Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm
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) (P...
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MDPI AG
2022-06-01
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| Series: | Polymers |
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| Online Access: | https://www.mdpi.com/2073-4360/14/13/2603 |
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| author | Tej Singh Punyasloka Pattnaik Amit Aherwar Lalit Ranakoti Gábor Dogossy László Lendvai |
| author_facet | Tej Singh Punyasloka Pattnaik Amit Aherwar Lalit Ranakoti Gábor Dogossy László Lendvai |
| author_sort | Tej Singh |
| collection | DOAJ |
| description | 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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| institution | Directory Open Access Journal |
| issn | 2073-4360 |
| language | English |
| last_indexed | 2024-03-09T10:25:51Z |
| publishDate | 2022-06-01 |
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| record_format | Article |
| series | Polymers |
| spelling | doaj.art-0774f66a17fb44cf9c097436655574832023-12-01T21:39:22ZengMDPI AGPolymers2073-43602022-06-011413260310.3390/polym14132603Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making AlgorithmTej Singh0Punyasloka Pattnaik1Amit Aherwar2Lalit Ranakoti3Gábor Dogossy4László Lendvai5Savaria Institute of Technology, Faculty of Informatics, Eötvös Loránd University, 9700 Szombathely, HungaryDepartment of Management Studies, Malaviya National Institute of Technology, Jaipur 302017, IndiaDepartment of Mechanical Engineering, Madhav Institute of Technology and Science, Gwalior 474005, IndiaMechanical Engineering Department, Graphic Era (Deemed to be University), Dehradun 248002, Uttarakhand, IndiaDepartment of Materials Science and Engineering, Széchenyi István University, 9026 Győr, HungaryDepartment of Materials Science and Engineering, Széchenyi István University, 9026 Győr, HungaryBased 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.https://www.mdpi.com/2073-4360/14/13/2603PLA biocompositewood wasterice huskphysicomechanicalwearCRITIC–MABAC |
| spellingShingle | Tej Singh Punyasloka Pattnaik Amit Aherwar Lalit Ranakoti Gábor Dogossy László Lendvai Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm Polymers PLA biocomposite wood waste rice husk physicomechanical wear CRITIC–MABAC |
| title | Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm |
| title_full | Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm |
| title_fullStr | Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm |
| title_full_unstemmed | Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm |
| title_short | Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm |
| title_sort | optimal design of wood rice husk waste filled pla biocomposites using integrated critic mabac based decision making algorithm |
| topic | PLA biocomposite wood waste rice husk physicomechanical wear CRITIC–MABAC |
| url | https://www.mdpi.com/2073-4360/14/13/2603 |
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