Testing and Inspection Using Acceptance Sampling Plans

By Mir Masoom Ali and Muhammad Aslam

Book Overview

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

• Format: Paperback
• Language: English
• ISBN: 9811393087
• ISBN13: 9789811393082
• Release Date: August 2020
• Publisher: Springer
• Length: 288 Pages
• Weight: 0.95 lbs.
• Dimensions: 0.6" x 6.1" x 9.2"