A study of process monitoring based on inverse Gaussian distribution |
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| Affiliation: | 1. School of Statistics, Zhejiang Gongshang University, Hangzhou, PR China;2. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, PR China;1. Department of Mathematics, Santipur College, West Bengal, India;2. Quantitative Methods and Operations Management Area, Indian Institute of Management, Kozhikode, Kerala, India;1. Zhejiang Gongshang University, China;2. Brunel University, UK;3. Durham University, UK;1. The School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China;2. The School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China;3. The Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong, China;1. Department of Mathematics, Faculty of Basic Science, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran;2. University of Nis, Faculty of Sciences and Mathematics, Visegradska 33, 18000 Nis, Serbia |
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| Abstract: | The inverse Gaussian distribution has considerable applications in describing product life, employee service times, and so on. In this paper, the average run length (ARL) unbiased control charts, which monitor the shape and location parameters of the inverse Gaussian distribution respectively, are proposed when the in-control parameters are known. The effects of parameter estimation on the performance of the proposed control charts are also studied. An ARL-unbiased control chart for the shape parameter with the desired , which takes the variability of the parameter estimate into account, is further developed. The performance of the proposed control charts is investigated in terms of the ARL and standard deviation of the run length. Finally, an example is used to illustrate the proposed control charts. |
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| Keywords: | Inverse Gaussian distribution Average run length Unbiased control chart |
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