{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T21:25:18Z","timestamp":1774387518535,"version":"3.50.1"},"reference-count":21,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,12,7]],"date-time":"2025-12-07T00:00:00Z","timestamp":1765065600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,7]],"date-time":"2025-12-07T00:00:00Z","timestamp":1765065600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Quality &amp;amp; Reliability Eng"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Traditional control charts usually fail to perform well in the case of outliers, or when the mean and variability of a process vary at the same time in quality control. In this paper, a very powerful exponentially weighted moving average (EWMA) control chart using the robust coefficient of variation (CV) has been proposed to overcome these hurdles. Unlike approaches that require data transformation or adaptive tuning, the scale\u2010invariance of the robust CV\u2010statistic can be used to stabilize the proposed RCV\u2010EWMA chart, keeping it sensitive in a polluted data setting. Through extensive Monte Carlo simulations, the capabilities of the chart are analyzed in different conditions of contamination levels and shift level. The total key performance indicators, such as Average Run Length (ARL), Standard Deviation of Run Length (SDRL), and Median Run Length (MRL) are given. The findings show that the suggested chart has good in\u2010control characteristics (ARL\u00a0=\u00a0370) and is a worthwhile chart to detect small\u2010to\u2010still shifts despite up to 25% contamination. Its applicability in practice is also confirmed by a real data application that demonstrates how the chart can determine the abnormalities in the processes and be resistant to outliers. The results place the RCV\u2010EWMA control chart as an effective and dependable modern tool of monitoring processes especially those in very noisy or highly variable conditions.<\/jats:p>","DOI":"10.1002\/qre.70128","type":"journal-article","created":{"date-parts":[[2025,12,7]],"date-time":"2025-12-07T12:30:08Z","timestamp":1765110608000},"page":"1149-1158","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Outlier\u2010Resistant Process Monitoring Using a RCV\u2010Based EWMA Control Chart"],"prefix":"10.1002","volume":"42","author":[{"given":"Hadeel","family":"AlQadi","sequence":"first","affiliation":[{"name":"Department of Mathematics College of Science Jazan University  Jazan Kingdom of Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7980-7414","authenticated-orcid":false,"given":"Amna","family":"Safeer","sequence":"additional","affiliation":[{"name":"University of Lahore  Lahore Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Alquraish","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering College of Engineering University of Bisha  Bisha Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hassan M.","family":"Aljohani","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics College of Science Taif University  Taif Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,12,7]]},"reference":[{"key":"e_1_2_11_2_1","volume-title":"Economic control of quality of manufactured product","author":"Shewhart W. 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