Time truncated efficient testing strategy for Pareto distribution of the 2nd kind using weighted poisson and poisson distribution

In this study, group acceptance sampling plan (GASP) proposed by Aslam et al. (2011) is redesigned where the lifetime of test items are following Pareto distribution of 2nd kind. The optimal plan parameters are found by considering various pre-determined designed parameters. The plan parameters were obtained using the optimization solution and it also concludes that the proposed plan is more efficient than the existing plan as it requires minimum sample size

Group acceptance sampling plan for re-submitted lots under generalized pareto distribution

In this study, a Group Acceptance Sampling Plan (GASP) for lot resubmitting is developed for situations in which the lifetime of a product follows the generalized Pareto distribution.The design parameters such as minimum group size and acceptance number are observed when the consumer’s risk, number of testers and the test termination time are pre-specified. The proposed plan requires less sample size than the ordinary GASP.The condition of lot re-sampling was examined and measurement of a resubmitted method having a GASP for inspection

Time truncated group chain sampling strategy for pareto distribution of the 2nd kind

The main goal of this study is to propose a chain Group Acceptance Sampling Plan (GASP) when the life time of a product follows the Pareto distribution of the 2nd kind. The design parameters such as the minimum group size and operating characteristic values are obtained by satisfying the producer’s and consumer’s risks at the specified quality level, acceptance number and the test termination time.A classical example is considered in order to compare the proposed plan with some existing plans

Time truncated generalized chain sampling plan for pareto distribution of the 2nd kind

The main purpose of this study is to intend a generalized chain sampling plan for Pareto distribution of the 2nd kind.The designed parameters such as the minimum sample size and operating characteristic values are found by satisfying the consumer's risk at the specified quality levels in terms of average. The results are explained by an example

New Challenges in Neutrosophic Theory and Applications

Neutrosophic theory has representatives on all continents and, therefore, it can be said to be a universal theory. On the other hand, according to the three volumes of “The Encyclopedia of Neutrosophic Researchers” (2016, 2018, 2019), plus numerous others not yet included in Encyclopedia book series, about 1200 researchers from 73 countries have applied both the neutrosophic theory and method. Neutrosophic theory was founded by Professor Florentin Smarandache in 1998; it constitutes further generalization of fuzzy and intuitionistic fuzzy theories. The key distinction between the neutrosophic set/logic and other types of sets/logics lies in the introduction of the degree of indeterminacy/neutrality (I) as an independent component in the neutrosophic set. Thus, neutrosophic theory involves the degree of membership-truth (T), the degree of indeterminacy (I), and the degree of non-membership-falsehood (F). In recent years, the field of neutrosophic set, logic, measure, probability and statistics, precalculus and calculus, etc., and their applications in multiple fields have been extended and applied in various fields, such as communication, management, and information technology. We believe that this book serves as useful guidance for learning about the current progress in neutrosophic theories. In total, 22 studies have been presented and reflect the call of the thematic vision. The contents of each study included in the volume are briefly described as follows. The first contribution, authored by Wadei Al-Omeri and Saeid Jafari, addresses the concept of generalized neutrosophic pre-closed sets and generalized neutrosophic pre-open sets in neutrosophic topological spaces. In the article “Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution”, the authors Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, and Abdur Razzaque Mughal discuss the use of probability distribution function of Birnbaum–Saunders distribution as a proportion of defective items and the acceptance probability in a fuzzy environment. Further, the authors Derya Bakbak, Vakkas Uluc¸ay, and Memet S¸ahin present the “Neutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Making” together with several operations defined for them and their important algebraic properties. In “Neutrosophic Multigroups and Applications”, Vakkas Uluc¸ay and Memet S¸ahin propose an algebraic structure on neutrosophic multisets called neutrosophic multigroups, deriving their basic properties and giving some applications to group theory. Changxing Fan, Jun Ye, Sheng Feng, En Fan, and Keli Hu introduce the “Multi-Criteria Decision-Making Method Using Heronian Mean Operators under a Bipolar Neutrosophic Environment” and test the effectiveness of their new methods. Another decision-making study upon an everyday life issue which empowered us to organize the key objective of the industry developing is given in “Neutrosophic Cubic Einstein Hybrid Geometric Aggregation Operators with Application in Prioritization Using Multiple Attribute Decision-Making Method” written by Khaleed Alhazaymeh, Muhammad Gulistan, Majid Khan, and Seifedine Kadry

Generalized group chain acceptance sampling plan

In this article, we proposed an acceptance sampling plan based on generalized group chain truncated life test.The decision on acceptance of a submitted lot can be made by using the cumulative information of the immediately preceding samples.The design parameters of the proposed plan such as the minimum number of groups are found to satisfy the desired quality standard.The benefits of this plan include smaller sample size and reduced overall costs

Testing a criterion-centric approach to validation for a leadership effectiveness framework in the context of South East Asia

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Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution

Acceptance sampling is one of the essential areas of quality control. In a conventional environment, probability theory is used to study acceptance sampling plans. In some situations, it is not possible to apply conventional techniques due to vagueness in the values emerging from the complexities of processor measurement methods. There are two types of acceptance sampling plans: attribute and variable. One of the important elements in attribute acceptance sampling is the proportion of defective items. In some situations, this proportion is not a precise value, but vague. In this case, it is suitable to apply flexible techniques to study the fuzzy proportion. Fuzzy set theory is used to investigate such concepts. It is observed there is no research available to apply Birnbaum-Saunders distribution in fuzzy acceptance sampling. In this article, it is assumed that the proportion of defective items is fuzzy and follows the Birnbaum-Saunders distribution. A single acceptance sampling plan, based on binomial distribution, is used to design the fuzzy operating characteristic (FOC) curve. Results are illustrated with examples. One real-life example is also presented in the article. The results show the behavior of curves with different combinations of parameters of Birnbaum-Saunders distribution. The novelty of this study is to use the probability distribution function of Birnbaum-Saunders distribution as a proportion of defective items and find the acceptance probability in a fuzzy environment. This is an application of Birnbaum-Saunders distribution in fuzzy acceptance sampling