Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing

Speeding up the simulation of discrete-event wafer-fabrication models is essential for fast decision-making to handle unexpected events in smart semiconductor manufacturing because decision-parameter optimization requires repeated simulation execution based on the current manufacturing situation. In...

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Main Authors: Seok, Moon Gi, Cai, Wentong, Sarjoughian, Hessam S., Park, Daejin
Other Authors: School of Computer Science and Engineering
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Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/145810
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1458102021-01-08T08:31:03Z Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing Seok, Moon Gi Cai, Wentong Sarjoughian, Hessam S. Park, Daejin School of Computer Science and Engineering Engineering::Electrical and electronic engineering Abstraction-level Conversion Wafer Fabrication Speeding up the simulation of discrete-event wafer-fabrication models is essential for fast decision-making to handle unexpected events in smart semiconductor manufacturing because decision-parameter optimization requires repeated simulation execution based on the current manufacturing situation. In this paper, we present a runtime abstraction-level conversion approach for discrete-event fab models to gain simulation speedup. During the simulation, if the fab's machine group model reaches a steady state, then the proposed method attempts to substitute this group model with a mean-delay model (MDM) as a high abstraction level model. The MDM abstracts detailed event-driven operations of subcomponents in the group into an average delay based on the queuing modeling, which can guarantee acceptable accuracy in predicting the performance of steady-state queuing systems. To detect the steadiness, the proposed abstraction-level converter (ALC) observes the queuing parameters of low-level groups to identify the statistical convergence of each group's work-in-progress (WIP) level. When a group's WIP level is converged, the output-to-input couplings between the models are revised to change a wafer-lot process flow from the low-level group to a MDM. When the ALC detects lot-arrival changes or any wafer processing status change (e.g., a machine-down), the high-level model is switched back to its corresponding low-level group model. During high-to-low level conversion, the ALC generates dummy wafer-lot events to re-initialize the machine states. The proposed method was applied to various case studies of wafer-fab systems and achieved simulation speedups up to about 4 times with 0.6 to 8.3% accuracy degradations. Agency for Science, Technology and Research (A*STAR) Published version This research is supported by Agency for Science, Technology and Research (A*STAR) Singapore, under its Research Innovation Enterprise (RIE) 2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund-Pre-Positioning (IAF-PP) Program Grant No. A19C1a0018, and partially supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF2019R1A2C2005099, NRF2018R1A6A1A03025109). 2021-01-08T08:31:02Z 2021-01-08T08:31:02Z 2020 Journal Article Seok, M. G., Cai, W., Sarjoughian, H. S., & Park, D. (2020). Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing. IEEE Access, 8, 165247-165262. doi:10.1109/ACCESS.2020.3022275 2169-3536 https://hdl.handle.net/10356/145810 10.1109/ACCESS.2020.3022275 8 165247 165262 en A19C1a0018 IEEE Access © 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Abstraction-level Conversion
Wafer Fabrication
spellingShingle Engineering::Electrical and electronic engineering
Abstraction-level Conversion
Wafer Fabrication
Seok, Moon Gi
Cai, Wentong
Sarjoughian, Hessam S.
Park, Daejin
Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
description Speeding up the simulation of discrete-event wafer-fabrication models is essential for fast decision-making to handle unexpected events in smart semiconductor manufacturing because decision-parameter optimization requires repeated simulation execution based on the current manufacturing situation. In this paper, we present a runtime abstraction-level conversion approach for discrete-event fab models to gain simulation speedup. During the simulation, if the fab's machine group model reaches a steady state, then the proposed method attempts to substitute this group model with a mean-delay model (MDM) as a high abstraction level model. The MDM abstracts detailed event-driven operations of subcomponents in the group into an average delay based on the queuing modeling, which can guarantee acceptable accuracy in predicting the performance of steady-state queuing systems. To detect the steadiness, the proposed abstraction-level converter (ALC) observes the queuing parameters of low-level groups to identify the statistical convergence of each group's work-in-progress (WIP) level. When a group's WIP level is converged, the output-to-input couplings between the models are revised to change a wafer-lot process flow from the low-level group to a MDM. When the ALC detects lot-arrival changes or any wafer processing status change (e.g., a machine-down), the high-level model is switched back to its corresponding low-level group model. During high-to-low level conversion, the ALC generates dummy wafer-lot events to re-initialize the machine states. The proposed method was applied to various case studies of wafer-fab systems and achieved simulation speedups up to about 4 times with 0.6 to 8.3% accuracy degradations.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Seok, Moon Gi
Cai, Wentong
Sarjoughian, Hessam S.
Park, Daejin
format Article
author Seok, Moon Gi
Cai, Wentong
Sarjoughian, Hessam S.
Park, Daejin
author_sort Seok, Moon Gi
title Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
title_short Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
title_full Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
title_fullStr Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
title_full_unstemmed Adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
title_sort adaptive abstraction-level conversion framework for accelerated discrete-event simulation in smart semiconductor manufacturing
publishDate 2021
url https://hdl.handle.net/10356/145810
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