نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشگاه علم و صنعت، تهران، ایران.
2 دانشگاه تهران, تهران، ایران
3 دانشگاه علم و صنعت، تهران، ایران
کلیدواژهها
عنوان مقاله English
نویسندگان English
Statistical process control is a powerful method for establishing stability and improving process performance by reducing variability. Control charts are among the most widely used tools in statistical process control and play a significant role in enhancing process quality. Recent studies have shown that adaptive control charts—such as those with variable sample sizes, variable sampling intervals, and variable parameters—detect mean shifts faster than standard Shewhart xˉ\bar{x}xˉ control charts. One common assumption in designing a control chart is that observations follow a normal distribution; however, this assumption may not hold in some processes. In this paper, the performance of adaptive control charts under non-normal data is investigated using a simulation approach in MATLAB. It is demonstrated that the variable-parameter control chart outperforms other adaptive xˉ\bar{x}xˉ control charts in detecting small mean shifts under non-normal data, and, most importantly, it reduces the risk of false alarms.
کلیدواژهها English
