Guest Editorial Special Section on Production-Level Artificial Intelligence Applications in Semiconductor Manufacturing

IF 2.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2023-10-30 DOI:10.1109/TSM.2023.3324469

John W. Fowler;Karl Kempf;Lars Mönch

引用次数: 0

Abstract

The increasing availability of data, advances in computational and storage capacities of IT systems, and algorithmic advances in Artificial Intelligence (AI), especially Machine Learning (ML) combine to enable significant improvements in the efficiency, operations and throughput of manufacturing systems at the production level. The semiconductor industry is one of the most data-intensive industries and has seen increased use of AI-based technologies over the last few years. In order to develop effective AI-based technologies in the semiconductor manufacturing industry several issues have to be taken into account, including scalability, heterogeneity of data, and the need for interpretability.

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客座编辑关于半导体制造中生产级人工智能应用的特别部分

数据可用性的提高、IT系统计算和存储能力的进步，以及人工智能（AI），特别是机器学习（ML）的算法进步，使制造系统在生产层面的效率、运营和吞吐量得以显著提高。半导体行业是数据密集度最高的行业之一，在过去几年中，基于人工智能的技术的使用有所增加。为了在半导体制造业中开发有效的基于人工智能的技术，必须考虑几个问题，包括可扩展性、数据的异构性和可解释性的必要性。

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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来源期刊

IEEE Transactions on Semiconductor Manufacturing 工程技术-工程：电子与电气

CiteScore

5.20

自引率

11.10%

发文量

101

审稿时长

3.3 months

期刊介绍： The IEEE Transactions on Semiconductor Manufacturing addresses the challenging problems of manufacturing complex microelectronic components, especially very large scale integrated circuits (VLSI). Manufacturing these products requires precision micropatterning, precise control of materials properties, ultraclean work environments, and complex interactions of chemical, physical, electrical and mechanical processes.