Performance of new nonparametric Tukey modified exponentially weighted moving average-Moving average control chart

PLoS One. 2022 Sep 29;17(9):e0275260. doi: 10.1371/journal.pone.0275260. eCollection 2022.

Abstract

Control charts are an amazing and essential statistical process control (SPC) instrument that is commonly used in monitoring systems to detect a specific defect in the procedure. The mixed Tukey modified exponentially weighted moving average - moving average control chart (MMEM-TCC) with motivation detection ability for fewer shifts in the process mean under symmetric and non-symmetric distributions is proposed in this paper. Average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) were used as efficiency criteria in the Monte Carlo simulation, and their efficiency was compared to existing control charts. Furthermore, the expected ARL (EARL) is a method for evaluating the performance of control charts beyond a specific range of shift sizes. The distinguishing feature of the proposed chart is that it performs efficiently in detecting small to moderate shifts. There are applications for PM 2.5 and PM 10 data that demonstrate the performance of the proposed chart.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Monte Carlo Method
  • Motivation*
  • Particulate Matter*

Substances

  • Particulate Matter

Grants and funding

We would like to express our gratitude to Thailand Science Research and Innovation, Ministry of Higher Education, Science, Research for supporting the research fund with Contract no. KMUTNB-FF-65-41. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.