A Proposal of a Method for Ready-Mixed Concrete Quality Assessment Based on Statistical-Fuzzy Approach

Area of Science:

• Materials Science
• Civil Engineering
• Statistical Modeling

Background:

• Current concrete quality control relies on European Standard EN 206, which uses statistical methods.
• Existing statistical criteria, like the 'concrete family' concept, face challenges and ongoing debate regarding their effectiveness.
• There is a need for alternative methods to enhance the reliability of concrete quality assessment.

Purpose of the Study:

• To develop and present a novel approach for concrete quality control and classification.
• To integrate statistical and fuzzy theories to manage both random and information uncertainties in concrete properties.
• To propose an improved method for assessing the conformity of ready-mixed concrete compressive strength.

Main Methods:

• A hybrid approach combining statistical and fuzzy logic theories was developed.
• Membership functions were defined for concrete classes to establish degrees of belonging.
• The method involves assessing concrete compressive strength conformity and classifying batches with fuzzy logic.

Main Results:

• The proposed method effectively represents random and information uncertainty in concrete quality assessment.
• Analysis revealed that the standard classification includes too many overlapping concrete classes.
• A refined classification strategy, focusing on every second class, enhances conformity assessment efficacy.

Conclusions:

• The novel approach offers a more robust method for ready-mixed concrete quality control.
• Fuzzy classification allows for nuanced quality assessment with a degree of certainty.
• The proposed procedure can be effectively employed in the production of ready-mixed concrete.