A Novel Virtual Metrology Scheme for Predicting CVD Thickness in Semiconductor Manufacturing

Hung, Min‐Hsiung; Lin, Tung-Ho; Cheng, Fan‐Tien; Lin, Rung-Chuan

doi:10.1109/tmech.2007.897275

Cited by 99 publications

(43 citation statements)

References 12 publications

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“…There are even cases of classical neural network usage [31]. This can easily be generalized to any process and really deserve to be better known.…”

Section: Virtual Metrology For Allmentioning

confidence: 99%

Pragmatic Big Data and smart manufacturing

Benhenni¹

2017

18th International Congress of Metrology

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Abstract. Smart manufacturing is usually associated with fancy cobots and automated production lines. But the Big Data ecosystem has a part to play, and is probably faster and cheaper to start with. The numerical revolution has dramatically accelerated these last years, with many implications in different industries. We propose in this article to present these new tools, and discuss some real use cases. We will also present the best practices and some of the inevitable challenges related to data projects.The upcoming Industry 4.0 movement is full of promises. However, many still think it is the vision of a distant future, implying heavy changes and new fancy but expensive machines and tools. But it is first and foremost a digital transformation, and as such, will generate its share of data. It will therefore be possible to leverage the Big Data technological ecosystem to: -harness and bring value out of the data, -improve quality and conformance, -automate controls on the production line, -have a tight control on industrial and manufacturing processes as well as on the machinery and tools.

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“…There are even cases of classical neural network usage [31]. This can easily be generalized to any process and really deserve to be better known.…”

Section: Virtual Metrology For Allmentioning

confidence: 99%

Pragmatic Big Data and smart manufacturing

Benhenni¹

2017

18th International Congress of Metrology

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“…Hung et al [6] based on RBFN to develop a VM model for predicting CVD (Chemical Vapor Deposition) thickness in semiconductor manufacturing. Imai and Kitabata [7] developed a VM model to perform fault detection and classification for preventing copper interconnection from failure in SOC (System on Chip).…”

Section: Related Workmentioning

confidence: 99%

“…Most VM systems in the existing VM-related literature (such as Refs. [6][7][8][9][10][11][12][13]) did not address the plant-wide VM deployment issue.…”

Section: Related Workmentioning

confidence: 99%

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Development of cloud-based automatic virtual metrology system for semiconductor industry

Huang

Lin

Hung

et al. 2015

Robotics and Computer-Integrated Manufacturing

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“…Semiconductor fabrication facilities (fabs) can only maintain competitive advantages by effectively controlling process variation, fast yield ramp up, and quick response to yield excursion, especially when the complexity of the process and product increase rapidly. In particular, most of applications using various data mining technologies included root cause identification [8,9], process improvement [10], defect pattern diagnosis [11], equipment backup control [12], cycle time prediction [13,14], demand forecast [15,16], and virtual metrology [17,18]. Most applications are yield improvement for wafer manufacturing and test phase.…”

Section: Semiconductor Phase and Datamentioning

confidence: 99%

An Analytic Framework of Design for Semiconductor Manufacturing

Hsu

2015

Lecture Notes in Business Information Processing

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Abstract. The manufacturing intelligence behind data, process, and system are used to assist extracted from a large amount of manufacturing-related data from many sources, which presents the relevant knowledge to enhance decision quality with operational efficiency. Based on the data-driven view, this study aims to develop an analytic framework of design for semiconductor manufacturing. To demonstrate the proposed framework, a case study in semiconductor manufacturing regarding the layout design of chip size was conducted. The proposed framework can be used to extract useful information and assist effectively process operation by data mining methods with hybrid algorithms to enhance decision quality and production effectiveness.

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A Novel Virtual Metrology Scheme for Predicting CVD Thickness in Semiconductor Manufacturing

Cited by 99 publications

References 12 publications

Pragmatic Big Data and smart manufacturing

Pragmatic Big Data and smart manufacturing

Development of cloud-based automatic virtual metrology system for semiconductor industry

An Analytic Framework of Design for Semiconductor Manufacturing

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