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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The Information Disclosure Statement (IDS) submitted on 02/18/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the Information Disclosure Statement is being considered by the Examiner.
Comments
Respectfully, it is the Examiner’s position that Applicant has yet to submit claims drawn to limitations, which define the operation and apparatus of Applicant’s disclosed invention in a manner, which distinguishes over the prior art. As it is Applicant’s right to claim as broadly as possible their invention. It is also the Examiner’s right to interpret the claim language as broadly as possible. It is the Examiner’s position that the detailed functionality that allows for Applicant’s invention to overcome the prior art used in the rejection (as well as several pieces of prior cited in the PTO -892 in addition several submitted in the IDS), fails to differentiate in detail how these features are unique. As it is extremely well known in the art as already shown by Shimada and other prior arts of records. Thus, it is clear that Applicant must submit amendments to the claims in order to distinguish over the prior art use in the rejection that discloses different features of Applicant’s claim invention.
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, 2, 7, 8, 14 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by JP 10137990, Shimada.
Regarding claim 1, Shimada discloses a method for assessing a state of a pressing punch of a rotary press (see Shimada, Fig. 1), comprising: providing the pressing punch comprising, a punch shaft with a punch head arranged at one end of the punch shaft and configured to interact with a pressure apparatus of the rotary press during operation (see Shimada, items 4 and 6 and Figs. 2 and 4-5), and a punch tip arranged at another end of the punch shaft and configured to press a material in a cavity of a die plate (4) of the rotary press to form a pellet (see Shimada, Figure 1); recording an image of at least one portion of the pressing punch with a camera (see Shimada, paragraph 18, the color camera unit (10) serving as a photographing means for photographing the surface (56) of the upper punch (5) and the lower punch (6) is disposed on each of the upper punch (5) and the lower punch (6)); transmitting the recorded image to an evaluation apparatus (see Shimada, para. 0022, when detecting an abnormality by processing the image signal, the area data obtained by photographing the normal state of the collar surface (56) of the upper collar (5) and the lower collar (6) in the ROM as comparison area data); performing a state analysis of the at least one portion by the evaluation apparatus, wherein the state analysis is performed using an image processing algorithm (see Shimada, para. 0022, when detecting an abnormality by processing the image signal, the area data obtained by photographing the normal state of the collar surface (56) of the upper collar (5) and the lower collar (6) in the ROM as comparison area data); assessing a state of the pressing punch by the evaluation apparatus based on the state analysis (see Shimada, para. 0022, when detecting an abnormality by processing the image signal, the area data obtained by photographing the normal state of the collar surface (56) of the upper collar (5) and the lower collar (6) in the ROM as comparison area data); and outputting a warning signal when the assessed state of the pressing punch is outside of a permissible range (see Shimada, paragraph 0019, 0023 and 0026; the microcomputer system includes a microcomputer, a ROM, RAM, I/O interface, and an A / D converter. Further, each of the upper and lower punch face controllers 11a and 11b includes a data-converting circuit for converting an input image signal into a digital signal when the image signal is processed. The sequencer 14 controls the operation order of the mechanism unit MP, and outputs a control signal so as to operate the mechanism unit MP according to a preset order. The sequencer 14 is electrically connected to a touch display 16 for inputting data necessary for controlling the mechanism section MP and displaying the contents of control being executed at that time. When a signal indicating the occurrence of an abnormality is inputted from at least one of the upper punch surface controller 11a and the lower punch surface controller 11b, a control signal for stopping the operation of the mechanism part MP is outputted. Thereafter, the measured area obtained from the image signal is compared with the comparison area stored in advance in the ROMs of the upper and lower punch face controllers 11a and 11b. As a result of this comparison, when the measured area data is larger than the comparison area data, it is determined that adhesion has occurred on the punch surface 56, and an abnormality is detected. On the other hand, when the area is equal to or less than the comparison area data, it is determined that the powder does not adhere to the punch surface 56, and it is detected that the punch surface 56 is normal.)
Regarding claim 2, Shimada discloses the method according to claim 1, further comprising performing the state analysis using an image processing algorithm that comprises a comparison of the recorded image with at least one reference image (see Shimada, paragraph 0026-0030).
