Singh Tej, Pattnaik Punyasloka, Aherwar Amit, Ranakoti Lalit, Dogossy Gábor, Lendvai László
Savaria Institute of Technology, Faculty of Informatics, Eötvös Loránd University, 9700 Szombathely, Hungary.
Department of Management Studies, Malaviya National Institute of Technology, Jaipur 302017, India.
Polymers (Basel). 2022 Jun 27;14(13):2603. doi: 10.3390/polym14132603.
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.
基于准则间相关性确定准则重要性法(CRITIC)和多属性边界近似区域比较法(MABAC),开发了一种决策算法,用于根据多个相互冲突的属性选择最佳生物复合材料。制备了含0、2.5、5、7.5和10 wt.%总添加剂含量的含木材废料的聚乳酸(PLA)基二元生物复合材料以及含木材废料/稻壳的三元生物复合材料,并对其物理力学性能和磨损性能进行了评估。对于该算法,通过测试考虑了以下性能属性:评估的物理性能(密度、吸水性)、力学性能(拉伸、弯曲、压缩和冲击)以及滑动磨损性能。发现未填充的PLA吸水性和强度性能最高,而对于添加了10 wt.%稻壳/木材废料的PLA生物复合材料,模量性能仍然最高。PLA生物复合材料的密度随稻壳含量增加而增加,随木材废料含量增加而降低。分别记录了含10 wt.%木材废料和含稻壳/木材废料的PLA生物复合材料的最低和最高密度值。添加5 wt.%稻壳/木材废料的PLA生物复合材料磨损最低。实验结果取决于组成,且没有任何明显趋势。因此,在一系列替代方案中优先考虑PLA生物复合材料的性能以选择最佳方案变得具有挑战性。因此,使用一种名为CRITIC-MABAC的决策算法来选择最佳组成。通过使用CRITIC方法分配权重来确定属性的重要性,而使用MABAC方法来评估生物复合材料的完整排名。混合CRITIC-MABAC方法得到的结果表明,添加7.5 wt.%木材废料的PLA生物复合材料具有最佳的物理力学性能和磨损性能。