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 .
DETAILED ACTION
2. This action is responsive to the Application filed on 7/25/2024. A filing date 7/25/2024 is acknowledged. 18832928 is a National Stage entry of PCT/JP2023/002099 and International Filing Date 1/24/2023. The sought benefit of JP application 2022-010197 (which was filed on 1/26/2022) is acknowledged. Claims 1-10, 12 are pending in this application. Claims 1, 10, 12 are independent claims.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
3. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a first unit that predicts in claim 1, a second unit that extracts in claim 8.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation: the apparatus includes, as hardware for executing the program, a computer that includes at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) ([0133]).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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 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 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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
4. Claims 1-3, 5-8, 10, 12 are rejected under 35 U.S.C. 103 as being unpatentable over Haw Ching Yang et al (US Publication 20180272491 A1, hereinafter Yang), and in view of Lee Sanders et al (US Publication 20220080545 A1, hereinafter Sanders), and He Zhang (US Publication 20190240804 A1, hereinafter Zhang).
As for independent claim 1, Yang discloses: An apparatus predicting wear amount (Abstract, A tool wear monitoring and predicting method is provided, and uses a hybrid dynamic neural network (HDNN) to build a tool wear prediction model) comprising:
a first unit that predicts, with use of a trained model, an amount of wear of a cutting tool in accordance with a processing time ([0041], the feature type includes a time domain, a frequency domain and/or a time-frequency domain); and
a display that displays information which is based on a result of prediction by the first unit (Fig. 4B, display the relationship of actual tool wear to tool life, and a maximum tool wear threshold), wherein: the trained model being generated by performing machine learning with training data using input data and output data as a dataset ([0007], a tool wear prediction model is built in accordance with a hybrid dynamic neural network (HDNN) algorithm by using the set of historical sensing data and the historical tool wear values), the input data being information which pertains to the cutting tool, a condition which concerns cutting ([0007], ranges of plural sets of factory machining conditions regarding a cutting tool product are first obtained), and information which pertains to a workpiece ([0033], an area of feasible machining conditions that can be accessed according to the material and tolerance of the workpiece to be machined. The cutting speeds (v.sub.1, v.sub.2) can be derived from the depth of cut (ap.sub.1, ap.sub.2), and the feed rate (f.sub.1, f.sub.2)) … and the first unit predicts the amount of wear based on data input, into the trained model and including, information pertaining to the cutting tool, a condition concerning cutting, and information pertaining to a workpiece (Abstract, A tool wear monitoring and predicting method is provided, and uses a hybrid dynamic neural network (HDNN) to build a tool wear prediction model).
Yang does not clearly disclose a processing time for which the cutting tool was used, in an analogous art of predicting cutting tool wear information using machine learning, Sanders discloses: and the output data being a processing time for which the cutting tool was used (Sanders: [0057], the system can store log data for the execution of the operation, where such log data may include metadata about the time of execution, positioning of the components, executed movements, configurations on the machine when the machining is performed, among other items) … an initial wear time which is from a start of the cutting by the cutting tool until completion of initial wear, and an initial wear amount which indicates an amount of wear of the cutting tool when the initial wear time has elapsed (Sanders: [0066], determine initial wear of the components);
Yang and Sanders are analogous arts because they are in the same field of endeavor, predicting tool wear data using machine learning. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention, to modify the invention of Yang using the teachings of Sanders to include determining initial wear of the components. It would provide Yang’s device with enhanced capabilities of providing specific wear information so user may prepare to replace the worn tool.
Further, Yang does not clearly disclose predicting wear amount data, in an analogous art of predicting tool wear data using machine learning, Zhang discloses: the amount of wear of the cutting tool which is due to processing (Zhang: Abstract, observes polishing condition data indicating a current environment state and performs, based on the state variable, learning or prediction by using a learning model which stores a correlation of the wear amount of the polishing tool with respect to the processing condition of polishing; [0005], measure a wear amount of the polishing tool unit of the polishing tool every time a series of polishing operations ends or after performing the polishing operation several times);
Yang and Zhang are analogous arts because they are in the same field of endeavor, predicting tool wear data using machine learning. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention, to modify the invention of Yang using the teachings of Zhang to include indicating the amount of wear data. It would provide Yang’s device with enhanced capabilities of providing specific wear information so user may prepare to replace the worn tool.
As for claim 2, Yang-Sanders-Zhang discloses: the dataset includes information pertaining to one or more factors that contributes to wear of the cutting tool; and
the display displays a factor that contributes to the wear of the cutting tool predicted by the first unit (Sanders: [0049], identify factors associated with faster wearing of machine components).
As for claim 3, Yang-Sanders-Zhang discloses: wherein the display displays the factors that contribute to the wear of the cutting tool predicted by the first unit and displays a degree of an effect of each of the plurality of factors on the wear (Sanders: [0022], Monitoring a level of wear of components of a CNC machine).
