AUXILIARY INFORMATION BASED GENERALLY WEIGHTED MOVING AVERAGE FOR PROCESS MEAN

Istin Fitriana Aziza (Department of Information Technology, Faculty of Engineering, Bumigora University, Indonesia)
Wirajaya Kusuma (Department of Computer Science, Faculty of Engineering, Bumigora University, Indonesia)
Siti Soraya (Department of Computer Science, Faculty of Engineering, Bumigora University, Indonesia)

Jurnal Statistika Universitas Muhammadiyah Semarang
Vol 11, No 1 (2023): Jurnal Statistika Universitas Muhammadiyah Semarang

The univariate mean process monitoring is only used the information from the study variable. One of the univariate control chart that used to monitor the mean process is GWMA control chart. But, in this research, we need to monitor process mean using the information from the study variable and information on the adding or auxiliary variable. The enhanced control chart in this research named AIB-GWMA control chart. In this research, we also made a comparison between the GWMA and AIB-GWMA to know the sensitivity and effectiveness of  these control chart. The comparison is used to know the effect of the auxiliary variable in process monitoring. The performance of these control chart is evaluated using Average Run Length with help of Monte Carlo simulation. The result of this study is AIB-GWMA has a smaller ARL than the GWMA control chart. It showed that AIB-GWMA is faster to detect a shift in mean process. In further study, we recommended to enhance the performance of the AIB-GWMA by extending the current work to the AIB-MaxGWMA, so it is possible to monitor process mean and variance simultaneously.