On designing a new control chart for Rayleigh distributed processes with an application to monitor glass fiber strength
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 3168-3184 |
Journal / Publication | Communications in Statistics: Simulation and Computation |
Volume | 51 |
Issue number | 6 |
Online published | 13 Jan 2020 |
Publication status | Published - 2022 |
Link(s)
Abstract
In this study, a Shewhart type control chart, namely VR chart, has been proposed to monitor a process that follows Rayleigh distribution. The proposed VR chart is implemented to monitor the single scale parameter of the Rayleigh distributed process. We have studied the proposed chart under two type of control limits namely probability and L-sigma limits. The performance of the proposed chart has been assessed by using power function. In addition, we have investigated run length properties including average run length (ARL), standard deviation of run length (SDRL) and median run length (MDRL). The analysis of run length profile reveals that the proposed VR chart outperforms the existing charts including the traditional Shewhart control chart and V control charts under Rayleigh distribution. The construction process for the newly proposed chart has been demonstrated using a simulated data. Finally, a real application of the proposed VR chart, along with the existing V chart, is presented that evaluates the strength of glass fiber in a manufacturing process.
Research Area(s)
- Control chart, Gamma distribution, Maximum likelihood estimation, Rayleigh distribution, Run length
Citation Format(s)
On designing a new control chart for Rayleigh distributed processes with an application to monitor glass fiber strength. / Hossain, M. Pear; Omar, M. Hafidz; Riaz, Muhammad et al.
In: Communications in Statistics: Simulation and Computation, Vol. 51, No. 6, 2022, p. 3168-3184.
In: Communications in Statistics: Simulation and Computation, Vol. 51, No. 6, 2022, p. 3168-3184.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review