提高半导体制造厂能效的数据驱动方法

IF 2.3 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhao Hong;Chew Ze Yong;Kosasih Lucky;Goh Jun Rong;Wang Joheng
{"title":"提高半导体制造厂能效的数据驱动方法","authors":"Zhao Hong;Chew Ze Yong;Kosasih Lucky;Goh Jun Rong;Wang Joheng","doi":"10.1109/TSM.2024.3483781","DOIUrl":null,"url":null,"abstract":"The semiconductor industry faces increasing pressure to improve energy efficiency while maintaining competitiveness and sustainability. Apart from more conventional energy efficiency measures look at equipment modernization and process and design optimization, this paper explores the potential of data-driven approaches to address these challenges and optimize energy consumption across both the facility and manufacturing space of a semiconductor manufacture plant. By harnessing advanced analytics, machine learning algorithms, and IoT technologies, semiconductor manufacturers can gain real-time insights into energy usage patterns, and identify areas of opportunities that leads to the implementation of targeted interventions to optimize performance. The paper first looks into the challenges and measures of enabling and enhancing data visibility which is the foundation of the data-driven approach, then it examines case studies, best practices and various systematic approaches, demonstrating the transformative impact of data-driven energy efficiency measures which leads to operational efficiency, cost reduction, and environmental sustainability. Ultimately, this paper aims to provide a fresh angle into the energy efficiency study for peers in semiconductor industries to leverage in their journey towards a more sustainable and energy efficient future.","PeriodicalId":451,"journal":{"name":"IEEE Transactions on Semiconductor Manufacturing","volume":"37 4","pages":"475-480"},"PeriodicalIF":2.3000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10742890","citationCount":"0","resultStr":"{\"title\":\"A Data-Driven Approach for Improving Energy Efficiency in a Semiconductor Manufacturing Plant\",\"authors\":\"Zhao Hong;Chew Ze Yong;Kosasih Lucky;Goh Jun Rong;Wang Joheng\",\"doi\":\"10.1109/TSM.2024.3483781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The semiconductor industry faces increasing pressure to improve energy efficiency while maintaining competitiveness and sustainability. Apart from more conventional energy efficiency measures look at equipment modernization and process and design optimization, this paper explores the potential of data-driven approaches to address these challenges and optimize energy consumption across both the facility and manufacturing space of a semiconductor manufacture plant. By harnessing advanced analytics, machine learning algorithms, and IoT technologies, semiconductor manufacturers can gain real-time insights into energy usage patterns, and identify areas of opportunities that leads to the implementation of targeted interventions to optimize performance. The paper first looks into the challenges and measures of enabling and enhancing data visibility which is the foundation of the data-driven approach, then it examines case studies, best practices and various systematic approaches, demonstrating the transformative impact of data-driven energy efficiency measures which leads to operational efficiency, cost reduction, and environmental sustainability. Ultimately, this paper aims to provide a fresh angle into the energy efficiency study for peers in semiconductor industries to leverage in their journey towards a more sustainable and energy efficient future.\",\"PeriodicalId\":451,\"journal\":{\"name\":\"IEEE Transactions on Semiconductor Manufacturing\",\"volume\":\"37 4\",\"pages\":\"475-480\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10742890\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Semiconductor Manufacturing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10742890/\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Semiconductor Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10742890/","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

半导体行业在保持竞争力和可持续性的同时,面临着越来越大的提高能源效率的压力。除了着眼于设备现代化、流程和设计优化的传统能效措施外,本文还探讨了数据驱动方法的潜力,以应对这些挑战并优化半导体制造工厂的设施和制造空间的能耗。通过利用先进的分析、机器学习算法和物联网技术,半导体制造商可以实时洞察能源使用模式,并确定机遇领域,从而实施有针对性的干预措施来优化性能。本文首先探讨了实现和提高数据可视性所面临的挑战和采取的措施,这是数据驱动方法的基础,然后研究了案例研究、最佳实践和各种系统方法,展示了数据驱动能效措施的变革性影响,从而提高运营效率、降低成本和实现环境的可持续发展。最终,本文旨在为半导体行业的同行提供一个全新的能效研究视角,以便他们在迈向更具可持续性和能效的未来的过程中加以利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Data-Driven Approach for Improving Energy Efficiency in a Semiconductor Manufacturing Plant
The semiconductor industry faces increasing pressure to improve energy efficiency while maintaining competitiveness and sustainability. Apart from more conventional energy efficiency measures look at equipment modernization and process and design optimization, this paper explores the potential of data-driven approaches to address these challenges and optimize energy consumption across both the facility and manufacturing space of a semiconductor manufacture plant. By harnessing advanced analytics, machine learning algorithms, and IoT technologies, semiconductor manufacturers can gain real-time insights into energy usage patterns, and identify areas of opportunities that leads to the implementation of targeted interventions to optimize performance. The paper first looks into the challenges and measures of enabling and enhancing data visibility which is the foundation of the data-driven approach, then it examines case studies, best practices and various systematic approaches, demonstrating the transformative impact of data-driven energy efficiency measures which leads to operational efficiency, cost reduction, and environmental sustainability. Ultimately, this paper aims to provide a fresh angle into the energy efficiency study for peers in semiconductor industries to leverage in their journey towards a more sustainable and energy efficient future.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Transactions on Semiconductor Manufacturing
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信