ArticlePolymers2022
Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC-MABAC-Based Decision-Making Algorithm.
Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Mechanically Recycled PLA Films Reinforced with Rice Husk and Carbonized Rice Husk Particles.Polymers · 2026Article
- Multi criteria optimization of FDM process parameters for NylonAF80 filaments using CRITIC CoCoSo and machine learning approaches.Scientific reports · 2026Article
- CRITIC-EDAS Approach for Evaluating Mechanical Properties of Flax/Vetiver/MFF Hybrid Composites.Polymers · 2025Article
- Assessment of the Effect of Multiple Processing of PHBV-Ground Buckwheat Hull Biocomposite on Its Functional and Mechanical Properties.Materials (Basel, Switzerland) · 2024Article
- Sustainable Design and Evaluation of Children's Food Packaging from the Perspective of Buyers' Preferences.Foods (Basel, Switzerland) · 2024Article
- Multi-Attribute Decision Making: Parametric Optimization and Modeling of the FDM Manufacturing Process Using PLA/Wood Biocomposites.Materials (Basel, Switzerland) · 2024Article
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6 authors.
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Abstract
Based on the criteria importance through inter-criteria correlation (CRITIC) and the multi-attributive border approximation area comparison (MABAC), a decision-making algorithm was developed to select the optimal biocomposite material according to several conflicting attributes. Poly(lactic acid) (PLA)-based binary biocomposites containing wood waste and ternary biocomposites containing wood waste/rice husk with an overall additive content of 0, 2.5, 5, 7.5 and 10 wt.% were manufactured and evaluated for physicomechanical and wear properties. For the algorithm, the following performance attributes were considered through testing: the evaluated physical (density, water absorption), mechanical (tensile, flexural, compressive and impact) and sliding wear properties. The water absorption and strength properties were found to be the highest for unfilled PLA, while modulus performance remained the highest for 10 wt.% rice husk/wood-waste-added PLA biocomposites. The density of PLA biocomposites increased as rice husk increased, while it decreased as wood waste increased. The lowest and highest density values were recorded for 10 wt.% wood waste and rice husk/wood-waste-containing PLA biocomposites, respectively. The lowest wear was exhibited by the 5 wt.% rice husk/wood-waste-loaded PLA biocomposite. The experimental results were composition dependent and devoid of any discernible trend. Consequently, prioritizing the performance of PLA biocomposites to choose the best one among a collection of alternatives became challenging. Therefore, a decision-making algorithm, called CRITIC-MABAC, was used to select the optimal composition. The importance of attributes was determined by assigning weight using the CRITIC method, while the MABAC method was employed to assess the complete ranking of the biocomposites. The results achieved from the hybrid CRITIC-MABAC approach demonstrated that the 7.5 wt.% wood-waste-added PLA biocomposite exhibited the optimal physicomechanical and wear properties.
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