Hybrid artificial neural network and genetic algorithm-based grey relational analysis for bi-objective optimization of 3D-printed polylactic acid parts | Synapse
March 3, 2026
Hybrid artificial neural network and genetic algorithm-based grey relational analysis for bi-objective optimization of 3D-printed polylactic acid parts
Key Points
This optimization approach improves the performance of 3D-printed parts, reducing defects while maximizing utility.
Achieving enhanced results, the procedure notably improves dimensional accuracy by 30%, crucial for effective product quality.
Analysis employing a hybrid artificial neural network and genetic algorithm refined the production parameters for polylactic acid parts.
The findings support advanced manufacturing realms, highlighting the need for comprehensive optimization techniques.