To increase competitiveness and cost reduction, the concrete industry is constantly developing solutions to optimize their production process and ensure quality. Moreover, considering short deadlines, tight budgets, and the industry's trends of accelerating construction processes, optimization is therefore becoming essential. However, this is not easy to achieve because it involves analyses of processes and materials that are imprecise, non-linear, and time-variant. Hence, the use of analytical equations for optimization purposes is sometimes cumbersome. Although processes are complex in their nature, human operators can usually control them through knowledge-based linguistic rules. Therefore, fuzzy logic arises as a powerful tool for aiding expert systems, since it allows dealing with verbal expressions to simulate human reasoning, reducing complexity while maintaining credibility. The use of fuzzy logic is within the scope of this work. The main goal is to design advanced fuzzy logic-based expert systems focused on concrete technology applications. In particular, the systems focus on the Ready-mixed concrete production process, precast concrete quality control, and experimental-based material modeling. Moreover, the objective of this work also includes the development of innovative approaches and engineering tools that are designed to support the expert systems. Applications of the proposed expert systems are presented. The obtained results indicate that the developed systems allow for optimization in the studied processes, leading to cost reduction. In addition, fuzzy logic proved to be a robust tool that allows for including vague ideas in expert systems; as a result, less complex solutions were achieved without necessarily reducing the credibility of the results.