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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.

Testing and Inspection Using Acceptance Sampling Plans

1 Introduction and genesis 1.1 Introduction 1.2 History 1.3 Background: acceptance sampling 1.4 Background: reliability theory 1.5 Censorship and truncation 1.6 Selecting a life distribution 1.7 Applications 2 Some life distributions 2.1 Introduction 2.2 Birnbaum-Saunders distribution 2.3 Burr type XII distribution 2.4 Gamma distribution 2.5 Generalized Birnbaum-Saunders distribution 2.6 Generalized exponential distribution 2.7 Generalized Rayleigh distribution 2.8 Inverse Gaussian distribution 2.9 Inverse Rayleigh 2.10 Log-logistic distribution 2.11 Pareto distribution 2.12 Lognormal distribution 3 Acceptance sampling from truncated life tests 3.1 Introduction 3.2 Plans based on one point of the OC curve 3.2.1 Simple acceptance sampling plans 3.2.2 Double acceptance sampling plans 3.2.3 Acceptance sampling plans by groups 3.2.4 Reliable economical acceptance sampling plans 3.3 Plans based on two points of the OC curve 3.3.1 Simple acceptance sampling plans 3.3.2 Double acceptance sampling plans 3.3.3 Two stage acceptance sampling plans using groups 3.3.4 Acceptance sampling plans by groups 3.3.5 Reliable economical acceptance sampling plans 3.3.6 Reliable economical group acceptance sampling plans 4 Acceptance sampling based on life tests from some specific distributions 4.1 Introduction 4.2 Birnbaum-Saunders distribution 4.3 Burr type XII distribution 4.4 Gamma distribution 3 4.5 Generalized Birnbaum-Saunders distribution 4.6 Generalized exponential distribution 4.7 Generalized Rayleigh distribution 4.8 Inverse Gaussian distribution 4.9 Inverse Rayleigh 4.10 Log-logistic distribution 4.11 Pareto distribution 4.12 Lognormal distribution 5 Some group acceptance sampling based on life tests from specific distributions 5.1 Introduction 5.2 Birnbaum-Saunders distribution 5.3 Burr type XII distribution 5.4 Gamma distribution 5.5 Generalized Birnbaum-Saunders distribution 5.6 Generalized exponential distribution 5.7 Generalized Rayleigh distribution 5.8 Inverse Gaussian distribution 5.9 Inverse Rayleigh 5.10 Log-logistic distribution 5.11 Pareto distribution 5.12 Lognormal distribution 6 Skip Sampling Plans 6.1 Introduction 6.2 Skip-V plans 6.3 Skip-R Plans 6.4 Design of Skip-R Plans 6.5 Economic Skip-R Plans 6.6 Skip plan using reference plans 7 Sampling Plans using Process Capability index (PCI) 7.1 Introduction 7.2 Repetitive sampling using PCI 7.3 Resubmitted sampling PCI 7.4 Mixed plan using PCI 8 Miscellaneous acceptance sampling plans 8.1 Bayesian Sampling plan 8.2 sampling plan using loss function 8.3 Sampling Plans using EWMA 8.4 Hybrid Plan 9 Sampling plan for Big Data 9.1 Introduction of Big Data 9.2 Application of Big Data in quality control 9.3 Inspection for Big Data 4 9.4 Sampling plans for Big Data 9.5 Application of sampling plan for Big Data