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 .
Filed IDS of 07/30/2024 has been entered and considered.
Claims 1-20 are currently pending.
Please refer to the action below.
Examiner Notes
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. However, the claimed subject matter, not the specification, is the measure of the invention.
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, 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) 1, and 17 is/are rejected under 35 U.S.C. 103 as obvious over Yamashita et al. (JP, 2023061528, A1) in view of Delisle et al (US 2023/0359178, A1).
Regarding claim 1, Yamashita teaches a method for tracking productivity of a printing device (Yamashita teaches at least in Figs. 3-6 realtime tracking of a “method of detecting a decrease in productivity (the number of prints per unit time) during printing, which is a feature of the present invention, and a notification method when the print completion time is delayed due to the decrease in productivity” of the device),
the method comprising:
performing printing operations to print a print job at the printing device (the main control unit 110 of at least Figs. 1-2 is configured for causing the device 100 for performing printing operations to print a print job at the printing device 100);
determining a cause of a time delay
wherein the cause of the time delay relates to a component of the printing device (the disclosure further cites that the “storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”, which in a case may indicate a paper jam as the cause of the time delay relating understoodly to a component of the printing device);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (at least Fig. 4 and the disclosure further cites the causes
further illustrating the “storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”, further implying obviously said categorizing causes of the Tds as obviously an equipment issue or an operator issue based on the component);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (aggregating at least in Fig. 4 a compiled time delay Td, and delta T, related to an equipment issue Tm and a compiled time delay Tu related to an operator resolved issue, the delay as cited includes “unexpected delay time Td has occurred, if the excess Δt (=Td) from the theoretical print completion time Ts is within the range of the margin Tmg, productivity Do not notify of degradation. A productivity drop is notified only when the delay time Td exceeds the margin Tmg. FIG. 4 shows the case where the delay time Td occurs once, but a plurality of the same or different delay times Td1, Td2, . . . occurs, Δt=Td1+Td2+ . . . becomes. When this total delay time Δt exceeds the margin Tmg, an alarm 24 notifies of a decrease in productivity. It should be noted that even if the notification of the decrease in productivity is not given, the storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”);
determining an actual production time for the print job (the recalculation further in at least Fig. 4 discloses a case of determining an actual production time Tr for the print job);
wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue (wherein the actual production time Tr includes the compiled time delay delta Tm’s related to an equipment issue and the compiled time delay Tu related to an operator issue);
comparing the actual production time to an estimated production time for the print job (comparing further in Fig. 4 the time Ts to Tr to determine if a productivity alarm should be generated); and
alerting an operator based on the comparison (sensing the alarm 24 of the disclosure when the allotted print production time exceed the margin Tmg).
Yamashita is silent regarding the above lined-out items such as detecting a print engine of the printing device is not printing; determining said cause of said time delay at the print engine using at least one sensor and processing the print job to complete the printing operations at the printing device.
Delisle teaches in at least para. 0043-0044, and 0076-0095 tracking of productivity of the print machines 12/22 further depicted in at least Figs. 1-2, Delisle further teaches in at least para. 0084-0095 and para. 0021-0025 the detecting of a print engine of the printing device is not printing; and further determined and categorized further in para. 0084-0095 and Fig. 4 the cause of the time delay as an equipment issue or an operator issue based on the component, further calculating the duration of the downtime or the breaks in the productivity and add it to the production time 60 of at least Fig. 5 and generate a warning based on the comparison between the duration of the downtime or the break time duration corresponding to the planned production time; the system may further as disclose in at least para. 0033 outsourced the print job based on determined duration of machine downtime period or the causes thereof to a secondary print machine for processing the print job to complete the printing operations at the printing device; and/or after the recovery of the primary machine from the downtime to process obviously the print job to complete the printing operations at obviously the primary printing device. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yamashita in view of Delisle to include wherein detecting a print engine of the printing device is not printing; determining said cause of said time delay at the print engine using at least one sensor and processing the print job to complete the printing operations at the printing device, as discussed above, as of Yamashita in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Yamashita, in such a way that when combined with the combination architecture of Delisle, it enables the system the realtime tracking productivity data of Yamashita to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device,
according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 4 (according to claim 1), Yamashita further teaches wherein further comprising collecting a total time delay corresponding to the cause within the printing device (the disclosure further cites “FIG. 4 shows the case where the delay time Td occurs once, but a plurality of the same or different delay times Td1, Td2, . . . occurs, Δt=Td1+Td2+ . . . becomes”, the delta T further indicates the collecting total time delay).
