DETAILED ACTION
Notice of Pre-AIA or AIA Status
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3, 5-7, 13, and 16-17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 3 recites that “the plating solution motion information” may include “an amount of liquid of the plating solution stored in the plating tank.” Does the applicant intend this to mean an amount of liquid provided to the tank, or an amount of liquid present in the tank at a given moment? Since the information is labeled “motion information,” the examiner assumes the applicant intends to describe moving an amount of liquid into a tank. This interpretation will be used for examination purposes.
Claim 5 recites that “the substrate plating device includes…a surrounding plating tank corresponding to the plating tank disposed near the target plating tank as a plurality of the plating tanks.” The examiner is confused by this language, and considers that any of the following could be intended by the applicant:
The substrate plating device has two tanks, one is the target tank, and the other is the surrounding tank;
The substrate plating device has more than two tanks, one is designated as the target tank, and one of the other tanks is designated as the surrounding tank;
The substrate plating device has more than two tanks, one is designated as the target tank, and all of the others are designated surrounding tanks; or
The substrate plating device has more than two tanks, one is designated as the target tank, and one or more (not necessarily all) of the others are designated surrounding tanks.
Furthermore, claim 5 recites that “the substrate plating device includes…a surrounding paddle corresponding to the paddle installed in the surrounding plating tank as a plurality of the paddles.” This is similarly confusing, as it is unclear whether there is just one surrounding paddle, or multiple surrounding paddles.
From ¶94 of the application, it seems that the applicant intends to collect data from all paddles, one of which is designated as the target paddle and the rest of which are surrounding paddles. However, the claim language seems to suggest that a broader interpretation is desirable. Therefore, the examiner assumes that the fourth interpretation above is the applicant’s intent. To reflect this meaning, the examiner recommends rewriting claim 5 to read:
The information processing device according to claim 1, wherein the substrate plating device includes:
a target plating tank corresponding to the plating tank in which the target paddle is installed and [[a]] one or more surrounding plating tanks corresponding to [[the]] plating tanks disposed near the target plating tank as a plurality of the one or more plating tanks; and
the target paddle and [[a]] one or more surrounding paddles corresponding to [[the]] paddles installed in the one or more surrounding plating tanks as a plurality of the one or more paddles,
wherein the operational motion information further includes surrounding paddle motion information indicating the agitating motion of the one or more surrounding paddles.
This explicitly references the “one or more plating tanks” and “one or more paddles” included in the “substrate plating device” in claim 1. The examiner will use this interpretation for examination purposes, and welcomes any clarifications by the applicant.
Claims 6-7 and 13 depend from claim 5, therefore they inherit the same issues and are rejected for the same reasons.
Claim 16 recites “a substrate plating device” which “[serves] as: the information processing device according to claim 1.” This is confusing for multiple reasons. Firstly, it refers to “a substrate plating device” but depends from claim 1 which already recites a “substrate plating device”; does the applicant intend for these to refer to the same substrate plating device? Secondly, since the substrate plating device of claim 16 can be interpreted as separate from that of claim 1, one could interpret the substrate plating device of claim 16 as only requiring the ability to perform the information processing device’s functions.
The examiner assumes that the applicant intends to recite the substrate plating device described in claim 1, and to further recite that it comprises the information processing device according to claim 1.
Rewriting claim 16 to reflect the above intent is not straightforward. For example, writing: “The substrate plating device according to claim 1, which further comprises the information processing device,” would be improper under 112(d) because there is no substrate plating device “according to” claim 1; claim 1 positively recites the information processing device, but only mentions the existence of a “substrate plating device.” Written this way, then, claim 16 would not be referring to a positively recited limitation of claim 1. For examination purposes, it will be assumed that claim 16 recites a device which comprises the information processing device according to claim 1.
Claim 17 is confusing for essentially the same reasons as claim 16, and for examination purposes the examiner will similarly interpret claim 17 as reciting a device which comprises the machine learning device of claim 15.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
At Step 1 of the 101 analysis, all claims are directed to one of the statutory categories of invention.
