Plasma information-based virtual metrology (PI-VM) and mass production process control

Park, Seolhye; Seong, Jaegu; Jang, Yongwon; Roh, Hyun-Joon; Kwon, Ji-Won; Lee, Jin Young; Ryu, Sangwon; Song, Ju Sun; Roh, Ki-Baek; Noh, Yeongil; Park, Yoona; Jang, Yongsuk; Cho, Taeyoung; Yang, Jungjin; Kim, Gon−Ho

doi:10.1007/s40042-022-00452-8

Cited by 8 publications

(3 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Building upon the foundations of previous research in PI-VM, it is evident that the approach to PI parameterization has been instrumental in crafting high-precision VM. This methodology demonstrated significant success in real-world OLED display production [15]. While these contributions have been pivotal in highlighting the potential of PI-VM to overcome challenges commonly observed in statistics-based VM models, our investigation takes a step further.…”

Section: Introductionmentioning

confidence: 92%

“…Real-time process diagnosis has been developed by applying machine learning (ML) techniques using input parameters and process results combined with virtual metrology (VM) technology [7][8][9][10][11][12][13][14]. Recently, plasma-information-based virtual metrology (PI-VM) has been actively researched, and highly accurate virtual models that predict process results by linking plasma factors that affect process characteristics have been developed [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial-Neural-Network-Driven Innovations in Time-Varying Process Diagnosis of Low-K Oxide Deposition

Lee,

Park,

Liu

et al. 2023

Sensors

View full text Add to dashboard Cite

To address the challenges in real-time process diagnosis within the semiconductor manufacturing industry, this paper presents a novel machine learning approach for analyzing the time-varying 10th harmonics during the deposition of low-k oxide (SiOF) on a 600 Å undoped silicate glass thin liner using a high-density plasma chemical vapor deposition system. The 10th harmonics, which are high-frequency components 10 times the fundamental frequency, are generated in the plasma sheath because of their nonlinear nature. An artificial neural network with a three-hidden-layer architecture was applied and optimized using k-fold cross-validation to analyze the harmonics generated in the plasma sheath during the deposition process. The model exhibited a binary cross-entropy loss of 0.1277 and achieved an accuracy of 0.9461. This approach enables the accurate prediction of process performance, resulting in significant cost reduction and enhancement of semiconductor manufacturing processes. This model has the potential to improve defect control and yield, thereby benefiting the semiconductor industry. Despite the limitations imposed by the limited dataset, the model demonstrated promising results, and further performance improvements are anticipated with the inclusion of additional data in future studies.

show abstract

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Artificial-Neural-Network-Driven Innovations in Time-Varying Process Diagnosis of Low-K Oxide Deposition

Lee,

Park,

Liu

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Nevertheless, most previous studies, especially in the computational area, have focused only on the problems induced by vertical scaling technology, not lateral scaling, especially in the HARC etching process. 8,9,[12][13][14][15] In this article, we address cell density-dependent feature-to-feature variation and distortion induced by lateral scaling, i.e., more holes between slots, during the HARC etching process for the first time. Moreover, the effects of heavy inert ions that incident into the feature of unpreferred etching profiles are investigated.…”

Section: Introductionmentioning

confidence: 99%

Effect of heavy inert ion strikes on cell density-dependent profile variation and distortion during the etching process for high-aspect ratio features

et al. 2022

View full text Add to dashboard Cite

Vertical scaling technique faces a physical limitation in 3D NAND device fabrication, even assuming superior etching technology. Another promising scaling technique to increase the storage density is lateral scaling, which increases the number of holes between slit and slit from four to nine and above. However, unpredictable small critical dimension, feature-to-feature variation, and distortion occur. To elucidate the profile deteriorations induced by the lateral scaling, we analyzed the effect of the angular etching yield dependency of the incident ion fluxes into a given feature using the multiscale technology computer-aided design methodology. As one of the inherent features of the gas, incident angle θmax in which the sputtering yield achieves its maximum value is a crucial factor for analyzing and modeling etching profiles. Moreover, the impact of the heavy inert ion strikes on the unpreferred etching profiles was investigated. In this study, the synergy of lower energy ions, larger fluxes, and larger θmax of heavy inert ions decrease the feature-to-feature variation, reducing hard mask distortion without the etch rate reduction.

show abstract

Virtual metrology for enabling zero-defect manufacturing: a review and prospects

Zhang,

Li,

2024

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Plasma information-based virtual metrology (PI-VM) and mass production process control

Cited by 8 publications

References 55 publications

Artificial-Neural-Network-Driven Innovations in Time-Varying Process Diagnosis of Low-K Oxide Deposition

Artificial-Neural-Network-Driven Innovations in Time-Varying Process Diagnosis of Low-K Oxide Deposition

Effect of heavy inert ion strikes on cell density-dependent profile variation and distortion during the etching process for high-aspect ratio features

Virtual metrology for enabling zero-defect manufacturing: a review and prospects

Contact Info

Product

Resources

About