Shooting-inspired fuzzy logic expert system for ready-mixed concrete plants

Abstract

With a goal of reducing the overall production process variability of Ready-mixed concrete (RMC) and decreasing production costs, a fuzzy logic-based expert system was developed. Inspired by shooting sports, the system guides the plant chief technician by recommending the actions to be taken to reduce variability. Such guidance is based on the evaluation of the compressive strength and coefficient of variation results from the samples molded by those responsible for testing concrete. The system was tested in a RMC plant with monthly production of ≈ 3300 m 3 . The results indicate that no major interventions are necessary for the investigated plant; however, training is likely recommended for some of the staff so as to attain a lower overall variability. These conclusions are in agreement with the technician's interpretation, proving that the system is satisfactory for application in the process. Additionally, a cost analysis was performed, and the results show that a potential reduction of 5.6 % in the monthly production cost can be reached. This represents an attractive reduction since the RMC profit margin is about 8.0 %.

Estimation of Ablation Depth in Concrete Slab Under Reactor During Nuclear Accident

“…The fuzzy logic, beside the other artificial intelligence techniques, such as the artificial neural network [18], has already proved itself as a very effective tool for solution of various civil engineering problems when there were no exact experimental data, the data were limited, or the historical data were extended to the current situation. Examples of these applications can be found in [7] where the risk of liquefaction of sandy soils due to earthquake was assessed, in [2] where the poorest link in the ready-mixed concrete distribution was identified, in [11] where the potential excessive deformation of a diaphragm wall was evaluated based on the past experience, in [17] where the hydration of concrete and the subsequent risk of cracking was modeled, or in [10,16] where the effect of winter road maintenance and cyclic loading on stiffness of concrete in compression was modeled, to name just few examples. Therefore, the trends identified in the graphs, equations and in the discussions in [1, 3-6, 8, 9, 12-15] were expressed using the fuzzy logic.…”

Finite Element Simulation of Hydration Heat Using Fuzzy Logic Model of Hydration

“…It is decided to use three-dimensional finite element simulation to reach the accurate solution. A fuzzy-logic model of the degree of hydration is used for defining the degree of hydration dependent on time and temperature, as the fuzzy logic proofed potential on several other occasions, for example for modeling of concrete plant efficiency, [2], degradation of concrete under the combined effect, [3], or already for hydration heat modeling, [4].…”