نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشگاه آزاد اسلامی، واحد اردبیل، گروه مهندسی صنایع، اردبیل، ایران.
2 دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران، گروه مهندسی صنایع، تهران، ایران.
3 مرکز آموزش عالی فنی و مهندسی بوئین زهرا، گروه مهندسی صنایع، قزوین، ایران.
کلیدواژهها
عنوان مقاله English
نویسندگان English
Traditional control charts are based on the basic assumption that process data are sequentially independent of each other and have a normal distribution. However, in many real-world cases, including chemical and continuous processes, this basic assumption does not exist and there is a kind of autocorrelation between the data collected from the process. The use of traditional control charts in autocorrelated processes is unreliable and increases false alarms. One of the methods developed to control autocorrelated processes is to identify the structure of the process time series and use the residual values to control the process. In this paper, a model based on neuro-fuzzy adaptive systems is designed to identify the structure of the time series and use the prediction. Finally, it is AR(2). Also, residual control charts based on this system for second-order autoregressive data using simulated data, the efficiency of the proposed method in the weighted moving average chart and for different degrees of correlation are evaluated, and it is shown that the proposed method has very good efficiency for data with high correlation.
کلیدواژهها English
