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Kuo-Ning Chiang

Researcher at National Tsing Hua University

Publications -  242
Citations -  2695

Kuo-Ning Chiang is an academic researcher from National Tsing Hua University. The author has contributed to research in topics: Electronic packaging & Chip-scale package. The author has an hindex of 25, co-authored 238 publications receiving 2368 citations. Previous affiliations of Kuo-Ning Chiang include Industrial Technology Research Institute & TSMC.

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An overview of solder bump shape prediction algorithms with validations

TL;DR: In this paper, the authors developed solder joint reliability design guidelines to accurately predict both the solder bump geometry and the standoff height for reflow soldered joints in area array packages, and three simulation methods such as truncated-sphere theory force-balanced analytical solution and energy-based approach for prediction of the solder bumps geometry are each examined in detail, and the thermal enhanced BGA (TBGA) and flip chip packages are selected as the benchmark models to compare the simulation and experimental results.
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Reliability analysis and design for the fine-pitch flip chip BGA packaging

TL;DR: In this paper, the effect of die/substrate-side pad size and underfill size on the solder joint reliability of a fine-pitched flip chip ball grid array (FCBGA) package is extensively investigated through finite element (FE) modeling and experimental testing.
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Current crowding-induced electromigration in SnAg3.0Cu0.5 microbumps

TL;DR: In this article, a three-dimensional dual bumps simulation model was designed to demonstrate how current crowding can enhance the local atomic flux along the electron flow path, and the finding of void formation occurred at the entrance points to the cathode sides and the enhancement of the growth and clustering of the intermetallic compound at the outgoing points of the anode sides along the path were verified experimentally.
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Sensitivity analysis of packaging effect of silicon-based piezoresistive pressure sensor

TL;DR: In this article, a finite element method (FEM) is adopted for sensor performance evaluation, packaging-induced signal variation, and thermal/packaging effects will be examined in this research.
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Thermal Modeling of Temperature Distribution in Metal Additive Manufacturing Considering Effects of Build Layers, Latent Heat, and Temperature-Sensitivity of Material Properties

TL;DR: In this article, a physics-based analytical model is proposed in order to predict the temperature profile during metal additive manufacturing (AM) processes, by considering the effects of temperature history in each layer, temperature-sensitivity of material properties and latent heat.