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

{"title":"Monte Carlo evidence for need of improved percolation model for non-weibullian degradation in high-κ dielectrics","authors":"N. Raghavan, K. Shubhakar, K. Pey","doi":"10.1109/RAMS.2013.6517659","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517659","url":null,"abstract":"Dielectric breakdown is one of the critical failure mechanisms and showstopper for ultra-large scale integrated (ULSI) circuits as it impacts the performance and functioning of the transistor, which is the fundamental unit governing the operation of all the advanced microprocessors that we have today. As a reliability engineer, it is essential that the failure mode and mechanism be best described using statistical distributions that correlate with the physical mechanism and driving forces causing failure. In many cases, the distributions used to represent the time to failure data are empirically assumed, without carefully considering its implications on the extrapolated predictions of field lifetime. Application of a wrong distribution can give lifetime estimates that vary by many orders of magnitude, which nullify the very purpose of the reliability study in itself. The Weibull distribution is commonly used to describe random defect generation induced percolation failure of the oxide (dielectric) by means of the “weakest link” phenomenology [1, 2]. While the assumption of a Weibull distribution is well justified for silicon oxide (SiO2) and silicon oxynitride (SiON) materials [3, 4], the application of the same stochastics for high permittivity (high-κ) dielectrics is questionable [5] - [7]. This is fundamentally attributable to the different microstructure of the grown / deposited dielectrics, which we will discuss in detail, along with strong physical analysis evidence. We will present further evidence using Kinetic Monte Carlo (KMC) simulations to explain the origin of the non-Weibullian trends observed. The key motivation of this study is to caution microelectronics reliability scientists against the use of standard statistical distributions for all scenarios. We may have to resort to the need for non-standard distributions or selectively use the standard distributions only over confined percentile ranges, as material and device failure mechanisms become increasingly complex and interdependent in nanoscale integrated circuits.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"26 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":"122776415","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":"IDREMA-process: Identification of reference market for defect parts routing","authors":"S. Peršin, S. Bracke, S. Haller, C. Wurz","doi":"10.1109/RAMS.2013.6517632","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517632","url":null,"abstract":"In the automotive industry the number of reports concerning large-scale product recalls of vehicles is increasing (cf. [1]) and thereby alarming not only affected but also future customers. Therefor the quality management of major automobile groups is facing an increasing challenge. The goal of a quick fault detection and removal is endangered by an increasing product complexity, an expansion of the international distribution into markets with highly divergent requirement profiles and a restricted access of defect parts from various countries. In order not to fall short of the objectives in the future, a concept for the “Worldwide Routing of Defected Parts in the Automotive Industries” (WORPA) is being developed. The idea is to deduce the fitting control option for providing the optimum analytical batch. Due to transport costs, customs duty issues, and the lack of necessary infrastructure, a worldwide access to every market with defect parts is neither available nor economically justifiable. Therefore it is common practice to define a market as a so-called reference market. This market should be representative of occurring failure modes depending on several boundary conditions such as climate, load profiles, stretches of way or fuel quality. Traditionally, the reference market is contractually fixed to be the domestic producer market. In an economically dynamic environment like the automotive industry, sales markets are continually shifting to countries with differing requirement profiles (e. g. China; fuel quality) and potential new failure modes. Thus, it is necessary to undertake a scientific review of the previously axiomatic selection of the reference market. In this article the “Identification of Reference Market” (IDREMA) process - as a part of the WORPA concept - is introduced and distinguished from other existing systems. The IDREMA process is a means to determine a reference market in a structured procedure. For this purpose, rudimentary prerequisites as well as qualitative and quantitative impacts concerning occuring failure modes are considered. The statistical analysis is based on the sampling range of dependable methods of testing. A synthesized practical example (Case Study Assembly Module) illustrates the way of proceeding.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"114 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":"117209706","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 roadmap and industry collaboration","authors":"L. Bechtold, D. Redman","doi":"10.1109/RAMS.2013.6517626","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517626","url":null,"abstract":"Reliability research is conducted by many organizations in government, academia and industry. A research roadmap developed collaboratively by the reliability community and led by the Aerospace Vehicle Systems Institute (AVSI) will result in a broad-based, common approach to predicting the reliability of electronics. Research that is proposed in accordance with the roadmap will build on existing results and engage experienced reliability researchers to leverage limited research funds. Future projects will develop the capabilities identified by the roadmap for a reliability prediction methodology that provides accurate, timely and necessary information to support reliable system design. New models and modeling methods will provide the capabilities needed to develop future systems; and will establish a normative basis for future industry and military standards.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":" 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":"120827231","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":"Establishing product reliability goals","authors":"F. Schenkelberg","doi":"10.1109/RAMS.2013.6517741","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517741","url":null,"abstract":"The way we communicate goals directly impacts the achievement of the goal. Creating and succinctly stating a reliability goal necessary for the leadership it provides an organization when designing a new product. The reliability goal statement includes four elements: function, environment, probability of success, and duration. The function definition provides one means to define failure conditions. The environment includes elements such as weather and elements related to use frequency. The probability of success and duration should always be stated in a couplet. Setting more than one probability and duration couplet further defines reliability over the expected lifespan of the product. And setting multiple couplets enables various focuses of the goal that concern different periods of time or constituents. Setting and stating a clear and complete reliability goal delineates the boundary between a reliable enough product and one that is not. The goal enables the design team to balance the myriad of other design considerations along with product reliability in a meaningful manner.