DETAILED ACTION
Claims 1-20 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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) 1-3, 5-14, and 16-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ho (US PG Pub No. 2023/0198771 A1), and further in view of Santamala et al. (US PG Pub No. 2022/0198839 A1).
Regarding claim Ho teaches a method for dynamically allocating computing resources for processing data, the method comprising:
obtaining, over a network, data from one or more units associated with a manufacturing plant (Fig 1B; [0007], wherein data from sensors is received at a manufacturing plant), the data indicating addition of a new process or asset to the manufacturing plant ([0041-42], wherein new assets are added to the network);
determining one or more calculations to be performed for the new process or asset ([0042]; [0014]);
determining an amount of processing resources for performing the one or more calculations ([0008], wherein processing resources are consumed to manage IoT data, therefore it is inherent that an amount of resources is determined if they are to be consumed);
processing, by the combination of resources, the data obtained from the one or more units associated with the manufacturing plant to generate one or more performance indicators associated with the manufacturing plant ([0014], wherein performance indicators are calculated based on the data).
Ho does not teaches generating one or more signals configured to commission the amount of processing resources as a combination of resources from (i) processing resources associated with a cloud-computing system and (ii) processing resources located at a site of the manufacturing plant.
Santamala teaches the use of edge and cloud processing resources for the processing of tasks ([0030]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to commission the amount of processing resources as a combination of cloud and edge processing resources. One would be motivated by the desire to utilize all available processing resources to speed up execution of the tasks.
Ho and Santamala do not teaches providing, to a user device, the one or more performance indicators. It is old and well known to display performance indicators or metrics in user interface dashboards for system administers to view. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to display performance indicators in a user display. One would be motivated by the desire to communicate pertinent information to a system administrator.
Regarding claim 2, Ho teaches obtaining data from the one or more units associated with the manufacturing plant over the network comprises: obtaining data from one or more computers communicably connected to manufacturing devices at the manufacturing plant ([0007]).
Regarding claim 3, Ho teaches wherein determining the one or more calculations to be performed for the new process or asset comprises: parsing a configuration file that includes one or more metrics to be calculated for the new process or asset ([0014], wherein it is inherent that key performance indicators are configured ahead of time such that they are to be calculated).
Regarding claim 5, Ho does not teaches determining the amount of processing resources for performing the one or more calculations comprises: generating one or more values representing an amount of sub-calculations to perform per calculation and an amount of data to process for the one or more calculations; and determining the amount of processing resources for performing the one or more calculations using the one or more values representing the amount of sub-calculations to perform per calculation and the amount of data to process for the one or more calculations.
It is old and well known that calculation/tasks can be comprised of multiple sub-calculations/sub-tasks, each requiring processing resources. It is old and well known to calculate the amount of processing resources for a task before allocating resources accordingly. Therefore, it would have been obvious to one of ordinary skill in the art to determining the amount of processing resources for performing the one or more calculations using the one or more values representing the amount of sub-calculations to perform per calculation and the amount of data to process for the one or more calculations.
Regarding claim 6, Santamala teaches generating the one or more signals configured to commission (i) the processing resources associated with the cloud-computing system and (ii) the processing resources located at the site of the manufacturing plant comprises: generating a signal configured to turn on a processing component of the processing resources associated with the cloud-computing system or the processing resources located at the site of the manufacturing plant ([0030]).
Regarding claim 7, Ho teaches obtaining, over the network, data generated by the combination of resources encoded in signals transmitted by the combination of resources, wherein the data includes the one or more performance indicators ([0007]).
Regarding claim 8, Ho teaches providing a portion of the data from the one or more units associated with the manufacturing plant to the processing resources associated with the cloud-computing system ([0014]).
Regarding claim 9, Ho teaches providing, to the user device, the one or more performance indicators comprises: generating a signal encoded with data generated by the combination of resources ([0014]); and providing the signal to a transmitting antenna ([0066]).
Regarding claim 10, Ho teaches after obtaining the data indicating addition of the new process or asset to the manufacturing plant: obtaining incoming values from the new process or asset during operation at the manufacturing plant; and providing the incoming values to temporary cache storage ([0012-13]).
Regarding claim 11, Ho teaches wherein the data from the one or more units associated with the manufacturing plant include the incoming values from the new process or asset ([0041-42], wherein new assets are added to the network).
Regarding claim 12-14 and 16-20, they are the medium and system claims of claims 1-3 and 5-8 above. Therefore, they are rejected for the same reasons as claims 1-3 and 5-8 above.
Claim(s) 4 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ho (US PG Pub No. 2023/0198771 A1), in view of Santamala et al. (US PG Pub No. 2022/0198839 A1), further in view of Wen et al. (US PG Pub No. 2021/0278825 A1).
Regarding claim 4, Ho and Santamala do not teach updating a digital twin model representing the manufacturing plant to include the new process or asset.
Wen teaches simulating a manufacturing plant to simulate production schedules to simulate states and changes over time ([0025]; [0057]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to update a digital twin model representing the manufacturing plant to include the new process or asset. One would be motivated by the desire to bridge the gap between the simulator and actual manufacturing processes as taught by Wen ([0025])
Regarding claim 15, it is the medium claim of claim 4 above. Therefore, it is rejected for the same reasons as claim 4 above.
Conclusion
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/Eric C Wai/Primary Examiner, Art Unit 2195