Download Run-to-Run Control in Semiconductor Manufacturing by James Moyne, Enrique del Castillo, Arnon M. Hurwitz PDF

By James Moyne, Enrique del Castillo, Arnon M. Hurwitz

Run-to-run (R2R) regulate is state-of-the-art know-how that permits amendment of a product recipe among desktop "runs," thereby minimizing procedure float, shift, and variability-and with them, expenditures. Its effectiveness has been tested in quite a few methods, comparable to vapor part epitaxy, lithography, and chemical mechanical planarization. the single barrier to the semiconductor industry's frequent adoption of this powerful method keep an eye on is an absence of figuring out of the expertise. Run to Run keep an eye on in Semiconductor production overcomes that barrier by means of delivering in-depth analyses of R2R keep an eye on.

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Advanced process control can reduce the requirement for NP wafers by more quickly qualifying the process. This capability is largely a function of the control algorithm used and, more specifically, the capability of the control algorithm to model the process shift associated with the PM event and any transient process behavior that directly follows this event. This topic is explored further in Chapter 18. 3 Benefit: Improved Wafer-to-Wafer and Lot-to-Lot Variability It has been suggested that process control will greatly improve wafer-to-wafer or lotto-lot processing quality.

The main purpose of this chapter is to provide the reader with a snapshot of the technical issues — past, present, and future — that are shaping the field of R2R control in semiconductor manufacturing. With this information, the reader is provided with a foundation for understanding the detailed aspects of R2R control that are described in the chapters that follow. 1 An uncontrolled drifting process. 1 However, new problems were beginning to emerge. Many processes were exhibiting steady drift in equipment performance.

SPC is a technique aimed at monitoring deviations from statistical control, a state of a process where measurements follow a stable, uncorrelated process. Derivations are usually identified through applying a set of rules or filters to the data. , removal of the assignable cause of variation, is usually left unmodeled, under the assumption that a process engineer will try to fix the problem at its root. Removal of the cause of variation avoids further occurrences of this problem in the future. 59 © 2001 by CRC Press LLC 1.

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