Regarding claim 3, Shimada discloses the method according to claim 2, wherein the at least one reference image (see rejection of claim 2) is at least one of: at least one reference image of the at least one portion of an unused pressing punch (see Shimada, paras. 0019 and 0022); and at least one reference image of the at least one portion of the pressing punch to be assessed before a last production process of the pressing punch to be assessed in the rotary press (see rejection of claim 1 and 2).
Regarding claim 4, Shimada discloses The method according to claim 1, further comprising performing the state analysis by extracting a region of interest from the recorded image, wherein the region of interest is an end face of the punch tip (see Shimada, paragraph 0018, In this embodiment, as shown in FIG. 5, the color camera units 10 as the photographing means for photographing the punch surfaces 56 of the upper punch 5 and the lower punch 6 are arranged for the upper punch 5 and the lower punch 6, respectively, and accordingly, the controller 11 as the abnormality detecting means is also set as an upper punch surface controller 11a and a lower punch surface controller 11b).
Regarding claim 7, Shimada discloses the method according to claim 1, wherein the at least one portion of the pressing punch is an end face of the punch tip of the pressing punch (see Shimada, para. 0020, The color camera section 10a includes a color CCD camera 10d mounted with a C-mount lens, a tube-type scope 10c for transmitting illumination light from the light-source-output unit 10d to the punch face 56 and sending an image of the punch face 56 to the color CCD camera 10e, and a reflector 10e integrally attached to the tip of the tube-type scope at an angle of about 45 ° with respect to the punch face 56. 10fThe color camera unit 10a is installed at a position in the circumferential direction where the upper punch 5 is pulled out from the die 4 after completion of the tableting and guided to the highest position by the guide rail 5a in order to photograph the punch surface 56 of the upper punch 5, that is, a position immediately after the powder filling. The mounting direction of the color camera portion 10a is such that the shaft of the tube-type scope 10e coincides with the radial direction of the turret 3 or coincides with the tangent direction of the circle of the center locus of the die 4, and in either case, the center of the reflector 10f coincides with the center line of the punch face 56. With this arrangement, it is possible to reduce the influence of the angular component due to the rotation of the rotary table 3 on the video signal. The tube-type scope 10e is configured to capture an image onto the color CCD camera 10d and illumination light from the light source-output unit 10c are integrally incorporated on the same axis. Illumination light enters the tube-type scope 10e from the light-source outputting unit 10g via the light guide 10c. In the case where the XYZ-stage 12 is not provided, the color camera unit 10a may be disposed so as to be adjustable in the vertical direction and the right, left, front, and rear directions.).
Regarding claim 8, Shimada discloses the method according to claim 7, wherein performing the state analysis using an image processing algorithm comprises determining a center point of a recorded end face of the punch tip (see Shimada, paragraphs 0031-0032, As shown in FIG. 13, instead of aligning the 10a of the tube-type scope with the radial direction of the turret 3 as shown in the above embodiment, the 10e of the tube-type scope may be aligned with the tangent direction of the circle passing through the center of the die 4 in the vicinity of the product take-out portion in order to photograph the punch surface 56 of the lower punch 6, for example. 10e and further the processing of the image signal of the imaged punch face 56 may be performed for every other punch or every two or three punches in order to reliably perform the processing, for example, in the case of a rotating disk that rotates at high speed such as a 60rpm. In this case, since the timing signal outputted from the synchronization sensor 15 corresponds to each punch, the image signal processing interval may be controlled by the timing signal).
Regarding claim 14, Shimada discloses the method according to claim 1, wherein the state analysis comprises detecting anomalies on the at least one portion of the pressing punch (see rejection of claim 1).
