contributor author | Jionghua Jin | |
contributor author | Huairui Guo | |
contributor author | Shiyu Zhou | |
date accessioned | 2017-05-09T00:20:50Z | |
date available | 2017-05-09T00:20:50Z | |
date copyright | February, 2006 | |
date issued | 2006 | |
identifier issn | 1087-1357 | |
identifier other | JMSEFK-27914#315_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/134232 | |
description abstract | This paper presents a supervisory generalized predictive control (GPC) by combining GPC with statistical process control (SPC) for the control of the thin film deposition process. In the supervised GPC, the deposition process is described as an ARMAX model for each production run and GPC is applied to the in situ thickness-sensing data for thickness control. Supervisory strategies, developed from SPC techniques, are used to monitor process changes and estimate the disturbance magnitudes during production. Based on the SPC monitoring results, different supervisory strategies are used to revise the disturbance models and the control law in the GPC to achieve a satisfactory control performance. A case study is provided to demonstrate the developed methodology. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Statistical Process Control Based Supervisory Generalized Predictive Control of Thin Film Deposition Processes | |
type | Journal Paper | |
journal volume | 128 | |
journal issue | 1 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.2114912 | |
journal fristpage | 315 | |
journal lastpage | 325 | |
identifier eissn | 1528-8935 | |
keywords | Thin films | |
keywords | Predictive control | |
keywords | Statistical process control | |
keywords | Errors AND Modeling | |
tree | Journal of Manufacturing Science and Engineering:;2006:;volume( 128 ):;issue: 001 | |
contenttype | Fulltext | |