Zobrazeno 1 - 10
of 6 093
pro vyhledávání: '"EWMA"'
Publikováno v:
Jurnal Matematika UNAND, Vol 13, Iss 4, Pp 309-315 (2024)
A control chart is an important statistical technique used to monitor the average quality of a process or dispersion. Shewhart control chart is used to detect larger disturbances in process parameters. Along with the times, a more sensitive univariat
Externí odkaz:
https://doaj.org/article/ede1feaaf8c841fb932ed311c4adb5ca
Autor:
Muhammad Umair Tariq, Muhammad Nouman Qureshi, Osama Abdulaziz Alamri, Soofia Iftikhar, Basim S.O. Alsaedi, Muhammad Hanif
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract In this article, we have proposed memory-type exponential and non-exponential estimators for population variance based on exponentially weighted moving average (EWMA) statistic in stratified sampling. We drive mathematical expressions for me
Externí odkaz:
https://doaj.org/article/508aae419fd74c85a67c15a11128efc3
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract In this study, we suggested an innovative approach by introducing an Adaptive Exponential Weighted Moving Average (AEWMA) control chart utilizing Variable Sample Size (VSS) under Bayesian methodology. The proposed methodology utilized an int
Externí odkaz:
https://doaj.org/article/01702ad0e5054dbfa302816c24516652
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract Pulse rate (PR) and respiratory rate (RR) are two of the most important vital signs. Monitoring them would benefit from easy-to-use technologies. Hence, wearable devices would, in principle, be ideal candidates for such systems. The neck, al
Externí odkaz:
https://doaj.org/article/07b08e6b1d814d879e82008c9afe11a5
Autor:
Seher Malik, Muhammad Hanif, Muhammad Noor-ul-Amin, Imad Khan, Bakhtiyar Ahmad, Abdelgalal O. I. Abaker, Jumanah Ahmed Darwish
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and m
Externí odkaz:
https://doaj.org/article/7000c09b521941fb92a711ee5f2e60cd
Publikováno v:
Journal of Taibah University for Science, Vol 18, Iss 1 (2024)
Control charts play a vital role in process monitoring to ensure the product's desired standards. Due to rapid improvements in data collection methods, multivariate charts are preferred over univariate charts. This paper proposes a bivariate exponent
Externí odkaz:
https://doaj.org/article/8ee6bdf9efe84e51a71e1bd2e2fc3f8c
Autor:
Fatimah A. Almulhim, Seher Malik, Muhammad Hanif, Abaker A. Hassaballa, Muhammad Nabi, Muhammad Usman Aslam
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract The control charts are frequently employed in process monitoring to assess the average and variability of a process, assuming a normal distribution. However, it is worth noting that some process distributions tend to exhibit a positively ske
Externí odkaz:
https://doaj.org/article/50719a02c9594c24b0bd6a94d807672c
Autor:
Sadaf Ayesha, Asma Arshad, Olayan Albalawi, Aiedh Mrisi Alharthi, Muhammad Hanif, Uzma Yasmeen, Muhammad Nabi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract This research presents a new adaptive exponentially weighted moving average control chart, known as the coefficient of variation (CV) EWMA statistic to study the relative process variability. The production process CV monitoring is a long-te
Externí odkaz:
https://doaj.org/article/6cca9657da22441890a7f94b67083a91
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract The study presents a new parameter free adaptive exponentially weighted moving average (AEWMA) control chart tailored for monitoring process dispersion, utilizing an adaptive approach for determining the smoothing constant. This chart is cra
Externí odkaz:
https://doaj.org/article/fac973c294c349e88b47203fe1d4a92e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract This article introduces an adaptive approach within the Bayesian Max-EWMA control chart framework. Various Bayesian loss functions were used to jointly monitor process deviations from the mean and variance of normally distributed processes.
Externí odkaz:
https://doaj.org/article/ff776769b56145ee967765d9f87ca67a