MATHEMATICAL JUSTIFICATION OF FILLED POLYPROPYLENE COMPOSITE FORMULATIONS FOR AUTOMOTIVE PART MANUFACTURING USING RSM–GRA ANALYSIS
DOI:
https://doi.org/10.30857/2786-5371.2026.3.8Keywords:
multi-criteria optimization, ranking, polypropylene, calcite concentrate, calcium carbonate, polyolefin elastomer, RSM, GRA, impact strength, melt flow indexAbstract
Purpose. The purpose of the study is to assess the applicability of a combined response surface methodology (RSM) and grey relational analysis (GRA) approach to the selection of filled polypropylene composite formulations for automotive part manufacturing, which can be selected for further experimental verification with regard to different engineering priorities.
Methodology. The mathematical modelling was performed retrospectively using experimental data obtained in previous studies by the authors. The contents of calcite concentrate and polyolefin elastomer were used as independent variables. Tensile strength, melt flow index and impact strength were selected as the responses. Second-order regression models were developed based on the experimental dataset using the least squares method. Based on the obtained RSM models a series of calculated composition variants of polymer composites was generated and GRA ranking was performed for these variants under different scenarios.
Findings. The use of GRA enabled responses with different dimensions to be transformed into a single dimensionless scale and allowed the same set of calculated composition variants to be compared under different weighting scenarios. GRA was performed under different scenarios corresponding to engineering priorities. As a result, a structured ranked list of competitive composition variants of polymer composites was obtained, which makes it possible to select formulations with balanced properties.
Originality. A scheme combining RSM and GRA methods for multi-criteria analysis of the composition of filled polypropylene composites based on a retrospective experimental dataset is proposed.
Practical value. The proposed approach can be used for the preliminary selection of filled polypropylene composite formulations for automotive part manufacturing prior to additional experimental verification. Scenario-based GRA ranking helps reduce the number of compositions requiring verification and supports the evaluation of compromise between tensile strength, melt flow index and impact strength.
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