Performance of Tukey's and Individual/Moving Range Control Charts

Control chart is a popular technique that is widely used in statistical process control to identify any possible deviations from a stable state of a process. Shewhart charts are famous for identifying larger shifts, while cumulative sum and exponentially weighted moving average control charts are well known for identifying smaller shifts in process parameters. This study examines the performance of a sequential-based EWMA (namely SEWMA Ò) chart for observing the location of a normally distributed process. The performance of SEWMA Ò is oberved by using several overall run length properties (like average, median and standard deviation). The comparative study reveals that the overall performance of the proposed design is better than the existing counterparts. Moreover, the superiority depends on the choice of the design parameters of the proposed chart. A real-life data set from a steel rod manufacturing industry were considered to show the real-life illustration of the proposed design.

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“…These run length properties may be calculated by using the following expressions (cf. Chakraborti [26], Khaliq et al [27])…”

Section: Performance Evaluation Techniquesmentioning

confidence: 97%

On designing a sequential based EWMA structure for efficient process monitoring

Khaliq

Omar

Riaz

2020

Journal of Taibah University for Science

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“…Khaliq at el. [10] did the comparative analysis to judge the performance of Tukey chart versus X/MR chart under the several probability models and Tukey chart was the best choice in many cases. The study revealed that this charts is a good alternative to Shewhart and X/MR chart for monitoring when data is of skewed form.…”

Section: Literature Reviewmentioning

confidence: 99%

On the Performance of Median Based Tukey and Tukey-EWMA Charts Under Rational Subgrouping

et al. 2019

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Control chart (CC) is used to monitor the special causes that arise during the process monitoring.These special causes produce continual shifts in the process parameters that last until it is identified and removed. There is a need for such techniques, which present the true representation of the entire process. Rational subgrouping is an essential concept in Statistical Process Control (SPC) which is seldom overlooked by the practitioner. Hence, most of the manufacturing, engineering, and production processes give output products in the form of batches over smaller intervals of time. The aim of this study is to provide a median based design for Tukey and Tukey-EWMA control charts under subgrouping. It will use the idea of boxplot to monitor the process behavior. This study also provides a brief discussion regarding selecting and forming subgroups from the process data. The performance of the median based Tukey and Tukey-EWMA charts are judged using Average, Median and Standard-Deviation run-length as performance measures. We have considered subgroup sizes of m=1,5 &10 at pre-specified ARL0 equal to 370. To real-life applications of the median based tukey designs are also presented to show their implementation in food manufacturing and hard-bake processes.2

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“…It has an effective charting structure that exhibits robustness for the skewed distributions. Alemi and several other authors have studied its properties such as Khaliq et al , Lee et al , Torng and Lee, Lee and Torng, Tercero‐Gomez et al , and Torng et al , among many others. The control limits for this chart are defined a

L C L = Q_{1} - L ((), I Q R), C L = Q_{2}, U C L = Q_{3} + L ((), I Q R)

where Q 1 and Q 3 are the first and third quartiles, Q 2 is the median, IQR is deviation of Q 1 and Q 3 , i.e., inter‐quartile range (IQR) is defined by Q 3 −Q 1 , and L is the control limits coefficient that may be fixed at a pre‐specified value of average run length (ARL), denoted by ARL 0 for an in‐control process.…”

Section: Design Of Tukey‐cusum Control Chartmentioning

confidence: 99%

“…It has an effective charting structure that exhibits robustness for the skewed distributions. Alemi 1 and several other authors have studied its properties such as Khaliq et al, 10 Lee et al, 12 Torng and Lee, 32 Lee and Torng, 13 Tercero-Gomez et al, 31 and Torng et al, 33 among many others. The control limits for this chart are defined a…”

Section: Tukey's Control Chartmentioning

confidence: 99%

“…Tukey control chart (TCC) was proposed by Alemi 1 and have been studied by several authors. To mention but a few of these: Borckardt et al, 3,4 Torng et al, 33 Lee, 11 Sukparungsee,28,29 Tercero-Gomez et al, 30 Tercero-Gomez et al, 31 Lee and Torng 13 , and Lee et al, 12 Khaliq et al, 10 Mekparyup et al, 14 and Mekparyup et al 15 This study intends to design a new memory structure for TCC under CUSUM setup. The proposed chart will combine the feature of TCC with CUSUM designs.…”

Section: Introductionmentioning

confidence: 99%

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Robust Tukey–CUSUM Control Chart for Process Monitoring

Khaliq

Riaz

2015

Quality & Reliability Eng

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In real world scenarios, we continuously inspect the performing behavior of different features of processes. A change in the process parameters may affect the product quality and therefore needs a timely identification. For this purpose we have designed new memory structure based on Tukey control chart (TCC) under cumulative sum (CUSUM) setup. The proposed chart, namely Tukey‐CUSUM, combines the feature of TCC with CUSUM design for improved detection of shifts for normal and non‐normal data. The performance of the study proposal is evaluated through different measures based on run length including ARL, EQL, PCI and RARL. We have observed that the proposed Tukey‐CUSUM design is quite robust and efficient, especially using asymmetrical decision intervals for different process models. An application example is also provided to illustrate the study proposal. Moreover, sample selection is always of great concern for practitioners so we have included a brief description of the steps for sample selection with reference to process monitoring. Copyright © 2015 John Wiley & Sons, Ltd.

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Performance of Tukey's and Individual/Moving Range Control Charts

Cited by 17 publications

References 31 publications

On designing a sequential based EWMA structure for efficient process monitoring

On designing a sequential based EWMA structure for efficient process monitoring

On the Performance of Median Based Tukey and Tukey-EWMA Charts Under Rational Subgrouping

Robust Tukey–CUSUM Control Chart for Process Monitoring

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