ResponseSurfaceMethoden
Response surface methodology (RSM) is a collection of statistical and mathematical techniques for modeling and analyzing problems in which a response of interest is influenced by several quantitative variables and the goal is to optimize that response. It provides a practical framework for exploring complex relationships, identifying interaction effects, and guiding decision making in process development and optimization.
RSM typically involves designing experiments to fit predictive models, most often second-order (quadratic) polynomials. Common designs
Once a reliable model is obtained, the response surface is explored through graphical tools such as contour
Applications of RSM span diverse fields, including chemical engineering, pharmaceuticals, food science, biotechnology, and materials development.
Limitations include reliance on correct experimental design and model specification, potential overfitting with higher-order terms, and