scholarly journals Design of Sampling Plan Using Regression Estimator under Indeterminacy

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 754 ◽  
Author(s):  
Muhammad Aslam ◽  
Ali AL-Marshadi
Keyword(s):  
Auxiliary Information ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Regression Estimator ◽  
Sampling Plans ◽  
Classical Statistics ◽  
Acceptance Sampling Plans ◽  
Neutrosophic Statistics ◽  
Lot Sentencing

The acceptance sampling plans are one of the most important tools for the inspection of a lot of products. Sometimes, it is difficult to study the variable of interest, and some additional or auxiliary information which is correlated to that variable is available. The existing sampling plans having auxiliary information are applied when the full, precise, determinate and clear data is available for lot sentencing. Neutrosophic statistics, which is the extension of classical statistics, can be applied when information about the quality of interest or auxiliary information is unclear and indeterminate. In this paper, we will introduce a neutrosophic regression estimator. We will design a new sampling plan using the neutrosophic regression estimator. The neutrosophic parameters of the proposed plan will be determined through the neutrosophic optimization solution. The efficiency of the proposed plan is discussed. The results of the proposed plan will be explained using real industrial data. From the comparison, it is concluded that the proposed sampling plan is more effective and adequate for the inspection of a lot than the existing plan, under the conditions of uncertainty.

scholarly journals A Variable Acceptance Sampling Plan under Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 114 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Operating Characteristic ◽  
Fuzzy Variable ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Interval Method ◽  
Acceptance Sampling Plan ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The acceptance sampling plan plays an important role in maintaining the high quality of a product. The variable control chart, using classical statistics, helps in making acceptance or rejection decisions about the submitted lot of the product. Furthermore, the sampling plan, using classical statistics, assumes the complete or determinate information available about a lot of product. However, in some situations, data may be ambiguous, vague, imprecise, and incomplete or indeterminate. In this case, the use of neutrosophic statistics can be applied to guide the experimenters. In this paper, we originally proposed a new variable sampling plan using the neutrosophic interval statistical method. The neutrosophic operating characteristic (NOC) is derived using the neutrosophic normal distribution. The optimization solution is also presented for the proposed plan under the neutrosophic interval method. The effectiveness of the proposed plan is compared with the plan under classical statistics. The tables are presented for practical use and a real example is given to explain the neutrosophic fuzzy variable sampling plan in the industry.

scholarly journals Inspection Plan Based on the Process Capability Index Using the Neutrosophic Statistical Method

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 631 ◽  
Author(s):  
Aslam ◽  
Albassam
Keyword(s):  
Production Process ◽  
Statistical Method ◽  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

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.

THE DESIGNS OF ACCEPTANCE SAMPLING FOR STRENGTH DISTRIBUTIONS WITH PERCENTILES

2012 ◽  
Vol 19 (01) ◽  
pp. 1250004
Author(s):  
Y. L. LIO ◽  
TZONG-RU TSAI ◽  
SHUO-JYE WU
Keyword(s):  
Breaking Strength ◽  
Numerical Study ◽  
Real Data ◽  
Acceptance Sampling ◽  
Data Set ◽  
Sampling Plans ◽  
Failure Times ◽  
Acceptance Sampling Plans ◽  
Manufacturing Applications

In material manufacturing applications, the lower percentiles of breaking strength of products contain critical reliability information. To promote the quality of product, it is important to ensure the lower percentiles of product breaking strength meet a satisfactory level. In this paper, two acceptance sampling plans are developed based on the percentiles of Weibull distribution and lognormal distribution with truncated life testing samples. An algorithm is provided to obtain acceptance sampling plans under the specified points of producer's risk and consumer's risk. Some tables are presented for numerical study, and an example of real data set regarding the first failure times of small electric carts used for internal transportation and delivery is provided for illustration.

scholarly journals Design of Variable Sampling Plan for Pareto Distribution Using Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 80 ◽  
Author(s):  
Muhammad Aslam ◽  
Nasrullah Khan ◽  
Ali Hussein AL-Marshadi
Keyword(s):  
Optimization Problem ◽  
Pareto Distribution ◽  
Measurement Data ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Uncertainty In Measurement ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The sampling plans have been widely used for the inspection of a lot of the product. In practice, the measurement data may be imprecise, uncertain, unclear or fuzzy. When there is uncertainty in the observations, the sampling plans designed using classical statistics cannot be applied for the inspection of a lot of the product. The neutrosophic statistic, which is the generalization of the classical statistics, can be used when data is not precise, uncertain, unclear or fuzzy. In this paper, we will design the variable sampling plan under the Pareto distribution using the neutrosophic statistics. We used the symmetry property of the normal distribution. We assume uncertainty in measurement data and sample size required for the inspection of a lot of the product. We will determine the neutrosophic plan parameters using the neutrosophic optimization problem. Some tables are given for practical use and are discussed with the help of an example.

scholarly journals Single-stage and two-stage total failure-based group-sampling plans for the Weibull distribution under neutrosophic statistics

2021 ◽  
Author(s):  
Muhammad Aslam ◽  
G. Srinivasa Rao ◽  
Nasrullah Khan
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Total Failure ◽  
Life Tests ◽  
Double Group

AbstractIf the sample or population has vague, inaccurate, unidentified, deficient, indecisive, or fuzzy data, then the available sampling plans could not be suitable to use for decision-making. In this article, an improved group-sampling plan based on time truncated life tests for Weibull distribution under neutrosophic statistics (NS) has been developed. We developed improved single and double group-sampling plans based on the NS. The proposed design neutrosophic plan parameters are obtained by satisfying both producer’s and consumer’s risks simultaneously under neutrosophic optimization solution. Tables are constructed for the selected shape parameter of Weibull distribution and various combinations of neutrosophic group size. The efficiency of the proposed group-sampling plan under the neutrosophic statistical interval method is also compared with the crisp method grouped sampling plan under classical statistics.

Design of Optimal Reliability Acceptance Sampling Plans for Exponential Distribution

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Mahesh Kumar ◽  
Ramyamol P C
Keyword(s):  
Exponential Distribution ◽  
Sequential Sampling ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Sequential Sampling Plan ◽  
Acceptance Sampling Plans ◽  
Reliability Sampling Plans

AbstractIn this paper, an attempt is made to derive the most efficient economic reliability sampling plans for accepting a lot containing identical units having exponentially distributed lifetime with parameter θ. We consider two types of sampling plans, namely, (a) sequential sampling plan

scholarly journals Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution

Mathematics ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Muhammad Zahir Khan ◽  
Muhammad Farid Khan ◽  
Muhammad Aslam ◽  
Abdur Razzaque Mughal
Keyword(s):  
Operating Characteristic ◽  
Real Life ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Acceptance Probability ◽  
Defective Items ◽  
Sampling Plans ◽  
Fuzzy Environment ◽  
Acceptance Sampling Plan ◽  
Acceptance Sampling Plans

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.

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