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 § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Claim 1 recites circulation data parcels, with the circulation data parcels being assigned to production system and request system accounts, match production capacity entries with production capacity nodes, with the production capacity nodes designating capacity categories, parameters, and magnitudes, designate the production capacity nodes as available or unavailable for the production system data profiles; v. designate the circulation data parcels as available or unavailable for the request system accounts, detecting a production initiation between a given request system and a given downstream production system, then detecting production requirements and circulation data parcel requirements associated with the production initiation, available production capacity nodes associated with the given downstream production system and available circulation data parcels assigned to the given request system, matching production requirements with production requirement nodes, with the production requirement nodes designating requirement categories, parameters, and magnitudes, comparing the production requirement nodes with the available production capacity nodes, designating the available production capacity nodes as sufficient if the available production capacity nodes correspond to the production requirement nodes, comparing the circulation data parcel requirements with the available circulation data parcels, designating the available circulation data parcels as sufficient if the circulation data parcel availability data corresponds with the circulation data parcel requirements, if both the available circulation data parcels and the available production capacity nodes are designated as sufficient, then designating portions of the available circulation data parcels and the available production capacity nodes as unavailable according to the circulation data parcel requirements and production requirement nodes and designating the production initiation as enabled; vii. track production progress by, extracting production progress indicator data from the production requirement nodes, creating production progress nodes using the production progress indicator data, with the production progress nodes designating progress categories, parameters, and magnitudes, comparing production update nodes with the production progress nodes, designating production update nodes as insufficient if the production update nodes do not correspond to the production progress nodes, creating production update nodes by combining production update entries, with the production update nodes designating update categories, parameters, and magnitudes, designating production update nodes as sufficient if the production update nodes correspond to the production progress nodes; viii. secure production progress by, if the production update nodes are designated as sufficient, then assigning to the production accounts circulation data parcels that were previously assigned to the request accounts according to the circulation data parcel requirements, if the production update nodes are designated as insufficient, then assigning to the request accounts circulation data parcels that were previously assigned to the given production accounts according to the circulation data parcel requirements. The above steps pertains to a mental process since assigning, designating, creating, determining, detecting, etc. can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
The claim does not integrate the judicial exceptions into a practical application. The claim includes additional limitations including: b. request systems, with the request systems comprising request system processors, request system accounts, and request system data profiles, confirmation input devices, with the confirmation input devices configured to detect or receive production capacity entries and production update entries; i. receive production capacity entries and production update entries from the confirmation input devices and receiving production update entries from the confirmation input devices,. These limitations are recited at a high level of generality and amount to mere data gathering and output recited at a high level of generality and thus are insignificant extra solution activity (MPEP 2106.05(g)). The claim further recites the additional elements of downstream production systems, with the downstream production systems comprising production system processors, production system accounts, and production system data profiles; e. a control system, with the control system comprising control processors. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As noted above, the receiving step relates to insignificant extra solution activity (MPEP 2106.05(g)). Further, downstream production systems, with the downstream production systems comprising production system processors, production system accounts, and production system data profiles; e. a control system, with the control system comprising control processors amounts to field of use and technological environment (2106.05(h)). Additionally, the receiving step amounts to receiving or transmitting data over a network and is well understood routine and conventional in the field (MPEP 2106.05(d)(II)). The claim does not include any further additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, claim 1 is rejected. Claim 17 recites similar limitations and is similarly rejected.
Claim 2 recites with the circulation data parcels being cryptocurrency tokens. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 2 is rejected.
Claim 3 recites with the production capacity entries including resource, equipment, hardware, and software data. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 3 is rejected.
Claim 4 recites with the production capacity entries including worker or user data. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 4 is rejected.
Claim 5 recites with the production update entries including part, unit, material, or product data. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 5 is rejected.
Claim 6 recites with the confirmation input devices including text input devices, with the text input devices configured to receive text descriptions. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 6 is rejected.
Claim 7 recites with the confirmation input devices including image capturing devices. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 7 is rejected.
Claim 8 recites with the confirmation input devices including EM readers configured to detect EM tags. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 8 is rejected.
Claim 9 recites with the confirmation input devices including sensors. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 9 is rejected.
