Taiwan Semiconductor Association Awards First Innovation Prizes to Three Universities

Taiwan's semiconductor industry is bolstering its innovation pipeline with the inaugural TSIA Semiconductor Equipment Innovation Award, recognizing advancements from three leading universities. Feng Chia University's engineering and science college, led by Dean Wang Chi-chang, received accolades for its work on improving advanced packaging equipment. The team developed an AI-driven system that optimizes heating furnace performance and energy efficiency by converting complex mechanical models into user-friendly applications.

Wang explained that their research directly addresses the practical needs of equipment manufacturers. "This research directly cuts into the real needs of equipment manufacturers," he stated, highlighting how their work helps optimize temperature uniformity and energy-saving designs. The team's innovations have already led to five technology transfers, including key techniques for improving hot plate temperature uniformity and smart burn-in simulation.

Ming Chi University of Technology's Mechanical Engineering Department also earned recognition for its contributions to the advanced packaging sector. Their Smart Medical Research Center developed efficient solutions for critical components in bonding processes, significantly enhancing overall equipment stability. Meanwhile, National Yang Ming Chiao Tung University's Silicon Carbide Power Device Laboratory in the Institute of Electronics successfully created a high-speed gate driver measurement framework. This framework achieves stable, low-distortion high-speed gate switching signal output, supporting dynamic characteristic measurements for components like Si and SiC.

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This research directly cuts into the real needs of equipment manufacturers, helping to optimize the temperature uniformity and energy-saving design of various heating furnaces. It transforms complex mechanical models into multiple exclusive APPs, allowing non-R&D application engineers, even without a deep theoretical foundation, to quickly obtain visualizable analysis results by simply inputting equipment geometry, material, and process parameters.