rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Reliability, Life Testing and the Prediction of Service Lives
    sub title: For Engineers and Scientists
  name:
    name part: Saunders, Sam C.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 308 p. online resource.
  abstract: This book is intended for students and practitioners who have had a calculus-based statistics course and who have an interest in safety considerations such as reliability, strength, and duration-of-load or service life. Many persons studying statistical science will be employed professionally where the problems encountered are obscure, what should be analyzed is not clear, the appropriate assumptions are equivocal, and data are scant. Yet tutorial problems of this nature are virtually never encountered in coursework. In this book there is no disclosure with many of the data sets what type of investigation should be made or what assumptions are to be used. Most reliability practitioners will be employed where personal interaction between disciplines is a necessity. A section is included on communication skills to facilitate model selection and formulation based on verifiable assumptions, rather than favorable conclusions. However, whether the answer is "right" can never be ascertained. Past and current applications of stochastic modeling to life-length can only be a guide for future adaptations under different conditions, with new materials in unknown usages. This book unifies the study of cumulative-damage distributions, namely, Wald and Tweedie (i.e., inverse-Gaussian and its reciprocal) with "fatigue-life." These distributions are most useful when the coefficient-of-variation is more appropriate than is the variance as a measure of dispersion. It is shown, uniquely, that the same hyperbolic-sine transformation of each life length variate has a Chi-square one-df distribution. This property is useful in the sample statistics. These IHRA distributions realistically model life-length, strength or duration of load under linear cumulative damage and can be combined as approximations in non-linear situations. Sam C. Saunders has served as a research engineer for 17 years at the Boeing Scientific Research Laboratories, 20 years as a consultant to the Advisory Committee fo…
  table of contents: Requisites -- Elements of Reliability -- Partitions and Selection -- Coherent Systems -- Applicable Life Distributions -- Philosophy, Science, and Sense -- Nonparametric Life Estimators -- Weibull Analysis -- Examine Data, Diagnose and Consult -- Cumulative Damage Distributions -- Analysis of Dispersion -- Damage Processes -- Service Life of Structures -- Strength and Durability -- Maintenance of Systems -- Mathematical Appendix.
  note: by Sam C. Saunders.
  subject:
    topic: Computer science
  subject:
    topic: Computer software
    topic: Reusability
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Engineering
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Quality control
  subject:
    topic: Reliability
  subject:
    topic: Industrial safety
  subject:
    topic: Computer Science
  subject:
    topic: Performance and Reliability
  subject:
    topic: Engineering, general
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Quality Control, Reliability, Safety and Risk
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  subject:
    topic: Probability Theory and Stochastic Processes
  classification: QA76.76.R44
  classification: TK5105.5956
  classification: 004.24
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Series in Statistics
  identifier: 9780387485386
  identifier: http://dx.doi.org/10.1007/978-0-387-48538-6
  record info:
    record creation date: 100423
    record change date: 20151204174345.0
    record identifier: 978-0-387-48538-6