Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system
Reexamination Certificate
2002-05-31
2004-07-20
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Mechanical measurement system
C702S035000, C702S034000, C702S177000, C702S185000, C702S189000, C700S174000, C700S178000, C073S865900, C340S680000, C318S565000
Reexamination Certificate
active
06766258
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 dynamically enabling trace data collection.
2. Description of the Related Art
There is a constant drive in the semiconductor industry to increase the quality, reliability, and throughput of integrated circuit devices such as 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 by the consumer have resulted in some improvements in the manufacture of semiconductor devices as well as in the manufacture of integrated circuit devices incorporating such semiconductor devices. Reducing the defects in the manufacture of these devices lowers the cost of the devices themselves. Accordingly, the cost of the final product incorporating these devices is also reduced, thus providing inherent monetary benefits to both the consumer and manufacturer.
The semiconductor manufacturing processes have become more reliable and robust over the past few years. In fact, today's semiconductor manufacturing processes may include an intricate network of multiple process tools for manufacturing semiconductor devices. While the benefits of linking multiple process tools are inherently obvious, there can, however, be some drawbacks, particularly from the standpoint of troubleshooting problems or faults. That is, determining the source of a fault that occurs during the semiconductor manufacturing process may prove to be challenging, as the fault may have occurred in any one of the several process tools that operate on the semiconductor device along the way. Failing to identify the source of the problem expeditiously may naturally delay any potential corrective measures that can be taken to address the problem. Because of these delays, the operation of the semiconductor manufacturing process may be adversely affected, thereby resulting in a potential increase in costs for the manufacturer and consumer.
One technique for identifying the behavior of a process tool involves collecting tool trace data during a processing run of the tool. The particular tool trace information collected depends on the specific process performed by the process tool. For example, exemplary tool trace data for an etch tool may include gas flow, chamber pressure, chamber temperature, voltage, reflected power, backside helium pressure, RF tuning parameters, etc. The tool trace data may also include data external to the process tool, such as ambient temperature, humidity, pressure, etc. Based on the tool state trace data collected, a monitoring device may evaluate the overall health of the process tool. One technique for monitoring the health of the process tool
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involves employing a multivariate tool health model adapted to predict the expected operating parameters of the process tool during the processing run. If the actual observed tool parameters are close to the predicted tool parameters, the process tool is said to have a high health metric (i.e., the process tool is operating as expected). As the gap between the expected tool parameters and the observed tool parameters widens, the tool health metric decreases. For example, the tool health metric may be expressed as a percentage, with a 100% tool health value equating to a perfect match between the expected tool parameters and the observed tool parameters.
Typically, the tool health model used to predict the operating parameters of the process tool, thereby measuring the health of the process tool, is based on the particular process tool and the base operating recipe employed by the process tool for processing the wafers. Hence, the process tool may have a separate tool health model for each of the base operating recipes run on the process tool. An exemplary tool health monitor software application is ModelWare™ offered by Triant, Inc. of Nanaimo, British Columbia, Canada Vancouver, Canada. An exemplary system for monitoring tool health is described in U.S. patent application Ser. No. 09/863,822, entitled “METHOD AND APPARATUS FOR MONITORING TOOL HEATH,” filed in the names of Elfido Coss Jr., Richard J. Markle, and Patrick M. Cowan, that is assigned to, the assignee of the present application and incorporated herein by reference in its entirety.
One limitation of a tool health monitoring technique is the extensive level of resources required to collect and process the data. The volume of data collected for the tool health analysis consumes significant storage resources. Also, the processing resources required to perform the analysis is significant. Wide-scale tool health monitoring may significantly tax the storage and processing bandwidth of the factory management system.
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 including identifing a degraded condition associated with the processing of a workpiece. At least one process tool associated with the degraded condition is identified. Trace data collection is enabled for the identified process tool.
Another aspect of the present invention is seen in a system including a processing system configured to process a workpiece and a tool monitor. The tool monitor is configured to identify a degraded condition associated with the processing of the workpiece, identify at least one process tool from the processing system associated with the degraded condition, and enable trace data collection for the identified process tool.
REFERENCES:
patent: 4559600 (1985-12-01), Rao
patent: 6266132 (2001-07-01), Stewart et al.
patent: 6512991 (2003-01-01), Davis et al.
patent: 2002/0177245 (2002-11-01), Sonderman et al.
Haiyun et al., “An On-Line Measuring Method of Workpiece Diameter Based on the Principle of 3-Sensor Error Separation”, Jan. 1990, IEEE, pp. 1308-1312.
Hickey Susan
Stewart Edward C.
Advanced Micro Devices , Inc.
Desta Elias
Hoff Marc S.
Williams Morgan & Amerson
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