• Development of real-time and wireless FSW tool temperature measurement system based on IoT devices

• AI-based prediction of FSWed joint quality (ultimate tensile strength) using transient FSW tool temperature profile

• XAI-base analysis of the effect of FSW tool temperature profile on FSWed joint quality 

Related Publications

• Jinsu Gim*, Mingoo Cho, Jaehwang Kim, Kwang-Jin Lee, Deva Prasaad Neelakandan, Chanho Lee, Yoon Chul Jung, and Sungwook Kang*, Design and application of wireless tool temperature measurement of friction stir welding (FSW) for process monitoring and control, Measurement 252, 117395, 2025. (JCR 2023; IF 5.2, JIF Rank 9.1% 17/181 Q1 in Engineering, Multidisciplinary) [PDF] 

• Mingoo Cho, Jinsu Gim*, Jaehwang Kim, Min-Suk Park, Hoon-Hee Lee, and Sungwook Kang*, Development of a real-time wireless tool temperature measurement system for friction stir welding monitoring, Journal of the Korean Society of Manufacturing Technology Engineers 34(2), 96-103, 2025. [PDF] 

• Decoupling of optimal valve gate (VG) position and VG sequence by melt front detection (MFD)

• Optimization of VG positions of SVG locating VG groups sequentially

• Optimization of VG sequence delay time

• Reduction of flow imbalance, flow front speed fluctuation, and minimization of injection pressure increase

Related Publications

• Bongju Kim†, Jinsu Gim†, Lih-Sheng Turng, and Byungohk Rhee*, Optimization of sequence valve gating (SVG) injection molding based on melt front detection (MFD), Journal of Manufacturing Processes 127(15), 289–303, 2024. (JCR 2023; IF 6.1, JIF Rank 12/68 Q1 in Engineering, Manufacturing) 

• Jinsu Gim, and Hoon Hee Lee, Hot runner valve system, KR Application 10-2024-0038060. 

A novel AI/ML modeling approach of injection molding dividing the whole process by in-mold condition and molding

• Modeling of the injection molding process by two AI/ML models

  • Process parameter - In-mold condition model (Machine - Mold)

  • In-mold condition - Quality model (Mold - Part)

A novel approach for analysis of the effect of in-mold conditions (IMC) on part quality by explainable artificial intelligence (XAI)

• Feature (process state points, PSPs) extraction from time-series data profiles (IMC profiles) based on geometrical characteristics

• Autonomous analysis of the relationship between IMC and part quality using XAI (quality-specific analysis results without dependency on previous knowledge and understanding)

A novel process optimization method based on in-mold conditions using XAI and AI-based generative design

• Generation of ideal IMC profiles for extreme quality improvement
  (limit of quality improvement based on IMC-Quality / Mold-Part relationship)

• Filtering (or optimization) physically feasible IMC profiles with consideration of spec of molding machines and influential features of IMCs
  (based on Process parameter - In-mold condition / Machine-Mold relationship, IMC-Quality / Mold-Part relationship, and XAI analysis of IMC)

Related Publications

• Jinsu Gim, Chung-Yin Lin, and Lih-Sheng Turng*, In-mold condition-centered and explainable artificial intelligence-based (IMC-XAI) process optimization for injection molding, Journal of Manufacturing Systems 72, 196–213, 2024. (JCR 2022; IF 12.1, JIF Rank 2/86 Q1 in Operations Research & Management Science) [Web Application] 

• Jinsu Gim, and Lih-Sheng Turng*, Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence, International Journal of Production Research 61(23), 8192–8212, 2023. (JCR 2022; IF 9.2, JIF Rank 5/86 Q1 in Operation Research & Management Science)

• Byungohk Rhee, and Jinsu Gim, Monitoring apparatus using sensor signal in injection mold and method thereof, KR 10-2500376. 

