Inspection Errors for Attributes in Quality Control

Informationen zum Autor Norman Lloyd Johnson (Author) , Samuel Kotz (Author) , Xizhi Wu (Author) Klappentext This book provides a comprehensive survey of the most recent methodology--both theoretical and applied--on the statistical analysis and detection of defective/"non-conforming" items in various types of inspection for attributes, when the inspection itself is subject to error. Zusammenfassung This book provides a comprehensive survey of the most recent methodology--both theoretical and applied--on the statistical analysis and detection of defective/"non-conforming" items in various types of inspection for attributes, when the inspection itself is subject to error Inhaltsverzeichnis Acceptance sampling.- Basic distributions: single sampling.- Basic distributions: multiple sampling.- Double and link sampling for acceptance.- Multitype nonconformities.- Identification of nonconforming items.- (Dorfman) group testing.- Dorfman-Sterrett group testing and its extensions.- Curtailed Dorfman-type procedures.- Graff and Roeloffs' approach and related procedures.- Binary search.- Miscellaneous.- Estimation of error probabilities.- Stratified populations: grading.

Product details

• Authors: Norman L. Johnson, Norman L. Kotz Johnson, Norman Lloyd Johnson, Johnson Norman L., Samuel Kotz, Kotz Samuel, Xizhi Wu, Xi-Zhi Wu
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 01.06.1991
• EAN: 9780412387708
• ISBN: 978-0-412-38770-8
• No. of pages: 227
• Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > Miscellaneous; MATHEMATICS / Probability & Statistics / General, MATHEMATICS / Applied, TECHNOLOGY & ENGINEERING / Industrial Engineering, TECHNOLOGY & ENGINEERING / Manufacturing, Probability & statistics, Production engineering, Maths for engineers, Probability and statistics, Production and industrial engineering