Applications of Factor Analysis and Response Surface Methodology in Chemical Process Optimization Problems

Abstract

Purpose: This work aims to show two applications of Design of Experiments to optimize processes in chemical industries. Theoretical Framework: Among the various mathematical modeling approaches, Design of Experiments (DoE) is widely used for the for the implementation of Quality by Design (QbD) in both research and industry. In QbD, understanding the product and the process is the key factor in ensuring the quality of the end product (Politis et al., 2017). Method: An assessment was made of the best method for creating mathematical models using Pareto graphs, factor graphs, contour graphs, response surface graphs and analysis of variance. Results and Conclusion: In both case studies, the statistical tools proved to be suitable for analyzing the processes and were able to find the optimum process factors to guarantee the best possible response variable. Originality/Value: Design of Experiments (DoE) is the main component of the statistical toolbox to deploy Quality by Design in both research and industrial settings.