Seung Ki Moon

Associate Professor

Nanyang Technological University (NTU)

Singapore

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About

Seung Ki Moon is an Associate Professor at Nanyang Technological University, Singapore. His research focuses on advanced manufacturing technologies, including laser-directed energy deposition, digital twins, and smart factory applications in the automotive industry. He has published multiple articles on topics such as crack detection through deep learning, job shop scheduling, and data-driven frameworks for manufacturing optimization.

Articles (15)

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2022

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2021

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2021

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2021

Collaborators (1)

Kevin Otto

Professor

AUSTRALIA

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Seung Ki Moon

Research Interests

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Articles (15)

Key Enabling Technologies for Smart Factory in Automotive Industry: Status and Applications

In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

A Two-Phase Iterative Mathematical Programming-Based Heuristic for a Flexible Job Shop Scheduling Problem with Transportation

A Two-Phase Iterative Mathematical Programming-Based Heuristic for a Flexible Job Shop Scheduling Problem with Transportation

Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition

How to Use the Levers of Modularity Properly-Linking Modularization to Economic Targets

Laser powder bed fusion for AI assisted digital metal components

A Surrogate Model to Predict Production Performance in Digital Twin-Based Smart Manufacturing

A data-driven framework to predict fused filament fabrication part properties using surrogate models and multi-objective optimisation

In-process adaptive dimension correction strategy for laser aided additive manufacturing using laser line scanning

In-situ acoustic monitoring of direct energy deposition process with deep learning-assisted signal denoising

A data-driven framework to predict fused filament fabrication part properties using surrogate models and multi-objective optimisation

Reviews on Machine Learning Approaches for Process Optimization in Noncontact Direct Ink Writing

Guidelines for 3D printed springs using material extrusion

Modelling the stiffness of plastic springs manufactured via additive manufacturing

Collaborators (1)

Kevin Otto

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