Claim 10 recites with the sensors including weight sensors, optical sensors, turbidity sensors, pressure sensors, chemical sensors, geographical positioning sensors, time sensors, or fingerprint sensors. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 10 is rejected.
Claim 11 recites with the control processors programmed to format a plurality of third-party standards and regulations data from a plurality of disparate formats into a uniform assessment format and create assessment nodes using the standards and regulations data in the uniform assessment format, a. with the assessment nodes designating assessment categories, parameters, and magnitudes. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
Therefore, claim 11 is rejected.
Claim 12 recites with the control processors programmed to secure production progress by: a. comparing production update nodes with the assessment nodes; b. designating production update nodes as insufficient if the production update nodes do not correspond to the assessment nodes; c. designating production update nodes as sufficient if the production update nodes correspond to the assessment nodes. The above steps pertains to a mental process since comparing and designating can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 12 is rejected.
Claim 13 recites with the control processors programmed to secure production progress by: a. comparing production update nodes with the assessment nodes; b. designating production update nodes as insufficient if the production update nodes do not correspond to the assessment nodes; c. designating production update nodes as sufficient if the production update nodes correspond to the assessment nodes. The above steps pertains to a mental process since comparing and designating can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 13 is rejected.
Claim 14 recites additionally comprising upstream production systems, a. with the control processors programmed to track exchanges of circulation data parcels between downstream and upstream production systems, create transitive production capacity nodes and stock the downstream production system profiles with the transitive production capacity nodes; b. with the transitive production capacity nodes indicating the upstream production systems and the exchanged circulation data parcels. The above steps pertains to a mental process since create can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 14 is rejected.
Claim 15 recites the control processors programmed to enable production initiation by: a. designating the available production capacity nodes as insufficient if the available production capacity nodes do not correspond to the production requirement nodes, then determining if the given downstream production system is stocked with production capacity nodes that separately or in concert with the available production capacity nodes do correspond to the production requirement nodes, then designating the available production capacity nodes as transitively sufficient; b. then designating the production initiation as enabled if the available production capacity nodes are designated as transitively sufficient and the available circulation data parcels are designated as sufficient.
The above steps pertains to a mental process since designating, determining, can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 15 is rejected.
Claim 16 recites with the upstream production systems comprising upstream production system data profiles, with the upstream production system data profiles being stocked with upstream production capacity nodes; b. with the control processor programmed to secure production progress by: i. if the production update nodes do not correspond to the production progress nodes, identifying upstream production capacity systems having upstream production capacity nodes that separately or in concert with the production capacity nodes correspond to requirement nodes associated with the production progress nodes, and engaging the identified upstream production systems with the downstream production systems.
The above steps pertains to a mental process since designating, determining, can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 16 is rejected.
Claim 18 recites ii. match production capacity entries with production capacity nodes, with the production capacity nodes designating capacity categories, parameters, and magnitudes; iii. stock production system data profiles with the production capacity nodes based on production capacity entries of the downstream production systems; iv. designate the production capacity nodes as available or unavailable for the production system data profiles; v. designate the circulation data parcels as available or unavailable for the request system accounts; vi. enable production initiation by: 1. detecting a production initiation between a given request system and a given downstream production system, then detecting production requirements and circulation data parcel requirements associated with the production initiation, available production capacity nodes associated with the given downstream production system and available circulation data parcels associated with the given request system, with the neural network configured to detect requirement categories, parameters, and magnitudes, configured to detect requirement and capacity categories, parameters, and magnitudes; a. with the second neural network configured to designate the available production capacity nodes as sufficient if all categories, parameters, and magnitudes of the production requirement nodes can be matched with the categories, parameters, and magnitudes of the available production capacity nodes; 4. comparing the circulation data parcel requirements with the available circulation data parcels; 5. designating the available circulation data parcels as sufficient if the circulation data parcel availability data corresponds with the circulation data parcel requirements; 6. if both the available circulation data parcels and the available production capacity nodes are designated as sufficient, then designating portions of the available circulation data parcels and the available production capacity nodes as unavailable according to the circulation data parcel requirements and production requirement nodes and designating the production initiation as enabled. The above steps pertains to a mental process since these steps can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
