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Design and Analysis of Universal Exponentially Weighted Moving Average Control Chart

Published: 25 February 2022 Publication History
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  • Abstract

    In order to improve the sensitivity of quality control chart in monitoring small to medium process deviation, a new universal exponentially weighted moving average (UEMWA) control chart for process mean monitoring is proposed. The control chart is a general generalization of EWMA control chart. To optimize the control effect, the smoothing coefficient λ1, λ2, … λs are selected according to the data characteristics; The calculation method of mean and control limit of UEWMA control chart are given, and the average run length (ARL) and standard deviation run length (SDRL) are derived. Finally, the influence of smoothing coefficient on the performance of the UEWMA control chart is studied, and is compared with some existing control charts for monitoring small to moderate shifts. The results show that UEWMA control chart has high flexibility and sensitivity, strong expansibility and excellent control effect by designing the smoothing coefficient according to the data characteristics, and has high research value.

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    ACAI '21: Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence
    December 2021
    699 pages
    ISBN:9781450385053
    DOI:10.1145/3508546
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

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    Published: 25 February 2022

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    Author Tags

    1. Average Run Length
    2. Quality Control Chart
    3. Statistical Process Control
    4. UEWMA

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