time and thus, the joint probability density function then cannot be the product of both marginal probability density functions.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"37 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126058111","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}