E-Book, Englisch, 288 Seiten, eBook
Aslam / Ali Testing and Inspection Using Acceptance Sampling Plans
1. Auflage 2019
ISBN: 978-981-13-9306-8
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 288 Seiten, eBook
ISBN: 978-981-13-9306-8
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1 Introduction and genesis1.1 Introduction1.2 History1.3 Background: acceptance sampling1.4 Background: reliability theory1.5 Censorship and truncation1.6 Selecting a life distribution1.7 Applications2 Some life distributions2.1 Introduction2.2 Birnbaum-Saunders distribution2.3 Burr type XII distribution2.4 Gamma distribution2.5 Generalized Birnbaum-Saunders distribution2.6 Generalized exponential distribution2.7 Generalized Rayleigh distribution2.8 Inverse Gaussian distribution2.9 Inverse Rayleigh2.10 Log-logistic distribution2.11 Pareto distribution2.12 Lognormal distribution3 Acceptance sampling from truncated life tests3.1 Introduction3.2 Plans based on one point of the OC curve3.2.1 Simple acceptance sampling plans3.2.2 Double acceptance sampling plans3.2.3 Acceptance sampling plans by groups3.2.4 Reliable economical acceptance sampling plans3.3 Plans based on two points of the OC curve3.3.1 Simple acceptance sampling plans3.3.2 Double acceptance sampling plans3.3.3 Two stage acceptance sampling plans using groups3.3.4 Acceptance sampling plans by groups3.3.5 Reliable economical acceptance sampling plans3.3.6 Reliable economical group acceptance sampling plans4 Acceptance sampling based on life tests from some specific distributions4.1 Introduction4.2 Birnbaum-Saunders distribution4.3 Burr type XII distribution4.4 Gamma distribution34.5 Generalized Birnbaum-Saunders distribution4.6 Generalized exponential distribution4.7 Generalized Rayleigh distribution4.8 Inverse Gaussian distribution4.9 Inverse Rayleigh4.10 Log-logistic distribution4.11 Pareto distribution4.12 Lognormal distribution5 Some group acceptance sampling based on life tests from specific distributions5.1 Introduction5.2 Birnbaum-Saunders distribution5.3 Burr type XII distribution5.4 Gamma distribution5.5 Generalized Birnbaum-Saunders distribution5.6 Generalized exponential distribution5.7 Generalized Rayleigh distribution5.8 Inverse Gaussian distribution5.9 Inverse Rayleigh5.10 Log-logistic distribution5.11 Pareto distribution5.12 Lognormal distribution6 Skip Sampling Plans6.1 Introduction6.2 Skip-V plans6.3 Skip-R Plans6.4 Design of Skip-R Plans6.5 Economic Skip-R Plans6.6 Skip plan using reference plans7 Sampling Plans using Process Capability index (PCI)7.1 Introduction7.2 Repetitive sampling using PCI7.3 Resubmitted sampling PCI7.4 Mixed plan using PCI8 Miscellaneous acceptance sampling plans8.1 Bayesian Sampling plan8.2 sampling plan using loss function8.3 Sampling Plans using EWMA8.4 Hybrid Plan9 Sampling plan for Big Data9.1 Introduction of Big Data9.2 Application of Big Data in quality control9.3 Inspection for Big Data49.4 Sampling plans for Big Data9.5 Application of sampling plan for Big Data