The claim does not integrate the judicial exceptions into a practical application. The claim includes additional limitations including: b. request systems, with the request systems comprising request system processors, request system accounts, and request system data profiles, confirmation input devices, with the confirmation input devices configured to detect or receive production capacity entries and production update entries; i. receive production capacity entries and production update entries from the confirmation input devices, entering the production requirements into a first neural network, with first neural network trained to match the production requirements with production requirement nodes, and entering the available production capacity nodes in a first input stream of a second neural network and the production requirement nodes in a second stream of the second neural network, with the second neural network. These limitations are recited at a high level of generality and amount to mere data gathering and output recited at a high level of generality and thus are insignificant extra solution activity (MPEP 2106.05(g)). The claim further recites a. downstream production systems, with the downstream production systems comprising production system processors, production system accounts, and production system data profiles, c. circulation data parcels, with the circulation data parcels being assigned to production system and request system accounts; d. a control system, with the control system comprising control processors, with the control processors. These limitations do not integrate the judicial exceptions but instead represents a field of use that is necessary for use of the recited judicial exception (2106.05(h)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As noted above, receiving step relates to insignificant extra solution activity (MPEP 2106.05(g)) and the other steps mentioned above relate to a field of use that is necessary for use of the recited judicial exception (2106.05(h)). The claim does not include any further additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, claim 18 is rejected.
Claim 19 recites with the control processors programmed to track production progress by: with the third neural network configured to extract production progress indicator data from the production requirement nodes and to create production progress nodes using the production progress indicator data, with the production progress nodes designating progress categories, parameters, and magnitudes, creating production update nodes by combining production update entries, with the production update nodes designating update categories, parameters, and magnitudes, with the fourth neural network configured to detect update and progress categories, parameters, and magnitudes. The above steps pertain to a mental process since these steps can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
The claim does not integrate the judicial exceptions into a practical application. The claim includes additional limitations including: a. entering the production requirement nodes into a third neural network, b. receiving production update entries from the confirmation input devices,; c. entering the production update nodes and the production progress nodes into a fourth neural network. These limitations are recited at a high level of generality and amount to mere data gathering and output recited at a high level of generality and thus are insignificant extra solution activity (MPEP 2106.05(g)).
Therefore, claim 19 is rejected.
Claim 20 recites with the control processors programmed to track exchanges of circulation data parcels between downstream and upstream production systems, create transitive production capacity nodes and stock the downstream production system profiles with the transitive production capacity nodes; b. with the transitive production capacity nodes indicating the upstream production systems and the exchanged circulation data parcels. c. with the control processors additionally programmed to enter the transitive production capacity nodes in a third stream of the second neural network, d. with the second neural network configured to detect transitive production capacity categories, parameters, and magnitudes and designate the available production capacity nodes as transitively sufficient if all categories, parameters, and magnitudes of the production requirement nodes or transitive production capacity nodes can be matched with the categories, parameters, and magnitudes of the available production capacity nodes. The above steps pertain to a mental process since these steps can be performed in the mind or using pen and paper and thus falls under the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)(III).
Therefore, claim 20 is rejected.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-14 and16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cella et al (US PUB. 20230083724, herein Cella) in view of Anicet Zanini et al (US PUB. 20220277405, herein Zanini) in further view of Badrinath et al (US PUB. 20230195741, herein Badrinath).
