Defect Networks and Waste Reduction in Additive Manufacturing

This study addresses a key challenge in Additive Manufacturing (AM): while it promises sustainable production, manufacturing defects often lead to significant material and energy waste. The purpose of this research is to apply the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to identify and map the cause-and-effect relationships among common AM defects. By doing this, the goal is to pinpoint the most influential ‘root’ causes, allowing for more targeted and effective quality improvements. The methodology is based on a qualitative approach using the expert judgment of a panel of six professionals. The DEMATEL analysis successfully sorted the defects into two categories: those that are primary causes and those that are symptoms or effects. The main findings show that contamination is the most significant causal factor, meaning that it strongly influences other defects. In contrast, dimensional inaccuracy is the most affected factor, acting as a symptom of other underlying issues. In conclusion, the study finds that focusing on mitigating root causes like contamination, warping, and porosity is crucial for achieving improvements across the process chain. This framework allows engineers to prioritize quality control efforts on the fundamental problems, rather than on superficial defects, thereby maximizing efficiency and waste reduction. Ultimately, this research provides a clear, actionable framework for improving quality control and promoting more sustainable manufacturing practices.