Minimizing environmental footprint in FDM additive manufacturing: Analyzing process efficiency through advanced optimization techniques

Considering the high energy and material consumption, the environmental impact of additive manufacturing through FDM has faced significant criticism. For a more sustainable production process, industries require efficient optimization of the FDM process to lower environmental impact while retaining process efficiency. This study utilizes advanced multi-criteria decision-making (MCDM) methodologies, specifically the fuzzy analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS), to evaluate and enhance the environmental performance of FDM. Focusing on standard thermoplastic materials (e.g., PLA and PETG) and applications such as functional prototyping, we optimize key parameters layer height, print speed, and infill density to achieve reductions in energy usage (20%) and material waste (15%) compared to baseline FDM practices. These findings not only highlight a pathway toward greener FDM processes but also lay the groundwork for future research in sustainable optimization frameworks, applicable to other additive manufacturing methods and materials.