Regarding claim 5 (according to claim 4), Yamashita further teaches wherein further comprising assigning a category for the cause and determining the total time delay within the category (the disclosure further cites “the storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence” further insinuating in the art the causes of the delay occurrence further comprises at least classified causes or assigning cause category for the cause and determining the delta T, as the total time delay within the category).
Regarding claim 17, Yamashita teaches at least in Figs. 1-2 a printing system comprising:
a processor (control device 110 of Figs. 1-2); and
a memory (storage 28 of Figs. 1-2) coupled to the processor,
wherein the memory includes instructions that, when executed on the processor, configures the printing system to perform the operations of performing printing operations to print a print job at the printing device (the main control unit 110 of at least Figs. 1-2 is configured for causing the device 100 for performing printing operations to print a print job at the printing device 100);
determining a cause of a time delay
wherein the cause of the time delay relates to a component of the printing device (the disclosure further cites that the “storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”, which in a case may indicate a paper jam as the cause of the time delay relating understoodly to a component of the printing device);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (at least Fig. 4 and the disclosure further cites the causes
further illustrating the “storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”, further implying obviously said categorizing causes of the Tds as obviously an equipment issue or an operator issue based on the component);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (aggregating at least in Fig. 4 a compiled time delay Td, and delta T, related to an equipment issue Tm and a compiled time delay Tu related to an operator resolved issue, the delay as cited includes “unexpected delay time Td has occurred, if the excess Δt (=Td) from the theoretical print completion time Ts is within the range of the margin Tmg, productivity Do not notify of degradation. A productivity drop is notified only when the delay time Td exceeds the margin Tmg. FIG. 4 shows the case where the delay time Td occurs once, but a plurality of the same or different delay times Td1, Td2, . . . occurs, Δt=Td1+Td2+ . . . becomes. When this total delay time Δt exceeds the margin Tmg, an alarm 24 notifies of a decrease in productivity. It should be noted that even if the notification of the decrease in productivity is not given, the storage unit 28 stores the information about the delay time Td, such as the delay time Td, the occurrence timing of the delay, and the cause of the occurrence”);
determining an actual production time for the print job (the recalculation further in at least Fig. 4 discloses a case of determining an actual production time Tr for the print job);
wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue (wherein the actual production time Tr includes the compiled time delay delta Tm’s related to an equipment issue and the compiled time delay Tu related to an operator issue);
comparing the actual production time to an estimated production time for the print job (comparing further in Fig. 4 the time Ts to Tr to determine if a productivity alarm should be generated); and
alerting an operator based on the comparison (sensing the alarm 24 of the disclosure when the allotted print production time exceed the margin Tmg).
Yamashita is silent regarding the above lined-out items such as detecting a print engine of the printing device is not printing; determining said cause of said time delay at the print engine using at least one sensor and processing the print job to complete the printing operations at the printing device.
Delisle teaches in at least para. 0043-0044, and 0076-0095 tracking of productivity of the print machines 12/22 further depicted in at least Figs. 1-2, Delisle further teaches in at least para. 0084-0095 and para. 0021-0025 the detecting of a print engine of the printing device is not printing; and further determined and categorized further in para. 0084-0095 and Fig. 4 the cause of the time delay as an equipment issue or an operator issue based on the component, further calculating the duration of the downtime or the breaks in the productivity and add it to the production time 60 of at least Fig. 5 and generate a warning based on the comparison between the duration of the downtime or the break time duration corresponding to the planned production time; the system may further as disclose in at least para. 0033 outsourced the print job based on determined duration of machine downtime period or the causes thereof to a secondary print machine for processing the print job to complete the printing operations at the printing device; and/or after the recovery of the primary machine from the downtime to process obviously the print job to complete the printing operations at obviously the primary printing device. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Yamashita in view of Delisle to include wherein detecting a print engine of the printing device is not printing; determining said cause of said time delay at the print engine using at least one sensor and processing the print job to complete the printing operations at the printing device, as discussed above, as of Yamashita in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Yamashita, in such a way that when combined with the combination architecture of Delisle, it enables the system the realtime tracking productivity data of Yamashita to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device,
according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
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 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.
