Speaker
Description
Abstract: This study aims to investigate the key AI-enabled benefits that enhance the performance of 3D printing technology. Eleven key AI-enabled benefits were identified through extensive literature review and in consultation with expertise in AI, additive manufacturing, industry workers, and higher institution academic staffs. Among the identified enablers, Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was employed to investigate cause and effect AI-enablers that improve the performance of 3D printing performance. The findings of the study investigates five cause enablers that affect six effect factors, Defect detection and quality monitoring (0.232), Process optimization and intelligent control (0.171), Design optimization and manufacturing flexibility (0.841), Predictive maintenance and predictive analytics (0.961), Human computer interaction and intelligent design support (1.173). This study extends the existing research by identifying the causal relationship and interdependencies among key AI- enabled benefits impacting 3D printing technology. The findings of this study provide both theoretical insights into AI-enabled additive manufacturing and practical guidance for researchers, practitioners, and decision-makers seeking to maximize the value of AI adoption in 3D printing systems.
| Topic Area | Design Optimization, Additive Manufacturing Technologies & Applications |
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