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Record W4231467787 · doi:10.1149/ma2020-01211284mtgabs

Fabrication of Low-Cost Molds for Manufacturing of High Precise Micro Parts By Electroforming

2020· article· en· W4231467787 on OpenAlexaff
Sayed MohammadAli Aghili, Zhaohan Zheng, Rolf Wüthrich

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsElectroformingFabricationLIGAMicrofabricationMolding (decorative)Materials science3D printingNanotechnologyPhotolithographyComposite materialLayer (electronics)

Abstract

fetched live from OpenAlex

Technology push and market pull lead to an intensification of micro molding processes development which have variety of applications such as micro-gears, micro-pumps, micro optical components, connectors, wave-guides, optical gratings and mass production of polymer micro parts and structures with high aspect ratios [1][2]. In these recent years, broad range of microfabrication technologies including, laser ablation, photolithography, lithography, electroplating, and molding (LIGA), chemical etching have been developed [3]. Most of these technologies have been developed for mass production. Manufacturing industry is however more and more facing the problem of producing personalized parts, resulting in low volume production. New technologies to allow economical fabrication of low volume micro-parts become a need. In this work, to address the issue of manufacturing high precise 3D micro-metallic parts for small series, we propose 3D printing of micro-molds followed by electroforming to produce micro 3D metallic parts. Advances in additive manufacturing allow for economical and costly manufacturing of polymer micro-molds with high-resolution to fabricate three-dimensional structures which enables the fabrication of personalized microproducts with virtually any shape. This combination of processes can highly decrease fabrication costs for low volume production. The process starts by printing a mold in Acrylonitrile Butadiene Styrene (ABS). A conductive layer must be included to allow subsequent copper electroforming. Dissolving the ABS part allows in the last step the creation of ultra-light micro-metal parts with a high-quality surface finish and accurate dimensions. Several applications can benefit from a technology able to produce micro dimensional metal parts with thin features like watch industry, medical devices [3] or aerospace and space applications where weight and fraction play key factor. To include the conductive layer into the mold, a two steps process was developed. First step consists in making an ABS substrate with a conductive layer and printing of the ABS mold. Second step is to bond both elements together (Figure, a). The challenge faced is how to bond the substrate with the conductive layer and the upper mold. The developed solution is to thermally bond the substrate’s conductive surface and the upper mold’s surface by apply an appropriate temperature and pressure. Refences [1] L. Weber, W. Ehrfeld, H. Freimuth, M. Lacher, H. Lehr, and B. Pech, “Micromolding: a powerful tool for large-scale production of precise microstructures,” Proc. SPIE - Int. Soc. Opt. Eng. , vol. 2879, no. September 1996, pp. 156–167, 1996. [2] T. Katoh, R. Tokuno, Y. Zhang, M. Abe, K. Akita, and M. Akamatsu, “Micro injection molding for mass production using LIGA mold inserts,” Microsyst. Technol. , vol. 14, no. 9–11, pp. 1507–1514, 2008. [3] M. Vaezi, H. Seitz, and S. Yang, “A review on 3D micro-additive manufacturing technologies,” Int. J. Adv. Manuf. Technol. , vol. 67, no. 5–8, pp. 1721–1754, 2013. Figure 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.214
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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