Claim(s) 13-15 is/are rejected under 35 U.S.C. 102(a)(1) as unpatentable over Kikumoto et al. (US 2014/0368866, A1).
Regarding claim 13, Kikumoto teaches a method for managing printing operations (Kikumoto teaches at least in para. 0051 and Figs. 3, 5-6, 8-11 and 13 depicting methods and systems for managing printing operations and for tracking productivity of a printing device),
the method comprising:
performing printing operations to print a print job at the printing device (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts print engine operations statuses and performed printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts detected interrupted and delayed printing job operations further indicating said detecting print engine of the printing device is not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts determined causes of a time delay or interrupted at the print engine using at least one sensor, wherein the cause of the time delay relates in a case to a component failure of the printing device of at least para. 0065);
aggregating the time delay with an actual production time for the print job; (aggregating at least in Figs. 10-11 and para. 0067 compiled wait or delay times related to an equipment issue and a compiled time delay related to an operator paper insertion issue to an actual production time for the print job);
processing the print job to complete the printing operations at the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts cases of processing the print job to complete the printing operations at the printing device);
determining an efficiency for the print job based on the actual production time to an estimated production time for the print job (determining further in at least para. 0051, 0086 and Figs. 5-6 producibility percentage and completion percentage of the print device further collectively defining in the art a print/device efficiency for the print job based on the actual production time to an estimated production time for the print job);
compiling the efficiency for the print job with an overall efficiency for a time period at the printing device (compiling further at lest in Fig. 6 and para. 0051 the efficiency percentage for the print job with an implied overall efficiency of para. 0051 for a time period at the printing device);
determining that the overall efficiency for the time period at the printing device falls below an efficiency threshold for the printing device (determining in a case of further para. 0051 that a designated overall efficiency at the printing device falls below an efficiency threshold for the printing device); and
alerting an operator that the overall efficiency for the printing device is below the efficiency threshold (said alerting of further para. 0051).
Regarding claim 14 (according to claim 13), Kikumoto further teaches wherein further comprising defining the efficiency threshold for the printing device (the fall efficiency threshold of further para. 0051 further defined in a case said defining efficiency threshold for the printing device).
Regarding claim 15 (according to claim 13), Kikumoto further teaches wherein further comprising receiving the print job at the printing device (the system further in at least Fig. 4 further renders the print job at the select print device thereby obviously comprising receiving the print job).
Claim(s) 1-12, and 16-20 is/are further rejected under 35 U.S.C. 103 as obvious over Kikumoto in view of Delisle.
Regarding claim 1, Kikumoto teaches a method for tracking productivity of a printing device (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 depicts a method for tracking productivity of a printing device),
the method comprising:
performing printing operations to print a print job at the printing device (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts print engine operations statuses and performed printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts detected interrupted and delayed printing job operations further indicating said detecting print engine of the printing device is not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts determined causes of a time delay or interrupted at the print engine using at least one sensor, wherein the cause of the time delay relates in a case to a component failure of the printing device of at least para. 0065);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (para. 0065-0067);
processing the print job to complete the printing operations at the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts cases of processing the print job to complete the printing operations at the printing device);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (aggregating at least in Figs. 10-11 and para. 0067 compiled wait or delay times related to an equipment issue and a compiled time delay related to an operator paper insertion issue);
determining an actual production time for the print job (at least in Figs. 10-11 further teaches actual production time for the print job);
comparing the actual production time to an estimated production time for the print job (at least in Figs. 10-11 and para. 0035 further teaches actual production time for the print job corresponding to predict start and end times); and
alerting an operator based on the comparison (providing the display interface of further Figs. 3, 5-6, 8-11 and 13 as a further productivity or efficiency notification or alert to an operator based on the comparison).
