INVENTORY OPTIMIZATION OF THE UNIVERSITY OF BENIN TABLE WATER FACTORY

ABSTRACT

In the pursuit of enhancing the inventory management practices at the University of Benin Table Water Factory, this research embarked on a journey to optimize the response through a systematic application of Central Composite Design (CCD) and Response Surface Methodology (RSM). The ultimate goal was to find the optimal combination of factor levels that would lead to improved inventory efficiency, reduced costs, and enhanced customer satisfaction. Through a well-structured research methodology, the study delved into the intricacies of the factory's inventory management process. The research problem of suboptimal inventory levels and inefficient practices served as the driving force behind this endeavor. Challenges of excess inventory, stockouts, and outdated decision-making strategies necessitated a transformative approach that embraced data-driven insights and advanced optimization techniques. The CCD experimental design allowed for a comprehensive exploration of various factors influencing inventory optimization. Factor identification, selection of levels, and execution of experiments facilitated a detailed understanding of the intricate relationships between factors and their impact on the desired response. The resulting response surface model provided valuable insights into the factors that had the most significant influence on inventory management.