Regarding claim 1, Cella teaches A supervisory production system for enabling production initiation and tracking and for securing production progress, with the supervisory production system comprising:
a. downstream production systems, with the downstream production systems comprising production system processors, production system accounts, and production system data profiles (2458 “variations in workpiece throughput may be modeled by the digital twin module 13420 including, for example, worker response times to events, worker fatigue, discontinuity within worker actions (e.g., natural variations in human-movement speed, differing positioning times, etc.), effects of discontinuities on downstream processes, and the like. In embodiments, individualized worker interactions may be modeled using historical data that is collected, acquired, and/or stored by the digital twin module 13420. The simulation may begin based on estimated amounts (e.g., worker age, industry averages, workplace expectations, etc.). The simulation may also individualize data for each worker (e.g., comparing estimated amounts to collected worker-specific outcomes)” 0410 “workflow may be configured by an artificial intelligence system 1160 that analyzes the problem with the product 1510, develops an understanding of value chain network activities that produce the product, determines resources required for the workflow, coordinates with inventory and production systems to adapt any existing workflows and the like”);
b. request systems, with the request systems comprising request system processors, request system accounts, and request system data profiles (0330 “an application for managing a set of vendors or prospective vendors and/or for managing procurement of a set of goods, components or materials that may be supplied in a value chain, such as involving features such as vendor qualification, vendor rating, requests for proposal, requests for information, bonds or other assurances of performance, contract management, and others)”);
c. circulation data parcels, with the circulation data parcels being assigned to production system and request system accounts (0337 “each data handling layer 608 has a set of application programming connectivity facilities 642 for automating data exchange with each of the other data handling layers 608. These may include data integration capabilities, such as for extracting, transforming, loading, normalizing, compression, decompressing, encoding, decoding, and otherwise processing data packets, signals, and other information as it exchanged among the layers and/or the applications 630, such as transforming data from one format or protocol to another as needed in order for one layer to consume output from another” 0330, 0347 “the storage layer 624 may include one or more blockchains 1180, such as ones that store identity data, transaction data, historical interaction data, and the like, such as with access control that may be role-based or may be based on credentials associated with a value chain entity 652, a service, or one or more applications’);
d. confirmation input devices, with the confirmation input devices configured to detect or receive production capacity entries and production update entries (0506 “the set of supply chain applications and demand management applications may include…user interface”);
e. a control system, with the control system comprising control processors, with the control processors (0550 “determination of a state may cause a control system to alter a control regime, for example, slowing or shutting down a machine that is in a deteriorating state”) programmed to:
i. receive production capacity entries and production update entries from the confirmation input devices (1583 “Manufacturing execution system (MES) 10646 connects and monitors machines, processes, equipment, tooling and materials to streamline manufacturing operations both within a manufacturing node and across multiple manufacturing nodes in the distributed manufacturing network 10130. The MES 10646 may integrate processes spanning production, distribution, supply chain, maintenance, quality and labor operations. Also, the MES 10646 may coordinate with other systems and entities in the distributed manufacturing network 10130 to help with making decisions related to advanced planning, production capacity analysis, inventory turns and lead times”, 0316 “value chain control tower 360 may be connected to, in communication with, or otherwise operatively coupled with adaptive data pipelines 302 and processing facilities that may be further connected to, in communication with, or otherwise operationally coupled with external data sources 320 and a data handling stack 330 (e.g., value chain network technology) that may include intelligent, user-adaptive interfaces”);
ii. match production capacity entries with production capacity nodes, with the production capacity nodes designating capacity categories, parameters, and magnitudes (1565 “The matching may be based on factors like additive manufacturing capabilities, locations of the customer and the manufacturing nodes, available capacity at each node, material availability, pricing (including materials, energy, labor and opportunity costs of other available uses for capacity) and timeline requirements. In embodiments, different parts of a product may be matched with different manufacturing nodes and the product may be assembled at one of the nodes”);
iii. stock production system data profiles with the production capacity nodes based on production capacity entries of the downstream production systems (1565 “The matching may be based on factors like additive manufacturing capabilities, locations of the customer and the manufacturing nodes, available capacity at each node, material availability, pricing (including materials, energy, labor and opportunity costs of other available uses for capacity) and timeline requirements. In embodiments, different parts of a product may be matched with different manufacturing nodes and the product may be assembled at one of the nodes”);
iv. designate the production capacity nodes as available or unavailable for the production system data profiles (1565 “The matching may be based on factors like additive manufacturing capabilities, locations of the customer and the manufacturing nodes, available capacity at each node, material availability, pricing (including materials, energy, labor and opportunity costs of other available uses for capacity) and timeline requirements. In embodiments, different parts of a product may be matched with different manufacturing nodes and the product may be assembled at one of the nodes”);
v. designate the circulation data parcels as available or unavailable for the request system accounts (0423 “a converged process involving a security application 834 and an inventory application 820, integrated automation of blockchain-based applications 844 with vendor management applications 832, and many others. In embodiments, converged processes may include shared data structures for multiple applications 630 (including ones that track the same transactions on a blockchain but may consume different subsets of available attributes of the data objects maintained in the blockchain or ones that use a set of nodes and links in a common knowledge graph)”).
