DETAILED ACTIONNotice 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 Objections
Claims 1, 5 and 11 are objected to because of the following informalities: The following lack antecedent basis: In claim 1, lines 7 and 8, “the display” and on lines 14 – 17 and 19, “the thickness measurements”. In claim 5, line 1, “the object use data”. In claim 11, line 15, “the thickness measurements”. Appropriate corrections are required.
Claim Rejections - 35 USC § 103
3. 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. 4. 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.
5. Claims 1 - 6, 9 - 17 and 20 are rejected under 35 U.S.C. 103 as being
unpatentable over Corriere et al. (2016/0148446, hereinafter Corriere) in view of Takigawa et al. (DE102017105224, hereinafter Takigawa).
Regarding claim 1, Corriere discloses a method and apparatus comprising at least one inspection device that includes a handheld computing device 912 (See Fig. 82) configured with an authentication tool to authenticate a user to the at least one inspection device, and an augmented reality application to present measuring locations on an inspected object as overlay data on the inspected object via a display, a meter 77 portion comprising at least two different meters configured to measure at least a thickness of layers formed on surfaces of the inspected object, an imaging device 72 configured to acquire an image of a region of interest on the inspected object; communication circuits configured to transmit at least the thickness measurements and images of the inspected object; and a server system configured to receive and store the thickness measurements and images from the at least one inspection device, (See Pg. 1, Para. 0013, Pg. 4, Para. 0103, Pg. 5, Para. 0114 and Pg. 6, Para. 0125 - 0127). Corriere fails to disclose that the server system comprises at least one machine learned statistical model configured to receive at least the thickness measurement and images as input values. However, Takigawa discloses an apparatus comprising a server system that comprises at least one machine learned statistical model 10, 13 configured to receive at least a thickness measurement of a workpiece 7 and images as input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 2, Corriere fails to disclose that the at least one machine learned statistical model is configured to generate valuation data for the inspected object in response to the input values. However, in Takigawa, the at least one machine learned statistical model is configured to generate valuation data for the inspected object in response to the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 3, Corriere fails to disclose that the at least one machine learned statistical model is configured to generate anticipated maintenance data for the inspected object in response to the input values. However, in Takigawa, the at least one machine learned statistical model is configured to generate anticipated maintenance data for the inspected object in response to the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 4, Corriere fails to disclose that the server system is configured to receive object identification values and object use data for other objects as training data for the at least one machine learned statistical model. However, in Takigawa, a server system 18 is configured to receive object identification values and object use data for other objects as training data for the at least one machine learned statistical model (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 5, in Corriere, object use data comprises location data (See Pg. 4, Para. 0103).
Regarding claim 6, in Corriere, the location data comprises global position system data (See Pg. 4, Para. 0103 and Pg. 6, Para. 0128). Regarding claim 9, Corriere fails to disclose that an object identification device is configured to store and transmit object identification data and object use data; and the at least one machine learned statistical model is configured to receive the object identification data and object use data as the input values. However, in Takigawa, an object identification device is configured to store and transmit object identification data and object use data; and the at least one machine learned statistical model 10, 13 is configured to receive the object identification data and object use data as the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 10, Corriere fails to disclose that the object identification device comprises an on-board diagnostic type device. However, in Takigawa, the object identification device comprises an on-board diagnostic type device (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 11, in Corriere, the at least one inspection device is authenticated to a user, a display presents overlay data on an image of an inspected object as it is viewed, the overlay data including inspection points on the inspected object; a meter portion 77 measures at least a thickness of a layer formed on a surface of the inspected object at the inspection points; at least one image of the inspected device is acquired, communication circuits are provided that receive at least object identification (ID) data for the inspected device and transmit at least the thickness measurements and object ID data; and the object ID data and thickness measurements are received at a server system (See Pg. 1, Para. 0013, Pg. 4, Para. 0103, Pg. 5, Para. 0114 and Pg. 6, Para. 0125 - 0127). Corriere fails to disclose applying at least the object ID data and thickness measurements as input values to at least one machine learned statistical model. However, Takigawa discloses an apparatus comprising a server system that comprises at least one machine learned statistical model 10, 13 configured to receive at least a thickness measurement of a workpiece 7 and images as input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 12, Corriere fails to disclose that by operation of the at least one machine learned statistical model, generating valuation data for the inspected object. However, in Takigawa, the at least one machine learned statistical model is configured to generate valuation data for the inspected object in response to the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 13, Corriere fails to disclose that by operation of the at least one machine learned statistical model, generating anticipated maintenance data for the inspected object. However, in Takigawa, the at least one machine learned statistical model is configured to generate anticipated maintenance data for the inspected object in response to the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 14, Corriere fails to disclose receiving object use data for the inspected object at the server system; and applying the object use data as input values to the at least one machine learned statistical model. However, in Takigawa, a server system 18 is configured to receive object identification values and object use data for other objects as training data for the at least one machine learned statistical model (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 15, in Corriere, object use data comprises location data (See Pg. 4, Para. 0103).
