Chandrasekar Raja
The selection of appropriate raw materials is crucial for improving the efficiency and cost- effectiveness of pyrolysis processes. In this study, we utilized the Evaluation based on Distance from Average Solution (EDAS) method, a multi-criteria decision-making approach, to comprehensively evaluate the suitability of different biomass sources for pyrolysis. We examined five specific bioresources—sunflower shells, hardwood, wheat straw, sugarcane bagasse, and corn cobs—based on key criteria: cellulose, hemicellulose, volatile matter, moisture content, and ash content. Utilizing the EDAS technique involved constructing a decision matrix, computing positive and negative distance metrics from the average solution, and ultimately determining a final evaluation score (ASi) for each bioresource. The analysis unveiled hardwood as the most preferable feedstock, achieving the highest ASi of 0.93866, closely followed by sugarcane bagasse with an ASi of 0.93765. These bioresources showcased superior performance across numerous criteria, including elevated cellulose and volatile matter contents, coupled with low moisture and ash levels. Sunflower shells and corn cobs secured the third and fourth positions, respectively, displaying moderate positive deviations from the average solution. Conversely, wheat straw ranked at the bottom, registering an ASi of 0.00000, indicative of its limited suitability as a pyrolysis feedstock due to its high moisture content and relatively low volatile matter content. The EDAS method&39;s capability to account for both positive and negative deviations from the average solution enabled a balanced evaluation, revealing the strengths and weaknesses of each biomass source. This methodology facilitated a deeper understanding of the trade-offs involved, aiding decision-making in selecting suitable feedstocks tailored to specific process needs and desired product attributes. The research highlighted the effectiveness of the EDAS method in assessing material selection for pyrolysis, offering a structured and transparent approach to tackling complex multi-criteria decision- making challenges. By incorporating relevant factors and capitalizing on the method&39;s simplicity and computational efficiency, researchers and industry experts can make well-informed choices to optimize pyrolysis processes and advance the sustainable conversion of biomass resources into valuable products.