Claim 1 is rejected in response to the following analysis:
At Step 2A, Prong One, the judicial exceptions are bolded in the copy of claim 1 below:
An information processing device comprising:
an information acquiring part configured to acquire plating process information including operational motion information including target paddle motion information indicating an agitating motion of a target paddle corresponding to a paddle to be processed, plating solution motion information indicating a motion of supplying a plating solution to a plating tank, and carrier machine motion information indicating a motion of carrying a substrate and operational-motion paddle vibration information indicating vibration characteristics of the target paddle when an operational motion is performed, the motion of agitating the target paddle, the motion of supplying a plating solution, and the motion of carrying a substrate being operational motions which are performed by a substrate plating device including one or more plating tanks storing a plating solution used for plating of a substrate, one or more paddles installed in the one or more plating tanks and agitating the plating solution, and one or more carrier machines carrying the substrate to the one or more plating tanks; and
an information generating part configured to generate agitating-motion paddle vibration information in response to the plating process information by inputting the plating process information acquired by the information acquiring part to a learning model which has learned a correlation between the plating process information and the agitating-motion paddle vibration information indicating vibration characteristics of the target paddle when only the agitating motion indicated by the target paddle motion information of the operational motion information included in the plating process information has been performed using machine learning.
Acquiring information, described without detail about how the data was acquired, is an abstract idea. For example, the act of reading a table of data describes acquiring information. While much of the language of claim 1 is devoted to describing what the information acquired represents, these limitations are not additional elements because they do not positively recite collecting the information. Furthermore, all of the elements of the substrate plating device, including paddles, tanks, plating solution, etc., are recited in such a way that they only describe the information that was gathered (the “operational motion information” represents “operational motions” performed by a “substrate plating device,” but an infringer would only need to access the information; they would not need to possess the substrate plating device itself).
Feeding information into a trained learning model to generate more information is a mathematical process.
The above details provide a particular field of use and describe a particular method of reaching a particular result. However, the claim never positively recites a particular machine, physical sensors, real-world transformations.
At Step 2A, Prong Two, the additional element is an information processing device comprising an information acquiring part and an information generating part. This encompasses a general-purpose computer which is relied upon to perform the judicial exceptions. As written, claim 1 is encompassed by a processor which implements an algorithm to access data and feed it to a ML to isolate vibration from a single source (a target paddle’s agitating motions). Generating this information alone does not describe a particular real-world transformation nor the functioning of a particular machine. Therefore, the additional elements do not integrate the judicial exceptions into a practical application.
At Step 2B, when considered as a whole, claim 1 does not amount to significantly more than the judicial exceptions for the reasons given above.
Claims 2-8 give further details about the information and substrate plating device in claim 1 but do not change the conclusions reached in the analysis of claim 1, therefore these claims are also rejected.
Claim 9 depends from claim 1 and recites an “abnormality determining part” which determines whether there is an abnormality in the target paddle based on the agitating-motion paddle vibration information. Determining whether the target paddle is abnormal may or may not have practical utility for a plating operation, depending on what the abnormality is and whether it affects the quality or efficiency of any plating process involving the target paddle. However, claim 9 is still encompassed by a processor which merely accesses pre-existing data and implements an algorithm to determine if a target paddle is out of the ordinary in some way. Therefore the results of the analysis of claim 1 still applies, and claim 9 is rejected.
Claims 10-13 recite the same limitations as claim 9 and are rejected for the same reasons.
Claim 16 recites a device which serves as the information processing device according to claim 1, therefore the analysis of claim 1 applies to claim 16, which is also rejected.
Claim 18 recites the method performed by the information processing device of claim 1 and is rejected for the same reasons.
Claim 14 describes an inference device comprising a memory and processor which performs the method described in claim 1 and is rejected for the same reasons.
Claim 19 describes the method performed by the inference device of claim 14 and is therefore rejected along with claim 1.
Claim 15 describes a machine learning device which is trained to perform the process of claim 1 and is therefore rejected for the same reasons as claim 1.
Claim 20 describes a machine learning method performed by the machine learning device of claim 15 and is therefore rejected along with claim 15.
Claim 17 recites a device which serves as the machine learning device according to claim 15, therefore the analysis of claim 15 applies to claim 17, which is also rejected.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 9-12, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Fujikata (US 20180294174 A1) in view of Kajuluri (US 11281286 B1).
