@ARTICLE{Lemieszewski2026:i9324,
	author="{Lemieszewski, Łukasz and Konstanciak, Anna and Bujak, Dorota}",
	title="{Multicriteria Classification-Based Selection of Natural Fibre–Polypropylene Composite Parameters for Door Panel Thermoforming}",
	year="2026",
	type="artykuł naukowy / referat",
	language="en",
	journal="{Procedia Computer Science}",
	issn="1877-0509",
	volume="292",
	pages="7642--7651",
	doi="10.1016/j.procs.2026.10.335",
	url="https://www.sciencedirect.com/science/article/pii/S1877050926039967?via%3Dihub",
	keywords="thermoforming; automotive; composite materials; natural fibres; multi-criteria decision support (MCDM); ELECTRE TRI",
	abstract="{The paper presents a classification-based approach to selecting composite parameters for thermoformed door panels. The study
covered polypropylene composites reinforced with natural fibres, for which material properties may vary between profiles. The
selection was treated as a multi-criteria problem involving thickness, strength, mass and uncertainty in the input data. Using
ELECTRE TRI, 244 material profiles were assigned to three quality classes in pessimistic, optimistic and virtual variants. The
pessimistic variant assigned most profiles to Class 2, and only about 23% to Class 3. In the optimistic variant, more than 60% of
profiles reached Class 3. The virtual classification revealed a large number of borderline cases, mainly between Classes 2 and 3,
while 52% of profiles kept the same class in all variants. The results show that mechanical properties and areal weight were the
main factors affecting the classification. This approach can support the selection of composite materials when the data are uncertain.}",
}