• Jinsu Gim, and Byungohk Rhee*, Novel analysis methodology of cavity pressure profiles in injection-molding processes using interpretation of machine learning model, Polymers 13(19), 3297, 2021. (JCR 2022; IF 5.0, JIF Rank 16/86 Q1 in Polymer Science) [PDF] 

• Jinsu Gim*, Chung-Yin Lin, and Lih-Sheng Turng, Analysis methodology for effect of in-mold condition (IMC) on quality based on explainable artificial intelligence (XAI) in injection molding, Journal of the Korean Society of Manufacturing Technology Engineers 33(5), 251–261, 2024. [PDF] 

• Artificial intelligence (AI) and machine learning (ML)-based approaches for changing manufacturing sites or molding machines

• Digital twin (DT) approach - AI/ML model transfer in the digital domain together with mold transfer to different manufacturing sites or molding machines in the physical domain

• Cost (reduction of physical data) and time (reduction of trial and error approaches)-effective optimization of injection molding in a new manufacturing condition by transferring knowledge from a previous manufacturing condition

Related Publications

• Chung-Yin Lin, Jinsu Gim, Demitri Shotwell, Mong-Tung Lin, Jia-Hau Liu, and Lih-Sheng Turng*, Explainable artificial intelligence and multi-stage transfer learning for injection molding quality prediction, Journal of Intelligent Manufacturing 2024, 2024. (JCR 2022; IF 8.3, JIF Rank 23/145 Q1 in Computer Science, Artificial Intelligence)

• Jinsu Gim, Huaguang Yang, and Lih-Sheng Turng*, Transfer learning of machine learning models for multi-objective process optimization of a transferred mold to ensure efficient and robust injection molding of high surface quality parts, Journal of Manufacturing Processes 87(3), 11–24, 2023. (JCR 2022; IF 6.2, JIF Rank 15/50 Q2 in Engineering, Manufacturing)

• Joohyeong Jeon, Byungohk Rhee*, and Jinsu Gim, Melt temperature estimation by machine learning model based on energy flow in injection molding, Polymers 14(24), 5548, 2022. (JCR 2022; IF 5.0, JIF Rank 16/86 Q1 in Polymer Science) [PDF] 

• Development photographic studios and image processing algorithms for measurement of quality of injection molding including warpage, surface gloss, gloss defects, flash (burr), ejector marks, gas marks / flow marks, birefringence,  and filling imbalance based on fundamental understandings of quality and defects

Related Publications

• (Warpage) Jinsu Gim, Chung-Yin Lin, and Lih-Sheng Turng*, In-mold condition-centered and explainable artificial intelligence-based (IMC-XAI) process optimization for injection molding, Journal of Manufacturing Systems 72, 196–213, 2024. (JCR 2022; IF 12.1, JIF Rank 2/86 Q1 in Operations Research & Management Science) [Web Application] 

• (Warpage) Jinsu Gim, and Lih-Sheng Turng*, Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence, International Journal of Production Research 61(23), 8192–8212, 2023. (JCR 2022; IF 9.2, JIF Rank 5/86 Q1 in Operation Research & Management Science)

• (Gas marks / flow marks) Jinsu Gim, Huaguang Yang, and Lih-Sheng Turng*, Transfer learning of machine learning models for multi-objective process optimization of a transferred mold to ensure efficient and robust injection molding of high surface quality parts, Journal of Manufacturing Processes 87(3), 11–24, 2023. (JCR 2022; IF 6.2, JIF Rank 15/50 Q2 in Engineering, Manufacturing)

• (Birefringence) Demitri Shotwell, Jinsu Gim, Huaguang Yang, Stefanie Glas, Edward Chen, and Lih-Sheng Turng*, Effect of static mixer on optical properties of plastic injection molded parts, Polymer Engineering and Science 62(12), 4185–4202, 2022. (JCR 2022; IF 3.2, JIF Rank 36/86 Q2 in Polymer Science) [PDF] 

