Machines as Craftsmen: Localized Parameter Setting Optimization for Fused Filament Fabrication 3D Printing
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Machines as Craftsmen: Localized Parameter Setting Optimization for Fused Filament Fabrication 3D Printing
Authors
Keywords
-
Journal
Advanced Materials Technologies
Volume 4, Issue 3, Pages 1800653
Publisher
Wiley
Online
2019-01-30
DOI
10.1002/admt.201800653
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing
- (2018) Wentao Yan et al. COMPUTATIONAL MECHANICS
- The barriers to the progression of additive manufacture: Perspectives from UK industry
- (2018) L.E.J. Thomas-Seale et al. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
- [INVITED] Computational intelligence for smart laser materials processing
- (2018) Giuseppe Casalino OPTICS AND LASER TECHNOLOGY
- Expert-guided optimization for 3D printing of soft and liquid materials
- (2018) Sara Abdollahi et al. PLoS One
- A review on quality control in additive manufacturing
- (2018) Hoejin Kim et al. RAPID PROTOTYPING JOURNAL
- A prediction and compensation scheme for in-plane shape deviation of additive manufacturing with information on process parameters
- (2018) Longwei Cheng et al. IISE Transactions
- Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts
- (2017) Mojtaba Khanzadeh et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Part Build Orientation Optimization and Neural Network-Based Geometry Compensation for Additive Manufacturing Process
- (2017) Sushmit Chowdhury et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- A limited-preview filtered B-spline approach to tracking control – With application to vibration-induced error compensation of a 3D printer
- (2017) Molong Duan et al. MECHATRONICS
- Effect of technical parameters on porous structure and strength of 3D printed calcium sulfate prototypes
- (2016) Mitra Asadi-Eydivand et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing
- (2016) Donghong Ding et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS
- (2016) Omar Mohamed et al. Materials
- Process characterisation of 3D-printed FDM components using improved evolutionary computational approach
- (2014) V. Vijayaraghavan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Forecasting process parameters for GMAW-based rapid manufacturing using closed-loop iteration based on neural network
- (2013) Jun Xiong et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Surface roughness prediction in fused deposition modelling by neural networks
- (2013) A. Boschetto et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Dimensional accuracy improvement of FDM square cross-section parts using artificial neural networks and an optimization algorithm
- (2013) A. Noriega et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Study on orthogonal turning of titanium alloys with different coolant supply strategies
- (2008) Z. G. Wang et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started