Regarding claim 1, Fujikata discloses a substrate plating device (Fig. 1, plating apparatus 1 along with controller 175) including one or more plating tanks (Fig. 1, plating cells 50; note that Fujikata describes a plating tank 10, but that the examiner intends to map the plating cells 50 to the “one or more plating tanks” described by the claim language) storing a plating solution used for plating of a substrate (¶39: “Each plating cell 50 houses one substrate W inside and immerses the substrate W into a plating solution held inside”), one or more paddles installed in the one or more plating tanks and agitating the plating solution (¶43: “In each plating cell 50, a paddle device 180 for agitating the plating solution in the plating cell 50 is disposed”), and one or more carrier machines (Fig. 1, the second transporter 144) carrying the substrate to the one or more plating tanks.
Fujikata further discloses acquiring plating process information including operational motion information including target paddle motion information indicating an agitating motion of a target paddle (¶57: sensors detect shift of shaft 38; ¶52: shaft 38 moves paddle 18 to agitate the plating fluid; ¶43: paddle 18 is part of the paddle device 180) corresponding to a paddle to be processed (¶57: the invention detects data related to the target paddle because it is interested in predicting the failure of the paddle device, thus the target paddle is a paddle “to be processed”), and plating process information including operational-motion paddle vibration information indicating vibration characteristics of the target paddle when an operational motion is performed (¶57: sensors detect vibration of motor 44; ¶52: motor 44 is part of paddle driving device 19, and it drives the shaft 38; ¶43: paddle driving device 19 is part of the paddle device 180). The above information is acquired by the information acquiring part of an information processing device (¶54: “a failure prediction process for the motor 44 of the paddle driving device 19 will be described. The failure prediction process can be performed by the controller 175, the control unit 46, or other computers provided on the inside or outside of the plating apparatus.”). The motion of agitating the target paddle is performed by the substrate plating device (Fig. 1, paddle device 180 is part of plating apparatus 1).
Fujikata also discloses that the information processing device comprises an information generating part (¶66: support vector machine is “configured as a program to be run in the controller 175, the control unit 46 and/or another computer (inside and/or outside the plating apparatus)”) configured to generate a result (determination of abnormality; see below) in response to inputting the plating process information acquired by the information acquiring part to a learning model (support vector machine and the part which calculates feature quantities; see below) which has learned a correlation between the plating process information and an abnormality in the target paddle (Fig. 11, S10-S12: ¶79: S10 physical quantities are acquired, including vibration of motor 44 and shift of shaft 38; at S11 “a feature quantity is calculated from a waveform of each physical quantity to create a feature quantity vector”; at S12-S13 a support vector machine determines whether the feature quantity indicates normal or abnormal operation of the paddle device 180; see also ¶69) using machine learning (¶67: the support vector machine is a learning model trained using machine learning).
Fujikata does not explicitly disclose that the operational motion information includes plating solution motion information indicating a motion of supplying a plating solution to a plating tank and carrier machine motion information indicating a motion of carrying a substrate, the motion of supplying a plating solution and the motion of carrying a substrate being operational motions which are performed by the substrate plating device; nor that the information generating part is configured to generate agitating-motion paddle vibration information in response to the plating process information by inputting the plating process information acquired by the information acquiring part to a learning model which has learned a correlation between the plating process information and the agitating-motion paddle vibration information indicating vibration characteristics of the target paddle when only the agitating motion indicated by the target paddle motion information of the operational motion information included in the plating process information has been performed using machine learning.
Kajuluri discloses an accelerometer to detect the vibrations associated with an engine (Column 4, lines 48-49 “accelerometer 106 detects the vibrations associated with an engine”). Kajuluri teaches that the accelerometer can detect vibrations from sources other than the engine operation, and may apply filters in order to isolate the vibrations due to engine operation (Column 4, line 65 – Column 5, line 1: “The accelerometer 106 may include one or more filters (not shown) configured to detect and/or remove the noise vibrations received by the accelerometer 106 from the sources other than the engine operation.”).
In the substrate plating device, operational motions including carrying a substrate with a carrier machine and supplying plating solution to a plating tank would occur. These motions cause vibrations at some scale, so it is reasonable to conclude that they could add noise to the operational-motion paddle vibration information. Since these vibrations are unrelated to the normality/abnormality of the target paddle, it would be reasonable to apply some filter to remove the vibrations. Finally, it would be reasonable to use a learning model trained using machine learning to do so, because machine learning is adept at training on large datasets to perform supervised learning processes such as identifying a desired signal from a superposition of signals.