The cited prior art do not teach vi. enable production initiation by: 1. detecting a production initiation between a given request system and a given downstream production system, then detecting production requirements and circulation data parcel requirements associated with the production initiation, available production capacity nodes associated with the given downstream production system and available circulation data parcels assigned to the given request system; 2. matching production requirements with production requirement nodes, with the production requirement nodes designating requirement categories, parameters, and magnitudes; 3. comparing the production requirement nodes with the available production capacity nodes; 4. designating the available production capacity nodes as sufficient if the available production capacity nodes correspond to the production requirement nodes; 5. comparing the circulation data parcel requirements with the available circulation data parcels; 6. designating the available circulation data parcels as sufficient if the circulation data parcel availability data corresponds with the circulation data parcel requirements; 7. if both the available circulation data parcels and the available production capacity nodes are designated as sufficient, then designating portions of the available circulation data parcels and the available production capacity nodes as unavailable according to the circulation data parcel requirements and production requirement nodes and designating the production initiation as enabled.
Zanini teaches vi. enable production initiation by:
1. detecting a production initiation between a given request system and a given downstream production system, then detecting production requirements and circulation data parcel requirements associated with the production initiation, available production capacity nodes associated with the given downstream production system and available circulation data parcels assigned to the given request system (0045 “established blockchain network and where the edge device is a second party node of the network, comprising a control interface to a control device of the control system, where the control device is connected to a simulation device, where the edge device is configured to identify validated order transactions in the blockchain network, where order transactions are published by first party nodes of the blockchain network and are validated by the blockchain network, and where the edge device is configured to extract order parameters comprising at least an ordered amount of a product and an ordered delivery deadline for the product out of an identified order transaction, and is configured to send the order parameters to the simulation device for simulation of a production process for the ordered product based on the order parameters, and is configured to receive a capacity parameter from the simulation device, generate an offer for a first party node of the identified order transaction based on the capacity parameter, and if the first party node accepts the offer, adapt the production process based on the offer”)
2. matching production requirements with production requirement nodes, with the production requirement nodes designating requirement categories, parameters, and magnitudes (0045 “established blockchain network and where the edge device is a second party node of the network, comprising a control interface to a control device of the control system, where the control device is connected to a simulation device, where the edge device is configured to identify validated order transactions in the blockchain network, where order transactions are published by first party nodes of the blockchain network and are validated by the blockchain network, and where the edge device is configured to extract order parameters comprising at least an ordered amount of a product and an ordered delivery deadline for the product out of an identified order transaction, and is configured to send the order parameters to the simulation device for simulation of a production process for the ordered product based on the order parameters, and is configured to receive a capacity parameter from the simulation device, generate an offer for a first party node of the identified order transaction based on the capacity parameter, and if the first party node accepts the offer, adapt the production process based on the offer”);
3. comparing the production requirement nodes with the available production capacity nodes (0047 “identifying, by the first party node, an offer transaction published by a second party node of the blockchain network corresponding to an offer of the second party node, where the offer transaction comprises offer parameters including the order parameters or adapted order parameters and including a price, where the offer parameters are based on a capacity parameter derived by the second party node, where the capacity parameter is derivable by a simulation of a production process for the ordered product based on the order parameters, and comprises accepting, by the first party node, the offer depending on the offer parameters, where the accepting comprises an ordering of the product”)
4. designating the available production capacity nodes as sufficient if the available production capacity nodes correspond to the production requirement nodes (0047 “identifying, by the first party node, an offer transaction published by a second party node of the blockchain network corresponding to an offer of the second party node, where the offer transaction comprises offer parameters including the order parameters or adapted order parameters and including a price, where the offer parameters are based on a capacity parameter derived by the second party node, where the capacity parameter is derivable by a simulation of a production process for the ordered product based on the order parameters, and comprises accepting, by the first party node, the offer depending on the offer parameters, where the accepting comprises an ordering of the product”);
5. comparing the circulation data parcel requirements with the available circulation data parcels (0072 “reseller can also use the blockchain network NW to broadcast an offer transaction including an offer 300 back to the customer node 10. The offer transaction can be validated in the same way as the order transaction. The customer node 10 can accept the offer 300 with the proposed price or deny the offer 300. If the customer and reseller can agree on the contract conditions for the product delivery and close a contract by preferably again using transactions over the blockchain network, then the reseller can run a smart contract with the production node 30 comprising production data 301 that describe the adaption of the production planning. On the production side, the production data needs to be sent to the production line. The planning is adapted to ensure that the production is going to support all customer requests according to the respective quantities and deadlines”);
