نوع مقاله : پژوهشی
نویسندگان
1 دانشکده فنی و مهندسی-دانشگاه تربیت مدرس
2 گروه مهندسی صنایع-دانشگاه شاهد
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Profile monitoring is one of the new research areas in statistical process control in which the quality of a process or product can be characterized by a relationship between a response variable and one or more explanatory variables. This relationship, which can be linear, nonlinear, or even a complicated model, is referred to as profile. Most of the control charts in profile monitoring literature are designed on the basis of fixed sampling rate. In other words in the traditional control charts, samples with fixed size are taken at fixed intervals. Despite many advantages, these charts are not sensitive enough to detect small even moderate shifts. Consequently, in order to improve the performance of the conventional fixed sampling rate control charts, adaptive control charts have been proposed. When adaptive control charts are applied, one or more design parameters vary during the process based on recent data obtained from the process. As a result the process changes could be detected more quickly.looseness=1 In this paper four adaptive control charts are considered for monitoring simple linear profiles in phase II based on the multivariate T2 control chart. These charts include variable sample size (VSS), variable sampling interval (VSI), variable sample size and sampling interval (VSSI) and variable sampling interval with sampling at fixed times (VSIFT) T2 charts. The performance of the proposed charts is compared in terms of the average time to signal (ATS). To compute the ATS, the Markov chain approach is used. Numerical examples show that adding adaptive features to traditional control charts increase the power of T2 control chart in detecting the shifts in the parameters of the simple linear profiles. Among the mentioned adaptive charts, VSSI T2 chart is the most efficient one to detect shifts in slope and intercept while VSI and VSIFT T2 charts have the best ability for detecting shifts in standard deviation.
کلیدواژهها [English]
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