For the reasons above, then, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Kajuluri with the invention of Fujikata by causing the operational motion information to include plating solution motion information indicating a motion of supplying a plating solution to a plating tank and carrier machine motion information indicating a motion of carrying a substrate, the motion of supplying a plating solution and the motion of carrying a substrate being operational motions which are performed by the substrate plating device; and to configure the information generating part to generate agitating-motion paddle vibration information in response to the plating process information by inputting the plating process information acquired by the information acquiring part to a learning model which has learned a correlation between the plating process information and the agitating-motion paddle vibration information indicating vibration characteristics of the target paddle when only the agitating motion indicated by the target paddle motion information of the operational motion information included in the plating process information has been performed using machine learning.
Regarding claim 2, Fujikata in view of Kajuluri teaches the limitations of claim 1, and further discloses that the target paddle motion information includes at least one of a motion speed, motion frequency, and motion stroke of the target paddle (Fujikata, ¶63: “the shift of the shaft 38” includes collecting “shift rate” and “inclination of the shaft”; a rate may refer to a speed or a frequency).
Regarding claim 3, Fujikata in view of Kajuluri teaches the limitations of claim 1. Furthermore, noting Kajuluri’s teaching that nearby movement can cause unwanted vibrations (see rejection of claim 1), it would have been obvious for the plating solution motion information to include at least one of: an amount of liquid of the plating solution stored in the plating tank; a motion status indicating whether a circulation pump circulating the plating solution is operating; and a rotation speed of the circulation pump. Operation characteristics of a nearby pump would reasonably cause vibrational noise; similarly, it is reasonable that the vibrational noise caused by storing plating solution in a tank is proportional to the amount of solution stored.
Regarding claim 4, Fujikata in view of Kajuluri teaches the limitations of claim 1. Furthermore, noting Kajuluri’s teaching that nearby movement can cause unwanted vibrations (see rejection of claim 1), it would have been obvious to cause the carrier machine motion information to include at least one of: a motion status indicating whether the carrier machine is operating; a motion speed of the carrier machine; a position of the carrier machine relative to the target paddle; and a distance between the target paddle and the carrier machine. An operating carrier machine would be a potential source of vibration; the speed of the carrier machine may change the nature of the vibration signal generated by the carrier machine; and the position and distance of the carrier machine relative to the target paddle may affect the amplitude of the noise produced by the carrier machine at the target paddle.
Regarding claims 9-12, Fujikata in view of Kajuluri teaches the limitations of claims 1-4, and further teaches that the information processing device comprises an abnormality determining part configured to determine occurrence of an abnormality in the target paddle (Fujikata, ¶69: the support vector machine determines whether a paddle device 180 is abnormal; this determination is based on acquired physical quantities and processing described in the rejection of claim 1). Furthermore, following the rationale in the rejection of claim 1 of first filtering out noise to obtain the vibration signal of the target paddle, it would be reasonable to base the abnormality determination on the agitating-motion paddle vibration information generated by the information generating part (see rejection of claim 1).
Regarding claim 14, claim 14 recites an inference device comprising a memory and a processor which performs the method of claim 1. This is encompassed by a general computer implementing the limitations of claim 1, and is rejected for the same reasons.
Regarding claim 15, claim 15 copies much of the language of claim 1 and recites a machine learning device which trains on data to cause a learning model to perform the functions described in claim 1. These limitations would have been obvious for the reasons given in the rejection of claim 1.
Regarding claim 16, Fujikata in view of Kajuluri teaches the limitations of claim 1. Fujikata also teaches a device which comprises the information processing device (see 112(b) rejection of claim 16 for the interpretation of claim 16; see the rejection of claim 1; controller 175 was defined as part of the substrate plating device in the rejection of claim 1; ¶52: the control unit 46 “may be achieved as part of the function of the controller 175”).
Regarding claim 17, claim 17 depends from claim 15 and recites limitations similar to those given in claim 16, and is rejected for the same reasons (see 112(b) rejection of claim 17 for the interpretation of claim 17).
Regarding claim 18, claim 18 recites the method performed by the information processing device of claim 1 and is rejected for the same reasons as claim 1.
Regarding claim 19, claim 19 recites the method performed by the inference device of claim 14 and is rejected for the same reasons.
Regarding claim 20, claim 20 recites the method performed by the machine learning device of claim 15 and is rejected for the same reasons.
Claims 5-7 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Fujikata (US 20180294174 A1) in view of Kajuluri (US 11281286 B1), and further in view of Masuda (US 20180221835 A1).
