Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/46409
標題: Grey forecasting run-to-run control system in copper chemical mechanical polishing
作者: Wang, G.J.
王國禎
Wang, M.T.
Yang, F.C.
Huang, M.L.
Loh, K.N.
Chen, J.
關鍵字: Copper chemical mechanical polishing (CMP);Run-to-run process control;Grey forecasting model (GFM);Recursive least-squares (RLS) algorithm;Semiconductors;Forecast;Simulations
Project: International Journal of Advanced Manufacturing Technology
期刊/報告no:: International Journal of Advanced Manufacturing Technology, Volume 41, Issue 1-2, Page(s) 48-56.
摘要: 
In this paper, an online grey forecasting run-to-run control system was proposed with the integration of run-to-run control system, recursive least-squares (RLS) algorithm, and grey forecasting model (GFM). One of the objectives of this study is to explore the possibility and feasibility of applying GFM to run-to-run control system in copper chemical mechanical polishing. Under the condition of limited experiment data, GFM is excellent at estimating and forecasting error of the next batch online. To keep the process under control, the controllers are then employed to adjust the process parameters in order to compensate the error. In addition, the RLS algorithm is used to construct dynamically a system estimation matrix for the purpose of stating precisely the relationship between process quality and process parameters, and to consequently improve processing performances. From the computer simulation and the experiment results, the proposed new method developed in this study was able not only to confine the processing performances' error within the range of 5% but also to supplement, when the process parameters are saturated, the control capability through adjusting other unsaturated process parameters, thus maintaining good processing performances.
URI: http://hdl.handle.net/11455/46409
ISSN: 0268-3768
DOI: 10.1007/s00170-008-1452-2
Appears in Collections:生醫工程研究所

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