A Literature Review on the Comparative Analysis of Response Surface Methodology and the Taguchi Method in Concrete Optimization

Abstract

This review paper provides a comprehensive comparison between response surface methodology (RSM) and the Taguchi method (TM) in the context of concrete mix design optimization. Existing studies often examine these methods independently, lacking a systematic comparison focused on their relevance to sustainable and cost-effective concrete production. This paper addresses this gap by analyzing the theoretical principles, practical implementations, and performance outcomes of both methods across a range of case studies. RSM is shown to be effective for modeling complex variable interactions and optimizing multiple responses, making it suitable for high-performance, environmentally conscious designs. Conversely, TM’s emphasis on robustness and minimal experimental runs makes it particularly valuable in large-scale industrial applications, where reduced experimentation lowers material usage and costs. The review highlights how each method supports sustainability RSM through detailed optimization of eco-friendly materials, and TM through resource efficiency. Finally, the paper explores emerging trends, including the integration of RSM and TM with artificial intelligence, to enhance the development of durable, high-strength, and sustainable concrete solutions.