INVENTORY OPTIMIZATION OF THE UNIVERSITY OF BENIN TABLE WATER FACTORY

ABSTRACT

This project focuses on applying Response Surface Methodology (RSM) to optimize inventory at the University of Benin Table Water Factory. The factory's personnel prioritize stability and optimality in the manufacturing process. The project intends to address this issue through the use of mathematical expert models. A design matrix was selected by experimentation, a production process was carried out, and the experimental matrix was built using Design Expert Software. The Response Surface Methodology was used, and the Design Expert application was created on May 18, 2021, with version 13.0.5 64-bit. Statistical diagnostics such as ANOVA, goodness of fit, and surface plots were employed to assess the quadratic models' appropriateness, significance, outliers, and reliability. This software provides a comprehensive range of data analysis tools, allowing users to investigate correlations between variables, create mathematical models, and optimize processes. The results of the RSM model indicated that the second order polynomial was the best model for explaining the interaction between the process parameters and the various responses, and adequacy was seen. The second-order quadratic model showed good coefficient determination (R²). The RSM model showed small mean square errors and projected response values that were close to the observed values, indicating that the model was reliable. Additional investigation revealed that the model is sufficient to optimize the process.