A novel approach for optimizing the processing of recycled coarse aggregates. (3rd March 2023)

• Record Type: Journal Article
• Authors: Rakesh Kumar Reddy, R.; Yaragal, Subhash C.
• Is Part Of: Construction & building materials. Volume 368(2023)
• Publication Date: 2023-03-03
• Subjects: Recycled coarse aggregate -- A novel approach -- Ball milling -- Taguchi method -- Grey relational analysis; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2023.130480
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: A novel approach is followed, to produce high-quality recycled coarse aggregates adopting a Ball mill. Taguchi's method of optimisation is adopted, to reduce the number of experiments from 125 to 25, resulting in substantial saving in time and energy. The effect of ball mill processing parameters, on the performance characteristics of recycled coarse aggregates is investigated. The best combination of processing parameters, are achieved for improved mechanical properties of recycled coarse aggregates. Grey relational analysis is performed, to achieve multi-objective optimisation of processing. Abstract: This paper proposes an alternative method for processing the demolition waste into high-quality recycled coarse aggregate using the ball mill. Taguchi's design of experiments based on orthogonal array was used to minimize the number of trials for saving material and time. Experiments were carried out based on L25 orthogonal array with three processing parameters: charge, revolution duration, and aggregate weight with five levels. The revolution speed of the ball mill was set to 60 revolutions per minute. The Taguchi method was then combined with grey relational analysis to achieve the best combination of processing parameters for producing high-quality aggregate. Experimental studies on water absorption, specific gravity, impact value, and abrasion value were used to assess the quality of recycled coarse aggregates. The best combination for each performance characteristic was achieved by using the mean of Signal to Noise ratio graphs. The optimal combination of processing parameter levels to generate superior quality recycled aggregates and the most significant processing parameter were identified based on the response table of means of grey relation grade.