Abstract

The widespread use of plastic materials poses significant environmental challenges, which have promoted a growing call for a circular approach to such materials, emphasizing waste reintegration into production. From this perspective, the present study focuses on analyzing a post-industrial recycled stream of chrome-plated automotive scraps composed of acrylonitrile–butadiene–styrene (ABS), polycarbonate (PC), and a commercial PC/ABS blend. The batch-to-batch varying proportions of these constituents make control of the recycled materials’ quality challenging. To address this problem, we formulated an I-optimal mixture design model using the infrared absorbance ratio of selected peaks and Izod impact resistance results for injection-molded samples as inputs to determine the composition of each batch quickly. The two model equations (adjusted R2 > 0.97) obtained, based on cubic expression and regressed from data obtained from 27 mixtures with known compositions, were combined into a single system for the determination of unknown batch compositions. The validation test showed that the models can satisfactorily predict both the infrared and Izod results of blends with known compositions, but in the latter case, the results are less reliable, probably due to specific blend morphological interactions according to specific compositions. The results can improve mechanical recycling methodologies for reintroducing plastic wastes to the market.

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