• (Surface gloss) Jinsu Gim, Eunsu Han, Byungohk Rhee*, Walter Friesenbichler, and Dieter P Gruber, Causes of the gloss transition defect on high-gloss injection-molded surfaces, Polymers 12(9), 2100, 2020. (JCR 2022; IF 5.0, JIF Rank 16/86 Q1 in Polymer Science) [PDF] 

• (Filling imbalance) Jin Su Gim, Joon-Sung Tae, Joo-Hyeong Jeon, Jae-Hyuk Choi, and Byung-Ohk Rhee*, Detection method of filling imbalance in a multi-cavity mold for small lens, International Journal of Precision Engineering and Manufacturing 16, 531–535, 2015. (JCR 2022; IF 1.9, JIF Rank 91/134 Q3 in Engineering, Mechanical; 45/50 Q4 in Engineering, Manufacturing) [PDF] 

Note: AI/ML based Detection of gloss defects, flash (burr), and ejector marks - Project funded by LGE Electronics (2020)

(Funded project by LG Electronics, Pyeongtaek, 2017-2018)

• Development of auto-triggering module (original terminology of the former version of the i-mold system) and control software [LabVIEW program]

• Autonomous control of valve gate sequence based on melt front arrival using in-mold sensors

• Autonomous correction of valve gate open/close lag time

• Process monitoring using in-mold sensors

Related Publications and Award

• Best Paper Presentation, Korean Society of Manufacturing Technology Engineers (KSMTE), 2020.

• Bongju Kim†, Jinsu Gim†, Lih-Sheng Turng, and Byungohk Rhee*, Optimization of sequence valve gating (SVG) injection molding based on melt front detection (MFD), Journal of Manufacturing Processes 127(15), 289–303, 2024. (JCR 2023; IF 6.1, JIF Rank 12/68 Q1 in Engineering, Manufacturing)

• Generation mechanism of gloss transition defects of high-gloss injection-molded surfaces

• Proposal and verification of root cause (rough surface generation by inhomogeneous micro-scale shrinkage due to the inhomogeneous polymer morphology) of low gloss surface generation in highly polished injection mold by light scattering theory (Kirchhoff theory with consideration of surface topography)

• Proposal of dimensionless number (Replication factor, RF) determining gloss transition defects considering pressure effect (driving factor) and cooling effect (resisting factor)

• Proposal process window determination method using the proposed dimensionless number

Related Publications and Award

• Best Paper Presentation, Korean Society of Manufacturing Technology Engineers (KSMTE), 2020.

• Jinsu Gim, Generation mechanism and control of gloss defects for high-gloss injection-molded products, Ph.D. Thesis, Ajou University, 2020.

• Jinsu Gim, and Lih-Sheng Turng*, A review of current advancements in high surface quality injection molding: Measurement, influencing factors, prediction, and control, Polymer Testing 115, 107718, 2022. (JCR 2022; IF 5.1, JIF Rank 1/32 in Materials Science, Characterization & Testing) [PDF] 

• Jinsu Gim, and Byungohk Rhee*, Control of gloss defect on high-gloss injection-molded surfaces, Korea-Australia Rheology Journal 33, 144–141, 2021. (JCR 2022; IF 1.3, JIF Rank 112/137 Q4 in Mechanics) [PDF] 

• Jinsu Gim, Eunsu Han, Byungohk Rhee*, Walter Friesenbichler, and Dieter P Gruber, Causes of the gloss transition defect on high-gloss injection-molded surfaces, Polymers 12(9), 2100, 2020. (JCR 2022; IF 5.0, JIF Rank 16/86 Q1 in Polymer Science) [PDF] 

• Jinsu Gim, and Byungohk Rhee*, Generation mechanism of gloss defect for high-glossy injection-molded surface, Korea-Australia Rheology Journal 32, 183–194, 2020. (JCR 2022; IF 1.3, JIF Rank 112/137 Q4 in Mechanics) [PDF] 

• Development of automatic SVG sequence controller with valve pin position measurement and melt front detection [LabVIEW program]

• Design of low-cost in-situ valve pin position measurement method for sequence valve gating (SVG) of hot runner

• Automatic SVG sequence control (valve gate open timing) by detection of melt front arrival to each valve gate

• Autonomous correction of valve gate open/close lag time

• Development of monitoring systems for injection molding capable of measurement of machine signals (screw position, injection speed, and injection pressure) and in-mold conditions (cavity pressure, mold surface temperature, and mold temperature stabilization)

Related Publications and Award

• Jinsu Gim, and Hoon Hee Lee, Hot runner valve system, KR Application 10-2024-0038060.

