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EPICS in IEEE
IEEE eLearning Library Series on Becoming a Better Instructor

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    Authors:Hansen, Christian andAscher, Harold
    Sponsored by:IEEE Reliability Society
    Tutorial Level: Intermediate
    Publication Date: Apr-2009
    Run Time: 1:30:00
    CEUs: .3
    PDHs: 3
    ECSA CPD (Category 1 - Development Activities): 1 - Includes study time

    Abstract
    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 nonrepairable 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.

    Keywords: FOM , Force of Mortality , Global Time , HPP , Homogeneous Poisson Process , Local Time , MCF , Mean Cumulative Number of Failures , NHPP , Nonhomogeneous Poisson Process , Part , ROCOF , RP , Rate of Occurrence of Failures , Renewal Process , Socket , System

    For individuals not subscribed to the IEEE eLearning Library, this course is available for individual purchase.

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    Authors:Keene, Samuel
    Sponsored by:IEEE Reliability Society
    Tutorial Level: intermediate
    Publication Date: Dec-2007
    Run Time: 1:00:00
    CEUs: .3
    PDHs: 3
    ECSA CPD (Category 1 - Development Activities): 1 - Includes study time

    Abstract
    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.

    Keywords: Critical to Quality; Data types; Effects Analysis ; Failure modes; Lower Specification Limit; Measurement System Variation; Potential Problem Analysis; Response Surface Methodology; Statistical Process Control; Sigma;Six Sigma Stages; Upper Control Limit; Upper Specification Limit

    For individuals not subscribed to the IEEE eLearning Library, this course is available for individual purchase.

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    Authors:Keene, Samuel
    Sponsored by:IEEE Reliability Society
    Tutorial Level: Intermediate
    Publication Date: Dec-2009
    Run Time: 1:00:00
    CEUs: .3
    PDHs: 3
    ECSA CPD (Category 1 - Development Activities): 1 - Includes study time

    Abstract
    This tutorial will introduce Design for Six Sigma (DFSS) concepts that assure good requirements are established to guide the product development. One US Army paper stated that requirements deficiencies were the cause of 99% of their field reliability problems. This has been expanded by Brendan Murhpy to say that the problems on computer systems were mostly due to requirements deficiencies and interface weaknesses. He labeled this combination of problem sources to be "system management" problems. He found this cause of problems dominated over either software or hardware problems. This author adds a third component to the system management problem. That is "change control."

    The good news is that six sigma tools can enhance team communication and perspective, leading to a more comprehensive and correct specification of system requirements. Four key tools will be taught.

    Keywords: CTQ , FMEA , MSA , Potential Problem Analysis , RSM , SPC , Six Sigma Stages

    For individuals not subscribed to the IEEE eLearning Library, this course is available for individual purchase.