As for claim 5, Yang-Sanders-Zhang discloses: wherein information related to a cutting tool that become defective within a predetermined time after processing started is excluded from the dataset (Zhang: [0071], exceptional estimation results are excluded from the sets of input data and output data acquired from each learning model, and a distilled model can be generated by using the sets of input data and output data with the exceptional estimation results excluded).
As for claim 5, Yang-Sanders-Zhang discloses: wherein a surface of the cutting tool for which the amount of wear is predicted is selected depending on the type of the cutting tool (Zhang: [0048], tool type data S4 indicating a type of the polishing tool (a type of the polishing tool unit) as one state variable S).
As for claim 7, Yang-Sanders-Zhang discloses: wherein the display displays the result of the prediction by the first unit with use of a graph allowing the processing time and the amount of wear to be viewed (Yang: Fig. 4B).
As for claim 8, Yang-Sanders-Zhang discloses: a second unit that extracts similar information from a database associating information which pertains to a cutting tool, a condition which concerns cutting with use of the cutting tool, a processing time for which the cutting tool was used, and a post-processing amount of wear of the cutting tool in past use, the similar information being similar in terms of information which pertains to a cutting tool, a condition which concerns cutting with use of the cutting tool, a processing time for which the cutting tool was used, and a post-processing amount of wear of the cutting tool, the display further displays the similar information which has been extracted by the second unit (Yang: [0007], plural historical tool runs of operation are sequentially performed using the second cutting tool under the set of actual machining conditions, thereby obtaining a relationship of actual tool wear to tool life, plural sets of historical sensing data and plural historical tool wear values, in which the historical tool wear values are corresponding to the sets of historical sending data and the historical runs of operation in a one-to-one manner. Then, a tool wear prediction model is built in accordance with a hybrid dynamic neural network (HDNN) algorithm by using the set of historical sensing data and the historical tool wear values).
As per claim 10, it recites features that are substantially same as those features claimed by claim 1, thus the rationales for rejecting claim 1 are incorporated herein.
Claim 11 canceled
As per claim 12, it recites features that are substantially same as those features claimed by claim 1, thus the rationales for rejecting claim 1 are incorporated herein.
5. Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Yang, Sanders and Zhang as applied on claim 1, and further in view of Linxia Liao et al (US Publication 20180005151 A1, hereinafter Liao).
As for claim 4, Yang-Sanders-Zhang does not clearly disclose a probability of a defect, in another analogous art of predicting cutting tool wear data, Liao discloses: the dataset includes information pertaining to the presence/absence of a defect in the cutting tool; and the display displays a probability of a defect in the cutting tool predicted by the first unit (Liao: [0012], provide an “individualized” failure probability representation for indicating or assessing the health condition of each individual asset).
Yang and Liao are analogous arts because they are in the same field of endeavor, predicting tool wear data using machine learning. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention, to modify the invention of Yang using the teachings of Liao to include determining failure probability. It would provide Yang’s device with enhanced capabilities of providing specific wear information so user may prepare to replace the worn tool.
6. Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Yang, Sanders and Zhang as applied on claim 1, and further in view of Richard Agudelo (US Publication 20180085878 A1, hereinafter Agudelo).
As for claim 9, Yang-Sanders-Zhang does not disclose display in a single graph the result of analysis, in another analogous art of predicting cutting tool wear data, Agudelo discloses: wherein the display displays, in a single graph, the result by the first unit and the similar information extracted by the second unit (Agudelo: Fig. 14, display all analysis data and prediction data in one graph).
Yang and Agudelo are analogous arts because they are in the same field of endeavor, predicting tool wear data. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention, to modify the invention of Yang using the teachings of Agudelo to include displaying analysis data in one graph. It would provide Yang’s device with enhanced capabilities of allowing user to view all analysis data in one user interface.
Examiner’s Note
Examiner has cited particular columns/paragraph and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131(b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as “Applicants believe no new matter has been introduced” may be deemed insufficient.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Applicants are required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
Shougo Inagaki et al (US Publication 20230129992) TOOL STATE LEARNING DEVICE, TOOL STATE ESTIMATION DEVICE, CONTROL DEVICE, TOOL STATE LEARNING METHOD, AND TOOL STATE ESTIMATION METHOD
Jeong (US Publication 20170320182) Method And Apparatus For Efficient Use Of CNC Machine Shaping Tool Including Cessation Of Use No Later Than The Onset Of Tool Deterioration By Monitoring Audible Sound During Shaping
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hua Lu whose telephone number is 571-270-1410 and fax number is 571-270-2410. The examiner can normally be reached on Mon-Fri 9:00 am to 6:00 pm EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Baderman can be reached on 571-272-3644. The fax phone number for the organization where this application or proceeding is assigned is 703-273-8300.
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/Hua Lu/
Primary Examiner, Art Unit 2118
Prosecution Insights