Design of NEWMA np control chart for monitoring neutrosophic nonconforming items
- PDF / 764,280 Bytes
- 10 Pages / 595.276 x 790.866 pts Page_size
- 75 Downloads / 160 Views
(0123456789().,-volV) (0123456789().,-volV)
METHODOLOGIES AND APPLICATION
Design of NEWMA np control chart for monitoring neutrosophic nonconforming items Muhammad Aslam1
•
Rashad A. R. Bantan2 • Nasrullah Khan3
Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract We will introduce a neutrosophic exponentially weighted moving average (NEWMA) statistic for the attribute data. We will use the proposed NEWMA to design an attribute control chart. We will introduce the neutrosophic Monte Carlo simulation to find the neutrosophic average run length (NARL). The comparative study shows the efficiency of the proposed NEWMA attribute. Two examples of having neutrosophic parameters will be given to explain the proposed control chart. We hope that the proposed chart will perform better under uncertainty. Keywords Uncertainty Neutrosophic statistics Classical statistics NEWMA shift Attribute
1 Introduction To maintain quality, the continuous monitoring of the production process is necessary. The product is said to be a high-quality product if it is manufactured according to the given specification limits. The control charts are powerful tools that have been used in the industry. The control charts provide the single when some external variation is detected in the process. These tools help the industrial engineers to bring back the process in an in-control state. The Shewhart variable and attribute control charts are popularly used in this industry for the monitoring of the process. These control charts are very simple in the operational procedure. As the Shewhart control chart utilizes only the current
Communicated by V. Loia. & Muhammad Aslam [email protected] Rashad A. R. Bantan [email protected] Nasrullah Khan [email protected] 1
Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
2
Department of Marine Geology, Faculty of Marine Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
3
Department of Statistics, University of Veterinary and Animal Sciences, Jhang Campus, Lahore, Pakistan
sample information, the main drawback of the Shewhart control chart is that these charts are unable to detect a small shift (a shift less than 3*r, where r is the population standard deviation) in the process. The data came from the production are either attribute data or variable data. The attribute control charts such as np chart and c chart are designed for attribute data, and variable control charts such as X-bar control chart are designed for the variable data. Both charts are important and applied for monitoring the process. The later charts are designed using measurable data. When the purpose is to control the nonconforming items, the attribute control charts are applied in the industry. Engin et al. (2008) discussed attribute control chart in multistage processes using the fuzzy approach. Senturk and Erginel (2009) used an alpha cut method to design Shewhart control charts. Hart et al. (2003) discussed the application of the char
Data Loading...