Kikumoto is silent regarding the above lined-out items such as citing specifically wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue.
Delisle teaches a case of at least para. 0082-0093 and Fig. 5 machine learning methods and systems to track productivity period, job efficiency and an actual production time including said compiled downtime or time delay related in a case to an equipment issue and the compiled time delay related to an operator issue. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Delisle to include wherein actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue, as discussed above, as of Kikumoto in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Kikumoto, in such a way that when combined with the combination architecture of Delisle, it enables the system to atomate the systems utilizing machine learnings for the realtime tracking productivity data of Kikumoto to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device, according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 2 (according to claim 1), Kikumoto further teaches wherein further comprising displaying the time delay within a calendar view (displaying further in at least Figs. 10-11 said estimated displayed time delays within an understood calendar view);
wherein the calendar view shows a graphic for the print job (displaying further at least in Figs. 6-7 a scheduled view showing a graphic for the print job, said scheduled view further indicative in the art of said calendar view shows a graphic for the print job).
Regarding claim 3 (according to claim 2), Kikumoto further teaches wherein the graphic is modified based on the time delay (graphic of further Figs. 8-11 and 13 further modified based at least in a case on the time delay).
Regarding claim 4 (according to claim 1), Kikumoto further teaches wherein further comprising collecting a total time delay corresponding to the cause within the printing device (collecting further in at least Figs. 8-11 and 13 a total time delay corresponding to the cause within the printing device
Regarding claim 5 (according to claim 4), Kikumoto further teaches wherein further comprising assigning a category for the cause and determining the total time delay within the category (assigned further in at least Figs. 10-11 a category for the cause and determining the total time delay within the category).
Regarding claim 6 (according to claim 1), Kikumoto further teaches wherein further comprising determining an efficiency at the printing device based on the compared actual production to the estimated production time for a time period at the printing device (Kikumoto further teaches at least in para. 0086 and 0051 the print efficiency associated with print productivity percentages and completed jobs percentages further indicating said determining efficiency at the printing device based on the compared actual production to the estimated production time for a time period at the printing device).
Regarding claim 7 (according to claim 6), Kikumoto further teaches wherein further comprising defining an efficiency threshold for the printing device (the system further in at least Figs. 5-6 assessed or defined productivity percentage further indicating as implied further in at least para. 0051 an efficiency threshold for the printing device which as cited when “extremely low, the user is able to intensively consider measures to increase the productivity”).
Regarding claim 8 (according to claim 7), Kikumoto further teaches wherein further comprising determining that the efficiency for processing at the printing device falls below the efficiency threshold (para. 0051).
Regarding claim 9 (according to claim 8), Kikumoto further teaches wherein further comprising alerting the operator that the efficiency for the print device is below the efficiency threshold (para. 0051).
Regarding claim 10 (according to claim 1), Kikumoto further teaches wherein further comprising receiving the print job at the printing device (the system further in at least Fig. 4 further renders the print job at the select print device thereby obviously comprising receiving the print job).
Regarding claim 11 (according to claim 10), Kikumoto is silent regarding wherein further comprising estimating the estimated production time for the print job using a neural network system.
Delisle teaches a case of at least para. 0082-0093 and Fig. 5 machine learning methods and systems comprising said neural network system to track productivity period, job efficiency and an actual production time including said compiled downtime or time delay related in a case to an equipment issue and the compiled time delay related to an operator issue. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Delisle to include wherein said estimating estimated production time for the print job using a neural network system, as discussed above, as of Kikumoto in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Kikumoto, in such a way that when combined with the combination architecture of Delisle, it enables the system to atomate the systems utilizing machine learnings for the realtime tracking productivity data of Kikumoto to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device, according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 12 (according to claim 11), Kikumoto is silent regarding wherein further comprising inputting the actual production time into the neural network system.
