A design of experiment application to improve raw materials utilization ratio of polymer concrete composites

Optimization techniques are widely used to save raw materials and to maintain the manufacturing process in optimum conditions. The non-linear programming, which is based on the response surface methodology, has been implemented with the aim of determining the effectiveness of the second optimization application and optimum mix proportions of polymer concrete composites. Polymers, which have got the highest variance on polymer concrete composites' properties such as thermal, mechanical, and workable, have been selected as polypropylene, thermoplastic elastomer, and dimethyl terephthalate that take into account the first multi-response optimization application. The polymer-mixed concrete has got 0.63 W/m*K thermal conductivity value, which is obtained with the two-stage optimization study included in C 25/30 compressive strength class as it has got 28-day compressive strength at 27.27 MPa value. When it is compared to the studies in the literature, it has got the lower thermal conductivity value at the higher compressive strength. The results show that the two-step multi-response optimization methodology is quite effective in producing concrete, which has got the desired properties by using fewer raw materials. These results also indicate that the interaction effect should be taken into consideration.