Decision making model for optimal reinforcement condition of natural fiber composites - Al-Oqla, Faris M.; S., M. Sapuan; Ishak, M. R.; A. A., Nuraini (The Korean Fiber Society and Springer, 2015)
Natural fiber reinforced polymer composites (NFCs) have recently received much attention as eco-friendly materials due to their desired characteristics such as the high specific properties, low cost, and recyclability features. Achieving an optimal reinforcement condition in NFCs to obtain desired properties is still challenging for both designers and industry. Selecting an appropriate reinforcement condition for natural fiber composites can dramatically enhance achieving better low-cost sustainable design possibilities. Several factors affect acquiring such reinforcement conditions, which make it a matter of multi-criteria decision making (MCDM) problem. This work was able to build and implement DM models in the field of NFCs to optimize the reinforcement conditions for the first time. Here, both Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods were utilized to achieve the optimal reinforcement condition of the date palm/epoxy composite to maximize its overall tensile property considering combined evaluation criteria. Eleven potential reinforcement conditions were evaluated regarding Maximum Tensile Strength (MTS), Maximum Shear Stress (MSS) and Elongation to Break (EL) criteria simultaneously. Experts’ feedback was surveyed to determine both the appropriateness of the evaluation criteria as well as their corresponding weights. MSS has the most contribution in the evaluation process with a weight of 39.0 %, whereas MTS and EL have weights of 31.0 % and 29.0 % respectively. The harmony between AHP and TOPSIS methods in determining the optimal reinforcement condition considering the whole desired evaluation criteria increased its reliability. This work presents a guide and roadmap for implementing proper decision making models in the field of natural fiber composites to optimize their desired characteristics as it is implemented here for the first time.