Abstract

In this study, a robust control chart as an alternative to the Tukey's control chart (TCC) based on the modified trimmed standard deviation (MTSD), namely MTSD-TCC, is proposed. The performance of the proposed and the competing Tukey's control chart (TCC) is measured using different length properties such as average run length (ARL), standard deviation of run length (SDRL), and median run length (MDRL). Also, the study covered normal and contaminated cases. We have observed that the proposed robust control chart (MTSD-TCC) is quite efficient at detecting process shifts. Also, it is evident from the simulation results that the proposed robust control chart (MTSD-TCC) offers superior detection ability for different trimming levels as compared to the Tukey's control chart (TCC) under the contaminated process setups. As a result, it is recommended to use the proposed robust control chart (MTSD-TCC) for process monitoring. An application numerical example using real-life data is provided to illustrate the implementation of the proposed robust control chart (MTSD-TCC) which also supported the results of the simulation study to some extent.

Highlights

  • Statistical process control (SPC), a compendium of valuable techniques for process monitoring, is widely used for checking, measuring, controlling and improving the quality of production in many fields of applications, including industry, manufacturing, finance, economics, epidemiology, health care, environmental sciences among others (Sukparungsee, 2013)

  • This section deals with the comparative performance of Modified Trimmed Standard Deviation (MTSD)-Tukey’s control chart (TCC) versus TCC using average run length (ARL), standard deviation of run length (SDRL) and median run length (MDRL) results given in Tables [3,4,5] respectively

  • General Comments: MTSD-TCC has better run length properties (ARL, MDRL, SDRL, Extra Quadratic Loss (EQL)) as compared to TCC for all trimming levels (5%, 10%, 20%, 30% and 40%), especially for δ ≤ 1

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Summary

Introduction

Statistical process control (SPC), a compendium of valuable techniques for process monitoring, is widely used for checking, measuring, controlling and improving the quality of production in many fields of applications, including industry, manufacturing, finance, economics, epidemiology, health care, environmental sciences among others (Sukparungsee, 2013). A few studies have attempted to modify TCC based on robust estimators; Mekparyup et al (2014) worked with modification to inter-quartile range (IQR) to set the symmetrical and asymmetrical control limits coefficients of TCC and concluded that the ATCC is more efficient to detect the process when it is in-control. Deviation (MTSD) denoted by sT* which was introduced by Sindhumol et al (2016) is used in this study as an alternative to the IQR and, the authors deemed that it would be interesting to construct a modified Tukey’s control chart (TCC) based on MTSD ( sT* ). This modified control chart is named in this paper as MTSD-TCC.

The Robust Estimators of Process Variability
Performance Measures
Assessment Criterion
Performance Evaluations and Comparisons
Run Length Performance of MTSD-TCC Versus TCC
Effects of Sample Size on ARL Profile of MTSD-TCC Versus TCC
Contamination Effect on MTSD-TCC and TCC
Findings
An Application Using Real Data
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