ESTIMATION MODEL FOR THE PRODUCTION OF RECYCLED AGGREGATES FROM THE CRUSHING OF CONSTRUCTION AND DEMOLITION WASTE

Abstract

Purpose: To propose a mathematical model of the CDW recycling process from the case study of a recycler in the city of Campo Grande/MS to predict the production of recycled aggregates in time and volume, verifying the influence of variables on the process. Theoretical framework: The civil construction sector realized the importance of quantifying the waste generated and planning its reinsertion into the system, however most recycling companies do not have predictability of production of recycled aggregates, compromising their sales and reverse logistics in the sector. Method/design/approach: Data collected in loco were statistically analyzed using multiple linear regression. The statistical model was formed by the dependent variable (volume of mixed recycled aggregate produced - ARM) and independent variables related to the crushing process (operating time and volume of CDW inserted in the crusher). Results and conclusion: The proposed ARM estimation model obtained an adjusted R2 value = 0.9857, indicating that 99% of the mixed recycled aggregate produced can be predicted from the free variables considered. It was also possible to estimate that 18.4% of the volume of RCC inserted in the crusher is lost during the recycling process. Research implications: The method of collecting data in loco at the recycler and the statistical analysis through linear regression can be applied in other RCC recycling companies for predictability of their ARM production. Originality/value: This study provides predictability of recycled aggregate production in recyclers, something pioneering in the RCC area.