• SPE Korea Award – Dow Hyun Award, Society of Plastics Engineers (SPE) Korea Section, 2017

Rheological Analysis of Curable Polymers and Adhesives (Rheokinetics)
(Funded project by Hyundai Motor Company and Hyundai NGV, 2020-2021)

• Rheological curing kinetics (rheokinestics) modeling and viscoelastic characteristics measurement of curable polymers including coating materials, waterborne Polyurethane adhesives for automotive applications, and optical epoxy for lens molding

• Adhesive performance measurement of waterborne Polyurethane and hot melt adhesives for automotive applications

Design of Rheometer Attachment and Mold-type Slit Rheometer

• Design of UV curing, extensional viscosity measurement attachment for rheometers such as Anton-Paar MCR rheometers

• Mold-type slit rheometer design for measurement of in-situ rheological characteristics of polymer/composites including long fiber thermoplastics (LFT) in injection molding 

Related Publications

• Eunsu Han, Jinsu Gim, Bongju Kim, and Byungohk Rhee*, Examination of the melt temperature stability of the mold-type slit rheometer affected by plasticizing conditions and the shear heating in the nozzle and sprue, Korea-Australia Rheology Journal 33, 151–162, 2021. (JCR 2022; IF 1.3, JIF Rank 112/137 Q4 in Mechanics) [PDF]

• Jinsu Gim, Measurement method of curing behavior and shrinkage rate of high-shrinking curable polymers, KR Application 10-2024-0076314.

• FEM analysis of multi-layer composite structures with multi-scale features such as honeycomb core (~1 mm size features) in long length (2 m size geometry) using homogenization approach

• Testing equipment design including structure and software for elastic and dynamic characteristics of composite structures

• Determination of elastic characteristics such as true bending stiffness and shear stiffness from apparent bending and shear stiffness [LabVIEW program]

• Determination of dynamic characteristics such as natural frequency, oscillation mode and shape, and damping ratio based on impact test method [LabVIEW program]

• Testing equipment and software design for pressure distribution of jumping skies [LabVIEW program]

• Design method of elastic and dynamic characteristics of multi-layer composite structure using cross-sectional geometry and material characteristics
  
  

Related Publications

• Yuzhou Ge, Zhangjie Zhan, Wanxia Wu, Jian Zhao*, Allen Jonathan Román, Jinsu Gim, Dongxiao Su, Xiubin Zuo, Lih-Sheng Turng*, and Tim A Osswald, Investigations of three-dimensional fiber orientation on mechanical impact behavior of short glass-fiber-reinforced PEEK composites, Journal of Reinforced Plastics and Composites, in-press (online first), 2024. (JCR2023; IF 2.3, JIF Rank 19/35 Q3 in Materials Science, Composites)

• Jinsu Gim, Joohyeong Jeon, Bongju Kim, Taejoon Jeong, Kyeonghyeon Jeon, and Byungohk Rhee*, Quantification and design of jumping-ski characteristics, Proceedings of the Institution of Mechanical Engineers Part P-Journal of Sports Engineering and Technology 232(2), 150–159, 2017. (JCR 2022; IF 1.5, JIF Rank 112/135 Q4 in Engineering, Mechanical) [EBS Documentary]

• Yunhyung Nam, Jinsu Gim, Taejoon Jeong, Byungohk Rhee, and Do-Nyun Kim*, A numerical study for the effect of ski vibration on friction, Multiscale Science and Engineering 1, 256–264, 2019. [PDF]