Delisle teaches a case of at least para. 0082-0093 and Fig. 5 machine learning methods and systems to track productivity period, job efficiency and an actual production time including said compiled downtime or time delay based understoodly on inputted actual production time into the learning systems embodying understoodly said neural network system. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Delisle to include wherein said inputting the actual production time into the neural network system, as discussed above, as of Kikumoto in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Kikumoto, in such a way that when combined with the combination architecture of Delisle, it enables the system to atomate the systems utilizing machine learnings for the realtime tracking productivity data of Kikumoto to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device, according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 16 (according to claim 15), Kikumoto is silent regarding wherein further comprising estimating the estimated production time for the print job using a neural network system.
Delisle teaches a case of at least para. 0082-0093 and Fig. 5 machine learning methods and systems comprising said neural network system to track productivity period, job efficiency and an actual production time including said compiled downtime or time delay related in a case to an equipment issue and the compiled time delay related to an operator issue. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Delisle to include wherein said estimating estimated production time for the print job using a neural network system, as discussed above, as of Kikumoto in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Kikumoto, in such a way that when combined with the combination architecture of Delisle, it enables the system to atomate the systems utilizing machine learnings for the realtime tracking productivity data of Kikumoto to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device, according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 17, Kikumoto teaches at least in Fig. 1 a printing system comprising:
a processor (print controller 12); and
a memory (para. 0037) coupled to the processor,
wherein the memory includes instructions that, when executed on the processor, configures the printing system to perform the operations of performing printing operations to print a print job at a printing device (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts print engine operations statuses and performed printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (graphical display 14e of at least Figs. 3, 5-6, 8-11 and 13 further depicts detected interrupted and delayed printing job operations further indicating said detecting print engine of the printing device is not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts determined causes of a time delay or interrupted at the print engine using at least one sensor, wherein the cause of the time delay relates in a case to a component failure of the printing device of at least para. 0065);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (para. 0065-0067);
processing the print job to complete the printing operations at the printing device (graphical display 14e of at least Figs. 10-11, and 13 and para. 0065-0066 further depicts cases of processing the print job to complete the printing operations at the printing device);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (aggregating at least in Figs. 10-11 and para. 0067 compiled wait or delay times related to an equipment issue and a compiled time delay related to an operator paper insertion issue);
determining an actual production time for the print job (at least in Figs. 10-11 further teaches actual production time for the print job);
comparing the actual production time to an estimated production time for the print job (at least in Figs. 10-11 and para. 0035 further teaches actual production time for the print job corresponding to predict start and end times); and
alerting an operator based on the comparison (providing the display interface of further Figs. 3, 5-6, 8-11 and 13 as a further productivity or efficiency notification or alert to an operator based on the comparison).
Kikumoto is silent regarding the above lined-out items such as citing specifically wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue.
Delisle teaches a case of at least para. 0082-0093 and Fig. 5 machine learning methods and systems to track productivity period, job efficiency and an actual production time including said compiled downtime or time delay related in a case to an equipment issue and the compiled time delay related to an operator issue. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Delisle to include wherein actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue, as discussed above, as of Kikumoto in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Kikumoto, in such a way that when combined with the combination architecture of Delisle, it enables the system to atomate the systems utilizing machine learnings for the realtime tracking productivity data of Kikumoto to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device,
according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 18 (according to claim 17), Kikumoto further teaches wherein the operations further comprise determining an efficiency at the printing device based on the compared actual production to the estimated production time for a time period at the printing device (Kikumoto further teaches at least in para. 0086 and 0051 and Figs. 5-6 the print efficiency associated with print productivity percentages and completed jobs percentages further indicating said determining efficiency at the printing device based on the compared actual production to the estimated production time for a time period at the printing device).
Regarding claim 19 (according to claim 18), Kikumoto further teaches wherein the operations further comprise defining an efficiency threshold for the printing device (the system further in at least Figs. 5-6 assessed or defined productivity percentage further indicating as implied further in at least para. 0051 an efficiency threshold for the printing device which as cited when “extremely low, the user is able to intensively consider measures to increase the productivity”).
Regarding claim 20 (according to claim 19), Kikumoto further teaches wherein the operations further comprise determining that the efficiency for processing at the printing device falls below the efficiency threshold (para. 0051).
