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RISQuantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Although complex geometries are attainable with additive manufacturing (AM), a major barrier preventing its use in mission-critical applications is the lack of geometric accuracy of AM parts. Existing geometric dimensioning ...
Layer-Wise Modeling and Anomaly Detection for Laser-Based Additive Manufacturing
Publisher: American Society of Mechanical Engineers (ASME)
Abstract: Additive manufacturing (AM) is a novel fabrication technique capable of producing highly complex parts. Nevertheless, a major challenge is the quality assurance of the AM fabricated parts. While there are several ways of ...
Multi-Objective Accelerated Process Optimization of Part Geometric Accuracy in Additive Manufacturing
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The goal of this work is to minimize geometric inaccuracies in parts printed using a fused filament fabrication (FFF) additive manufacturing (AM) process by optimizing the process parameters settings. This is a challenging ...
Quantifying Parameter Sensitivity and Uncertainty for Interatomic Potential Design: Application to Saturated Hydrocarbons
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The research objective herein is to understand the relationships between the interatomic potential parameters and properties used in the training and validation of potentials, specifically using a recently developed modified ...