Condition monitoring and operational decision making in semiconductor manufacturing


Autoria(s): Cholette, Michael E.; Celen, Merve; Djurdjanovic, Dragan; Rasberry, John D.
Data(s)

01/11/2013

Resumo

Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/64647/

Publicador

Institute of Electrical and Electronics Engineers

Relação

http://eprints.qut.edu.au/64647/1/cholette_et_al_IEEE_TSM_accepted_version.pdf

http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6532392

DOI:10.1109/TSM.2013.2268861

Cholette, Michael E., Celen, Merve, Djurdjanovic, Dragan, & Rasberry, John D. (2013) Condition monitoring and operational decision making in semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 26(4), pp. 454-464.

Direitos

Copyright 2013 IEEE

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Fonte

School of Chemistry, Physics & Mechanical Engineering; Science & Engineering Faculty

Palavras-Chave #Condition monitoring #Condition-based maintenance #Semiconductor manufacturing
Tipo

Journal Article