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“Concepts and Models for Repairable Systems Reliability” by Harold Ascher and Christian Hansen, sponsored by the IEEE Reliability Society Almost all systems of interest in reliability applications are designed to be repaired, rather than discarded, after their first failure. Nevertheless, most reliability texts overemphasize non-repairable items (henceforth, "parts"); if repairable systems (henceforth, "systems") are addressed, they usually are assumed to be same-as-new after repair. Such renewal by repair is neither plausible, nor mathematically tractable, nor even desirable since reliability growth is sought. Moreover, even with the utmost care in distinguishing between parts and systems, failure-data-sets for parts and systems look similar, their mathematical models look similar and even fundamentally different analysis results often look similar. Most reliability texts are impeccably rigorous when addressing parts but, unfortunately, many become extremely sloppy when treating systems - which require much more rigor! All these interacting factors have caused widespread misconceptions about even basic systems' reliability concepts. For example, what could be simpler than the idea that a system's reliability is improving if it fails less often with increasing operating time? In general, there is no connection between this concept and decreasing "failure rate" since the blatant misnomer "failure rate" almost always is defined as a property of a part's distribution of time-to-failure. Moreover, even under the definition for parts, increasing "failure rate" does not imply a monotonically increasing average number of part failures per unit time. This course presents basic concepts and models for parts and systems and stresses their up to infinite differences, rather than their superficially striking but relatively unimportant similarities. After completing you should be able to develop an understanding of:
Harold E. Ascher is a consultant and lecturer in reliability engineering and applied statistics. He has a B.S. in Physics from City College of New York and an M.S. in Operations Research from New York University. He is a life senior member of the IEEE and a member of the American Statistical Association and of the Society of Reliability Engineers. Christian K. Hansen joined Eastern Washington University in 1993, and is currently Department Chair and professor of mathematics with specialty in statistics. Dr. Hansen, a native of Denmark, earned his M.S. in Electrical Engineering (1988) and his Ph.D. in Statistics (1991) from the Technical University of Denmark.
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"Design for Six Sigma" by Samuel Keene, sponsored by the IEEE Reliability Society Six Sigma improves both product and process quality, eliminating defects using a suite of tools that span: statistical, analytical, and collaborative domains. The six sigma nomenclatures cross over different languages and cultures with improved understanding and exactness. Six Sigma improves our every day processes. The Six Sigma process has been extended to take the initiative in developing better designs that avoid problems rather than having to go back and correct them. This is the Design-for-Six Sigma (DFSS) initiative. It focuses on getting correct requirements, communicating these effectively across the team, examining and managing the design and environment anomalies, and flowing down tolerances from the system level to the component levels (also known as critical parameter management). Recently, the practices within DFSS have been further extended from Hardware Reliability to Software Quality and Reliability, and for that matter, to other aspects of product development including: Portfolio and Marketing Analysis, Technology Research and Development, Product Commercialization, Supply Chain and other support functions. These processes have been shown to deliver products with as few as 3-4 defects per million opportunities, such as seen on space shuttle software or commercial aircraft flights in the US. Ten basic tools are taught that promote better engagement of the customer, in concept development and design, as well as improving the cross-functional perspective of the team. These tools improve the system management aspect of the design and deliver a product that will delight the customer. After completing this course you should be able to develop an understanding of:
Dr. Samuel Keene is a Six Sigma Senior Master Black Belt. He has taught Black Belts and Green Belts, DFSS, mentored Black Belt projects and certified new Black Belts. Sam also has personally executed at least two major cross-functional six sigma projects each year for the past 5 years while supporting Seagate Technology. Sam also led Seagate’s Corporate Master Black Belt Council, comprising MBB’s from Seagate location s around the world. This council promotes world-class practices, develops and organizes tools and procedures, and promotes cross-organizational project facilitation.
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"Effects of Reliability Mechanisms on VLSI Circuit Functionality" by Wayne Ellis, co-sponsored by the IEEE Electron Devices Society and IEEE Reliability Society This course provides examples of reliability mechanisms and how these can affect the normal operation of selected VLSI circuits. Large circuit-count ASIC chips use standard digital and analog circuits such as Logic gates, eSRAM, eDRAM and I/O circuits which must function properly under various voltage and thermal environments. These chips are subjected to Reliability Screens such as Burn In to activate latent defects and screen out those chips that cannot meet product specifications for performance, power and operating margins. The advent of degraded VLSI circuit operating margins due to the activated defects as well as reliability mechanisms such as negative bias temperature instability (NBTI), hot carrier injection (HCI), and others will be discussed. How these failing circuits can then manifest themselves in observed product failures will also be discussed. After completing this course you should be able to develop an understanding of:
Wayne Ellis has worked from 1977 to the present at the IBM Microelectronics division labs in Essex Junction Vermont.
