Simulation-Based Optimization of Plastic Transfer Molding Parameter for IC Package Encapsulation Process

Mohd Uzair Rosli; M. Najih; Mohd Fathullah Ghazli

doi:10.58915/aset.v5i1.3199

Authors

Mohd Uzair Rosli Universiti Malaysia Perlis
M. Najih Universiti Malaysia Perlis
Mohd Fathullah Ghazli Universiti Malaysia Perlis

DOI:

https://doi.org/10.58915/aset.v5i1.3199

Keywords:

Central Composite Design (CCD), Design Expert, Plastic Transfer Molding, Quad Flat No-Lead (QFN), Response Surface Methodology (RSM)

Abstract

This study focuses on the simulation-based optimization of plastic transfer molding parameters in the Quad Flat No-Lead (QFN) encapsulation process, which is widely used in the semiconductor industry due to its compact size and reliable performance. However, process-related issues such as air traps, incomplete filling, and uneven curing can compromise product quality, leading to performance failures and higher rejection rates. To address these challenges, this study aims to analyze and optimize critical molding parameters to minimize such defects and improve the consistency of the QFN package. Four key numerical parameters, such as mold temperature, melt temperature, curing time, and injection pressure, were selected based on their significant influence on flow behaviour and material curing. The study employs Response Surface Methodology (RSM) with a Central Composite Design (CCD) to systematically evaluate the effect of each parameter and its interactions. A total of 30 simulation runs were generated using Design Expert software, and Autodesk Moldflow was used to simulate the transfer molding process. The results demonstrated that optimized settings significantly reduced defects, with validation showing minimal percentage differences (<10%) in key responses, including 0.0000% for Fill time, 0.0000% for Air traps, 0.0607% for Curing level, 1.7179% for Shear rate, and 0.1246% for Shear stress. This study concludes that simulation-based optimization effectively improves the QFN encapsulation process, ensuring better quality and process consistency. Future research could focus on experimental validation, integration of advanced materials, and real-time monitoring to further enhance the process.

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