This technical paper delves into the intricacies of oil blending optimization within the fast-moving consumer goods (FMCG) industry, focusing on the challenges faced by the client in manual oil blending, and the proposed solution leveraging advanced optimization techniques. The study showcases the development of a robust web-based application, incorporating mixed integer linear programming (MILP) to optimize oil selection and blending, focused on enhancing efficiency, consistency, and overall production excellence. The paper also discusses the application interface, lessons learned, key benefits, and outlines future enhancements involving machine learning for predictive analytics.