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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on November 25, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim(s) 1-6 and 9-10 are rejected under 35 U.S.C. 102(a)(1) as being anticipate by Luca Pagani, Marco Grasso, Paul J. Scott, Bianca M. Colosimo, Automated layerwise detection of geometrical distortions in laser powder bed fusion, Additive Manufacturing, Volume 36, 2020, 101435, ISSN 2214-8604, https://doi.org/10.1016/j.addma.2020.101435. (hereinafter Pagani).
Regarding independent claim 1, Pagani discloses A method for dimensionally inspecting at least one component manufactured by an additive manufacturing machine (abstract, “This study presents a methodology that combines an active contours methodology for image segmentation with a statistical process monitoring approach suitable to deal with complex geometries that change layer by layer. The proposed approach enables a data-driven and automated alarm rule to detect the onset of geometrical distortions during the build by comparing the slice contour re construction with the nominal geometry in each layer.”), the additive manufacturing being carried out by successive depositions of a powder bed and by melting the powder bed after each deposition (abstract, “In-situ layerwise imaging in laser powder bed fusion (L-PBF) has been implemented by many system developers to monitor the powder bed homogeneity;” page 12, left column, “In-situ sensing and monitoring methodologies have been gaining a continuously increasing attention in L-PBF to anticipate the detection of defects during the process, and to support the qualification of additively produced parts.”), said method comprising:
acquiring an image of the component being manufactured after at least one step of depositing and melting a powder bed (page 2, left column, “Fig. 1A shows a layerwise image acquired with the powder bed camera installed on an EOS M290 during the production of a complex shape;” page 3, left column, “The build was produced by using a Ti6Al4V ELI gas atomized powder with average grain size lower than 45 μm supplied by TLS Technik. An EOS M290 equipped with an embedded powder bed camera mounting a 1280×1024 pixels sensor was used. Default process parameters defined by the AM service bureau that hosted the experimentation for the production of Ti6Al4V parts with this L-PBF system were applied. Fig. 3 shows a scheme of the placement of the powder bed camera and the low angle side illumination source already available in the machine.”);
comparing said image with an image of a reference template (page 5, “Fig. 5. Example of an acquired image (A) and its nominal mask (B), and the contour of the mask superimposed on the original image (C);” page 3, right column, “Fig. 5 shows an example of layerwise image (after camera perspective correction), the corresponding mask showing the nominal shape of the printed slice and their super imposition, which highlights the proper alignment between the image and the mask.”), the reference template being obtained from a reference component corresponding to a first set of images acquired upon manufacturing the reference component, the reference template comprising the first set of images (page 3, left column, “Fig. 2 (right panel) shows how different replicates of the test specimen were placed in the 250 mm×250mm build area of an EOS M290 L-PBF system. Orientations 1 and 2 were replicated three times (different re plicates were indicated with the capital letters A, B and C). Three additional replicates of the test specimen, namely 3A, 3B and 3C, were included into the build with a 45° orientation;” the reference geometry is determined from the actual produced specimens), the images acquired of the first set including a minimum internal contour and/or a minimum external contour (page 7, right column, “The use of the absolute value in the definition of di minmax allows one to signal any extreme deviation from the nominal geometry regardless of the direction of the deviation itself. If = d d| | i i minmax min , the most extreme deviation is towards the inside of the foreground region, which corresponds to a portion of the reconstructed slice that is missing. If = d d| | i i minmax max , the most extreme deviation is towards the outside of the foreground region, which corresponds to a portion of the re constructed slice that is larger than the nominal shape. Both these two conditions are of interest from a process monitoring perspective, as a lack of material or an excess of material in the slice are both potential symptoms of an anomaly.”), and
checking dimensional compliance of the component on the basis of the comparison (page 7, right column, “Since the goal of the proposed method is to automatically signal only anomalous large deviations from the nominal shape, a one-sided control chart is proposed. It allows comparing the di minmax index value in the ith layer with an upper control limit (UCL) and, whenever the computed value violates the limit, an alarm is signalled.”).