Regarding claim 16, Corriere fails to disclose receiving at least the object use data from an object identification device of the inspected object. However, in Takigawa, an object identification device is configured to store and transmit object identification data and object use data; and the at least one machine learned statistical model 10, 13 is configured to receive the object identification data and object use data as the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 17, Corriere fails to disclose that the object identification device comprises an on-board diagnostic type device. However, in Takigawa, the object identification device comprises an on-board diagnostic type device (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2). Regarding claim 20, Corriere fails to disclose receiving object ID data and object use data for other objects at the server system; and training the at least one machine learned statistical model with at least the object ID data and object use data for other objects. However, in Takigawa, an object identification device is configured to store and transmit object identification data and object use data; and the at least one machine learned statistical model 10, 13 is configured to receive the object identification data and object use data as the input values (See Pg. 10, Paras. 2 – 5, Pg. 11, Paras. 1 – 3 and Pg. 23, Para. 6). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to modify Corriere according to the teachings of Takigawa for the purpose of, advantageously providing an improved device since this type of device can determine laser processing condition data that exists even when many laser processing condition parameters and many state variables of a laser processing system that can influence a laser processing result enable a detection of an optimal or substantially optimal machining result (See Takigawa, Pg. 5, Para. 2).
Allowable Subject Matter
Claims 7, 8, 18 and 19 are objected to as being dependent upon a rejected base
claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.7. The following is a statement of reasons for the indication of allowable subject matter: The primary reasons for indicating allowable subject matter is that the prior art does not anticipate or make obvious the provisions of “the at least one inspection device is configured to measure a physical spacing between adjacent parts of the inspected object; transmit physical spacing measurements; and the server system is configured to receive physical spacing measurements as part of the input values” (referring to claim 7) and “the server system is configured to determine a physical spacing between adjacent parts of inspected objects from data generated by the at least one inspection device” (referring to claim 8) in combination with the other limitations presented in claim 1 and “by operation of the at least one inspection device, generating spacing measurements by measuring a spacing between adjacent parts of the inspected object, and by operation of the wireless communication circuits of the inspection device, transmitting spacing measurements” (referring to claim 18) and “determining spacing measurements for spaces between adjacent parts of the inspected object, and applying the spacing measurements as input values to the at least one machine learned statistical model” (referring to claim 19) in combination with the other limitations presented in claim 11.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to
applicant's disclosure. 9. Nickel (11,566,881) discloses devices, systems, and methods for evaluating objects subject to repair or other alteration. Bare et al. (9,684,909) disclose a system and method for using an augmented reality display in surface treatment procedures. Corriere et al. (9,478,080) disclose a method and system for providing condition reports for vehicles. Koch et al. (RE41,342) disclose a coating thickness gauge. Dobler et al. (6,198,278) disclose a process for determining the thickness of a layer of electroconductive material deposited on a body. Pfanstiehl (6,055,860) discloses a method for measuring vehicle damage.10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to OCTAVIA HOLLINGTON whose telephone number is (571)272-2176. The examiner can normally be reached Monday-Friday 9am-5pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Breene can be reached at 5712724107. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/OCTAVIA HOLLINGTON/Primary Examiner, Art Unit 2855 2/6/26