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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/155775


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/155775


    Title: Pollution concentration monitoring using a new Birnbaum-Saunders control chart
    Authors: 楊素芬
    Yang, Su-Fen;Lu, Ming-Che
    Contributors: 統計系
    Keywords: air pollution monitoring;exponentially weighted moving average control chart;fatigue life;statistical process control
    Date: 2024-11
    Issue Date: 2025-02-24 15:36:52 (UTC+8)
    Abstract: Air pollution monitoring is an important issue in environmental science. The Birnbaum–Saunders (BS) distribution, originally applied to describe product failure time distribution to fatigue failures and general random wear failures, is also well to describe the pollutant concentration data due to accumulations of various pollutants in the air over time. Sulfur dioxide (SO2) is a critical factor in air pollution. Hence, it is important to monitor its concentration variation for air pollution prevention. Due to the complexity of its distribution form, there is no reliable and easy-to-use control chart for monitoring pollutant concentrations based on the BS distribution. We found that the SO2 concentration data follows the BS distribution. In this study, we propose a new median control chart based on the exact sampling distribution of the monitoring statistic to detect shifts in the median of BS distribution. Thus, given the false alarm rate, the control limits for such control charts can be obtained precisely satisfying a preset in-control average run length using Monte Carlo simulations. The out-of-control average run lengths are calculated by simulation to evaluate the detection performance of the proposed chart when the median shifts occur. We further compare the detection performance of the proposed chart and those of the existing control charts based on asymptotic sampling distributions. In order to improve the detection ability of the proposed chart for small median shifts, an exponentially weighted moving average (EWMA) control chart is constructed. The results of numerical analyses demonstrated that the proposed EWMA chart performs much better than all existing control charts for monitoring the median of BS distribution. Finally, the proposed control charts are applied to monitor the median of SO2 concentrations for air pollution control, showing that both charts can effectively detect a shift in the median of SO2 concentrations. The proposed EWMA control chart even detects out a small shift in the median of SO2 concentrations. The results provide a continuous monitoring solution for air pollution prevention.
    Relation: Quality and Reliability Engineering International, Vol.40, No.7, pp.3913-3933
    Data Type: article
    DOI 連結: https://doi.org/10.1002/qre.3608
    DOI: 10.1002/qre.3608
    Appears in Collections:[統計學系] 期刊論文

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