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Operations Research, Systems Engineering and Industrial Engineering Commons

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Master's Theses

Additive Manufacturing

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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Minimizing Leakage In Thin Walled Structures Printed Through Selective Laser Melting, Andrew Spencer Yap Jun 2021

Minimizing Leakage In Thin Walled Structures Printed Through Selective Laser Melting, Andrew Spencer Yap

Master's Theses

In this project, the scan strategy of selective laser melting (SLM) for thin walled structures was investigated by changing laser parameters and tool path. Producing thin walled structures is difficult due to defects such as warpage and porosity. A layer on the SLM 125 consists of hatch volume, fill contours, and borders, however, for thin walls, hatch volume can become unavailable, resulting in a solely border/fill contour laser tool path.

Three central composite designs (CCD) were created to optimize the laser parameters of borders to minimize leakage rate and porosity. The two factors changed were border laser power and scanning …


Transfer Learning Approach To Powder Bed Fusion Additive Manufacturing Defect Detection, Michael Wu Jun 2021

Transfer Learning Approach To Powder Bed Fusion Additive Manufacturing Defect Detection, Michael Wu

Master's Theses

Laser powder bed fusion (LPBF) remains a predominately open-loop additive manufacturing process with minimal in-situ quality and process control. Some machines feature optical monitoring systems but lack automated analytical capabilities for real-time defect detection. Recent advances in machine learning (ML) and convolutional neural networks (CNN) present compelling solutions to analyze images in real-time and to develop in-situ monitoring.

Approximately 30,000 selective laser melting (SLM) build images from 31 previous builds are gathered and labeled as either “okay” or “defect”. Then, 14 open-sourced CNN were trained using transfer learning to classify the SLM build images. These models were evaluated by F1 …