Data processing: generic control systems or specific application – Specific application – apparatus or process – Product assembly or manufacturing
Reexamination Certificate
2001-02-23
2004-08-31
Picard, Leo (Department: 2125)
Data processing: generic control systems or specific application
Specific application, apparatus or process
Product assembly or manufacturing
C700S100000, C700S103000, C700S121000, C702S182000, C702S183000, C702S184000, C702S185000
Reexamination Certificate
active
06785586
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 adaptively scheduling tool maintenance.
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 processing tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. The technologies underlying semiconductor processing 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 processing 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 nonoptimal 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 semiconductor processing line includes using a factory wide control system to automatically control the operation of the various processing 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 which 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.
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.
Commonly, a processing tool undergoes periodic preventative maintenance procedures or calibrations to keep the tool in optimum operating condition. For example, polishing tools include polishing pads that are periodically conditioned or replaced. Etch tools and deposition tools are periodically cleaned using both in situ cleans or complete disassembly cleans. Steppers are periodically calibrated to maintain alignment accuracy and exposure dose consistency. Many of these preventative maintenance procedures are performed at discrete intervals based on vendor recommendations, past history, and expected degradation rates of consumable items used in the tools. The use of fixed preventative maintenance intervals is not always an effective solution for optimizing tool and line efficiency. If the maintenance activities are performed more often than actually needed, the efficiency of the line and the operation cost of the tool is increased. If maintenance activities are performed less often than needed, product quality and tool reliability may be degraded.
Another potential drawback of scheduled maintenance intervals is that unexpected conditions may arise during the time period between maintenance activities. For example, the calibration of a tool (e.g., focus on a stepper) may drift outside expected tolerances. A process controller used to control a particular tool may adjust the operating recipe of the tool trying to correct for what it thinks is normal process variation, while in actuality, the variation is caused by the unexpected condition. Over time, the process controller may adjust its performance model based on post-processing metrology feedback. In some situations, the process controller might not be able to stabilize the process. These control problems may result in increased variation or even defective wafers.
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 for adaptively scheduling tool maintenance. The method includes controlling an operating recipe of a tool using a plurality of control actions, monitoring the control actions to identify a degraded tool condition, and automatically initiating a tool maintenance recommendation in response to identifying the degraded tool condition.
Another aspect of the present invention is seen in a manufacturing system including a tool, a process controller, and a tool health monitor. The tool is adapted to process a workpiece in accordance with an operating recipe. The process controller is adapted to control the operating recipe of the tool using a plurality of control actions. The tool health monitor is adapted to monitor the control actions to identify a degraded tool condition and automatically initiate a tool maintenance recommendation in response to identifying the degraded tool condition.
REFERENCES:
patent: 5446672 (1995-08-01), Boldys
patent: 5934974 (1999-08-01), Tzeng
patent: 6138056 (2000-10-01), Hardesty et al.
patent: 6217412 (2001-04-01), Campbell et al.
patent: 6326309 (2001-12-01), Hatanaka et al.
Bode Christopher A.
Hewett Joyce S. Oey
Miller Michael L.
Pasadyn Alexander J.
Peterson Anastasia Oshelski
Kasenge Charles
Picard Leo
Williams Morgan & Amerson P.C.
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