Quantifying geometric accuracy with unsupervised machine learning: Using self-organizing map on fused filament fabrication additive manufacturing parts

M Khanzadeh, P Rao… - Journal of …, 2018 - asmedigitalcollection.asme.org
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 …

Image-guided multi-response modeling and characterization of design defects in metal additive manufacturing

F Imani, M Khanzadeh - … Engineering Congress and …, 2021 - asmedigitalcollection.asme.org
The capability of metal additive manufacturing (AM) to produce parts with complex
geometries manifests its potential to revolutionize manufacturing. However, the presence of …

Prediction of fatigue lives in additively manufactured alloys based on the crack-growth concept

A Yadollahi, MJ Mahtabi… - 2017 International …, 2017 - repositories.lib.utexas.edu
This paper aims to predict the fatigue behavior of additively manufactured alloys using crack-
growth data. Among different sources of damage under cyclic loadings, fatigue due to cracks …

[PDF][PDF] Data-driven Service Optimization and Quality Management in Cyber-physical Manufacturing Systems

R Chen - 2021 - etda.libraries.psu.edu
Recent advancements in sensing and communication technology provide unprecedented
opportunities to synchronize the additive manufacturing (AM) machine world and facilities to …

Investigation of the Stability of a Squeak Test Apparatus Based on an Analytical and Finite Element Models

GJ Lee, J Kim - Journal of Vibration and Acoustics, 2018 - asmedigitalcollection.asme.org
Squeak is an unwanted, annoying noise generated by self-excited, friction-induced
vibration. A unique squeak test apparatus that can generate squeak noises consistently was …

[图书][B] Advanced data analytic methodology for quality improvement in additive manufacturing

M Khanzadehdaghalian - 2019 - search.proquest.com
One of the major challenges of implementing additive manufacturing (AM) processes for the
purpose of production is the lack of understanding of its underlying process-structure …

[图书][B] Using Self-organizing Maps for In-situ Monitoring of Melt Pool Thermal Profiles for Porosity Prediction in Laser-based Additive Manufacturing Processes

M Khanzadeh, S Chowdhury, M Marufuzzaman… - 2018 - apps.dtic.mil
The objective of this technical note is to use unsupervised machine learning to characterize
the underlying thermophysical dynamics of laser-based additive manufacturing LBAM …

Mojtaba Khanzadeh

P Rao, R Jafari-Marandi… - Journal of …, 2018 - asmedigitalcollection.asme.org
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 …