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Wiley Accelerated Life Testing of One-shot Devices: Data Collection and Analysis

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Description

Provides authoritative guidance on statistical analysis techniques and inferential methods for one-shot device life-testingEstimating the reliability of one-shot devices—electro-expolsive devices, fire extinguishers, automobile airbags, and other units that perform their function only once—poses unique analytical challenges to conventional approaches. Due to how one-shot devices are censored, their precise failure times cannot be obtained from testing. The condition of a one-shot device can only be recorded at a specific inspection time, resulting in a lack of lifetime data collected in life-tests.Accelerated Life Testing of One-shot Devices: Data Collection and Analysis addresses the fundamental issues of statistical modeling based on data collected from accelerated life-tests of one-shot devices. The authors provide inferential methods and procedures for planning accelerated life-tests, and describe advanced statistical techniques to help reliability practitioners overcome estimation problems in the real world. Topics covered include likelihood inference, competing-risks models, one-shot devices with dependent components, model selection, and more. Enabling readers to apply the techniques to their own lifetime data and arrive at the most accurate inference possible, this practical resource:Provides expert guidance on comprehensive data analysis of one-shot devices under accelerated life-testsDiscusses how to design experiments for data collection from efficient accelerated life-tests while conforming to budget constraintsHelps readers develops optimal designs for constant-stress and step-stress accelerated life-tests, mainstream life-tests commonly used in reliability practiceIncludes R code in each chapter for readers to use in their own analyses of one-shot device testing dataFeatures numerous case studies and practical examples throughoutHighlights important issues, problems, and future research directions in reliability theory and practiceAccelerated Life Testing of One-shot Devices: Data Collection and Analysis is essential reading for graduate students, researchers, and engineers working on accelerated life testing data analysis.  From the Inside Flap PROVIDES AUTHORITATIVE GUIDANCE ON STATISTICAL ANALYSIS TECHNIQUES AND INFERENTIAL METHODS FOR ONE-SHOT DEVICE LIFE-TESTINGEstimating the reliability of one-shot devices—electro-explosive devices, fire extinguishers, automobile airbags, and other units that perform their function only once—poses unique analytical challenges to conventional approaches. Due to the nature of data collection, the precise failure times of devices cannot be obtained from tests. The condition of a one-shot device can only be recorded at a specific inspection time, resulting in a lack of lifetime data collected from tests. Accelerated Life Testing of One-Shot Devices: Data Collection and Analysis addresses the fundamental issues of statistical modeling based on data collected from accelerated life-tests of one-shot devices. The authors provide inferential methods and procedures for planning accelerated life-tests, and describe advanced statistical techniques to help reliability practitioners overcome estimation problems in the real world. Topics covered include likelihood inference, competing-risks models, one-shot devices with dependent components, model selection, and more. Enabling readers to apply the techniques to their own lifetime data and arrive at the most accurate inference possible, this practical resource: Provides expert guidance on comprehensive data analysis of one-shot devices under accelerated life-testsDiscusses how to design experiments for data collection from efficient accelerated life-tests while conforming to budget constraintsHelps readers develop optimal designs for constant-stress and step-stress accelerated life-tests, mainstream life-tests commonly used in reliability practiceIncludes R code in each chapter for readers to use in their

Product Specifications

Brand
Wiley
Format
Hardcover
Domain
Amazon UK
Release Date
04 February 2021
Listed Since
20 July 2020

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No barcode data available

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