Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Quality evaluation
Reexamination Certificate
2002-07-31
2003-12-16
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Quality evaluation
C324S765010, C438S014000
Reexamination Certificate
active
06665623
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates generally to the field of semiconductor device manufacturing and, more particularly, to a method and apparatus for optimizing downstream uniformity.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of processing steps is performed on a lot of wafers using a variety of process tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal process tools, implantation tools, etc. The technologies underlying semiconductor process tools have attracted increased attention over the last several years, resulting in substantial refinements. However, despite the advances made in this area, many of the process tools that are currently commercially available suffer certain deficiencies. In particular, such tools often lack advanced process data monitoring capabilities, such as the ability to provide historical parametric data in a user-friendly format, as well as event logging, real-time graphical display of both current processing parameters and the processing parameters of the entire run, and remote, i.e., local site and worldwide, monitoring. These deficiencies can engender non-optimal control of critical processing parameters, such as throughput, accuracy, stability and repeatability, processing temperatures, mechanical tool parameters, and the like. This variability manifests itself as within-run disparities, run-to-run disparities and tool-to-tool disparities that can propagate into deviations in product quality and performance, whereas an ideal monitoring and diagnostics system for such tools would provide a means of monitoring this variability, as well as providing means for optimizing control of critical parameters.
One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various process tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface that facilitates communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple manufacturing tools for multiple processes, generating data relating to the quality of the processed semiconductor devices.
During the fabrication process various events may take place that affect the performance of the devices being fabricated. That is, variations in the fabrication process steps result in device performance variations. Factors, such as feature critical dimensions, doping levels, contact resistance, particle contamination, etc., all may potentially affect the end performance of the device. Various tools in the processing line are controlled in accordance with performance models to reduce processing variation. Commonly controlled tools include photolithography steppers, polishing tools, etching tools, and deposition tools. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters, such as processing time, are calculated by the process controllers based on the performance model and the metrology information to attempt to achieve post-processing results as close to a target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate to increased profitability.
Target values for the various processes performed are generally based on design values for the devices being fabricated. For example, a particular process layer may have a target thickness. Operating recipes for deposition tools and/or polishing tools may be automatically controlled to reduce variation about the target thickness. In another example, the critical dimensions of a transistor gate electrode may have an associated target value. The operating recipes of photolithography tools and/or etch tools may be automatically controlled to achieve the target critical dimensions.
Typically, a control model is used to generate control actions for changing the operating recipe settings for a process tool being controlled based on feedback or feedforward metrology data collected related to the processing by the process tool. For some tools, the operating recipe parameters determined by the control model depend on a measure of uniformity on the wafer being processed. Various types of uniformity may be considered, such as feature critical dimension uniformity (e.g., line width, trench depth), process layer thickness uniformity, extent of sacrificial film removal (e.g., etch stop layer). Uniformity may vary in different ways across the wafer. For example, the uniformity may vary based on radial position or X-Y position (e.g., left-to-right). The control model may factor in the measured non-uniformity to attempt to reduce the variation after the next process has been performed. For example, a polishing tool may have separately controllable polishing zones that result in the polishing rate differing at different radial positions. This polishing variation may be used to polish a thicker portion of a process layer at a higher rate than a thinner portion, thus equalizing the process layer thickness after the polishing has completed. In another example, the parameters of an etch tool, such as plasma power, may be adjusted to compensate for variations in uniformity. Typically, adjusting the plasma power may affect whether the etch tool etches at a higher or lower rate in the center of the wafer as compared to the periphery.
In some cases, the non-uniformity present on the wafer may be of a high magnitude. For example, one region of the wafer (e.g., center) may have a characteristic that varies slightly from a target value, while another region (e.g., periphery) may have a characteristic that varies a greater amount. Attempting to process the wafer to compensate for the non-uniformity in the periphery region may actually deleteriously affect the center region, reducing the quality of the devices formed therein. For example, aggressive polishing in the periphery region may result in overpolishing in the center region that could cause dishing or erosion of features formed therein.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.
SUMMARY OF THE INVENTION
One aspect of the present invention is seen in a method that includes measuring a characteristic of a workpiece at a plurality of locations. A uniformity profile is generated based on the characteristic measurements. At least one acceptable region of the workpiece is identified based on the uniformity profile. At least one unacceptable region of the workpiece is identified based on the uniformity profile. The uniformity profile is filtered to remove at least a portion of the characteristic measurements associated with the secon
Bode Christopher A.
Pasadyn Alexander J.
Advanced Micro Devices , Inc.
Barlow John
Le John
Williams Morgan & Amerson P.C.
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