Design of a New Attribute Control Chart Under Neutrosophic Statistics

In this paper, a control chart scheme has been introduced for the mean monitoring using gamma distribution for belief statistics using multiple dependent (deferred) state sampling under the neutrosophic statistics. The coefficients of the control chart and the neutrosophic average run lengths have been estimated for specific false alarm probabilities under various process conditions. The offered chart has been compared with the existing classical chart through simulation and the real data. From the comparison, it is concluded that the performance of the proposed chart is better than that of the existing chart in terms of average run length under uncertain environment. The proposed chart has the ability to detect a shift quickly than the existing chart. It has been observed that the proposed chart is efficient in quick monitoring of the out-of-control process and a cherished addition in the toolkit of the quality control personnel.

Download Full-text

Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme

Journal of Mathematics ◽

10.1155/2021/6635846 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Abdullah M. Almarashi ◽

Muhammad Aslam

Keyword(s):

Control Chart ◽

Simulation Study ◽

Average Run Length ◽

Control Process ◽

Practical Application ◽

Interval Method ◽

Length Measurements ◽

Neutrosophic Statistics ◽

Run Lengths ◽

Different Levels

In this article, a repetitive sampling control chart for the gamma distribution under the indeterminate environment has been presented. The control chart coefficients, probability of in-control, probability of out-of-control, and average run lengths have been determined under the assumption of the symmetrical property of the normal distribution using the neutrosophic interval method. The performance of the designed chart has been evaluated using the average run length measurements under different process settings for an indeterminate environment. In-control and out-of-control nature of the proposed chart under different levels of shifts have been described. The comparison of the proposed chart has been made with the existing chart. A real-world example from the healthcare department has been included for the practical application of the proposed chart. It has been observed from the simulation study and real example that the proposed control chart is efficient in quick monitoring of the out-of-control process. It can be concluded that the proposed control chart can be applied effectively in uncertainty.

Download Full-text

A new sudden death chart for the Weibull distribution under complexity

Complex & Intelligent Systems ◽

10.1007/s40747-021-00316-x ◽

2021 ◽

Author(s):

Osama H. Arif ◽

Muhammad Aslam

Keyword(s):

Sudden Death ◽

Control Chart ◽

Control Process ◽

Value Addition ◽

Detection Ability ◽

Classical Statistics ◽

Monitoring Reliability ◽

Neutrosophic Statistics ◽

Industrial Use ◽

Run Lengths

AbstractThis article presents a new control chart for monitoring reliability using sudden death testing under the neutrosophic statistics (NS). The average run lengths of the in-control and the out-of-control process have been determined for evaluating the quick detection ability for small and moderate shifts. For the industrial use, tables and figures have been presented for different parameters. The proposed control chart is efficient in comparison with the existing control chart under classical statistics and value addition in the toolkit of the quality control personnel.

Download Full-text

Control Chart for Monitoring Variation Using Multiple Dependent State Sampling Under Neutrosophic Statistics

10.1007/978-3-030-57197-9_4 ◽

2021 ◽

pp. 55-70

Author(s):

Nasrullah Khan ◽

Liaquat Ahmad ◽

Muhammad Azam ◽

Muhammad Aslam ◽

Florentin Smarandache

Keyword(s):

Control Chart ◽

Neutrosophic Statistics ◽

Dependent State

Download Full-text

Monitoring the Variability in the Process Using Neutrosophic Statistical Interval Method

Symmetry ◽

10.3390/sym10110562 ◽

2018 ◽

Vol 10 (11) ◽

pp. 562 ◽

Cited By ~ 21

Author(s):

Muhammad Aslam ◽

Nasrullah Khan ◽

Muhammad Khan

Keyword(s):

Control Chart ◽

Control Charts ◽

Average Run Length ◽

Interval Methods ◽

Interval Method ◽

Classical Statistics ◽

Neutrosophic Statistics ◽

Imprecise Observations ◽

Better Than

Existing variance control charts are designed under the assumptions that no uncertain, fuzzy and imprecise observations or parameters are in the population or the sample. Neutrosophic statistics, which is the extension of classical statistics, has been widely used when there is uncertainty in the data. In this paper, we will originally design S 2 control chart under the neutrosophic interval methods. The complete structure of the neutrosophic S 2 control chart will be given. The necessary measures of neutrosophic S 2 will be given. The neutrosophic coefficient of S 2 control chart will be determined through the neutrosophic algorithm. Some tables are given for practical use. The efficiency of the proposed control chart is shown over the S 2 control chart designed under the classical statistics in neutrosophic average run length (NARL). A real example is also added to illustrate the proposed control chart. From the comparison in the simulation study and case study, it is concluded that the proposed control chart performs better than the existing control chart under uncertainty.

Download Full-text

Control Chart for Failure-Censored Reliability Tests under Uncertainty Environment

Symmetry ◽

10.3390/sym10120690 ◽

2018 ◽

Vol 10 (12) ◽

pp. 690 ◽

Cited By ~ 8

Author(s):

Muhammad Aslam ◽

Nasrullah Khan ◽

Mohammed Albassam

Keyword(s):

Weibull Distribution ◽

Control Chart ◽

Control Charts ◽

Scale Parameter ◽

Type Ii ◽

Classical Statistics ◽

Neutrosophic Statistics ◽

Uncertainty Environment

Existing control charts based on failure-censored (Type-II) reliability tests were designed using classical statistics. Classical statistics was applied for the monitoring of the process when observations in the sample or the population were determined. Neutrosophic statistics (NS) are applied when there is uncertainty in the sample or population. In this paper, a control chart for failure-censored (Type-II) reliability tests was designed using NS. The design of a control chart for the Weibull distribution, which is applied when there is a lack of symmetry using neutrosophic statistics, is given. The proposed control chart was used to monitor the neutrosophic mean and neutrosophic variance, which are related to the neutrosophic scale parameter. The advantages of the proposed control chart over the existing control chart are discussed.

Download Full-text

Monitoring of production of blood components by attribute control chart under indeterminacy

Scientific Reports ◽

10.1038/s41598-020-79851-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Nasrullah Khan ◽

Muhammad Aslam ◽

P. Jeyadurga ◽

S. Balamurali

Keyword(s):

Control Chart ◽

Control Charts ◽

Blood Components ◽

Interval Method ◽

Uncertain Environment ◽

Classical Statistics ◽

Neutrosophic Statistics

AbstractThe existing control chart for monitoring the blood components by attribute is designed using classical statistics. The existing attribute control chart can be applied only when the experimenter is sure about the proportion of defective or all the observations in the sample are determined. In this paper, new attribute control charts for monitoring the blood components under the neutrosophic statistics will be presented. The design of the proposed control chart is given under the neutrosophic statistical interval method. The applications of these control charts demonstrate that the proposed control charts are quite effective, adequate, flexible, and informative for monitoring the blood components under uncertain environment.

Download Full-text