Advancing Condition-Based Maintenance in the Semiconductor Industry: Innovations, Challenges and Future Directions for Predictive Maintenance

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

IEEE Transactions on Semiconductor Manufacturing Pub Date : 2025-01-17 DOI:10.1109/TSM.2025.3530964

Jingyu Park;Byeongsun Yoo;Song Yi Baek;Chulkyu Youn;Sundoo Kim;Dowan Kim;Sangho Roh;Se Jun Park;Jaehyun Kim;Changsoo Lee;Chulhwan Choi

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引用次数: 0

Abstract

This study focuses on the criticality of failure detection and condition-based maintenance (CBM) within the semiconductor industry, employing Fault Detection and Classification (FDC) systems and Machine Learning (ML) techniques for equipment log analysis to anticipate equipment conditions and timely maintenance. Initiatives emphasize the cultivation of data engineering experts, enhancing depth in data analytics and equipment monitoring. Moreover, the imperative to advance the field lies in the development of innovative sensor technologies, a task that necessitates close collaboration with equipment manufacturers. This strategic partnership is indispensable for augmenting the precision and breadth of data acquisition. It ultimately enables more sophisticated analytics, thereby facilitating the creation of advanced predictive failure models through enhanced data capture and analysis. This paper illustrates the semiconductor sector’s competitive adoption of diverse strategies and technologies for maintenance innovation, aiming to bolster industry productivity, equipment reliability, and sustainability. Such endeavors are pivotal for outlining the future trajectory of manufacturing and ensuring sustainable growth within the industry.

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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.