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"Molecular Electronics Part 1: Potential and Applications" by Curt Richter, sponsored by the IEEE Electron Devices Society and the IEEE Reliability Society This course will begin by outlining approaching limits of conventional CMOS technology. New architectural requirements and paradigms for future nanoelectronics will be described. ‘Top-down’ and ‘bottom-up’ manufacturing paradigms, particularly self-assembly of organic monolayers will be discussed. Theoretical and experimental realizations of molecular-scale electronic switches will be described. This course will also show nanoscale memory and logic circuits built with these materials and methods and will discuss potential nanoscale chemical and biological sensors built with these materials and methods After completing this course you should be able to develop an understanding of:
Curt A. Richter, Ph.D. has worked in the Semiconductor Electronics Division of the National Institute of Standards and Technology, Gaithersburg, MD since 1993. He is currently Project Leader of the Nanoelectronic Device Metrology Project.
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"Molecular Electronics Part 2: Molecular Electronic Device Fabrication and Characterization " by Duncan Stewart, sponsored by the IEEE Electron Devices Society and the IEEE Reliability Society This course will begin by discussing the advantages of molecular electronic devices and present experimental proof of concepts. The formation of molecular junctions, the central component of molecular electronic devices will be described as well as the design and fabrication approaches for some of the most successful molecular electronic device prototypes. This course will also present electrical characterization approaches and challenges and discuss non-device based electrical screening approaches. Finally, the current status and outlook for molecular electronic devices will be presented. After completing this course you should be able to develop an understanding of:
Duncan R. Stewart, Ph.D. first studied physics and electrical engineering at the University of Toronto, Canada, earning his BASc in 1992. He moved to Stanford University to complete a PhD in Applied Physics in 1999, where he studied nanoscale electron transport in high-mobility GaAs quantum dots, particularly many-body effects in the excited state spectra of these ‘artificial atoms’.
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"Planning and Performing Failure Mode and Effects Analysis on Software" by Nathaniel Ozarin, sponsored by the IEEE Reliability Society Failure Mode Effects Analyses (FMEA) have proven to be an effective method for improving the reliability of hardware systems but many still consider software FMEAs to be problematic. This course provides a proven methodology and a detailed example for planning and performing FMEAs on software. An introduction to Software FMEA and relation to Hardware FMEA will be provided along with a step-by-step approach to performing software FMEA--using excerpts from a real example. After completing this course you should be able to develop an understanding of:
Nathaniel Ozarin is a senior engineering consultant at The Omnicon Group Inc., a company specializing in reliability and safety analysis for the military, medical, industrial, and transportation industries.
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"Reliability Analysis of Computer Based Systems Using Dynamic Fault Trees" by Joanne Bechta Dugan, sponsored by the IEEE Reliability Society Redundant or fault tolerant computer-based systems provide several challenges to reliability analysis and probabilistic risk assessment. Computer systems which are designed to achieve high reliability frequently employ high levels of redundancy, dynamic redundancy management and complex fault and error recovery techniques. It is precisely this flexibility and adaptability inherent in fault tolerant computer systems that makes analysis problematic. In this course, Dynamic Fault Tree (DFT) modeling techniques for handling these difficulties are described. The dynamic fault tree methodology extends the traditional (also called static) fault tree methodology by providing special gates to capture specific types of sequence dependencies that arise in modeling computer-based systems. The DFT is automatically converted to the equivalent Markov model for solution; the solution results are translated back to the FT framework. The DFT model seeks to address these difficulties by providing a methodology for including Markov modeling within the fault tree framework, thus extending the applicability of the fault tree model, and by extension, the Probabilistic Risk Assessment methodology. In addition to sequence-dependent failure scenarios, reliability analysis of fault tolerant computer systems must include the notion of fault coverage. A covered fault is one that can be tolerated by the system, that is, the system is able to utilize redundant components to continue correct operation. However, an uncovered fault may occur that could defeat the fault tolerance mechanisms and result in immediate system failure. The DFT approach allows the analyst to include consideration of fault coverage. In this course we introduce the DFT approach and apply the special gates to the analysis of several example systems. Subsequent sections discuss fault coverage and its impact on reliability analysis. After completing this course you should be able to develop an understanding of:
Joanne Bechta Dugan is currently Professor of Electrical and Computer Engineering at the University of Virginia.
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