6. designating the available circulation data parcels as sufficient if the circulation data parcel availability data corresponds with the circulation data parcel requirements (0073 “optimization smart contract that runs on the blockchain can be based on, for example, the back pack loading algorithm. Given the parameters quantity, deadline and capacity of the production, this algorithm can distribute the orders over time in an optimized manner”);
7. if both the available circulation data parcels and the available production capacity nodes are designated as sufficient, then designating portions of the available circulation data parcels and the available production capacity nodes as unavailable according to the circulation data parcel requirements and production requirement nodes and designating the production initiation as enabled (0045 0072 “reseller can also use the blockchain network NW to broadcast an offer transaction including an offer 300 back to the customer node 10. The offer transaction can be validated in the same way as the order transaction. The customer node 10 can accept the offer 300 with the proposed price or deny the offer 300. If the customer and reseller can agree on the contract conditions for the product delivery and close a contract by preferably again using transactions over the blockchain network, then the reseller can run a smart contract with the production node 30 comprising production data 301 that describe the adaption of the production planning. On the production side, the production data needs to be sent to the production line. The planning is adapted to ensure that the production is going to support all customer requests according to the respective quantities and deadlines”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the teachings of Cella with the teachings of Zanini since Zanini teaches a means for “using the blockchain based ordering mechanism, the data concerning orders and offers as well as additional communication regarding delivery of a product etc. is stored in the blockchain database decentrally” (0094).
The cited prior art do not teach vii. track production progress by: 1. extracting production progress indicator data from the production requirement nodes, creating production progress nodes using the production progress indicator data, with the production progress nodes designating progress categories, parameters, and magnitudes; 2. receiving production update entries from the confirmation input devices, creating production update nodes by combining production update entries, with the production update nodes designating update categories, parameters, and magnitudes; 3. comparing production update nodes with the production progress nodes; 4. designating production update nodes as insufficient if the production update nodes do not correspond to the production progress nodes; 5. designating production update nodes as sufficient if the production update nodes correspond to the production progress nodes.
Badrinath teaches vii. track production progress by:
1. extracting production progress indicator data from the production requirement nodes, creating production progress nodes using the production progress indicator data, with the production progress nodes designating progress categories, parameters, and magnitudes (0051 “task scheduling and monitoring routine 146 may evaluate the progress of the copied data. For instance, if copying by one of the worker nodes 315 is lagging behind the other nodes for each of the assigned tables, this may indicate that the worker node 315 is working slower than expected. Alternatively, if copying of one table is lagging behind the other tables for each of the worker nodes 315, this may indicate that the table is larger than approximated or that access to the table is slower. At block 350, the task scheduling and monitoring routine 146 may reschedule tasks based on the progress evaluation 340”);
2. receiving production update entries from the confirmation input devices, creating production update nodes by combining production update entries, with the production update nodes designating update categories, parameters, and magnitudes (0051)
3. comparing production update nodes with the production progress nodes (0051” For instance, in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency.”);
4. designating production update nodes as insufficient if the production update nodes do not correspond to the production progress nodes (0051 “in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency”);
5. designating production update nodes as sufficient if the production update nodes correspond to the production progress nodes (0051 “if one or more tables are being copied faster than the other tables, worker node resources may be redistributed away from those tables to improve the overall efficiency. In other instances, tables may be reassigned for purposes of concurrency control. The task scheduling and monitoring routine 146 may monitoring progress of the reassigned tasks and the progress table 330 may updated to reflect the reassignments”)
viii. secure production progress by:
1. if the production update nodes are designated as sufficient, then assigning to the production accounts circulation data parcels that were previously assigned to the request accounts according to the circulation data parcel requirements (0051 “if one or more tables are being copied faster than the other tables, worker node resources may be redistributed away from those tables to improve the overall efficiency. In other instances, tables may be reassigned for purposes of concurrency control. The task scheduling and monitoring routine 146 may monitoring progress of the reassigned tasks and the progress table 330 may updated to reflect the reassignments”); and
2. if the production update nodes are designated as insufficient, then assigning to the request accounts circulation data parcels that were previously assigned to the given production accounts according to the circulation data parcel requirements (0051 “in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the teachings of Cella and the teachings of Zanini with the teachings of Badrinath since Badrinath teaches a means for improving efficiency with its progress tracking (0051).