Regarding claim 20, Shimada discloses a device for assessing a state of a pressing punch, comprising: a camera configured to record an image of at least one portion of the pressing punch (see rejection of claim 1); and an evaluation apparatus in electrical communication with the camera (see Shimada, para. 0023), wherein the evaluation apparatus is configured to: perform a state analysis of the at least one portion of the pressing punch using at least one image processing algorithm (see rejection of claim 1); assess the state of the pressing punch based on the state analysis (see rejection of claim 1); and output a warning signal if the state of the assessed pressing punch is outside of a stored permissible range (see Shimada, paragraph 0019, 0023 and 0026; the microcomputer system includes a microcomputer, a ROM, RAM, I/O interface, and an A / D converter. Further, each of the upper and lower punch face controllers 11a and 11b includes a data-converting circuit for converting an input image signal into a digital signal when the image signal is processed. The sequencer 14 controls the operation order of the mechanism unit MP, and outputs a control signal so as to operate the mechanism unit MP according to a preset order. The sequencer 14 is electrically connected to a touch display 16 for inputting data necessary for controlling the mechanism section MP and displaying the contents of control being executed at that time. When a signal indicating the occurrence of an abnormality is inputted from at least one of the upper punch surface controller 11a and the lower punch surface controller 11b, a control signal for stopping the operation of the mechanism part MP is outputted. Thereafter, the measured area obtained from the image signal is compared with the comparison area stored in advance in the ROMs of the upper and lower punch face controllers 11a and 11b. As a result of this comparison, when the measured area data is larger than the comparison area data, it is determined that adhesion has occurred on the punch surface 56, and an abnormality is detected. On the other hand, when the area is equal to or less than the comparison area data, it is determined that the powder does not adhere to the punch surface 56, and it is detected that the punch surface 56 is normal.).
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 (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 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.
Claims 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of Lin Chen-Sheng et at., (Lin), TW201510487.
Regarding claim 5, Shimada-Lin discloses the invention substantially as claimed. Shimada discloses the method according to claim 1, wherein the recorded image is a color image (see Shimada, paragraph 0021-0022). However, Shimada fails to explicitly disclose and wherein performing the state analysis using an image processing algorithm comprises a grayscaling of the color image.
But, in the same field of endeavor, Lin discloses and wherein performing the state analysis using an image processing algorithm comprises a grayscaling of the color image (see Lin, page 11, In most image processing, in addition to the color recognition of images, the algorithms of general images are processed under grayscale images, which can not only simplify the algorithm and computational workload, but also speed up the processing speed and make it easier to improve the algorithm).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to have implemented Lin’s optical encoder assembly and evaluation device and method with the system of Shimada in order to improve upon the quality of the resolution of the signals as stated in Lin. (The same motivation to combine that was applied to claim 5 applies to claim 13 as well.
Regarding claim 13 Shimada-Lin discloses the method according to claim 1, wherein the state analysis comprises a Canny algorithm (see Lin, page 8, In the first figure, the circle is the image brightness recognition range of the optical encoder, and the intensity of the brightness is the main signal of the optical encoder's image analysis, so the average grayscale pixel intensity of this range is taken as the brightness degree of the optical encoder signal, and in order to make the analysis range of the circle selected closer to the actual required area, the present invention adopts Canny Edge Detection to extract the image intensity analysis range of the optical encoder. The position in the image can be anywhere, in any direction, and the intensity is also different, so in order to find the position, direction and intensity of the edges, Canny uses the one-dimensional Gaussian function (1) formula, which is calculated as follows: Its first-order derivative is equation (2): Its second-order derivative is equation (3). When σ we take an ideal edge and the Gaussian function as a convolution, if we want to find the position of the edge in the image, we can find the crest in the graph by accumulating the original image and the first-order derivative as a spin product. Or we can find the zero crossing point after accumulating the original image and the second-order derivative function, that is, we can find the edge we are looking for, and the spin of the image and the Gaussian function can be calculated by equation (4). g(x,y)=D[Guass(x,y)*f(x,y)](4) This formula is equivalent to (5): g(x,y)=D[Guass(x,y)]*f(x,y)(5) In the formula, D represents differentiating it. Guass(x,y) is a Gaussian function.).
Claim Rejections - 35 USC § 103
Claims 6 and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of Grenov et al., (Grenov), US PG PUB 20170078634 A1.