Claim(s) 1, and 17 is/are further rejected under 35 U.S.C. 103 as obvious over Sasaki et al. (AU 2020210235, A1), in view of Yamashita et al.
Regarding claim 1, Sasaki teaches a method for tracking productivity of a printing device (at least pages 10-12 teaches a method for tracking productivity of a printing device 20),
the method comprising:
performing printing operations to print a print job at the printing device (the at least printers 20 of further pages 10-12 further configured for performing printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (at least Fig. 8 and pages 11 and 22 further illustrates a case detecting an abnormality of printer 20 not printing which abnormality causes may comprise at least one of the RIP, system down, device error further comprises obviously print engine abnormality of the printing device not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (detected abnormality event of Figs. 8, and 12, further comprises determined causes and types of a time delay using at least one sensor, wherein the cause of the time delay of further pages 21-22 and Fig. 8 relates in a case to a component of the printing device);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (categorizing further in at least Fig. 8 and page 22 said cause of the time delay as an equipment issue or an operator issue based on the component);
processing the print job to complete the printing operations at the printing device (the disclosure further cites a case of processing said print job after the time delay such as “in a case where an abnormality occurs in the printing device 20 and it is estimated that end time of the print process calculated from the estimated completion prediction time of the print process is delayed more than end time of the planned print process 38, some countermeasures may be taken to remove the delay. As one of the countermeasures, it is conceivable to remove the delay by adding at least one printing device 20 (hereinafter, referred to as a "preliminary printing device 20B") that is not previously assigned to a print process in which a delay occurs initially and that is in an unavailable state, to the printing device 20 different from the printing device 20 (hereinafter, referred to as an "operational printing device 20A") that is previously assigned to the print process and is in printing, during the print process, and by performing printing using the preliminary printing device 20B” and further in at least page 29 another printing countermeasure of finishing the job at the initial print device after the abnormality is resolved);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (at least steps S38 and page 25 further illustrates aggregating at least compiled delay or recovery times related to an equipment issue before notifying the recovery worker and a compiled time delay related to a specific worker performing the recovery);
determining an actual production time for the print job (at least pages 20-21 and 29 further teaches actual production time for the print job);
wherein the actual production time includes the compiled time delay related to an equipment issue or the compiled time delay related to an operator issue (at least Fig. 12 and page 29 further illustrates a new predict time being estimated as the combined actual production time including the compiled recovery time of the time delay related to an equipment issue or the compiled time delay related to an operator issue);
comparing the actual production time to an estimated production time for the print job (at least pages 20-21 and 29 further teaches comparing the actual production time for the print job with an estimated prediction production time for the print job); and
alerting an operator based on the comparison (providing a notification to an administrator of at least page 33 and 29 based on an estimation comparison).
However, Sasaki is silent regarding specifically wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue; comparing said actual production time to an estimated production time for the print job and alerting an operator based on said comparison.
