Optimal parameter estimation for the online control of ion milling etch depth
Identifieur interne : 000929 ( Main/Exploration ); précédent : 000928; suivant : 000930Optimal parameter estimation for the online control of ion milling etch depth
Auteurs : Eric J. Klein [États-Unis] ; W. Fred Ramirez [États-Unis]Source :
- AIChE Journal [ 0001-1541 ] ; 2002-02.
Abstract
The use of optimal parameter estimation for the online regulation of final etch depth in an ion milling process is described. A model‐based control system utilizes a 3‐D surface evolution model to predict dynamic surface profiles and etch depth. A heterodyne laser interferometer is used to measure trench height in situ for calculation of the difference in etch rates between the photoresist layer and the exposed portion of the underlying substrate layer. Adaptive material‐specific etch rate parameters and operating parameters such as ion beam strength and angle of incidence are estimated optimally with an extended Kalman filter. Optimal estimates of the in situ etch depth are calculated from the adaptive model, allowing the stopping time of the milling process to be varied from run to run to regulate final etch depth in the presence of disturbances. The system installed on an ion milling machine shows that the controller is capable of accurately regulating final etch depth in the presence of large process faults.
Url:
DOI: 10.1002/aic.690480215
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">The use of optimal parameter estimation for the online regulation of final etch depth in an ion milling process is described. A model‐based control system utilizes a 3‐D surface evolution model to predict dynamic surface profiles and etch depth. A heterodyne laser interferometer is used to measure trench height in situ for calculation of the difference in etch rates between the photoresist layer and the exposed portion of the underlying substrate layer. Adaptive material‐specific etch rate parameters and operating parameters such as ion beam strength and angle of incidence are estimated optimally with an extended Kalman filter. Optimal estimates of the in situ etch depth are calculated from the adaptive model, allowing the stopping time of the milling process to be varied from run to run to regulate final etch depth in the presence of disturbances. The system installed on an ion milling machine shows that the controller is capable of accurately regulating final etch depth in the presence of large process faults.</div>
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