Regarding claim 6, Shimada discloses the invention substantially as claimed. However, Shimada does not explicitly disclose the method according to claim 1, wherein performing the state analysis using an image processing algorithm comprises converting the recorded image into a binary image.
But, in the same field of endeavor, Grenov discloses the method according to claim 1, wherein performing the state analysis using an image processing algorithm comprises converting the recorded image into a binary image (see Grenov, abstract, para. 0008, 0096-0099, Dual binary image generation (dynamic thresholding and isotropic gradient thresholding) and composite binary image creation).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to have included Grenov’s teachings of reference’s image‑processing techniques for component image extraction, dual‑binary/composite image formation, and morphological/ring detection filtering with Shimada’s punch‑face imaging and defect detection system. With Grenov’s teachings of robust thresholding, gradient analysis, morphological filtering, and specialized feature detection provide predictable improvements in accuracy and reliability with Shimada’s simple color‑threshold/area‑comparison method. Applying Grenov’s processing pipeline to Shimada’s punch‑face images would have been a routine substitution of one set of known image‑processing techniques for another, yielding enhanced detection of adhesion, cracks, or other surface anomalies. One would have had a reasonable expectation of success because the inspection targets in both references are stationary relative to the camera during imaging, the image‑processing steps are standard in digital vision, and the output defect masks in both systems are used for control or reporting purposes.
Regarding claim 17, Shimada discloses the method according to claim 1, wherein one of:
the pressing punch to be assessed is mounted in the rotary press during the assessment (see Shimada, paras. 0019 and 0024); and the pressing punch to be assessed is held in a holder outside of the rotary press during the assessment, wherein the holder comprises a washing apparatus for the pressing punches of the rotary press (Official Notice is taken).
Regarding claim 18, Shimada discloses the method according to claim 17, wherein the camera is held on a supporting arm that is configured to be moved into a pressing space of the rotary press (see Grenov, para. 0057).
Regarding claim 19, Shimada discloses the method according to claim 18, further comprising assessing the pressing punches of the rotary press by rotating a rotor successively such that the at least one portion of the pressing punches of the rotary press are recorded by the camera one after another (see Shimada, paras. 0019, 0022, 0024, 0029, 0030).
Claim Rejections - 35 USC § 103
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of Gonzalez et al., (Gonzalez), Digital Image Processing, 3rd Edition.
Regarding claim 9, Shimada discloses the invention substantially as claimed. Shimada does not explicitly disclose the method according to claim 8, wherein performing the state analysis using an image processing algorithm comprises transforming coordinates of the recorded image into a polar coordinate system.
However, in the same field of endeavor, Gonzalez discloses the method according to claim 8, wherein performing the state analysis using an image processing algorithm comprises transforming coordinates of the recorded image into a polar coordinate system (see Gonzalez, section 2.3.2 and pages Mapping to polar coordinates transforms circular edges into near-straight lines in the warped image, allowing simple radial profiling by scanning rows.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have implemented Gonzalez’s teachings of digital processing with the teachings of Shimada since Gonzalez teaches the polar transformation that reparameterizes circular images by radius and angle via r = sqrt((x−x0)^2 + (y−y0)^2) and θ = arctan2(y−y0, x−x0), simplifying circumference-wise measurements. Furthermore, it would have been obvious to a person of ordinary skill in the art to apply the polar-coordinate transform taught by Gonzalez and Shimada’s end-face images to facilitate identifying inner/outer borders and performing radial/circumferential measurements. This substitution is a conventional image-processing step with a predictable result, and there would have been a reasonable expectation of success.
Claim Rejections - 35 USC § 103
Claims 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of well-known in the art (Official Notice).
Regarding claim 10, Shimada disclose the invention substantially as claimed. Shimada does not explicitly disclose the method according to claim 7, wherein the end face of the punch tip comprises an outer region comprising an annular flat portion, and wherein the state analysis comprises identifying an outer and inner border of the annular flat portion. However, the examiner takes Official notice in that be A person of ordinary skill in the art would recognize that, given an image of a circular punch face as taught by Shimada, locating inner and outer annular borders by these routine techniques requires no more than ordinary skill and would be a predictable application of well‑known image‑processing methods
Regarding claim 11, Shimada discloses the method according to claim 10, wherein the state analysis further comprises determining a distance between an outer and inner border over a circumference of the annular flat portion (Official Notice is taken).