Yamashita is configured at least in the Abstract and Figs. 3-4, and 6 to generate an actual production time as the estimated print completion time Tr comprising actual production time and compiled job time delay related to an equipment issue and the compiled time delay related to an operator issue where based on a margin calculation the system may determine that said actual production time compared to an estimated production time for the print job fall below a threshold and configured in that case alerting an operator of productivity deterioration based on said comparison. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Sasaki in view of Yamashita to include wherein actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue; comparing said actual production time to an estimated production time for the print job and alerting an operator based on said comparison, as discussed above, as of Sasaki in view of Yamashita are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Yamashita’s combination of combining print completion time estimation with the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue and the performed comparison further compliments the realtime monitoring and tracking productivity data of the printing device of Sasaki, in such a way that when combined with the combination architecture of Yamashita, it enables the system to automatedly determine efficiency of the print system when comparing the actual print completion statics to the overall print delay times wherein optimized countermeasures may be taken to overcome future or current delay events according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 17, Sasaki teaches at least in Figs. 1-2 a printing system comprising:
a processor (control device 110 of Figs. 1-2) and a memory (storage 28 of Figs. 1-2) coupled to the processor, wherein the memory includes instructions that, when executed on the processor, configures the printing system to perform the operations of performing printing operations to print a print job at the printing device (the at least printers 20 of further pages 10-12 further configured for performing printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (at least Fig. 8 and pages 11 and 22 further illustrates a case detecting an abnormality of printer 20 not printing which abnormality causes may comprise at least one of the RIP, system down, device error further comprises obviously print engine abnormality of the printing device not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (detected abnormality event of Figs. 8, and 12, further comprises determined causes and types of a time delay using at least one sensor, wherein the cause of the time delay of further pages 21-22 and Fig. 8 relates in a case to a component of the printing device);
categorizing the cause of the time delay as an equipment issue or an operator issue based on the component (categorizing further in at least Fig. 8 and page 22 said cause of the time delay as an equipment issue or an operator issue based on the component);
processing the print job to complete the printing operations at the printing device (the disclosure further cites a case of processing said print job after the time delay such as “in a case where an abnormality occurs in the printing device 20 and it is estimated that end time of the print process calculated from the estimated completion prediction time of the print process is delayed more than end time of the planned print process 38, some countermeasures may be taken to remove the delay. As one of the countermeasures, it is conceivable to remove the delay by adding at least one printing device 20 (hereinafter, referred to as a "preliminary printing device 20B") that is not previously assigned to a print process in which a delay occurs initially and that is in an unavailable state, to the printing device 20 different from the printing device 20 (hereinafter, referred to as an "operational printing device 20A") that is previously assigned to the print process and is in printing, during the print process, and by performing printing using the preliminary printing device 20B” and further in at least page 29 another printing countermeasure of finishing the job at the initial print device after the abnormality is resolved);
aggregating a compiled time delay related to an equipment issue and a compiled time delay related to an operator issue (at least steps S38 and page 25 further illustrates aggregating at least compiled delay or recovery times related to an equipment issue before notifying the recovery worker and a compiled time delay related to a specific worker performing the recovery);
determining an actual production time for the print job (at least pages 20-21 and 29 further teaches actual production time for the print job);
wherein the actual production time includes the compiled time delay related to an equipment issue or the compiled time delay related to an operator issue (at least Fig. 12 and page 29 further illustrates a new predict time being estimated as the combined actual production time including the compiled recovery time of the time delay related to an equipment issue or the compiled time delay related to an operator issue);
comparing the actual production time to an estimated production time for the print job (at least pages 20-21 and 29 further teaches comparing the actual production time for the print job with an estimated prediction production time for the print job); and
alerting an operator based on the comparison (providing a notification to an administrator of at least page 33 and 29 based on an estimation comparison).
However, Sasaki is silent regarding specifically wherein the actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue; comparing said actual production time to an estimated production time for the print job and alerting an operator based on said comparison.
Yamashita is configured at least in the Abstract and Figs. 3-4, and 6 to generate an actual production time as the estimated print completion time Tr comprising actual production time and compiled job time delay related to an equipment issue and the compiled time delay related to an operator issue where based on a margin calculation the system may determine that said actual production time compared to an estimated production time for the print job fall below a threshold and configured in that case alerting an operator of productivity deterioration based on said comparison. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Kikumoto in view of Sasaki in view of Yamashita to include wherein actual production time includes the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue; comparing said actual production time to an estimated production time for the print job and alerting an operator based on said comparison, as discussed above, as of Sasaki in view of Yamashita are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Yamashita’s combination of combining print completion time estimation with the compiled time delay related to an equipment issue and the compiled time delay related to an operator issue and the performed comparison further compliments the realtime monitoring and tracking productivity data of the printing device of Sasaki, in such a way that when combined with the combination architecture of Yamashita, it enables the system to automatedly determine efficiency of the print system when comparing the actual print completion statics to the overall print delay times wherein optimized countermeasures may be taken to overcome future or current delay events according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Claim(s) 13 is/are further rejected under 35 U.S.C. 103 as obvious over Sasaki in view of Delisle.
