Process design of microchip encapsulation : a case based reasoning with fuzzy retrieval approach

K. Tong, C. Kwong
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引用次数: 2

Abstract

The microelectronic industry continues to grow rapidly in size and importance. The industry has already reached the size of other major industries with sales of product and equipment totalling billions of dollars a year. Among all the options available for semiconductor assembly, plastic packaging by using epoxy based encapsulation process is less expensive and accounts for approximately 80% of the worldwide packaging share and this percentage is increasing. Microchip encapsulation based on transfer molding is one of the important processes of semiconductor manufacturing. Quality is heavily dependent on the encapsulation mold design, selection of molding compound and process parameter setting of encapsulation molding. In current practice, encapsulation mold design and parameter setting of the transfer molding are done manually in a trial-and-error manner which would result in long lead time for obtaining acceptable molding quality. In this paper, an artificial intelligence technique, Case Based Reasoning with Fuzzy Retrieval, is described to perform process design of microchip encapsulation from which a case based system for microchip encapsulation, named CBS-ME, was developed. The system aims to automate the design of the key elements of encapsulation molds, suggest process parameters for transfer molding and improve its own design know-how through a learning process. A validation test was performed and the system solutions were benchmarked with the solutions obtained from the actual molding. Deviation of the two sets of solutions for mold design parameter setting and process parameter setting are 3.5% and 6% respectively.
微芯片封装工艺设计:基于案例推理的模糊检索方法
微电子工业的规模和重要性继续迅速增长。该行业已经达到了其他主要行业的规模,每年的产品和设备销售额总计达数十亿美元。在所有可用于半导体组装的选项中,使用环氧基封装工艺的塑料封装成本较低,约占全球封装份额的80%,而且这一比例还在增加。基于传递成型的微芯片封装是半导体制造的重要工艺之一。产品的质量在很大程度上取决于封装模具的设计、成型材料的选择和封装成型工艺参数的设置。在目前的实践中,封装模具的设计和传递成型的参数设置都是手工进行的,采用试错的方式,这将导致获得可接受的成型质量需要很长时间。本文介绍了基于案例推理和模糊检索的人工智能技术在微芯片封装过程设计中的应用,并在此基础上开发了基于案例的微芯片封装系统CBS-ME。该系统旨在自动化设计封装模具的关键要素,为传递成型提供工艺参数建议,并通过学习过程提高自己的设计知识。进行了验证试验,并将系统解决方案与实际成型得到的解决方案进行了基准测试。两套解决方案对模具设计参数设定和工艺参数设定的偏差分别为3.5%和6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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