scholarly journals Inspection Strategy under Indeterminacy Based on Neutrosophic Coefficient of Variation

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 193 ◽  
Author(s):  
Muhammad Aslam ◽  
Mansour Sattam Aldosari
Keyword(s):  
Sample Size ◽  
Coefficient Of Variation ◽  
Operating Characteristic ◽  
Uncertain Data ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Inspection Strategy ◽  
Classical Statistics

The existing sampling plans which use the coefficient of variation (CV) are designed under classical statistics. These available sampling plans cannot be used for sentencing if the sample or the population has indeterminate, imprecise, unknown, incomplete or uncertain data. In this paper, we introduce the neutrosophic coefficient of variation (NCV) first. We design a sampling plan based on the NCV. The neutrosophic operating characteristic (NOC) function is then given and used to determine the neutrosophic plan parameters under some constraints. The neutrosophic plan parameters such as neutrosophic sample size and neutrosophic acceptance number are determined through the neutrosophic optimization solution. We compare the efficiency of the proposed plan under the neutrosophic statistical interval method with the sampling plan under classical statistics. A real example which has indeterminate data is given to illustrate the proposed plan.

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.

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 Product Acceptance Determination with Measurement Error Using the Neutrosophic Statistics

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Optimization Problem ◽  
Sampling Plan ◽  
Measurement Process ◽  
Comparison Study ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Variable Data ◽  
Uncertainty Environment

The variable data is obtained from the measurement process which is not fully complete or clear in nature due to measurement error. The neutrosophic statistics which is the extension of classical statistics can be applied in the industry for the lot senescing when observations or parameters are uncertain or indeterminate or unclear. In this manuscript, a new sampling plan for the measurement error using the neutrosophic statistics is designed. The proposed sampling plan has two neutrosophic parameters, namely, sample size and acceptance number. The neutrosophic operating function is also given. The neutrosophic plan parameters will be determined through the neutrosophic optimization problem. Some tables are given for some specified parameters. From the comparison study, it is concluded that the proposed sampling plan is more flexible, adequate, and effective in the uncertainty environment as compared to the existing sampling plan under the classical statistics. A real example is given for the illustration purpose.

scholarly journals Sampling Hazelnuts for Aflatoxin: Effect of Sample Size and Accept/Reject Limit on Reducing the Risk of Misclassifying Lots

2007 ◽  
Vol 90 (4) ◽  
pp. 1028-1035 ◽  
Author(s):  
Guner Ozay ◽  
Ferda Seyhan ◽  
Aysun Yilmaz ◽  
Thomas B Whitaker ◽  
Andrew B Slate ◽  
...  
Keyword(s):  
Sample Size ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Food Additives ◽  
Sampling Plan ◽  
Test Results ◽  
Sampling Plans ◽  
Wide Range ◽  
Sample Test

Abstract About 100 countries have established regulatory limits for aflatoxin in food and feeds. Because these limits vary widely among regulating countries, the Codex Committee on Food Additives and Contaminants began work in 2004 to harmonize aflatoxin limits and sampling plans for aflatoxin in almonds, pistachios, hazelnuts, and Brazil nuts. Studies were developed to measure the uncertainty and distribution among replicated sample aflatoxin test results taken from aflatoxin-contaminated treenut lots. The uncertainty and distribution information is used to develop a model that can evaluate the performance (risk of misclassifying lots) of aflatoxin sampling plan designs for treenuts. Once the performance of aflatoxin sampling plans can be predicted, they can be designed to reduce the risks of misclassifying lots traded in either the domestic or export markets. A method was developed to evaluate the performance of sampling plans designed to detect aflatoxin in hazelnuts lots. Twenty hazelnut lots with varying levels of contamination were sampled according to an experimental protocol where 16 test samples were taken from each lot. The observed aflatoxin distribution among the 16 aflatoxin sample test results was compared to lognormal, compound gamma, and negative binomial distributions. The negative binomial distribution was selected to model aflatoxin distribution among sample test results because it gave acceptable fits to observed distributions among sample test results taken from a wide range of lot concentrations. Using the negative binomial distribution, computer models were developed to calculate operating characteristic curves for specific aflatoxin sampling plan designs. The effect of sample size and accept/reject limits on the chances of rejecting good lots (sellers' risk) and accepting bad lots (buyers' risk) was demonstrated for various sampling plan designs.

