• Smart Structures and Systems
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• v.29 no.6
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• pp.767-775
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• 2022

Metal additive manufacturing (AM), also known as metal three-dimensional (3D) printing, produces 3D metal products by repeatedly adding and solidifying metal materials layer by layer. During the metal AM process, products experience repeated local melting and cooling using a laser or electron beam, resulting in product defects, such as warpage, cracks, and internal pores. Such defects adversely affect the final product. This paper proposes the in situ monitoring-based warpage prediction of metal AM products with experimental feature extraction. The temperature profile of the metal AM substrate during the process was experimentally collected. Time-domain features were extracted from the temperature profile, and their relationships to the warpage mechanism were investigated. The standard deviation showed a significant linear correlation with warpage. The findings from this study are expected to contribute to optimizing process parameters for metal AM warpage reduction.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.3
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• pp.24-37
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• 2024

Due to the thin nature of semiconductor packages, even minor thermal loads can cause significant warpage, impacting product reliability through issues like delamination or cracking. The mold curing process, which encloses the package to protect the semiconductor chip, is particularly challenging to predict due to the complex thermal, chemical, and mechanical interactions. This study proposes a cost-effective machine learning model to predict warpage in the mold curing process. We developed methods to characterize the curing degree based on time and temperature and quantify the material's mechanical properties accordingly. A Finite Element Method (FEM) simulation model was created by integrating these properties into ABAQUS UMAT to predict warpage for various design factors. Additionally, a Warpage formula was developed to estimate local warpage based on the package's stacking structure. This formula combines bending theory with thermo-chemical-mechanical properties and was validated through FEM simulation results. The study presents a method to construct a machine learning model for warpage prediction using this formula and proposes a cost-effective approach for building a training dataset by analyzing input variables and design factors. This methodology achieves over 98% prediction accuracy and reduces simulation time by 96.5%.

• Transactions of Materials Processing
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• v.32 no.6
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• pp.367-375
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• 2023

Composite materials, known for their excellent mechanical properties and lightweight characteristics, are applied in various engineering fields. Recently, efforts have been made to develop an automotive battery protection panel using a plain-woven composite composed of glass fiber and polypropylene to reduce the weight of automobiles. However, excessive warpage occurs during the GF/PP compression molding process, which makes car assembly challenging. This study aims to develop a model that predicts the warpage during the compression molding process. Obtaining out-of-plane properties such as elastic or shear modulus, essential for predicting warpages, is tricky. Existing mechanical methods also have limitations in calculating these properties for woven composite materials. To address this issue, finite element analysis is conducted using representative volume elements (RVE) for woven composite materials. A warpage prediction model is developed based on the estimated physical properties of GF/PP composite materials obtained through representative volume elements. This model is expected to be used for reducing warpages in the compression molding process.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.3
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• pp.89-93
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• 2020

Complex warpage behavior of the electronic packages causes internal stress so many kinds of mechanical failure occur such as delamination or crack. Efforts to predict the warpage behavior accurately in order to prevent the decrease in yield have been approached from various aspects. For warpage prediction, silicon is generally treated as a homogeneous material, therefore it is described as showing no warpage behavior due to thermal loading. However, it was reported that warpage is actually caused by residual stress accumulated during grinding and polishing in order to make silicon wafer thinner, which make silicon wafer inhomogeneous through thickness direction. In this paper, warpage behavior of the single-side polished wafer at solder reflow temperature, the highest temperature in packaging processes, was measured using 3D digital image correlation (DIC) method. Mechanism was verified by measuring coefficient of thermal expansion (CTE) of both mirror-polished surface and rough surface.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.165.2-165.2
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• 2005

• Polymer(Korea)
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• v.38 no.6
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• pp.708-713
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• 2014

Most plastics products are being produced by injection molding process. However, mold shrinkage is inevitable in injection molding process and it deteriorates dimensional quality through deflections and warpages. Mold shrinkage depends upon the material property of resin as well as injection molding condition. In this study, material property of resin has been predicted for glass fiber reinforced polycarbonate to control the warpage, and computer simulation of injection molding has been performed using predicted property. It was observed that the deflection of part decreased by the glass fiber reinforced resin. In order to verify the validity of this method and confidence of results, experiments of injection molding were performed. The results of experiments and computer simulations showed good agreement in their tendency of deflections. Consequently, it was concluded that the method of designing the material property of resin conducted in this study can be utilized to control the dimensional accuracy of injection molded products.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2002.09a
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• pp.79-94
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• 2002

Root cause -Thermal expansion coefficient mismatch -Tape warpage -Initial die crack (die roughness) Guideline for failure prevention -Optimized tape/Substrate design for minimizing the warpage -Fine surface of die backside Root cause -Thermal expansion coefficient mismatch - Repetitive bending of a signal trace during TC cycle - Solder mask damage Guideline for failure prevention - Increase of trace width - Don't make signal trace passing the die edge - Proper material selection with thick substrate core Root cause -Thermal expansion coefficient mismatch -Creep deformation of solder joint(shear/normal) -Material degradation Guideline for failure Prevention -Increase of solder ball size -Proper selection of the PCB/Substrate thickness -Optimal design of the ball array -Solder mask opening type : NSMD -In some case, LGA type is better

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.673-674
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• 2010

• Composites Research
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• v.27 no.4
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• pp.174-181
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• 2014

This study describes viscoelasticity analysis of carbon-fiber reinforced polymer matrix composite material. One of the most important problem during high temperature molding process is residual stress. Residual stress can cause warpage and cracks which can lead to serious defects of the final product. For the difference in thermal expansion coefficient and change of resin property during curing, it is difficult to predict the final deformed shape of carbon-fiber reinforced polymer matrix composite. The consideration of chemical shrinkage can reduce the prediction errors. For this reason, this study includes the viscoelasticity and chemical shrinkage effects in FE analysis by creating subroutines in ABAQUS. Analysis results are compared with other researches to verify the validity of the subroutine developed, and several stacking sequences are introduced to compare tested results.

• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.117-123
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• 2004

The prediction to the hydroscopic moisture warping behaviors is analyzed for cellulose-based laminates using a numerical method base on a modified classical laminate(MCL) theory for hygroscopic moisture deformations with cycling testing data. The experimental measurement of the interferometric hygroscopic warping effects, moisture generator, and curvature of cellulose reinforced epoxy laminates is studied under cyclic environmental conditions using a Moire interferometer coupled. Accurate determination of curvatures provides a description of dimensional stability evolution; the tools for validation of computational internal stress and for the warpage prediction in model safety.