Metal additive manufacturing adoption in SMEs: Technical attributes, challenges, and opportunities

Recent advancements in Metal Additive Manufacturing (MAM) are transforming manufacturing. Most research and market adoption of MAM have focused on Powder Bed Fusion (PBF), with less attention given to Directed Energy Deposition (DED), Binder Jetting (BJ), and Metal Material Extrusion (MEX), which are only now reaching industrial readiness. This increased availability of MAM processes provides SMEs with a wider range of options, opening up new opportunities that were previously inaccessible. However, despite recent technological improvements that broaden potential applications, the suitability of these processes for industrial use by SMEs is not yet well understood. SMEs currently face difficulties in adopting MAM due to complexities and costs. Moreover, existing literature often overlooks the distinct characteristics and needs of SMEs, making it challenging for them to identify the most suitable MAM processes. This study addresses this gap by using a fuzzy logic approach to evaluate the technical characteristics of PBF, DED, BJ, and MEX, focusing on their compatibility with SME requirements. Each process is ranked based on criteria including costs, complexity, energy consumption, mechanical quality, geometrical quality, speed, and market demand. This evaluation is refined through logarithmic normalization and scaling, resulting in a comprehensive scoring system from 1 to 5. Based on these findings, an SME-focused evaluation matrix is proposed to guide SMEs in selecting the most appropriate MAM process for their specific contexts. This matrix promotes informed and effective adoption strategies, supported by practical examples illustrating the application of each MAM process in SME environments. • Technical comparison of four prominent MAM processes: PBF, MEX, BJ, and DED. • Assesses each MAM process compatibility with SMEs operational framework. • Comparative summary of each MAM process strengths and weakness. • Strategic insights for MAM adoption in SMEs with a decision-making evaluation matrix.