Regarding claim 12, Shimada discloses the method according to claim 11, further comprising identifying the outer and inner border of the annular flat portion by determining maxima in the image processed as part of the state analysis (see Shimada, Fig. 5, items 4-6 and 10).
Claim Rejections - 35 USC § 103
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of Ester et al., (Ester), A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases.
Regarding claim 15, Shimada discloses the invention substantially as claimed. Shimada does not explicitly disclose the method according to claim 14, further comprising using an image processing algorithm for cluster analysis to detect anomalies on the at least one portion of the pressing punch.
However, in the same field of endeavor. Ester discloses the method according to claim 14, further comprising using an image processing algorithm for cluster analysis to detect anomalies on the at least one portion of the pressing punch (see Ester, pg. 226-228 and sections 2 and 3).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to have included Ester’s teachings of a clustering algorithm for the management of databases with the teachings of Shimada for the purpose of effectiveness and efficiency of a DBSCAN using data and real data (see Ester, Abstract and Introduction.
Claim Rejections - 35 USC § 103
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Shimada in view of Klaer et al., (Klaer), US PG PUB No. 20220332077.
Regarding claim 16, Shimada discloses the invention substantially as claimed. Shimada does not explicitly disclose the method according to claim 1, further comprising performing the state analysis using machine learning algorithms (see Klaer, 0148--0150).
However, in the same field of endeavor, Klaer discloses the method according to claim 1, further comprising performing the state analysis using machine learning algorithms (see Klaer, paras. 0140, 0144, 0147-0150, in a further preferred embodiment, the method is characterized in that the recorded measured values of the measuring device are analyzed in combination with externally recorded and/or provided measured values via algorithms (preferably machine learning algorithms). In the sense of the invention, machine learning algorithms are a subarea of artificial intelligence. Machine Learning uses mathematical and statistical models to “learn” from data sets. In general, machine learning algorithms have the advantage that information that is too complex for a human observer can be automatically extracted from a large data set. There are a variety of machine learning algorithms that can be broadly categorized into three different learning methods: supervised learning, unsupervised learning, and reinforcement learning. In a preferred embodiment, supervised learning is used to analyze or process the stored measurement data. In the supervised learning method, a so-called training process is first carried out. Here, training data is provided in the form of input data together with the corresponding target data. The purpose of training is generally in machine learning methods to adjust parameters of a function so that the function is subsequently able to determine the target value with high accuracy from the corresponding input value. The adapted function is then used after the training process to predict target data for previously unseen input data. The function is described by a mathematical and/or statistical model. In a preferred embodiment, the function is designed by support vector machines, Bayesian networks and/or decision trees. Particularly preferably, the function is described by an artificial neural network. In accordance with the invention, the artificial neural networks can have different architectures. In the sense of the invention, the input data are preferably defined by machine parameters, environmental parameters and/or measured data of the measuring device. Machine parameters are preferably rotational speed of the turret, various material properties and/or key figures of the components, running time or operating time, age of the machine, number of punches or other components, etc. Environmental parameters are preferably ambient temperature, humidity, etc.,).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included Klaer’s punch‑mounted sensing and data‑processing system (which teaches local preprocessing, communication, and explicit application of machine‑learning algorithms to sensor data, Klaer (see Klaer, paras.0076–0079, 0144, 0148–0156) with Shimada’s camera‑based punch‑face inspection (which teaches real‑time image capture and extraction of adhered‑powder area, (see Shimada, paras. 0011, 0021, 0025–0027). It would have been routine and predictable to incorporate Shimada’s image‑derived features (adhesion/edge metrics) as additional input features to the machine learning framework taught by Klaer to improve detection performance and reduce false positives/negatives.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM C VAUGHN JR whose telephone number is (571)272-3922. The examiner can normally be reached Monday-Friday, 8:30am-5:00pm.
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/WILLIAM C VAUGHN JR/Supervisory Patent Examiner, Art Unit 2481