A unique, practical guide for industry professionals who need to improve product quality and reliability in repairable systems
Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Methods for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Written by two highly recognized members of the reliability and statistics community, this new work offers a unique, systematic treatment of probabilistic models used for repairable systems as well as the statistical methods for analyzing data generated from them.
Liberally supplemented with examples as well as exercises boasting real data, the book clearly explains the difference between repairable and nonrepairable systems and helps readers develop an understanding of stochastic point processes. Data analysis methods are discussed for both single and multiple systems and include graphical methods, point estimation, interval estimation, hypothesis tests, goodness-of-fit tests, and reliability prediction. Complete with extensive graphs, tables, and references, Statistical Methods for the Reliability of Repairable Systems is an excellent working resource for industry professionals involved in producing reliable systems and a handy reference for practitioners and researchers in the field.
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STEVEN E. RIGDON, PhD, is Professor of Statistics at Southern Illinois University Edwardsville. ASIT P. BASU, PhD, is Professor of Statistics at the University of Missouri Columbia.
A unique, practical guide for industry professionals who need to improve product quality and reliability in repairable systems
Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Methods for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Written by two highly recognized members of the reliability and statistics community, this new work offers a unique, systematic treatment of probabilistic models used for repairable systems as well as the statistical methods for analyzing data generated from them.
Liberally supplemented with examples as well as exercises boasting real data, the book clearly explains the difference between repairable and nonrepairable systems and helps readers develop an understanding of stochastic point processes. Data analysis methods are discussed for both single and multiple systems and include graphical methods, point estimation, interval estimation, hypothesis tests, goodness-of-fit tests, and reliability prediction. Complete with extensive graphs, tables, and references, Statistical Methods for the Reliability of Repairable Systems is an excellent working resource for industry professionals involved in producing reliable systems and a handy reference for practitioners and researchers in the field.
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Da: Companion Books, Burnaby, BC, Canada
Hardcover. Condizione: Very Good. 1st Edition. The book is in very good condition, little shelf rubbing apparent. The text and diagrams inside appear clean and clear throughout. 'A unique, practical guide for industry professionals who need to improve product quality and reliability in repairable systems. Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Methods for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Written by two highly recognized members of the reliability and statistics community, this new work offers a unique, systematic treatment of probabilistic models used for repairable systems as well as the statistical methods for analyzing data generated from them. Liberally supplemented with examples as well as exercises boasting real data, the book clearly explains the difference between repairable and nonrepairable systems and helps readers develop an understanding of stochastic point processes. Data analysis methods are discussed for both single and multiple systems and include graphical methods, point estimation, interval estimation, hypothesis tests, goodness-of-fit tests, and reliability prediction. Complete with extensive graphs, tables, and references, Statistical Methods for the Reliability of Repairable Systems is an excellent working resource for industry professionals involved in producing reliable systems and a handy reference for practitioners and researchers in the field.' xii+281 pages. 9.5 x 6.4 inches. May require additional postage. This listing was made by a small independent book shop. We carefully inspect every single book we list and give accurate descriptions. If you require we will promptly send pictures of listed books upon request. Size: 8vo - over 7¾ - 9¾" tall. Book. Codice articolo 052367
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Da: Second Story Books, ABAA, Rockville, MD, U.S.A.
Hardcover. Octavo, xii, 281 pages. In Very Good minus condition. Spine is blue with white print. Boards in blue paper with white print. Vendor label on rear. Illustrated: b&w graphs, diagrams. NOTE: Shelved in Locked Annex Area, ND-HV Section. 1378649. FP New Rockville Stock. Codice articolo 1378649
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. A unique, practical guide for industry professionals who need to improve product quality and reliability in repairable systems Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Methods for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Written by two highly recognized members of the reliability and statistics community, this new work offers a unique, systematic treatment of probabilistic models used for repairable systems as well as the statistical methods for analyzing data generated from them. Liberally supplemented with examples as well as exercises boasting real data, the book clearly explains the difference between repairable and nonrepairable systems and helps readers develop an understanding of stochastic point processes. Data analysis methods are discussed for both single and multiple systems and include graphical methods, point estimation, interval estimation, hypothesis tests, goodness-of-fit tests, and reliability prediction. Complete with extensive graphs, tables, and references, Statistical Methods for the Reliability of Repairable Systems is an excellent working resource for industry professionals involved in producing reliable systems and a handy reference for practitioners and researchers in the field. Owing to its vital role in product quality, reliability has been intensely studied in recent decades. Most of this research, however, addresses systems that are nonrepairable and therefore discarded upon failure. Statistical Models for the Reliability of Repairable Systems fills the gap in the field, focusing exclusively on an important yet long-neglected area of reliability. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780471349419
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 32577
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L1-9780471349419
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 32577-n
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 32577
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