Abstract
Polymer composites have emerged as versatile materials with widespread applications across diverse industries due to their unique properties and advantages over conventional materials. This research presents a comprehensive evaluation of the performance of various types of polymer composites, including fiber-reinforced, particulate, Nano, and structural composites, using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The study aims to provide a systematic approach for assessing the suitability of these composites for specific industrial applications based on multiple criteria. The marine industry emerged as a promising sector for the application of fiber-reinforced composites, while the automotive industry presented opportunities for the implementation of particulate composites, capitalizing on their tailorable properties. The TOPSIS method provided a structured framework for decision-makers to evaluate and rank polymer composites based on their performance metrics, underscoring the importance of careful material selection, as each composite type excels in specific criteria and industries. While this study offers valuable insights, it is acknowledged that material selection is a dynamic process influenced by evolving industry demands, technological advancements, and emerging applications. Continuous research and development efforts are necessary to explore new composite materials, optimize existing ones, and refine decision-making methodologies like TOPSIS to adapt to changing requirements.