Optimization of Bio-based Polymer Composites Using Grey Relational Analysis (GRA) Method

Bio-based polymer composites comprise polymers sourced from renewable biological origins like plants, algae, or bacteria, combined with reinforcing agents such as natural fibers or nanoparticles. They serve as eco-friendly substitutes for traditional petroleum-based plastics, lessening environmental concerns and lessening dependence on finite fossil resources. Employing bio-based polymers diminishes carbon footprint and decreases reliance on non-renewable materials, fostering a more circular and sustainable economy. Natural fibers like hemp, flax, or kenaf are commonly integrated as reinforcements due to their robustness and biodegradability. These composites are widely applicable across industries like automotive, construction, packaging, and consumer goods. They're utilized in automotive interiors to reduce weight and bolster fuel efficiency, in construction for insulation, panels, and structural elements, and in packaging as biodegradable alternatives to conventional plastics, thus lowering environmental impact. Despite their environmental merits, challenges persist, including optimizing mechanical properties, scaling up production, and managing end-of-life disposal. Ongoing research and innovation endeavor to overcome these hurdles, making bio-based polymer composites more competitive and sustainable on a global scale. Research significance: Bio-based polymer composites research is crucial for tackling environmental issues and pushing forward sustainable materials technology. These composites combine renewable resources with polymer matrices, resulting in less reliance on fossil fuels, decreased carbon footprints, and improved biodegradability compared to traditional options. They offer eco-friendly alternatives in packaging, automotive, construction, and biomedical fields. Delving into their characteristics, manufacturing techniques, and effectiveness allows for the creation of novel materials that lessen environmental harm while meeting diverse needs, thus aiding in building a more sustainable and robust future. Methodology: Grey Relational Analysis (GRA) is a technique employed to examine the correlation among numerous variables, especially in scenarios where data might be scant or uncertain. It gauges the extent of linkage between variables by evaluating their likeness or disparity patterns. GRA empowers decision-makers to pinpoint influential elements, rank actions, and refine procedures in intricate systems like engineering, finance, and management. Through the conversion of qualitative and quantitative data into grey numbers, GRA addresses uncertainties and offers valuable insights for problem-solving, decision-making, and performance improvement across various domains, facilitating more knowledgeable and efficient decision-making strategies. Alternative: PLA (Polylactic Acid) Composites, Hemp Fiber Reinforced Composites, Kenaf Fiber Reinforced Composites, Soy Protein-based Composites, Cellulose Nanocrystal Composites, Bamboo Fiber Reinforced Composites, Corn Starch-based Composites, Algae-based Composites. Evaluation preference: Mechanical Strength, Environmental Impact, Biodegradability, Renewable Resource, Cost-effectiveness. Results: From the result it is seen that Cellulose Nanocrystal Composites is got the first rank whereas is the Corn Starch-based Composites is having the lowest rank