This paper extends the idea of multiple dependent state sampling plans to the case of using process capability index when the quality characteristic of the product follows the normal distribution. The plan parameters are determined using the optimization process with minimum values of sample size so that the specified producer's risk and consumer's risk should be satisfied simultaneously for given values of acceptable quality level and limiting quality level in terms of fraction defective beyond two specification limits. The plan parameters are determined under symmetric and asymmetric cases of fraction defective. The advantage of the proposed plan is discussed over the single variable sampling plan. A real example is presented to illustrate the proposed plan in practice.

In this paper, a mixed multiple dependent state sampling plan based on the process capability index is presented for a quality characteristic of interest follows a normal distribution. The parameters of the proposed plan are determined with regard to the producer's and consumer's risks for specified values of acceptable quality level and limiting quality level. Tables containing parameters of the proposed plan are provided for symmetry and asymmetry cases. The advantages of the proposed plan over the attribute plan in terms of the sample size are discussed. An industrial example is given to explain the proposed procedure.

This paper presents the designing of a sampling plan using the process loss consideration for the multiple dependent state sampling under the neutrosophic statistics. The operating characteristics under the neutrosophic statistical interval method (NSIM) are developed to nd the neutrosophic plan parameters of the proposed sampling plan. A non-linear optimization under NSIM is used to nd the optimal neutrosophic plan parameters under the given conditions. The advantages of the proposed sampling plan are discussed over the existing sampling plans. A real example having some uncertain observations is given for the illustration purpose.

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.

The Process Capability Index (PCI) has been widely used in industry to advance the quality of a product. Neutrosophic statistics is the more generalized form of classical statistics and is applied when the data from the production process or a product lot is incomplete, incredible, and indeterminate. In this paper, we will originally propose a variable sampling plan for the PCI using neutrosophic statistics. The neutrosophic operating function will be given. The neutrosophic plan parameters will be determined using the neutrosophic optimization solution. A comparison between plans based on neutrosophic statistics and classical statistics is given. The application of the proposed neutrosophic sampling plan will be given using company data.

In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.

This book addresses new concepts, methods, algorithms, modeling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, linear problems and new information related to optimization for the topic from the theoretical and applied viewpoints of neutrosophic sets and logic. The book is an innovatory of new tools and procedures, such as: Neutrosophic Statistical Tests and Dependent State Samplings, Neutrosophic Probabilistic Expert Systems, Neutrosophic HyperSoft Set, Quadripartitioned Neutrosophic Cross-Entropy, Octagonal and Spherical and Cubic Neutrosophic Numbers used in machine learning. It highlights the process of neutrosofication {which means to split the universe into three parts, two opposite ones (Truth and Falsehood), and an Indeterminate or neutral one (I) in between them}. It explains Three-Ways Decision, how the universe set is split into three different distinct areas, in regard to the decision process, representing: Acceptance, Noncommitment, and Rejection, respectively. The Three-Way Decision is used in the Neutrosophic Linguistic Rough Set, which has never been done before.