2024 Annual Reliability and Maintainability Symposium (RAMS)最新文献_第2页

Reliability and Availability Analysis of Photovoltaic Systems 光伏系统的可靠性和可用性分析

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457827

Kim Hintz, M. Dazer

{"title":"Reliability and Availability Analysis of Photovoltaic Systems","authors":"Kim Hintz, M. Dazer","doi":"10.1109/RAMS51492.2024.10457827","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457827","url":null,"abstract":"This paper introduces a novel simulation that combines the reliability modeling of photovoltaic (PV) system components with their respective I-V characteristic curves. The simulation encompasses varied system designs, including string inverter and module-integrated inverter concepts, and accounts for diverse solar irradiation and shading scenarios across multiple operating conditions. By integrating reliability aspects with real-world operating scenarios, the approach offers a holistic view of PV system performance considering the impact of frequency and occurrence of component failures and different repair strategies. The research delves deep into how the inverter reliability and the choice of repair strategies can influence the profitability of a PV system in various environmental conditions. A thorough statistical analysis revealed that both inverter lifetime and repair strategy have a significant effect on profitability. Key results indicate that in Germany, the optimal repair limit for the string inverter design is approximately at a 2.5 kWh daily power loss. In contrast, if the inverter lifetime in the module-inverter concept is sufficiently long, no repairs are necessary to achieve an optimal profit. These findings highlight the intricate relationship between inverter lifetime, application scenarios, and environmental conditions when determining optimal repair strategies.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"294 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531194","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

Exploratory Data Analysis for Failure Detection and Isolation in Complex Systems 用于复杂系统故障检测和隔离的探索性数据分析

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457810

Navid Zaman, You-Jung Jun, Daniel Chan

{"title":"Exploratory Data Analysis for Failure Detection and Isolation in Complex Systems","authors":"Navid Zaman, You-Jung Jun, Daniel Chan","doi":"10.1109/RAMS51492.2024.10457810","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457810","url":null,"abstract":"Failure detection and isolation (FDI) is a crucial step in diagnostics and is quickly shifting to towards using analytical techniques such as machine learning and deep learning, rather than traditional rules-based approaches. This is partially due to the availability of sensor systems, hardware and networking allowing for a vast collection and processing of data. However, this information is prone to issues such as noise, corruption, poor formatting and recording practices. In most cases, a diagnostics project may stall midway due to late discovery of these problems. This paper proposes exploring the data beforehand, to locate issues in the data and/or optimize data quality to maximize performance or explain possible performance loss. Various techniques such as data visualization, statistical analysis and feature importance are mentioned. Most importantly, a domain knowledge set is to be integrated with such correlation-based methods to ensure that data quality decisions are made with understanding of the system. The limitations of such analysis including scalability and interpretation issues are discussed as well, leading to proposals of possible future paths to improvement such as sensor fusion and AI-based recommendations.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"282 11","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530977","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 UAV Case Study on an MBSE Workflow with Integrated Modular Safety and Reliability Analysis 无人飞行器案例研究：集成模块化安全与可靠性分析的 MBSE 工作流程

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457654

Bernhard Kaiser, Michael Soden, Nils Heuermann

引用次数: 0

Machine Learning Qualification Process and Impact to System Assurance 机器学习鉴定流程及对系统保证的影响

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457743

Benjamin Werner, Benjamin Schumeg, Jason E. Summers, V. Berisha

{"title":"Machine Learning Qualification Process and Impact to System Assurance","authors":"Benjamin Werner, Benjamin Schumeg, Jason E. Summers, V. Berisha","doi":"10.1109/RAMS51492.2024.10457743","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457743","url":null,"abstract":"To address the technical challenges associated with the verification, validation, assurance, and trust of Artificial Intelligence and Machine Learning (AI/ML) in safety critical applications, ARiA in partnership with Arizona State University (ASU) proposed the framework of a Machine Learning Qualification Process (MLQP) in response to a Small Business Technology Transfer (STTR) solicitation. The MLQP incorporates measures and metrics to qualify data sets and models and considerations for the use of data cards, feature cards, and model cards. The US Army Combat Capabilities Development Command Armaments Center (DEVCOM AC) has been developing a roadmap [1] to mitigate the risks associated with the development and deployment of AI/ML enabled systems. The proposed MLQP addresses many of the key challenges and considerations from that roadmap to enable the development of assured and trusted AI/ML enabled systems. This paper will examine how the proposed approach can be leveraged as a tool to build assurance into the cycle of AI/ML development and deployment to ensure safe and reliable systems and the alignment to Army assurance practices as well as DoD guidance.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"283 4","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530976","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

