Daniel Silva

Associate Professor

Auburn University

United States

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Daniel Silva is an Associate Professor at Auburn University, USA. His research interests include the application of machine learning in manufacturing processes, drone delivery systems, and optimization in additive manufacturing. Recent publications include articles on drone resupply for last-mile delivery, machine learning techniques for laser beam powder bed fusion, and sustainable parcel delivery using drones.

Articles (13)

Year:

2024

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2024

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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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2021

Year:

2021

Collaborators (8)

Alexander Vinel

Auburn University

UNITED STATES

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Shuai Shao

Associate Professor

Auburn University

UNITED STATES

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Saeed Maghsoodloo

Professor Emeritus

Auburn University

UNITED STATES

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Juan Carlos Pina Pardo

Massachusetts Institute of Technology

UNITED STATES

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Alice E. Smith

Auburn University

UNITED STATES

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Jia Liu

Assistant Professor

Auburn University

UNITED STATES

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Oguz Toragay

Assistant Professor

Lawrence Technological University

UNITED STATES

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Kayla Corriveau

Assistant Professor

Auburn University College of Veterinary Medicine

UNITED STATES

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Daniel Silva

Research Interests

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Contact this professor

About

Articles (13)

Fleet resupply by drones for last-mile delivery

Dynamic vehicle routing problem with drone resupply for same-day delivery

Ti-6Al-4V powder reuse in laser powder bed fusion (L-PBF): The effect on porosity, microstructure, and mechanical behavior

Machine learning augmented X-ray computed tomography features for volumetric defect classification in laser beam powder bed fusion

Sustainable last mile parcel delivery and return service using drones

The exponentially-weighted control charts for geometrically moving averages

A further note on the exponentially weighted moving average control charts for monitoring gradual shifts in a process mean

Bending properties of additively manufactured commercially pure titanium (CPTi) limited contact dynamic compression plate (LC-DCP) constructs: Effect of surface treatment

Exact global optimization of frame structures for additive manufacturing

On-Demand Public Transit: A Markovian Continuous Approximation Model

A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing

Fast heuristic approach for control of complex authentication systems

Surface roughness parameter and modeling for fatigue behavior of additive manufactured parts: A non-destructive data-driven approach

Collaborators (8)

Alexander Vinel

Shuai Shao

Saeed Maghsoodloo

Juan Carlos Pina Pardo

Alice E. Smith

Jia Liu

Oguz Toragay

Kayla Corriveau

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