Use of Loose Shelled Kernels to Estimate Aflatoxin in Farmers Stock Peanut Lots1

1999 ◽  
Vol 26 (1) ◽  
pp. 39-44 ◽  
Author(s):  
T. B. Whitaker ◽  
F. G. Giesbrecht ◽  
W. M. Hagler
Keyword(s):  
Sample Size ◽  
Coefficient Of Variation ◽  
Functional Relationship ◽  
Test Sample ◽  
Sampling Plan ◽  
Sample Sizes ◽  
Total Aflatoxin ◽  
Aflatoxin Concentration

Abstract Loose shelled kernels (LSK) are a defined grade component of farmers stock peanuts and represented, on the average, 33.3% of the total aflatoxin mass and 7.7% of the kernel mass among the 120 farmers stock peanut lots studied. The functional relationship between aflatoxin in LSK taken from 2-kg test samples and the aflatoxin in farmers stock peanut lots was determined to be linear with zero intercept and a slope of 0.297. The correlation between aflatoxin in LSK and aflatoxin in the lot was 0.844 which suggests that LSK taken from large test samples can be used to estimate the aflatoxin concentration in a farmer's lot. Using only LSK allows large test samples to be used to estimate the lot concentration since LSK can be easily screened from a large test sample. If LSK accounts for 7.7% of the lot kernel mass, a 50-kg sample will yield about 3.9 kg of LSK which can be easily prepared for aflatoxin analysis. Increasing the test sample size from 2 to 50 kg reduced the coefficient of variation associated with estimating a lot with 100 parts per billion (ppb) aflatoxin from 114 to 23%, respectively. As an example, a farmers stock aflatoxin sampling plan with dual tolerances (10 and 100 ppb) that classified lots into three categories was evaluated for two test sample sizes (2 and 50 kg). The effect of increasing test sample size from 2 to 50 kg on the number of lots classified into each of the three categories was demonstrated when measuring aflatoxin only in LSK.

scholarly journals Sampling plan in health surveys, city of São Paulo, Brazil, 2015

2018 ◽  
Vol 52 ◽  
pp. 81 ◽  
Author(s):  
Maria Cecilia Goi Porto Alves ◽  
Maria Mercedes Loureiro Escuder ◽  
Moises Goldbaum ◽  
Marilisa Berti de Azevedo Barros ◽  
Regina Mara Fisberg
Keyword(s):  
Sample Size ◽  
Health Survey ◽  
Coefficient Of Variation ◽  
Sample Size Calculation ◽  
Sao Paulo ◽  
Sampling Plan ◽  
São Paulo ◽  
Design Effect ◽  
Sampling Procedures ◽  
The City

OBJECTIVE: To evaluate the sampling plan of the Health Survey of the City of São Paulo (ISA-Capital 2015) regarding the accuracy of estimates and the conformation of domains of study by the Health Coordinations of the city of São Paulo, Brazil. METHODS: We have described the population, domains of study, and sampling procedures, including stratification, calculation of sample size, and random selection of sample units, of the Health Survey of the City of São Paulo, 2015. The estimates of proportions were analyzed in relation to precision using the coefficient of variation and the design effect. We considered suitable the coefficients below 30% at the regional level and 20% at the city level and the estimates of the design effect below 1.5. We considered suitable the strategy of establishing the Health Coordinations as domains after verifying that, within the coordinations, the estimates of proportions for the age and sex groups had the minimum acceptable precision. The estimated parameters were related to the subjects of use of services, morbidity, and self-assessment of health. RESULTS: A total of 150 census tracts were randomly selected, 30 in each Health Coordination, 5,469 households were randomly selected and visited, and 4,043 interviews were conducted. Of the 115 estimates made for the domains of study, 97.4% presented coefficients of variation below 30%, and 82.6% were below 20%. Of the 24 estimates made for the total of the city, 23 presented coefficient of variation below 20%. More than two-thirds of the estimates of the design effect were below 1.5, which was estimated in the sample size calculation, and the design effect was below 2.0 for 88%. CONCLUSIONS: The ISA-Capital 2015 sample generated estimates at the predicted levels of precision at both the city and regional levels. The decision to establish the regional health coordinations of the city of São Paulo as domains of study was adequate.

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 Designing of Chain Sampling Plan under Gamma-Poisson Distribution

2019 ◽  
Vol 9 (1S4) ◽  
pp. 711-714
Keyword(s):  
Poisson Distribution ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sampling Plan ◽  
Conditional Sampling ◽  
Optimal Parameters ◽  
Sampling Plans ◽  
Operating Characteristic Curve

In this manuscript, we discuss the designing procedure of chain sampling plan which is known as one of the conditional sampling plans under gamma-Poisson distribution. We determine the optimal parameters namely, number of items to be chosen for inspection from the lot and number of preceding lots to be considered in order to dispose the current lot by specifying two points on the operating characteristic curve, which is the usual designing approach of sampling plan. The procedure which is used to execute the proposed plan is provided and comparison is made among the proposed plan and existing sampling plans performance.

scholarly journals Reliability Sampling Procedure For High Priced Products

2021 ◽  
Vol 12 (4) ◽  
pp. 1117-1120
Author(s):  
V. Jemmy Joyce, Et. al.
Keyword(s):  
Characteristic Function ◽  
Sample Size ◽  
Exponential Distribution ◽  
Operating Characteristic ◽  
Design Procedure ◽  
Sampling Procedure ◽  
Sampling Plan ◽  
Life Testing ◽  
Operating Characteristic Function ◽  
Very High

Life testing for very high priced products with least of sample size can be done using the procedure of sampling plan designed in this paper. The required sample size for various of operating characteristic function using new design procedure is obtained using program in OCTAVE based on Lomaxdistribution and is compared with sample size obtained based on exponential distribution.

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