Optimization of mixture proportions by statistical experimental design using response surface method - A review

A comprehensive review of the statistical experimental optimization problem concerning the mixture design of various cement-based materials is presented herein. This review summarizes and discusses over 80 applications of optimum design regarding the basic test information under response surface method (RSM), including influence factor and corresponding response, statistical method, and coefficient of determination. The statistical experimental design reported in previous studies has shown that RSM is a sequential procedure to provide a suitable approximation for the mixture optimization. Then, linear, quadratic and interactive relationships of the statistical model can be evaluated available. Especially, the multi-objective optimization issues with multiple or competing performance requirements for various cement-based materials have also been reported, by considering fluidity, strength development, environmental impact, cost and durability. Overall, the results from existing publications have demonstrated that statistical inference and analysis of variance (ANOVA) are suitable for mix proportion design and process optimization of cement-based materials. The W/B ratio and mixture components are the prevalent factors in experimental design optimization, and then the fluidity and strength as the most popularly used response. Thus, theoretical optimum mixture proportioning can be used to predict valuable fresh and hardened properties. Finally, a critical discussion of the selection of design strategy, independent factors and their responses, and the experimental region involved in statistical experimental design, is provided. Based on this review, we conclude that the multi-objective optimization approaches need a further systematic study, and further studies of sustainable concrete optimization are needed by comparing the different chemical composition and particle characteristics.