Abstract
In the present paper we address the problem of control relevant process modeling from production data for the N-Well Reactive Ion Etching processed by LAM Rainbow Etchers. Due to physical constraints we consider building an empirical neural network model using one lot of data which usually contains 24 wafers. Using the existence result of feedforward networks as universal approximators, we experimentally developed different network structures as models of the etching process under investigation. Our results are built upon extensive simulations on different lots of the process.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the American Control Conference |
| Publisher | IEEE |
| Pages | 1583-1587 |
| Number of pages | 5 |
| Volume | 3 |
| State | Published - 1997 |
| Event | Proceedings of the 1997 American Control Conference. Part 3 (of 6) - Albuquerque, NM, USA Duration: Jun 4 1997 → Jun 6 1997 |
Other
| Other | Proceedings of the 1997 American Control Conference. Part 3 (of 6) |
|---|---|
| City | Albuquerque, NM, USA |
| Period | 6/4/97 → 6/6/97 |
ASJC Scopus subject areas
- Control and Systems Engineering