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Erschienen in: Engineering with Computers 2/2021

20.09.2019 | Original Article

Recognition and classification of protrusion features on thin-wall parts for mold flow analysis

verfasst von: Jiing-Yih Lai, Pei-Pu Song, An-Sheng Hsiao, Yao-Chen Tsai, Chia-Hsiang Hsu

Erschienen in: Engineering with Computers | Ausgabe 2/2021

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Abstract

Thin-wall plastic parts exist in many products and are frequently manufactured by injection molding. The inner surface of a thin-wall part has many functional and structural features, typically divided into depressions and protrusions. While recognition of protrusion features is important in mold flow analysis, this recognition is difficult owing to the complexity and variety of the designed shapes. The purpose of this study was to develop a method for the detection and classification of protrusion features on thin-wall plastic parts. In the proposed algorithm, the inner and outer faces of a part model were detected first. Auxiliary faces, including translational, wall, and bottom faces, were recognized next. With auxiliary faces available, protrusion faces can thus be recognized and grouped in accordance with their neighboring relationship. A feature classification algorithm was finally implemented to classify five types of protrusions, namely tubes, ribs, columns, polygon blocks, and irregular extrusions. A detailed description of the procedures in each step of the proposed algorithm is provided. Twelve CAD models and analysis results are also presented to demonstrate the feasibility of the proposed protrusion recognition algorithm.

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Metadaten
Titel
Recognition and classification of protrusion features on thin-wall parts for mold flow analysis
verfasst von
Jiing-Yih Lai
Pei-Pu Song
An-Sheng Hsiao
Yao-Chen Tsai
Chia-Hsiang Hsu
Publikationsdatum
20.09.2019
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 2/2021
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-019-00859-1

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