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 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.
1. 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.
2. Claim limitation is a positioning means (13) for positioning the laser projector unit in claim 1. See Page 11 of the provided specification dated 12 Feb, 2025, “The positioning means of each laser projector unit preferably comprises a suitable motor-driven actuator adapted to move the laser projector unit along the track. The actuator can be controlled in an entirely automated manner. For example, following a layup plan, the positioning means can move a laser projector unit further along in the direction of the tip end, so that the next section of the layup can be carried out.”
3. 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:
a laser projector (12) configured to project in claim 1. See Fig. 2, Element 12.
an imaging arrangement (11) adapted to capture images in claim 1. See Fig. 2, Element 11.
a calibration module (16) configured to calibrate in claim 1. See Fig. 3, Element 16.
Because this/these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have 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.
Regarding claim 7, which recites “and/or”, and the Examiner treats the features affected as the disjunctive “or”, where only one alternative may be presented to satisfy the limitation.
Claim Objections
4. Claim 14 is objected to because of the following informalities:
Claim 14 recites “patters” in multiple instances and each instance should be corrected and changed to “patterns”.
Appropriate correction is required.
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.
5. Claims 1-15 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.
Regarding claim 1, it is not clear if “that mould” is the same or different mould than the rotor blade mould.
Regarding claims 10-15, it is unclear the order of dependency and the Examiner cannot fully ascertain which claims are independent and which claims are dependent.
Independent claim 1 is in regards to “A laser projector assembly”; However, claims 10 and 11 are in regards to “A method” yet claims 10 and 11 depend upon claim 1. The Examiner treats claim 10 as independent and claim 11 as dependent upon claim 1. Claim 12 is written as an independent method claim yet claims to depend upon claim 10. The Examiner treats claim 12 as dependent upon claim 10. Claim 13 is written as an independent claim that still depends upon claim 1. Claim 13 is being treated as an independent claim toward “A machine-learning algorithm”. Claim 14 is written as an independent method claim that still depends on claim 13, which in turn depends on Claim 1, but it is unclear what liitations are being incorporated at each level (i.e. how much of the laser projector assembly is required at the point the limitations added b Claim 14 are relevant.). Claim 14 may be dependent upon claim 13. Claim 15 is written as an independent method claim that still depends upon claim 14. The Examiner treats claim 15 as dependent upon claim 14.
Correction or clarification is required.
Non-application of art to Claims 14-15 is not an indication of their allowability but an indication of the indefiniteness of (especially) Claim 14.
Furthermore, if claim 13 does indeed depend upon claim 1, then it is unclear if the algorithm discussed in claim 13 is the same or a different algorithm introduced in claim 1.
The remaining dependent claims are rejected for their dependency on a rejected claim.
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.
6. 35 U.S.C. 101 requires that a claimed invention must fall within one of the four eligible categories of invention (i.e. process, machine, manufacture, or composition of matter) and must not be directed to subject matter encompassing a judicially recognized exception as interpreted by the courts. MPEP 2106. Three categories of subject matter are found to be judicially recognized exceptions to 35 U.S.C. § 101 (i.e. patent ineligible) (1) laws of nature, (2) physical phenomena, and (3) abstract ideas. MPEP 2106(II). To be patent-eligible, a claim directed to a judicial exception must as whole be integrated into a practical application or directed to significantly more than the exception itself (MPEP 2106). Hence, the claim must describe a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.
7. Claim 13 is rejected under 35 U.S.C. 101 as not falling within one of the four statutory categories of invention because the claimed invention is directed to computer program per se. See MPEP 2106(I). A claim directed toward a non-transitory computer-readable medium having the program encoded thereon establishes a sufficient functional relationship between the program and a computer so as to remove it from the realm of “program per se”. MPEP 2111.05(III). Hence, adding the limitation of “stored on a non-transitory computer-readable medium” would resolve this issue.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
8. Claims 1-4, 6-7, and 9-13 as best understood are rejected under 35 U.S.C. 102(a)(1) as being anticipated by D1: US 20240109264 A1: Hendrik Gulink et al., (herein after “Gulink”).
Regarding claim 1, as best understood, A laser projector assembly (1) for use in a wind turbine rotor blade manufacturing facility (3) (Gulink, §Abstract: “A production system for producing a composite fiber component, in particular a wind turbine blade”, P[0030]: “the system includes a projector device for projecting a pattern of light on the working surface”, P[0032]: “the projector device including one or more lasers”), comprising
- a number of laser projector units (10) (Gulink, Fig. 1, Element 21), wherein each laser projector unit (10) comprises a positioning means (13) for positioning the laser projector unit (10) above a selected rotor blade mould (Gulink, P[0030]: “the system includes a projector device for projecting a pattern of light on the working surface”, where the working surface is the mould as disclosed by Gulink in P[0016]: ““Working surface” is any surface configured to support the plies. The working surface may be a surface of a mold, mold portion”) (2) (where the means for positioning the laser projector units is provided in Fig. 1 of Gulink, where the projector units, Element 21 are attached in a way to hold them without falling, which provides a means for positioning.), and a laser projector (12) configured to project layup guides (12G) into that mould (2) during a manual layup procedure (Gulink, P[0030]: “the system includes a projector device for projecting a pattern of light on the working surface”);
- an imaging arrangement (11) adapted to capture images (110) of that mould (2) (Gulink, Fig. 1, P[0019]: “the optical device comprises a plurality of optical cameras and/or lidar sensors.”);
- a machine learning algorithm (Gulink, P[0012]: “The reference parameter, the comparative value and/or the given feedback or guidance may be improved through machine learning (using e.g. neural networks and/or deep learning) during the operation of the system.”) (18) trained to determine coordinates of a feature (2M, 12P) in an image (110) (Gulink, P[0024]: “the captured features comprise edges, material and/or defects of the plies, reference points on the working surface and/or foreign objects and/or the parameter includes a position (e.g., 3D-coordinates), geometry, color and/or texture.”, where the steps of the algorithm are recited in P[0059 - 0078]) ; and
- a calibration module (16) configured to calibrate a laser projector (12) to that mould (2) prior to the manual layup procedure on the basis of an output (180) of the machine learning algorithm (Gulink, P[0012]: “The reference parameter, the comparative value and/or the given feedback or guidance may be improved through machine learning (using e.g. neural networks and/or deep learning) during the operation of the system.”) (18) (Gulink, P[0059 – 0064]: “the method comprises the steps of: … determining a position of the captured features of the first ply and a comparative result depending on a comparison of the determined position and a reference position … projecting a second pattern corresponding to a target position of a second ply depending on the comparative result.”).
