نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشگاه آزاد اسلامی واحد پرند, ایران.
2 دانشگاه علم و صنعت, ایران.
کلیدواژهها
عنوان مقاله English
نویسندگان English
As is well known, data obtained from real-world processes are typically autocorrelated, and monitoring such processes requires accounting for this autocorrelation. The control charts developed so far for monitoring the defective proportion (p) are generally based on the assumption that binary observations are independent, which ignores the inherent correlation in the data.
In this paper, a cumulative sum (CUSUM) control chart is proposed that incorporates the autocorrelation between binary observations using a first-order two-state Markov chain model. Furthermore, using the Average Number of Observations to Signal (ANOS) index, it is shown that under 100% inspection conditions, the proposed chart performs better than the Bernoulli CUSUM chart—which assumes independent observations—and, in other words, detects increases in p more quickly.
کلیدواژهها English
