DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDSes) submitted on 11/13/2025, 01/29/2026, and 05/19/2026 are being considered by the examiner.
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 1-6, 9-16, and 19-20 are rejected under 35 U.S.C. 101 for the following reasons:
Claim 1 is rejected under 35 U.S.C. 101 because, while independent claim 1 falls within a statutory class of a machine (i.e., claim 1 passes Step 1 of the § 101 analysis, see MPEP § 2106.03.II), under Step 2A of the § 101 analysis, claim 1 recites a judicial exception without integrating the judicial exception into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 1 recites “an analytics component configured to, based on a first analysis of the multi-tenant data, identify a change to a predicted state of the supply chain and, based on a second analysis of the multi-tenant data and the change to the predicted state of the supply chain, formulate a modification to a production schedule of the manufacturing entity that causes a business metric of the manufacturing entity to satisfy an optimization criterion [and] a scheduling component configured to implement the modification to the production schedule.” The claimed “identify a change …” and/or the claimed “formulate a modification …” and/or the claimed “implement the modification to the production schedule” are abstract ideas because they can be performed mentally (e.g., with the aid of pen and paper). See MPEP § 2106.04(a)(2).I, II.
Further, claim 1 does not recite any additional elements that integrate the abstract ideas discussed above into a practical application. For example, claim 1 does not positively recite that the modified production schedule is actually implemented (see, e.g., claim 7 which implements the modified production schedule). See MPEP § 2106.04(d). In addition, the claim does not recite any improvement to the relevant technology, such as, for example, “improves the functioning of a computer or improves another technology or technical field.” Thus, the abstract ideas discussed above do not integrate the judicial exception into a practical application. See MPEP § 2106.04(d)(1).
Finally, claim 1 also fails under Step 2B of the § 101 analysis because claim 1 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §
2106.05. Even assuming, arguendo, that modifying the production schedule as claimed is a new idea, the claimed modification is still an abstract idea, as discussed above, and thus does not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Independent claims 11 and 19 are rejected under 35 U.S.C. 101 for the reasons given above with respect to claim 1. Claims 2-6, 9-10, 12-16, and 20 do not transform the abstract ideas discussed above into a practical application and thus are rejected based on their dependency.
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.
Claims 1-9 and 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2018/0357334 to Chao et al. (“Chao”) in view of U.S. Patent Application Publication No. 2020/0387818 to Chan et al. (“Chan”), and further in view of U.S. Patent Application Publication No. 2022/0187847 to Cella et al. (“Cella”). (Chao and Chan were submitted by Applicant in the IDS of 11/13/2025.)
Regarding claim 1:
A system (Chao at Abstract and Figs. 1 and 2), comprising:
a memory that stores executable components (Chao at pars. [0051]-[0056] and Fig. 2, memory 218.); and
a processor, operatively coupled to the memory, that executes the executable components (Chao at pars. [0051]-[0056] and Fig. 2, processor 216.), the executable components comprising:
internal services that implement a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system that executes a supply chain analytics service that collects multi-tenant data from multiple entities of a supply chain, the multiple entities comprising at least a manufacturing entity (Chao discloses “a cloud-based data ingestion and analysis architecture that integrates and collects data from multiple diverse sources at one or more industrial facilities” that “can include manufacturing floor data.” See Chao at pars. [0047]-[0048] and Figs. 1 and 2; see also pars. [0065]-[0066] and Fig. 5.);
an analytics component configured to, based on a first analysis of the multi-tenant data, identify a change to a predicted state of the supply chain and, based on a second analysis of the multi-tenant data and the change to the predicted state of the supply chain, formulate a modification to a production schedule of the manufacturing entity that causes a business metric of the manufacturing entity to satisfy an optimization criterion (Chao discloses an “analytics platform 506 [that] can be implemented on an on-premise device (e.g., an industrial device or edge device) to carry out device-level analytics (see FIG. 7), or on a cloud platform to carry out higher-level analytics (see FIG. 8) [and] … configured to collect data 502 from multiple different data sources ….” Chao also disclose that “system 302 can modify maintenance schedules, work schedules, production schedules, or other related schedules based on results of the analysis performed by analysis component 304. In an example scenario, analysis component 304 may determine that a performance metric of a controlled process is beginning to drift and is expected to fall outside the preferred range for that metric defined by model data 1202.” See Chao at Abstract and pars. [0065]-[0066], [0069], and [0120].); and
a scheduling component configured to implement the modification to the production schedule (Chao disclose that “system 302 can modify maintenance schedules, work schedules, production schedules, or other related schedules based on results of the analysis performed by analysis component 304.” See Chao at pars. [0065]-[0066], [0069], and [0119]-[0120].).
