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Multi‐objective optimization of part‐ building orientation in stereolithography

Cheng, W., Fuh, J.Y.H., Nee, A.Y.C., Wong, Y.S., Loh, H.T., Miyazawa, T.·1995·Rapid Prototyping Journal

Abstract

In rapid prototyping, such as SLA (stereolithography apparatus) and FDM (fused deposition modelling), the orientation of the part during fabrication is critical as it can affect part accuracy, reduce the production time, and minimize the requirement for supports and, thus, the cost of building the model. Presents a multi‐objective approach for determining the optimal part‐building orientation. Considers different objectives such as part accuracy and building time. Objective functions have been developed based on known sources of errors affecting part accuracy and the requirements of good orientations during the building of a model. The objective functions employ weights assigned to various surface types affecting part accuracy. The primary objective is to attain the specified accuracy achievable with the process. The secondary objective is to minimize the building time. Gives examples to illustrate the algorithm for deriving the optimal orientation which can assure better part quality and higher building efficiency.

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Metadata

Authors
Cheng, W., Fuh, J. Y. H., Nee, A. Y. C., Wong, Y. S., Loh, H. T., & Miyazawa, T.
Venue
Rapid Prototyping Journal
Publisher
Emerald
Published
1995-12-01
Volume
1
Issue
4
Pages
12-23
ISSN
1355-2546 (ISSN-L)
OpenAlex
W2001993296
Cited by
267
References
0
FWCI
9.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multi‐objective optimization of part‐ building orientation in stereolithography. https://app.cochat.ai/papers/10.1108/13552549510104429
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Cheng, W., Fuh, J. Y. H., Nee, A. Y. C., Wong, Y. S., Loh, H. T., & Miyazawa, T. (1995). Multi‐objective optimization of part‐ building orientation in stereolithography. Rapid Prototyping Journal. https://doi.org/10.1108/13552549510104429

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.