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"10 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":"127204458","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 considerations of ULP scaled CMOS in spacecraft systems","authors":"M. White, K. MacNeal, M. Cooper","doi":"10.1109/RAMS.2013.6517720","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517720","url":null,"abstract":"NASA, the aerospace community, and other high reliability (hi-rel) users of advanced microelectronic products face many challenges as technology continues to scale into the deep sub-micron region. Decreasing the feature size of CMOS devices not only allows more components to be placed on a single chip, but it increases performance by allowing faster switching (or clock) speeds with reduced power compared to larger scaled devices. Higher performance, and lower operating and stand-by power characteristics of Ultra-Low Power (ULP) microelectronics are not only desirable, but also necessary to meet low power consumption design goals of critical spacecraft systems. The integration of these components in such systems, however, must be balanced with the overall risk tolerance of the project.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"16 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":"128119963","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":"Effective use of accelerated testing in the medical device industry","authors":"J. A. Hansen","doi":"10.1109/RAMS.2013.6517713","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517713","url":null,"abstract":"Accelerating Testing techniques can be used in the medical device industry as a tool to enhance device reliability, ensure patient safety, and comply with regulatory agency risk management requirements.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"85 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":"126235232","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 reliability prediction based on degradation data and environmental data","authors":"Liu Zhenyu, Ma Xiaobing, Zhao Yu","doi":"10.1109/RAMS.2013.6517755","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517755","url":null,"abstract":"This paper outlines a method that can be used for field reliability prediction using degradation data and environmental data. From different perspectives about the effects of dynamic environment on field reliability, we proposed two methods to relate the environmental variables to degradation process. The modeling technique and estimation method are illustrated by an example to predict the field failure time distribution of a product. The result of this study shows that it is possible to predict field performance by using ADT results, if done carefully and with good characterization of field environmental conditions.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"38 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":"114132021","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":"Acoustic emission-based fatigue crack growth prediction","authors":"A. Keshtgar, M. Modarres","doi":"10.1109/RAMS.2013.6517715","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517715","url":null,"abstract":"Acoustic Emission (AE) is a non-destructive testing (NDT) with potential applications for locating and monitoring fatigue cracks during structural health management and prognosis. To do this, a correlation between acoustic emission signal characteristics and crack growth behavior should be established. In this paper, a probabilistic model of fatigue crack length distribution based on acoustic emission is validated. Using the results from AE-based fatigue experiments the relationship between AE count rates and crack growth rates is reviewed for the effect of loading ratio. Predictions of crack growth rates based on AE count rates model show reasonable agreement with the actual crack growth rates from the test results. Bayesian regression analysis is performed to estimate the marginal distribution of the unknown parameters in the model. The results of the Bayesian regression analysis shows that the results are consistent with respect to changes in loading ratio. Additional experimental evidence might be required to further reduce the uncertainties of the proposed model and further study the effects of the changes in loading frequency, sample geometry and material.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"52 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":"124003089","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":"Return on investment for a Design for Reliability program","authors":"M. Silverman","doi":"10.1109/RAMS.2013.6517623","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517623","url":null,"abstract":"Last year we presented a paper on Design for Reliability (DFR), reviewing the benefits of a good DFR program and included some of the essential building blocks of DFR along with pointing out some erroneous practices that people today are using today. We discussed a good DFR Program having the following attributes: 1.Setting Goals at the beginning of the program and then developing a plan to meet the goals. 2.Having the reliability goals being driven by the design team with the reliability team acting as mentors. 3.Providing metrics so that you have checkpoints on where you are against your goals. 4.Writing a Reliability Plan (not only a test plan) to drive your program. A good DFR Program must choose the best tools from each area of the product life cycle: identify, design, analyze, verify, validate, monitor and control. The DFR Program must then integrate the tools together effectively.effectively. Since then, we have developed a method to calculate the Return on Investment (ROI) from a Design for Reliability (DFR) program, also known as the DFR ROI. In this paper, we will discuss a method we have developed to calculate the Return on Investment (ROI) from a Design for Reliability (DFR) program, also known as the DFR ROI. There are a number of factors involved in calculating the ROI for your DFR program, including: 1) improved warranty rate (derived from your reliability maturity level) 2) current warranty rate 3) cost per repair 4) cost of new reliability program 5) savings from losing a customer 6) volume. In this paper, we will show you how to calculate each of these to derive your DFR ROI.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"18 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":"121581357","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":"Early supplier integration and management in ultrasound device development","authors":"N. Chandrappa, P. Grotjahn, D. Kawathekar","doi":"10.1109/RAMS.2013.6517759","DOIUrl":"https://doi.org/10.1109/RAMS.2013.6517759","url":null,"abstract":"The system reliability was computed at several stages during project execution using the statistical and predictive information from system design, individual supplier's predictions, system reliability demonstration test results, prior Field reliability data for like assemblies, and tests conducted at the supplier's locations. One of the Field Reliability metric followed and tracked by Philips is MTBSE which means Mean Time Between Service Events. It is the ration of number of system days to the number of service events. The results at each stage were used to suitably update the predicted system reliability and determine required actions for the subsequent stages in order to achieve the end goal of an MTBSE equal or greater than 2.5 times that of the current products.","PeriodicalId":189714,"journal":{"name":"2013 Proceedings Annual Reliability and Maintainability Symposium (RAMS)","volume":"79 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":"125062674","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}