Regarding dependent claim 2, the rejection of claim 1 is incorporated herein. Additionally, Pagani further discloses wherein the acquiring is performed by a metal oxide semiconductor (CMOS) sensor or charge coupled device (CCD) sensor camera arranged inside the machine (page 2, left column, “Fig. 1A shows a layerwise image acquired with the powder bed camera installed on an EOS M290 during the production of a complex shape;” page 3, left column, “The build was produced by using a Ti6Al4V ELI gas atomized powder with average grain size lower than 45 μm supplied by TLS Technik. An EOS M290 equipped with an embedded powder bed camera mounting a 1280×1024 pixels sensor was used. Default process parameters defined by the AM service bureau that hosted the experimentation for the production of Ti6Al4V parts with this L-PBF system were applied. Fig. 3 shows a scheme of the placement of the powder bed camera and the low angle side illumination source already available in the machine.”).
Regarding dependent claim 3, the rejection of claim 1 is incorporated herein. Additionally, Pagani further discloses wherein each image acquired includes an internal contour and/or an external contour of the component being manufactured, the internal contour delimiting a perimeter of an internal space of the component in the image and the external contour delimiting an external perimeter of the component in the image (page 7, right column, “The use of the absolute value in the definition of di minmax allows one to signal any extreme deviation from the nominal geometry regardless of the direction of the deviation itself. If = d d| | i i minmax min , the most extreme deviation is towards the inside of the foreground region, which corresponds to a portion of the reconstructed slice that is missing. If = d d| | i i minmax max , the most extreme deviation is towards the outside of the foreground region, which corresponds to a portion of the re constructed slice that is larger than the nominal shape. Both these two conditions are of interest from a process monitoring perspective, as a lack of material or an excess of material in the slice are both potential symptoms of an anomaly.”).
Regarding dependent claim 4, the rejection of claim 1 is incorporated herein. Additionally, Pagani discloses acquiring an image after each step of depositing and melting a powder bed upon manufacturing said reference component (page 3, right column, “The layerwise image acquired at the end of the L-PBF of the current layer and before the recoating of the next layer needs to be pre-processed in order to enhance the results in following segmentation and analysis steps.”);
measuring dimensions of the reference component after manufacturing the reference component (page 9, right column, “Fig. 16 shows a detail of an ex-situ reconstruction of the deviation between the outer geometry of sample 1A measured by means of X-ray computed tomography (CT) and its nominal geometry.”);
checking compliance of the reference component by comparing the dimensions of the component with the dimensions provided by a specification (page 7, right column, “the estimation of the deviation between the in-situ reconstructed contour of the slice, representative of the as-built geometry in the current layer, and its nominal contour, representative of the as-designed geometry;” the designed geometry is read as the specification);
the reference template comprising the first set of images acquired of the reference component the compliance of which is checked (page 3, left column, “Fig. 2 (right panel) shows how different replicates of the test specimen were placed in the 250 mm×250mm build area of an EOS M290 L-PBF system. Orientations 1 and 2 were replicated three times (different re plicates were indicated with the capital letters A, B and C). Three additional replicates of the test specimen, namely 3A, 3B and 3C, were included into the build with a 45° orientation;” the reference geometry is determined from the actual produced specimens).
Regarding dependent claim 5, the rejection of claim 4 is incorporated herein. Additionally, Pagani in the combination further discloses wherein measuring the dimensions of the reference component after manufacturing the reference component is achieved by X-ray or dissection (page 9, right column, “Fig. 16 shows a detail of an ex-situ reconstruction of the deviation between the outer geometry of sample 1A measured by means of X-ray computed tomography (CT) and its nominal geometry.”).
Regarding dependent claim 6, the rejection of claim 5 is incorporated herein. Additionally, Pagani in the combination further discloses wherein the reference template is obtained from a plurality of reference components, each reference component the compliance of which with a specification is checked being associated with a set of images acquired of said component, the reference template including the sets of images acquired (page 3, left column, “Fig. 2 (right panel) shows how different replicates of the test specimen were placed in the 250 mm×250mm build area of an EOS M290 L-PBF system. Orientations 1 and 2 were replicated three times (different re plicates were indicated with the capital letters A, B and C). Three additional replicates of the test specimen, namely 3A, 3B and 3C, were included into the build with a 45° orientation;” the analysis is viewed at multiple angles and also at each layer).
