نوع مقاله : مقاله پژوهشی
نویسندگان
1 مدیریت سیستم و بهره وری مهندسی صنایع دانشگاه تربیت مدرس تهران
2 گروه مهندسی صنایع دانشگاه آزاد اسلامی، واحد تهران غرب
کلیدواژهها
عنوان مقاله English
نویسندگان English
Profile monitoring is one of the emerging research areas in the field of statistical process control. A profile describes the relationship between a response variable and one or more independent variables. This relationship, which is typically modeled using a regression equation, may be simple linear, multiple linear, polynomial, or in some cases nonlinear. In order to monitor the quality of a process or product whose quality characteristic is expressed as a profile, multivariate control charts must be used due to the correlation among the regression model parameters. Various types of multivariate control charts can be applied to detect small and large shifts in the process.
A major limitation of multivariate control charts is their inability to identify the specific parameter that goes out of control once a change is detected. In this study, after a multivariate MCUSUM control chart in the MCUSUM–Chi-square method signals a shift in a polynomial profile, a multilayer perceptron neural network is employed to identify the out-of-control parameter. The designed network is trained and then tested, and the results demonstrate its strong performance in identifying the parameter that has shifted out of control.
کلیدواژهها English
