Application of multivariate statistical quality control schemes in cement industry

In this thesis, it is aimed to improve product quality by analyzing SiO2, Al2O3 and Fe2O3 components affecting LSF, which is the quality characteristic of clinker in a cement plant, in a multivariate statistical quality control program. Multivariate exponentially weighted moving average (MEWMA) and Hotelling T2 methods were used to determine which quality characteristics caused the out of control situation, i.e. variability. Accordingly, by examining the relationship between the variables in the produced product, it is aimed to increase customer satisfaction through optimization of quality parameters and process control. Minitab program was used for calculations in the study.