Regarding claim 5, Fujikata in view of Kajuluri teaches the limitations of claim 1, and further teaches that the substrate plating device includes a target plating tank corresponding to the plating tank in which the target paddle is installed (define the cell 50 with the paddle device 180 as the target tank) and one or more surrounding plating tanks corresponding to plating tanks disposed near the target plating tank (define one or more of the other cells 50 as surrounding plating tanks) as a plurality of the one or more plating tanks; and the target paddle (paddle device 180 in the target tank) and one or more surrounding paddles corresponding to paddles installed in the one or more surrounding plating tanks (the paddle devices 180 in the surrounding tanks) as a plurality of the one or more paddles.
Fujikata in view of Kajuluri does not explicitly teach that the operational motion information further includes surrounding paddle motion information indicating the agitating motion of the one or more surrounding paddles.
Masuda teaches that the motions of multiple proximate paddles can cause large vibrations to occur, such as when their motions synchronize (¶63). It is reasonable then that the motion of surrounding paddles can cause vibrational noise at the target paddle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Masuda with the invention of Fujikata in view of Kajuluri by causing the operational motion information to further include surrounding paddle motion information indicating the agitating motion of the one or more surrounding paddles. Doing so would enable one to account for vibrational noise caused by the surrounding paddles.
Regarding claim 6, Fujikata in view of Kajuluri and Masuda teaches the limitations of claim 5. Furthermore, noting Kajuluri’s teaching that nearby movement can cause unwanted vibrations (see rejection of claim 1), it would have been obvious to cause the surrounding paddle motion information to include at least one of: a motion state indicating whether the surrounding paddle is operating; a motion speed of the surrounding paddle; a motion frequency of the surrounding paddle; a motion stroke of the surrounding paddle; and a phase difference between the target paddle and the surrounding paddle. An operating surrounding paddle would be a potential source of vibration; the speed, frequency, and stroke of the surrounding paddle may influence the character of the vibration signal; and a phase difference between the target and surrounding paddles may affect the constructive/destructive nature of the vibrational noise from the surrounding paddle, which would be useful information for isolating the vibration of the target paddle due solely to its agitating motions.
Regarding claim 7, Fujikata in view of Kajuluri and Masuda teaches the limitations of claim 6. Furthermore, noting Kajuluri’s teaching that nearby movement can cause unwanted vibrations (see rejection of claim 1), it would have been obvious to cause the operational motion information to further include device arrangement information on arrangement of the plating tanks and the paddles, wherein the device arrangement information includes at least one of: a position of the surrounding paddle relative to the target paddle; a distance between the target paddle and the surrounding paddle; a position of the surrounding plating tank relative to the target plating tank; and a distance between the target plating tank and the surrounding plating tank. Determining the relative positions or distances of the target and surrounding paddles, or the relative positions or distances of the target and surrounding tanks, would be useful because the closer an object is, more likely it would be a source of vibrational noise at the target paddle.
Regarding claim 13, Fujikata in view of Kajuluri and Masuda teaches the limitations of claim 5, and further teaches that the information processing device comprises an abnormality determining part configured to determine occurrence of an abnormality in the target paddle (Fujikata, ¶69: the support vector machine determines whether a paddle device 180 is abnormal; this determination is based on acquired physical quantities and processing described in the rejection of claim 1). Furthermore, following the rationale in the rejection of claim 1 of first filtering out noise to obtain the vibration signal of the target paddle, it would be reasonable to base the abnormality determination on the agitating-motion paddle vibration information generated by the information generating part (see rejection of claim 1).
Examiner’s Note
Claim 8 is patentably distinct from the prior art of record.
Regarding claim 8, Fujikata in view of Kajuluri teaches the limitations of claim 1. However, the examiner finds that it would not have been obvious to cause the operational motion information to further include anode electrode information, and for the anode electrode information to include at least a weight of the anode electrode. Fujikata in view of Kajuluri would have been interested in determining sources of vibrational noise for the target paddle, and it is not clear that they would have considered the anode electrode or its weight to be relevant to removing vibrational noise at the target paddle.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ETHAN WESLEY EDWARDS whose telephone number is (571)272-0266. The examiner can normally be reached Monday - Friday, 7:30am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached at (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ETHAN WESLEY EDWARDS
Examiner
Art Unit 2857
/E.W.E./ Examiner, Art Unit 2857
/ANDREW SCHECHTER/ Supervisory Patent Examiner, Art Unit 2857