Testing and inspection using acceptance sampling plans [Documento eletrónico] / by Muhammad Aslam, Mir Masoom Ali
Language: eng.Country: SG - Singapura.Publication: Singapore : Springer Nature Singapore, 2019Description: XVI, 288 p. : il.ISBN: 978-981-13-9306-8.Subject - Topical Name: Amostragem (Estatística) Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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This book introduces a number of new sampling plans, such as time truncated life tests, skip sampling plans, resubmitted plans, mixed sampling plans, sampling plans based on the process capability index and plans for big data, which can be used for testing and inspecting products, from the raw-materials stage to the final product, in every industry using statistical process control techniques. It also presents the statistical theory, methodology and applications of acceptance sampling from truncated life tests. Further, it discusses the latest reliability, quality and risk analysis methods based on acceptance sampling from truncated life, which engineering and statisticians require in order to make decisions, and which are also useful for researchers in the areas of quality control, lifetime analysis, censored data analysis, goodness-of-fit and statistical software applications. In its nine chapters, the book addresses a wide range of testing/inspection sampling schemes for discrete and continuous data collected in various production processes. It includes a chapter on sampling plans for big data and offers several illustrative examples of the procedures presented. Requiring a basic knowledge of probability distributions, inference and estimation, and lifetime and quality analysis, it is a valuable resource for graduate and senior undergraduate engineering students, and practicing engineers, more specifically it is useful for quality engineers, reliability engineers, consultants, black belts, master black belts, students and researchers interested in applying reliability and risk and quality methods.
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