Regarding claim 13, Sasaki teaches a method for managing printing operations (at least pages 10-12 teaches a method for tracking printing operations, managing printers and tracking their productivity),
the method comprising:
performing printing operations to print a print job at the printing device (the at least printers 20 of further pages 10-12 further configured for performing printing job operations to print a print job at the printing device);
detecting a print engine of the printing device is not printing (at least Fig. 8 and pages 11 and 22 further illustrates a case detecting an abnormality of printer 20 not printing which abnormality causes may comprise at least one of the RIP, system down, device error further comprises obviously print engine abnormality of the printing device not printing);
determining a cause of a time delay at the print engine using at least one sensor, wherein the cause of the time delay relates to a component of the printing device (detected abnormality event of Figs. 8, and 12, further comprises determined causes and types of a time delay using at least one sensor, wherein the cause of the time delay of further pages 21-22 and Fig. 8 relates in a case to a component of the printing device);
aggregating the time delay with an actual production time for the print job (at least Fig. 12 and pages 20-21, and 29 further illustrates compiled and aggregating recovery time associated with delay time in addition to combined actual production time to estimate a predict print completion time);
processing the print job to complete the printing operations at the printing device (the disclosure further cites a case of processing said print job after the time delay such as “in a case where an abnormality occurs in the printing device 20 and it is estimated that end time of the print process calculated from the estimated completion prediction time of the print process is delayed more than end time of the planned print process 38, some countermeasures may be taken to remove the delay. As one of the countermeasures, it is conceivable to remove the delay by adding at least one printing device 20 (hereinafter, referred to as a "preliminary printing device 20B") that is not previously assigned to a print process in which a delay occurs initially and that is in an unavailable state, to the printing device 20 different from the printing device 20 (hereinafter, referred to as an "operational printing device 20A") that is previously assigned to the print process and is in printing, during the print process, and by performing printing using the preliminary printing device 20B” and further in at least page 29 another printing countermeasure of finishing the job at the initial print device after the abnormality is resolved);
However, Sasaki is silent regarding specifically determining an efficiency for the print job based on the actual production time to an estimated production time for the print job; compiling the efficiency for the print job with an overall efficiency for a time period at the printing device; determining that the overall efficiency for the time period at the printing device falls below an efficiency threshold for the printing device; and alerting an operator that the overall efficiency for the printing device is below the efficiency threshold.
Delisle teaches a case of at least para. 0051, 0082-0093 and Figs. 5-6 machine learning methods and systems to track an actual production time including said compiled downtime or time delay, productivity period, and job efficiency further indicating tracked efficiency for the print job based on the actual production time to an estimated production time for the print job where the productivity and completion percentages further comprises compiled efficiency for the print job with an overall efficiency for a time period at the printing device and further determining in para. 0051 and 0086 determining overall efficiency for the time period at the printing device which when falls below an efficiency threshold for the printing device for alerting an operator that the overall efficiency for the printing device is below the efficiency threshold. It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Sasaki in view of Delisle to include wherein determining an efficiency for the print job based on the actual production time to an estimated production time for the print job; compiling the efficiency for the print job with an overall efficiency for a time period at the printing device; determining that the overall efficiency for the time period at the printing device falls below an efficiency threshold for the printing device; and alerting an operator that the overall efficiency for the printing device is below the efficiency threshold, as discussed above, as of Sasaki in view of Delisle are in the same of endeavor of monitoring and tracking in realtime productivity data of a printing device, Delisle’s combination of utilizing machine learning methods and systems to track actual and expected print production time, in addition to the print downtime calculation and the outsourcing of the print job to one or more secondary print device further compliments the realtime monitoring and tracking productivity data of the printing device of Sasaki, in such a way that when combined with the combination architecture of Delisle, it enables the system to automate the systems utilizing machine learnings for the realtime tracking productivity data of Sasaki to additionally detect printer malfunctions whether due to downtime, equipment failures or that of not printing wherein based on a recalculated actual productivity time data to determine whether the print job needs to be outsourced to secondary print devices whereby the system successfully complete processing of said printing operations at a printing device, according to further understood known means/methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Conclusion
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/MARCELLUS J AUGUSTIN/Primary Examiner, Art Unit 2682 06/22/2026
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