scholarly journals Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 162775-162784 ◽  
Author(s):  
Ritwik Bhattacharya ◽  
Muhammad Aslam
Keyword(s):  
Measurement Data ◽  
Sampling Plans ◽  
Dependent State

Mixed Multiple Dependent State Sampling Plans Based on Process Capability Index

2014 ◽  
Vol 43 (1) ◽  
pp. 20130009 ◽  
Author(s):  
Muhammad Aslam ◽  
Saminathan Balamurali ◽  
Muhammad Azam ◽  
G. Sirnvasa Rao ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plans ◽  
Capability Index ◽  
Dependent State

Multiple dependent state variable sampling plans with process loss consideration

2014 ◽  
Vol 71 (5-8) ◽  
pp. 1337-1343 ◽  
Author(s):  
Muhammad Aslam ◽  
Ching-Ho Yen ◽  
Chia-Hao Chang ◽  
Chi-Hyuck Jun
Keyword(s):  
Sampling Plans ◽  
State Variable ◽  
Variable Sampling ◽  
Process Loss ◽  
Dependent State

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.

Generalized multiple dependent state sampling plans for coefficient of variation

2021 ◽  
pp. 1-25
Author(s):  
Gadde Srinivasa Rao ◽  
Muhammad Aslam ◽  
Rehan Ahmad Khan Sherwani ◽  
Muhammad Ahmed Shehzad ◽  
Chi-Hyuck Jun
Keyword(s):  
Coefficient Of Variation ◽  
Sampling Plans ◽  
Dependent State
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