Assessing the effectiveness of the ZICOMP-Shewhart control chart for monitoring zero-inflated processes

Aqsa Sattar, Muhammad Ali Raza, Laila A. Al‐Essa, Hanen Louati, Mohammed M. A. Almazah, Arailym Zaitzhanova

Scientific Reports, 2026

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1038/s41598-025-32581-y
Data confidence 70 medium
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Abstract

The zero-inflated Conway-Maxwell Poisson (ZICOMP) distribution models count data with many zero observations. This distribution assumes that zero observations occur with probability [Formula: see text], and the count of nonconformities in a product unit follows the Conway-Maxwell Poisson (COMP) distribution with parameters [Formula: see text] and [Formula: see text]. The ZICOMP distribution is flexible in accommodating various dispersion patterns in zero-inflated (ZI) datasets and effectively models over-dispersed, under-dispersed, or equi-dispersed data. This study provides an in-depth analysis of the ZICOMP-Shewhart control chart, as discussed by Alevizakos and Tasias1, to assess its effectiveness in detecting shifts in the rate parameter ([Formula: see text]) while assuming constant dispersion and zero-inflation parameters. The key focus of this research is the selection of the limit coefficient to achieve the desired in-control (IC) average run length and assessing Type II error sensitivity for improved out-of-control (OOC) detection. Through extensive simulations, we examine the comparative efficiency of the ZICOMP-Shewhart chart against the traditional Shewhart chart under the COMP distribution. Additionally, the effectiveness of the ZICOMP-Shewhart control chart is demonstrated through a real-life example.