Implementation of Mewma Chart Using Time Series Model for Monitoring the White Cristal Sugar Quality

Abstract

The basic assumption of implementing a control chart is that the observed process values should be normally distributed and independent. However, the production process at the factory is carried out repeatedly with the same machine, so there is a possibility that the observation data is not independent and the resulting control chart becomes inaccurate. Therefore, a time series model approach is needed to create an accurate control chart. This study aims to conduct statistical quality control of white crystal sugar (WCS) production at Madukismo Sugar Factory (MSF) Yogyakarta to maintain product stability and quality according to the standards. MSF performs quality control on WCS products with several quality characteristic variables, including drying shrinkage (%), grain size (mm), polarization, and color of sugar solution (ICUMSA). This study is only limited to the four quality characteristics with research data in the form of secondary data from the MSF QC Laboratory. The data used were WCS quality characteristics from May 9 - July 16, 2022. The four characteristics influence each other, so a MEWMA control chart is used. This study found autocorrelation between observations so that time series modeling was carried out and resulted in VARIMA (1,1,2) as the best time series model. While the implementation of the MEWMA chart shows uncontrollable results with an optimal weighting value λ of 0.8. For process capability, the results show that the process is capable.