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Identifying the time of a step change in bivariate binomial processes

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Abstract

Control charts are one of the most applicable tools in statistical process control. The time in which the control chart signals an out-of-control alarm is not the actual time in which the change has occurred. In other words, control chart detects the change with some delay. The actual time of the change taking place is referred to as change point. Change point estimation facilitates the identification of cause(s) of change and reduces the corresponding time and cost. There are many processes in which the control of two correlated attributes is necessary. Multiattribute control charts are used in such cases due to correlation between attributes. In this paper, two methods including maximum likelihood estimation (MLE) and clustering are proposed for estimating change point in nonconformity ratio vector of a process with bivariate binomial distribution. Also, the performances of these methods are evaluated and compared by Monte Carlo simulations.

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Authors and Affiliations

  1. Industrial Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran

    Amirhossein Amiri, Saeed Allahyari & Fatemeh Sogandi

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  1. Amirhossein Amiri
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  2. Saeed Allahyari
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  3. Fatemeh Sogandi
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Correspondence to Amirhossein Amiri.

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Amiri, A., Allahyari, S. & Sogandi, F. Identifying the time of a step change in bivariate binomial processes. Int J Adv Manuf Technol 77, 225–233 (2015). https://doi.org/10.1007/s00170-014-6418-y

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  • DOI: https://doi.org/10.1007/s00170-014-6418-y

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