Response Surface Methodology in Experimental Design: A Comprehensive Review of Its Development, Applications, and Analytical Techniques

Qianyong Zhang; Chun Zhao; Zhirao Yin; Rui Sun; Yongjian Zhao; Nan Yang; Shaojun Zhang

doi:10.54691/sa0adp44

Authors

Qianyong Zhang
Chun Zhao
Zhirao Yin
Rui Sun
Yongjian Zhao
Nan Yang
Shaojun Zhang

DOI:

https://doi.org/10.54691/sa0adp44

Keywords:

Response Surface Methodology; Experimental Design; Optimization; Central Composite Design.

Abstract

Response Surface Methodology (RSM) is a widely used statistical technique in experimental design and optimization, valued for its ability to model complex systems with interacting variables. This paper provides a comprehensive review of RSM, tracing its historical development and exploring its diverse applications in fields such as engineering, biotechnology, and environmental studies. Key analytical approaches, including Central Composite Design and Box-Behnken Design, are discussed in the context of their effectiveness for different experimental scenarios. Advantages such as cost-effectiveness and predictive capability are highlighted, alongside limitations like reduced efficiency in high-dimensional systems and potential inaccuracies in highly non-linear responses. The paper concludes by identifying opportunities for future research, including integrating RSM with advanced computational methods. This review aims to offer insights into the methodological framework and potential innovations for researchers employing RSM in experimental design.

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