internal services that implement a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system (Chao does not explicitly disclose that the “manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system.” However, in a same field of endeavor, models and solutions to optimize operations (and thus analogous art), Chan discloses that its computer software instructions 92 can be implemented in a Software as a Service (SaaS) and in a cloud computing environment. See Chan at Abstract and pars. [0158] and [0164] and Fig. 4C. Chan shows that SaaS was known in the art and both Chao and Chan relate to optimizing operations using cloud-based systems. Accordingly, it would have been obvious and one skilled in the art would have been motivated to implement Chao’s system in SaaS. This is because one skilled in the art would have recognized that the combination merely applies a known technique to the system of Chao and that the combination would yield predictable results. See MPEP § 2143.I.A.)
internal services that implement a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system that executes a supply chain analytics service that collects multi-tenant data from multiple entities of a supply chain … [and] an analytics component configured to, based on a first analysis of the multi-tenant data, identify a change to a predicted state of the supply chain and, based on a second analysis of the multi-tenant data and the change to the predicted state of the supply chain (Chao in view of Chan discloses changes to production when there are disruptions in the system (see Chao at par. [0126]), but Chao in view of Chan does not explicitly disclose “the manufacturing cloud system … [that] executes a supply chain analytics service that collects multi-tenant data from multiple entities of a supply chain … [or] an analytics component configured to… identify a change to a predicted state of the supply chain and, based on a second analysis of the multi-tenant data and the change to the predicted state of the supply chain.” However, in a same filed of endeavor, cloud-based system to optimize operations (and thus analogous art), Cella discloses a cloud-based management platform that uses data collected from the distributed manufacturing to analyze the value chain (e.g., supply chain) in a manufacturing process in order to “optimize” the value chain. See Cella at pars. [0002], [0034] and [0073]. Optimizing a value chain would naturally include identifying changes to the value chain that deviate from optimum and making changes that are needed to reoptimize the value chain. It would have been obvious and one skilled in the art would have been motivated to incorporate the “an artificial intelligence system [that is] configured to learn on a training set of outcomes, parameters, and data collected from the distributed manufacturing network entities” in order “to optimize manufacturing and value chain workflows [which includes supply chains].” See Cella at par. [0073]. Because Chao, Chan, and Cella related to cloud-based management platforms, there would have been a reasonable chance of success. See MPEP § 2143.I.G.).
Regarding claim 2:
The system of claim 1, wherein the business metric is at least one of a profitability metric, a demand fulfilment metric, an energy consumption metric, a production cost metric, or an emissions metric (See Chao at par. [0095] (“the resulting model data 1202 will be representative of acceptable automation system behavior or statuses that are expected to yield the indicated desired outcome (e.g., highest product throughput, least energy consumption, least amount of machine downtime, highest product quality, etc.).”).
Regarding claim 3:
The system of claim 1, wherein the multi-tenant data comprises at least one of production data from the manufacturing entity, the production schedule, an inventory level of a product manufactured by the manufacturing entity or a component part used to manufacture the product, customer demand data for the product, purchase order data for the manufacturing entity, transportation scheduling data from a transportation entity, shipping route information for the transportation entity, or a production schedule of a supplier entity that manufactures a component part or material used by the manufacturing entity to manufacture the product (See Chao at pars. [0066] (“product inventory database”), [0067] (“production outcomes (e.g., whether a current production rate will meet demand”), [0069] (“production schedule”),[0138] (“purchase order data”).).
Regarding claim 4:
The system of claim 1, wherein the change to the predicted state of the supply chain is at least one of a change in availability of a component part or material used by the manufacturing entity, a change to a product transportation schedule, a supply chain disruption, or a change in a demand for a product manufactured by the manufacturing entity (Chao disclose changes and disruptions in production can lead to reduction in production or sourcing parts from another source. See Chao at par. [0126].)
Regarding claim 5:
The system of claim 1, wherein the modification to the production schedule at least one of changes a type of product scheduled to be manufactured on a production line for a specified time period, changes a time period during which a product is scheduled to be produced, or changes a source from which to obtain a component part or material used by the manufacturing entity to produce the product (Chao discloses altering production for maintenance and changing the source of a part used in production. See Chao at pars. [0066],[0069], [0079], [0120], and [126].).
Regarding claim 6:
The system of claim 1, wherein the multiple entities of the supply chain further comprise at least one of supplier entities, manufacturing entities, transportation entities, warehouse entities, retail entities, or distributor entities (See Chao at [0052] and [0126]; see also; Cella at par. [0004].).
