DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Funk et al. US 2005/0187649 (“Funk”).
Funk discloses:
1. An electronic device manufacturing system, comprising:
a process tool (e.g., Fig. 1 #110); and
a tool server coupled to the process tool and comprising a communication node (e.g., Fig. 1 #150) and an evaluation system (e.g., Fig. 1 #160), wherein the communication node is configured to:
receive, from a monitoring device registered on the process tool (e.g., [0026]: “processing tool 110 can comprise a tool agent (not shown)”), data based on a data collection plan (e.g., [0026]: “which can be a software process that runs on a tool 110 and which can provide event information, context information, and start-stop timing commands used to synchronize data acquisition with the tool process”, [0036], [0043]-[0044]: “data collection plan”);
send the received data to the evaluation system (e.g., [0076]: “collecting data and then feeding that data into a software algorithm that models the behavior of a particular tool, process module, and/or sensor”);
receive, from the evaluation system, feedback data based on the received data (e.g., [0076]: “The APC system outputs process parametric adaptations that are then either fed forward or back”); and
cause the process tool to perform a corrective action based on the feedback data (e.g., [0076]: “fed forward or back to keep tool performance within the specified limits”, [0156]).
2. The electronic device manufacturing system of claim 1, wherein the tool server is configured to send the feedback data to a client device (e.g., Fig. 1 #170, [0053], [0061]).
3. The electronic device manufacturing system of claim 1, wherein the communication node communicates with the evaluation system and the process tool using Remote Procedure Calls (e.g., [0030]).
4. The electronic device manufacturing system of claim 1, wherein the feedback data comprises at least one of predictive data, diagnostic data, corrective data, optimization data, efficiency data, or health data (e.g., [0055]).
5. The electronic device manufacturing system of claim 1, wherein the communication node is further configured to: send the feedback data to a client device (e.g., Fig. 1 #170, [0053], [0061]).
6. The electronic device manufacturing system of claim 1, wherein the monitoring device comprises at least one of a device driver, an application programming interface (API), a software application, a virtual device, an image file, or firmware (e.g., [0026]: “processing tool 110 can comprise a tool agent (not shown)”, which can be a software process that runs on a tool 110”).
7. The electronic device manufacturing system of claim 1, wherein the monitoring device provides a data collection plan that is based on one or more attributes, wherein the one or more attributes comprise at least one of an input used by the process tool, an output generated from the process tool, a control mode, a recipe set-point to be monitored, or an equipment constant to be monitored (e.g., [0043]-[0048]).
8. The electronic device manufacturing system of claim 1, wherein the monitoring device is registered with a frontend server of the process tool (e.g., [0035]: “a common tool agent can be installed on a plurality of processing tools”).
9. The electronic device manufacturing system of claim 1, wherein the evaluation system comprises at least one of a machine learning model, an inference engine, a heuristics model, a physics-based engine, or an algorithm (e.g., [0055]: “performs multivariate analysis of summary data using models based upon historical data”, [0076]-[0077]).
10. The electronic device manufacturing system of claim 1, wherein the monitoring device is configured to obtain the received data via a system bus of the process tool (e.g., Fig. 7).
11. The electronic device manufacturing system of claim 1, wherein the communication node comprises a gateway node (e.g., [0022]: “IS 150 can comprise a real-time memory database that can be viewed as a “Hub”) that configures the monitoring device and communicates with a plurality of evaluation systems (e.g., [0051]-[0053]).
12. The electronic device manufacturing system of claim 1, wherein the communication node is further configured to:
register the monitoring device with the process tool without causing software changes to the process tool (e.g., [0064]: “configuration component for allowing a user to configure processing tools, processing modules, sensors”).
13. The electronic device manufacturing system of claim 1, wherein the communication node is further configured to:
assign, to a process recipe step of a process recipe, a trigger function (e.g., [0046], [0071]); and
responsive to receiving an indication associated with an output of the trigger function, initiating, via the monitoring device, data collection operations (e.g., [0046], [0071]).
14. A method, comprising:
receiving, by a processing device, from a monitoring device registered on a process tool (e.g., [0026]: “processing tool 110 can comprise a tool agent (not shown)”), data based on a data collection plan (e.g., [0026]: “which can be a software process that runs on a tool 110 and which can provide event information, context information, and start-stop timing commands used to synchronize data acquisition with the tool process”, [0036], [0043]-[0044]: “data collection plan”);
sending the received data to an evaluation system (e.g., [0076]: “collecting data and then feeding that data into a software algorithm that models the behavior of a particular tool, process module, and/or sensor”);
receiving, from the evaluation system, feedback data based on the received data (e.g., [0076]: “The APC system outputs process parametric adaptations that are then either fed forward or back”); and
causing the process tool to perform a corrective action based on the feedback data (e.g., [0076]: “fed forward or back to keep tool performance within the specified limits”, [0156]).
15. The method of claim 14, wherein the monitoring device comprises at least one of a device driver, an application programming interface (API), a software application, a virtual device, an image file, or firmware (e.g., [0026]: “processing tool 110 can comprise a tool agent (not shown)”, which can be a software process that runs on a tool 110”).
16. The method of claim 14, wherein the monitoring device is registered with a frontend server of the process tool (e.g., [0035]: “a common tool agent can be installed on a plurality of processing tools”).
17. The method of claim 14, wherein the monitoring device is configured to obtain the received data via a system bus of the process tool (e.g., Fig. 7).
18. The method of claim 14, wherein the evaluation system comprises at least one of a machine learning model, an inference engine, a heuristics model, a physics-based engine, or an algorithm (e.g., [0055]: “performs multivariate analysis of summary data using models based upon historical data”, [0076]-[0077]).
19. The method of claim 14, further comprising: communicating with the evaluation system and the process tool using Remote Procedure Calls (e.g., [0030]).
20. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processing device operatively coupled to a memory, performs operations comprising:
receiving from a monitoring device registered on a process tool (e.g., [0026]: “processing tool 110 can comprise a tool agent (not shown)”), data based on a data collection plan (e.g., [0026]: “which can be a software process that runs on a tool 110 and which can provide event information, context information, and start-stop timing commands used to synchronize data acquisition with the tool process”, [0036], [0043]-[0044]: “data collection plan”);
sending the received data to an evaluation system (e.g., [0076]: “collecting data and then feeding that data into a software algorithm that models the behavior of a particular tool, process module, and/or sensor”);
receiving, from the evaluation system, feedback data based on the received data (e.g., [0076]: “The APC system outputs process parametric adaptations that are then either fed forward or back”); and
causing the process tool to perform a corrective action based on the feedback data (e.g., [0076]: “fed forward or back to keep tool performance within the specified limits”, [0156]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Toprac et al. US 6,622,059 discloses an automated process monitoring method comprising processing a workpiece, measuring a parameter characteristic of the processing, and forming an output signal corresponding to the characteristic parameter measured by using the characteristic parameter measured as an input to a transistor model. The method also comprises predicting a wafer electrical test (WET) resulting value based on the output signal, detecting faulty processing based on the predicted WET resulting value, and correcting the faulty processing.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN A JARRETT whose telephone number is (571)272-3742. The examiner can normally be reached M-F 9:00-5:30.
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/RYAN A JARRETT/
Primary Examiner, Art Unit 2116
03/13/26
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