Regarding claim 2, --the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the circulation data parcels being cryptocurrency tokens (0330).
Regarding claim 3, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the production capacity entries including resource, equipment, hardware, and software data (0853 “e management platform 604 may manage the connections, configure or provision resources to enable connectivity, and/or manage applications 630 that take advantage of the connections knowing that are many maritime environments where connectivity may be poor or non-existent relative to when the floating assets 620 are closer to port or other land-based communication systems. In many examples, a port infrastructure facility 660, such as a yard for holding shipping containers 7080, may inform a fleet of floating assets 620 via connections to the floating assets 620 that the port is near capacity.”).
Regarding claim 4, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the production capacity entries including worker or user data (0468 “supply factors 1550 as mentioned throughout this disclosure may include, for example and without limitation, ones involving component availability, material availability, component location, material location, component pricing, material pricing, taxation, tariff, impost, duty, import regulation, export regulation, border control, trade regulation, customs, navigation, traffic, congestion, vehicle capacity, ship capacity, container capacity, package capacity, vehicle availability, ship availability, container availability, package availability, vehicle location, ship location, container location, port location, port availability, port capacity, storage availability, storage capacity, warehouse availability, warehouse capacity, fulfillment center location, fulfillment center availability, fulfillment center capacity, asset owner identity, system compatibility, worker availability, worker competency, worker location, goods pricing, fuel pricing, energy pricing, route availability, route distance, route cost, route safety, and many others”).
Regarding claim 5, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the production update entries including part, unit, material, or product data (0916 “a COO digital twin or a CFO digital twin may be configured to depict a set of operations entities and workflows (e.g., flow diagrams that represent a production process, an assembly process, a logistics process, or the like), where entities (including human workers, robots, processing equipment, and other assets) are depicted to operate on a set of inputs such as materials, components, products, containers and information) in order produce and hand off a set of outputs (of similar varied types) to the next set of entities in the workflow for further processing”).
Regarding claim 6, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the confirmation input devices including text input devices, with the text input devices configured to receive text descriptions (0925 “the collaboration tools may include an in-twin collaboration tool that that enables a digital twin experience and a collaboration experience within the same interface (e.g., within a AR/VR-enabled user interface, a standard GUI, or the like), such as where collaboration entities and events (such as version-controlled objects, comment streams, editing events and other changes) are represented within the digital twin interface and linked to digital twin entities”).
Regarding claim 7, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the confirmation input devices including image capturing devices (0351).
Regarding claim 8, the cited prior art teach The supervisory production system of claim 1.
Sella teaches with the confirmation input devices including EM readers configured to detect EM tags (0311).
Regarding claim 9, the cited prior art teach The supervisory production system of claim 1.
Cella teaches with the confirmation input devices including sensors (0351).
Regarding claim 10, the cited prior art teach The supervisory production system of claim 9.
Cella teaches with the sensors including weight sensors, optical sensors, turbidity sensors, pressure sensors, chemical sensors, geographical positioning sensors, time sensors, or fingerprint sensors (0081).
Regarding claim 11, the cited prior art teach The supervisory production system of claim 2.
Cella teaches with the control processors programmed to format a plurality of third-party standards and regulations data from a plurality of disparate formats into a uniform assessment format and create assessment nodes using the standards and regulations data in the uniform assessment format, a. with the assessment nodes designating assessment categories, parameters, and magnitudes (0442 “opportunity miners 1460 may include methods, systems, processes, components, services and other elements for mining for opportunities for smart contract definition, formation, configuration and execution. Data collected within the platform 604, such as any data handled by the data handling layers 608, stored by the data storage layer 624, collected by the monitoring layer 614 and collection systems 640, collected about or from entities 652 or obtained from external sources may be used to recognize beneficial opportunities for application or configuration of smart contracts”).
