Predictive Maintenance for Improved Sustainability - An Ion Beam Etch Endpoint Detection System Use Case

Jian Wan, Seán McLoone, Patrick English, Paul G. O'Hara, Adrian Johnston

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In modern semiconductor manufacturing facilities maintenance strategies are increasingly shifting from traditional preventive maintenance (PM) based approaches to more efficient and sustainable predictive maintenance (PdM) approaches. This paper describes the development of such an online PdM module for the endpoint detection system of an ion beam etch tool in semiconductor manufacturing. The developed system uses optical emission spectroscopy (OES) data from the endpoint detection system to estimate the RUL of lenses, a key detector component that degrades over time. Simulation studies for historical data for the use case demonstrate the effectiveness of the proposed PdM solution and the potential for improved sustainability that it affords.
Original languageEnglish
Title of host publicationIntelligent Computing in Smart Grid and Electrical Vehicles
Subtitle of host publicationInternational Conference on Life System Modeling and Simulation, LSMS 2014 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2014 Shanghai, China, September 20-23, 2014 Proceedings, Part III
EditorsKang Li, Yusheng Xue, Shumei Cui, Qun Niu
PublisherSpringer
Pages147-156
Volume463
ISBN (Electronic)978-3-662-45286-8
ISBN (Print)978-3-662-45285-1
DOIs
Publication statusPublished - 2014
Event2014 Intelligent Computing for Sustainable Energy and Environment (ICSEE'2014) - Shanghai, China
Duration: 20 Sep 201423 Nov 2014

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer Berlin Heidelberg
Volume463
ISSN (Print)1865-0929

Conference

Conference2014 Intelligent Computing for Sustainable Energy and Environment (ICSEE'2014)
CountryChina
CityShanghai
Period20/09/201423/11/2014

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  • Cite this

    Wan, J., McLoone, S., English, P., O'Hara, P. G., & Johnston, A. (2014). Predictive Maintenance for Improved Sustainability - An Ion Beam Etch Endpoint Detection System Use Case. In K. Li, Y. Xue, S. Cui, & Q. Niu (Eds.), Intelligent Computing in Smart Grid and Electrical Vehicles: International Conference on Life System Modeling and Simulation, LSMS 2014 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2014 Shanghai, China, September 20-23, 2014 Proceedings, Part III (Vol. 463, pp. 147-156). (Communications in Computer and Information Science; Vol. 463). Springer. https://doi.org/10.1007/978-3-662-45286-8_16