Regarding claim 2, wherein the machine learning algorithm (18) is a convolutional neural network (Gulink, P[0012]: “The reference parameter, the comparative value and/or the given feedback or guidance may be improved through machine learning (using e.g. neural networks and/or deep learning) during the operation of the system.”).
Regarding claim 3, wherein the output (180) of the machine learning algorithm (18) is the spanwise distance (AMP) between a target marker (2M) and a laser calibration pattern (12P) (Gulink, P[0072]: “determining a position of the captured features and a comparative result depending on a comparison of the determined position and a reference position”, where the output is the distance between the measured feature position and reference position.).
Regarding claim 4, comprising a plurality of target markers (2M) provided at predetermined coordinates about the perimeter of a rotor blade mould (2), (Gulink, Fig. 1, Element(s) 13).
Regarding claim 6, configured to receive a layup plan (2layup) for the selected mould (2) (Gulink, P[0060]: “projecting a first pattern corresponding to a target position of a first ply”).
Regarding claim 7, as best understood, wherein the layup plan (21ayup) of a selected mould (2) determines the order of placement of a plurality of composite material pieces in that mould and/or the shape of each composite material piece and/or the type of each composite material piece and/or the position of each composite material piece in that mould (Gulink, P[0060 - 0064]: “projecting a first pattern corresponding to a target position of a first ply … projecting a second pattern corresponding to a target position of a second ply depending on the comparative result”).
Regarding claim 9, wherein the imaging arrangement (11) comprises a plurality of cameras arranged above a mould (2) (Gulink, Fig. 1, P[0019]: “the optical device comprises a plurality of optical cameras and/or lidar sensors.”).
Regarding claim 10, as best understood, moving a laser projector unit (10) into position above a selected mould is disclosed by Gulink in Fig.1 where an operator installed and moved the laser projector units into position above the mould.
The rest of the features of claim 10 are recited nearly identically to those recited in claim 1. Claim 10 is rejected for reasons analogous to those discussed above in conjunction with claim 1.
Regarding claim 11, wherein the machine learning algorithm (18) determines the coordinates of target markers (2M) and laser calibration patterns (12P) shown in the captured images (110) Gulink, P[0072]: “determining a position of the captured features and a comparative result depending on a comparison of the determined position and a reference position”.
Regarding claim 12, comprising a step of receiving a layup plan (21ayup) for the selected mould (2), and wherein the step of calibrating a laser projector unit (10) comprises adjusting the layup plan (21ayup) on the basis of an output (180) of the machine learning algorithm (18) Gulink, P[0060 - 0064]: “projecting a first pattern corresponding to a target position of a first ply … projecting a second pattern corresponding to a target position of a second ply depending on the comparative result”).
Regarding claim 13, as best understood, A machine-learning algorithm (18) for use in a laser projector assembly (Gulink, P[0103]: “The computing device 15 uses machine learning, i.e., algorithms that improve automatically through experience (for example using deep learning and/or neural networks developed by labelling data sets), to analyze the data recorded by the cameras 9 in FIG. 1. Therein, the features (in particular, the scissors 12, the reference points 13 and edges 14) are extracted (the extraction process may be error checked using chi squared statistical analysis) and associated with 3D-coordinates”, where the datasets and images are of the mold area which includes the target markers and light patterns from the projectors, See Fig. 1. And P[0103]: “(for example using deep learning and/or neural networks developed by labelling data sets”) (1) according to claim 1, comprising
- a neural network comprising an input layer, an output layer and a number of intermediate layers (Gulink, P[0103]: “The computing device 15 uses machine learning, i.e., algorithms that improve automatically through experience (for example using deep learning and/or neural networks developed by labelling data sets)), wherein
- the input layer is configured to receive annotated images (lOlabel) of a mould (2) in which target markers (2M) and laser calibration patterns (12P) have been labelled is disclosed by Gulink in P[0103]: “(for example using deep learning and/or neural networks developed by labelling data sets”, where the images are of the work area including the markers and light calibration patterns. ; and
- the output layer is configured to provide coordinates of target markers (2M) and laser calibration patterns (2P) in a reference frame of that mould (2) (Gulink, P[0024]: “the captured features comprise edges, material and/or defects of the plies, reference points on the working surface and/or foreign objects and/or the parameter includes a position (e.g., 3D-coordinates), geometry, color and/or texture.”).
To make explicit where Gulink seems to be implicit on the architecture of a standard or generic neural network. See, “Neural Network (machine learning) Wikipedia Article”: “Signals travel from the first layer (the input layer) to the last layer (the output layer), typically passing through multiple intermediate layers”
Allowable Subject Matter
9. Claims 5 and 8 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
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/TY MITCHELL BEATTY/Examiner, Art Unit 2663
/GREGORY A MORSE/Supervisory Patent Examiner, Art Unit 2698
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