Regarding claim 12, the cited prior art teach The supervisory production system of claim 11.
Badrinath teaches with the control processors programmed to secure production progress by: a. comparing production update nodes with the assessment nodes; b. designating production update nodes as insufficient if the production update nodes do not correspond to the assessment nodes; c. designating production update nodes as sufficient if the production update nodes correspond to the assessment nodes (0051 “in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency).
Regarding claim 13, the cited prior art teach The supervisory production system of claim 11.
Badrinath teaches with the control processors programmed to enable production initiation by: a. comparing production capacity nodes with the assessment nodes; b. designating production capacity nodes as insufficient if the production capacity nodes do not correspond to the assessment nodes; c. designating production capacity nodes as sufficient if the production capacity nodes correspond to the assessment nodes (0051 “in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency).
Regarding claim 14, the cited prior art teach The supervisory production system of claim 1.
Cella teaches additionally comprising upstream production systems, a. with the control processors programmed to track exchanges of circulation data parcels between downstream and upstream production systems, create transitive production capacity nodes and stock the downstream production system profiles with the transitive production capacity nodes; b. with the transitive production capacity nodes indicating the upstream production systems and the exchanged circulation data parcels (0047 “provide a method for a product ordering process, where the method comprises publishing, by a first party node of the blockchain network, at least one order transaction in a blockchain network, where the at least one order transaction comprises order parameters including at least an ordered amount of a product and an ordered delivery deadline for the product, where published order transactions are validated by the blockchain network, and comprises identifying, by the first party node, an offer transaction published by a second party node of the blockchain network corresponding to an offer of the second party node, where the offer transaction comprises offer parameters including the order parameters or adapted order parameters and including a price, where the offer parameters are based on a capacity parameter derived by the second party node, where the capacity parameter is derivable by a simulation of a production process for the ordered product based on the order parameters, and comprises accepting, by the first party node, the offer depending on the offer parameters, where the accepting comprises an ordering of the product”).
Regarding claim 16, the cited prior art teach The supervisory production system of claim 1.
Badrinath teaches additionally comprising upstream production systems, a. with the upstream production systems comprising upstream production system data profiles, with the upstream production system data profiles being stocked with upstream production capacity nodes; b. with the control processor programmed to secure production progress by: i. if the production update nodes do not correspond to the production progress nodes, identifying upstream production capacity systems having upstream production capacity nodes that separately or in concert with the production capacity nodes correspond to requirement nodes associated with the production progress nodes, and engaging the identified upstream production systems with the downstream production systems (0051 “ask scheduling and monitoring routine 146 may evaluate the progress of the copied data. For instance, if copying by one of the worker nodes 315 is lagging behind the other nodes for each of the assigned tables, this may indicate that the worker node 315 is working slower than expected. Alternatively, if copying of one table is lagging behind the other tables for each of the worker nodes 315, this may indicate that the table is larger than approximated or that access to the table is slower. At block 350, the task scheduling and monitoring routine 146 may reschedule tasks based on the progress evaluation 340. For instance, in the case of one or more failed or lagging worker nodes 315, tasks may be reassigned or migrated from the failed or lagging worker nodes 315 to other worker nodes 315 that are on pace or ahead of pacing for copying the data. Conversely, if one or more worker nodes 315 are ahead of pace, data from other worker nodes 315 could be assigned to the faster worker nodes 315 to improve overall efficiency. For further instance, in the case of one or more production tables for which progress is lagging, additional worker node resources may be concentrated on those tables in order to improve overall efficiency. Conversely, if one or more tables are being copied faster than the other tables, worker node resources may be redistributed away from those tables to improve the overall efficiency. In other instances, tables may be reassigned for purposes of concurrency control. The task scheduling and monitoring routine 146 may monitoring progress of the reassigned tasks and the progress table 330 may updated to reflect the reassignments”).
Claim 17 is rejected using similar reasoning as the rejection of claims 1-14 and 16 due to reciting similar limitations but directed towards a supervisory production system.
Conclusion
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/TAMEEM D SIDDIQUEE/
Primary Examiner
Art Unit 2116