Planning Inspection Times for Degradation Tests 规划降解试验的检查时间

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457819

Rong Pan, Guanqi Fang

{"title":"Planning Inspection Times for Degradation Tests","authors":"Rong Pan, Guanqi Fang","doi":"10.1109/RAMS51492.2024.10457819","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457819","url":null,"abstract":"Degradation tests are often accompanied by pre-defined product inspection plans because real-time monitoring of product performance is difficult, if not impossible, in most cases. If the purpose of an inspection plan is to predict a failure time before an actual failure happens, it is reasonable to increase inspection frequency gradually over time as the test unit deteriorates over time. Curiously, this strategy has not been discussed much in the degradation test (DT) planning literature. In this paper, we propose a risk-based inspection (RBI) method to determine the final inspection time. By balancing the probability of failure and the consequence of failure, we place the optimal inspection time at the moment of highest failure risk, thus it is closer to the soft failure time that engineers actually care about. Furthermore, we test three inspection scheduling strategies - the equal-distance inspection time strategy, the equal-proportion inspection time strategy, and the middle inspection time strategy. It is found that progressively adding middle inspection times can enhance the prediction property of the degradation model. Through simulation, we show that this inspection plan performs better than other plans.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"250 10","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531031","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 and Availability Model of a Kubernetes Cluster Using SysML 使用 SysML 建立 Kubernetes 集群的可靠性和可用性模型

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457826

Myron Hecht, Scott Agena

{"title":"A Reliability and Availability Model of a Kubernetes Cluster Using SysML","authors":"Myron Hecht, Scott Agena","doi":"10.1109/RAMS51492.2024.10457826","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457826","url":null,"abstract":"This paper demonstrates the use of Model Based Systems Engineering and SysML for a Kubernetes cluster and how the results of such models can be used for design and architectural decisions. There are two major innovations in this paper. The first is use of SysML for reliabiltiy/availability modeling of a computer system with a containerized software architecture using Kubenetes, the most common orchestration (system management) platform for containerized architectures [1]. By using SysML, it is possible to incorporate reliability and availability models into a Model Based Systems Engineering (MBSE) development process. The benefits are better design decisions and lower cost. The second innovation is a description of how the Litmus Chaos failure simulation testing framework [8] can be used for empirical measurement of reliability/availability model parameters. Systems built on the Kubernetes platform can be developed incrementally so that executable systems with partial functionality can be observed and measured to provide early feedback on system reliability and availability performance. The early feedback enables more accurate assessments and more effective corrective actions if necessary. The numerical results of the SysML model were verified using an independent model. The results of the two models agreed to the 9th significant figure or better.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"294 4","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530963","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

MLOps FMEA: A Proactive & Structured Approach to Mitigate Failures and Ensure Success for Machine Learning Operations MLOps FMEA：减轻故障并确保机器学习运营成功的积极主动的结构化方法

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457600

Abhishek Paul, Roderick Y. Son, Shiv A. Balodi, K. Crooks

引用次数: 0

Do Bayesian Neural Networks Weapon System Improve Predictive Maintenance? 贝叶斯神经网络武器系统能否改善预测性维护？

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457828

Michael L. Potter, Miru D. Jun

引用次数: 0

Measures and Metrics of ML Data and Models to Assure Reliable and Safe Systems 确保系统可靠安全的 ML 数据和模型的衡量标准和指标

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457615

Benjamin Werner, Benjamin Schumeg, Jon Vigil, Shane N. Hall, Benjamin G. Thengvall, Mikel D. Petty

{"title":"Measures and Metrics of ML Data and Models to Assure Reliable and Safe Systems","authors":"Benjamin Werner, Benjamin Schumeg, Jon Vigil, Shane N. Hall, Benjamin G. Thengvall, Mikel D. Petty","doi":"10.1109/RAMS51492.2024.10457615","DOIUrl":"https://doi.org/10.1109/RAMS51492.2024.10457615","url":null,"abstract":"The US Army solicited partners through a Broad Agency Announcement to propose solutions under a Small Business Technology Transfer contract mechanism for the program “Metrics and Methods for Verification, Validation, Assurance and Trust of Machine Learning Models & Data for Safety-Critical Applications in Armaments Systems.” OptTek Systems, Inc. and University of Alabama in Huntsville (UAH) were one of the selected proposals for Phase I. Under this contract agreement OptTek and UAH set the goal to research & develop (R&D) fundamental metrics & measures for the certification & qualification of ML training data sets & models. Of particular note, the use of a safety score calculated from the accuracy as well as a dedicated look at data quality have been demonstrated as reasonable approaches to the proposed topic. As the Technical Point of Contact for this effort, the US Army Combat Capabilities Development Command Armaments Center (DEVCOM AC) authored the topic and provided guidance on the effort to align with mission objectives. This paper is an exploration of the research and development conducted by OptTek and UAH within the framework of how it may be applied to the assurance of systems to be developed by the US Army and augment practices in reliability and safety.","PeriodicalId":518362,"journal":{"name":"2024 Annual Reliability and Maintainability Symposium (RAMS)","volume":"15 9","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530654","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

Scaled Reliability Prediction Model for Gallium Nitride (GaN) Monolithic Microwave Integrated Circuit 氮化镓（GaN）单片微波集成电路的比例可靠性预测模型

2024 Annual Reliability and Maintainability Symposium (RAMS) Pub Date : 2024-01-22 DOI: 10.1109/RAMS51492.2024.10457769

O. L. Kedienhon

引用次数: 0