Regarding dependent claim 9, the rejection of claim 1 is incorporated herein. Additionally, Pagani further discloses wherein the reference template includes at least one set of images of at least one reference component, the method further comprising, after each image acquisition step, a step of superimposing an image of the reference template on the image acquired (page 5, “Fig. 5. Example of an acquired image (A) and its nominal mask (B), and the contour of the mask superimposed on the original image (C);” page 3, right column, “Fig. 5 shows an example of layer wise image (after camera perspective correction), the corresponding mask showing the nominal shape of the printed slice and their super imposition, which highlights the proper alignment between the image and the mask.”).
Regarding dependent claim 10, the rejection of claim 1 is incorporated herein. Additionally, Pagani further discloses comprising stopping manufacture and/or modifying parameters of the additive manufacturing machine, in the event of non-dimensional compliance of the component being manufactured (page 7, right column, “Since the goal of the proposed method is to automatically signal only anomalous large deviations from the nominal shape, a one-sided control chart is proposed. It allows comparing the di minmax index value in the ith layer with an upper control limit (UCL) and, whenever the computed value violates the limit, an alarm is signalled;” page 10, right column, “With the available spatial resolution, the signalled alarms corresponded to deviations in the order of about 1.5–3mm. These deviation entities were in agreement with the distortions observed via X-ray CT;” page 12, right column, “However, if a major departure from the expected shape is observed in one layer, it is worth signalling to let the operator decide if actions are needed or, at least, to support following post-process qualification steps.”).
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.
Claim(s) 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Pagani.
Regarding dependent claim 7, the rejection of claim 6 is incorporated herein. Additionally, Pagani further discloses wherein the reference template is obtained from at least two reference components(page 7, right column, “The use of the absolute value in the definition of di minmax allows one to signal any extreme deviation from the nominal geometry regardless of the direction of the deviation itself. If = d d| | i i minmax min , the most extreme deviation is towards the inside of the foreground region, which corresponds to a portion of the reconstructed slice that is missing. If = d d| | i i minmax max , the most extreme deviation is towards the outside of the foreground region, which corresponds to a portion of the re constructed slice that is larger than the nominal shape. Both these two conditions are of interest from a process monitoring perspective, as a lack of material or an excess of material in the slice are both potential symptoms of an anomaly.” Page 7, right column, “The minimum and maximum deviations from the nominal contour in the ith layer can be estimated as follows:” see equation 8).
In the case of Pagani as noted above, Pagani uses one entire dataset for the determination of the deviation values. However, one of ordinary skill in the art before the effective filing date would easily understand the ability to generate two separate data sets; one correlating to a inside deviation and one to an outside. Said differently, being that the values are determined based on the sample itself in Pagani, one sample imaged may have deviations on the inside of the object, while others may have deviations on the outer side. Thus, imaging one object using one data set may not be enough to quantify deviations in both the inner and outer dimensions. Thus, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Pagani in order to accurately quantify the changes using multiple images of multiple objects as a measuring point.
Regarding dependent claim 8, the rejection of claim 6 is incorporated herein. Additionally, Pagani fails to explicitly disclose wherein the reference template is obtained from a mean between the contours of the plurality of sets of images for each reference component.
However, Pagani discloses at page 3, left column, “Fig. 2 (right panel) shows how different replicates of the test specimen were placed in the 250 mm×250mm build area of an EOS M290 L-PBF system. Orientations 1 and 2 were replicated three times (different re plicates were indicated with the capital letters A, B and C). Three additional replicates of the test specimen, namely 3A, 3B and 3C, were included into the build with a 45° orientation.” Thus, Pagani does discloser determining a reference set from a plurality of values. One of ordinary skill in the art before the effective filing date of the claimed invention would easily know that when a plurality of values are analyzed, using mean or averaging allow for limiting the impacts of an extreme. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Pagani in order to ensure extreme measurements don’t have a massive effect on the output value to be measured against.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
U.S. Publication No. 2018/0341248 to Mehr et al. discloses, “machine learning-based methods and systems for automated object defect classification and adaptive, real-time control of additive manufacturing and/or welding processes (abstract).”
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/COURTNEY JOAN NELSON/Primary Examiner, Art Unit 2661
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