Jinsu Gim

Dr. Jinsu Gim

University of Wisconsin–Madison, Madison, Alabama, USA
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 January 2023 in Journal of Manufacturing Processes
Verified
Journal Article
Closed access
Jinsu GimJinsu Gim
Jinsu Gim
HYHuaguang Yang
Huaguang Yang
LTLih-Sheng Turng
Lih-Sheng Turng

8 December 2023 in Journal of Manufacturing Systems
Verified
Journal Article
Closed access
Jinsu GimJinsu Gim
Jinsu Gim
CLChung-Yin Lin
Chung-Yin Lin
LTLih-Sheng Turng
Lih-Sheng Turng

27 September 2021 in Polymers
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Journal Article
Open access
PDF file
Jinsu GimJinsu Gim
Jinsu Gim
Byungohk RheeByungohk Rhee
Byungohk Rhee
The cavity pressure profile representing the effective molding condition in a cavity is closely related to part quality. Analysis of the effect of the cavity pressure profile on quality requires prior knowledge and understanding of the injection-molding process and polymer materials. In this work, an analysis methodology to examine the effect of the cavity pressure profile on part quality is proposed. The methodology uses the interpretation of a neural network as a metamodel representing the relationship between the cavity pressure profile and the part weight as a quality index. The process state points (PSPs) extracted from the cavity pressure profile were used as the input features of the model. The overall impact of the features on the part weight and the contribution of them on a specific sample clarify the influence of the cavity pressure profile on the part weight. The effect of the process parameters on the part weight and the PSPs supported the validity of the methodology. The influential features and impacts analyzed using this methodology can be employed to set the target points and bounds of the monitoring window, and the contribution of each feature can be used to optimize the injection-molding process.

12 March 2015 in International Journal of Precision Engineering and Manufacturing
Verified
Journal Article
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Jinsu GimJinsu Gim
Jinsu Gim
JTJoon-Sung Tae
Joon-Sung Tae
JJJoo-Hyeong Jeon
Joo-Hyeong Jeon
JCJae-Hyuk Choi
Jae-Hyuk Choi
Byungohk RheeByungohk Rhee
Byungohk Rhee

15 September 2020 in Polymers
Verified
Journal Article
Open access
PDF file
Jinsu GimJinsu Gim
Jinsu Gim
Eunsu HanEunsu Han
Eunsu Han
Byungohk RheeByungohk Rhee
Byungohk Rhee
WFWalter Friesenbichler
Walter Friesenbichler
DGDieter P Gruber
Dieter P Gruber
The gloss transition defect of injection-molded surfaces should be mitigated because it creates a poor impression of product quality. Conventional approaches for the suppression of the gloss transition defect employ a trial-and-error approach and additional equipment. The causes of the generation of a low-gloss polymer surface and the surface change during the molding process have not been systematically analyzed. This article proposes the causes of the generation of a low-gloss polymer surface and the occurrence of gloss transition according to the molding condition. The changes in the polymer surface and gloss were analyzed using gloss and topography measurements. The shrinkage of the polymer surface generates a rough topography and low glossiness. Replication to the smooth mold surface compensates for the effect of surface shrinkage and increases the surface gloss. The surface stiffness and melt pressure influence the degree of mold surface replication. The flow front speed and mold temperature are the main factors influencing the surface gloss because they affect the development rate of the melt pressure and the recovery rate of the surface stiffness. Therefore, the mold design and process condition should be optimized to enhance the uniformity of the flow front speed and mold temperature.