In-plane shape-deviation modeling and compensation for fused deposition modeling processes
Abstract
Additive manufacturing (AM) or 3-D printing refers to a new class of technologies that actively construct products directly from any 3-D digital model. In the future, the broader applications of AM will require a cost reduction of AM machines. Currently, the products fabricated by low-end machines, such as those fabricated using fused deposition modeling (FDM) processes, suffer from the issue of low dimensional accuracy due to multiple error sources. To properly manage error sources for improved prevision, this paper proposes a novel strategy for error compensation in the FDM processes. First, we consecutively attribute the dimensional inaccuracy to two major error sources that affect the geometric shape of the product: 1) positioning error of the extruder and 2) shape deformation induced by processing error, including material phase change and other variations that occur. The extruder positioning error is characterized by a Kriging model, while the modeling of shape deformation due to processing error follows the method developed by Huang et al. Second, using error equivalence concept, we transform the positioning error into the equivalent amount of design input error. Finally, we adjust the design to compensate for the overall shape deviation. To validate this strategy, we conduct a designed experiment for the shape deviation prediction and the compensation. The experimental results successfully demonstrate the effectiveness of the proposed three-step strategy to manage multiple error sources in the FDM processes.
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Powder-based processes are prone to issues of porosity, lack-of-fusion, balling, and cracks, while geometry deviation, shape shrinkage, surface imperfections, layer misalignment, and adhesion issues are the main concerns in the FFF processes.
“Powder-based processes are prone to issues of porosity, lackof-fusion, balling, and cracks [428,430,431], while geometry deviation, shape shrinkage, surface imperfections, layer misalignment, and adhesion issues [432-435] are the main concerns in the FFF processes.”
From A comprehensive review of lunar-based manufacturing and construction (2024) · cites this paper as [433]
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- Authors
- Wang, A., Song, S., Huang, Q., & Tsung, F.
- Affiliations
- Hong Kong University of Science and Technology (HK)
- University of Southern California (US)
- Venue
- IEEE Transactions on Automation Science and Engineering
- Published
- 2017-04
- Volume
- 14
- Issue
- 2
- Pages
- 968-976
- ISSN
- 1545-5955 (ISSN-L)
- 1558-3783
- OpenAlex
- W2345286239
- Cited by
- 79
- References
- 31
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 6 · 2023: 6 · 2022: 7 · 2021: 10 · 2020: 13 · 2019: 5 · 2018: 11 · 2017: 6 · 2016: 3
- FWCI
- 7.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Automation Science and Engineering (publishedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- U.S. National Science Foundation (CMMI-1333550)
- Research Grants Council
- General Research Fund
- University Grants Committee (619612, 619913, SSTSP FP302)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Measurement and Metrology Techniques
- Physical Sciences › Engineering › Mechanical Engineering › Additive Manufacturing Materials and Processes
- Keywords
- fused deposition modeling, dimensional accuracy, shape deviation, error compensation, shape deformation, Kriging model, additive manufacturing
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