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.

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.

Multiple Dependent State Sampling Plan Based on Process Capability Index

2013 ◽  
Vol 41 (2) ◽  
pp. 20120012 ◽  
Author(s):  
Muhammad Aslam ◽  
Muhammad Azam ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index ◽  
Dependent State

scholarly journals A mixed repetitive sampling plan based on process capability index

2013 ◽  
Vol 37 (24) ◽  
pp. 10027-10035 ◽  
Author(s):  
Muhammad Aslam ◽  
Muhammad Azam ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index

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.

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