Regarding claim 7:
The system of claim 1, wherein the analytics component is further configured to generate and send configuration data to one or more industrial devices operating at a plant facility of the manufacturing entity, and the configuration data configures the one or more industrial devices to implement the modification to the production schedule (See Chao at pars. [0067],[0069], [0090], [0116], [120], and [126].).
Regarding claim 8:
The system of claim 7, wherein the configuration data at least one of changes a configuration setting of an industrial device or changes control code being executed by an industrial controller to monitor and control an automation system (See Chao at par. [0126] (device operation is altered based on unacceptable loss or efficiency.).)
Regarding claim 9:
The system of claim 1, wherein the scheduling component is further configured to modify another schedule of the manufacturing entity that causes the business metric of the manufacturing entity to satisfy the optimization criterion, and the other schedule is at least one of a work schedule, a shipping schedule for a product manufactured by the manufacturing entity, a purchase order for component parts used to manufacture the product, an inventory schedule for the product or the component part, or a bill of materials (Chao discloses that to “mitigate risk of production waste” the analytic system 402 can reduce production (“work schedule”) and/or provide “instructions to appropriate upstream systems to begin providing material or parts to the new production line), sourcing a production line with parts from an alternate production line or source, or other such countermeasures” (“a shipping schedule for a product manufactured by the manufacturing entity, a purchase order for component parts used to manufacture the product”). See Chao at par. [0126].).
Regarding claim 11:
A method, comprising: implementing, by a manufacturing cloud system comprising a processor, a multi-tenant Software-as-a-Service (SaaS) system that executes a supply chain analytics service that collects multi-tenant data from multiple entities of a supply chain, the multiple entities comprising at least a manufacturing entity; identifying, by the manufacturing cloud system based on first analysis of the multi-tenant data, a change to a predicted state of the supply chain; in response to the identifying, formulating, by the manufacturing cloud system based on second analysis of the multi-tenant data and the change to the predicted state of the supply chain, a modification to a production schedule of the manufacturing entity predicted to cause a business metric of the manufacturing entity to satisfy an optimization criterion; and implementing, by the manufacturing cloud system, the modification to the production schedule (See analysis in claim 1).
Regarding claim 12:
The method of claim 11, wherein the business metric is at least one of a profitability metric, a demand fulfilment metric, an energy consumption metric, a production cost metric, or an emissions metric (See analysis in claim 2).
Regarding claim 13:
The method of claim 11, wherein the multi-tenant data comprises at least one of production data from the manufacturing entity, the production schedule, an inventory level of a product manufactured by the manufacturing entity or a component part used to manufacture the product, customer demand data for the product, purchase order data for the manufacturing entity, transportation scheduling data from a transportation entity, shipping route information for the transportation entity, or a production schedule of a supplier entity that manufactures a component part or material used by the manufacturing entity to manufacture the product (See analysis in claim 3).
Regarding claim 14:
The method of claim 11, wherein the change to the predicted state of the supply chain is at least one of a change in availability of a component part or material used by the manufacturing entity, a change to a product transportation schedule, a supply chain disruption, or a change in a demand for a product manufactured by the manufacturing entity (See analysis in claim 4).
Regarding claim 15:
The method of claim 11, wherein the implementing comprises at least one of changing a type of product scheduled to be manufactured on a production line for a specified time period, changing a time period during which a product is scheduled to be produced, or changing a supplier entity from which to obtain a component part or material used by the manufacturing entity to produce the product (See analysis in claim 5).
Regarding claim 16:
The method of claim 11, wherein the multiple entities of the supply chain further comprise at least one of supplier entities, manufacturing entities, transportation entities, warehouse entities, retail entities, or distributor entities (See analysis in claim 6).
Regarding claim 17:
The method of claim 11, further comprising: generating configuration data directed to one or more industrial devices operating at a plant facility of the manufacturing entity, wherein the configuration data is configured to reconfigure the one or more industrial devices to implement the modification to the production schedule; and sending, by the manufacturing cloud system, the configuration data to the one or more industrial devices (See analysis in claim 7).
Regarding claim 18:
The method of claim 17, wherein the configuration data at least one of changes a configuration setting of an industrial device or changes control code being executed by an industrial controller to monitor and control an automation system (See analysis in claim 8).
Regarding claim 19:
A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause a manufacturing cloud system comprising a processor to perform operations, the operations comprising: collecting multi-tenant data from multiple entities of a supply chain, the multiple entities comprising at least a manufacturing entity; identifying, by the manufacturing cloud system based on a first analysis of the multi-tenant data, a change to a predicted state of the supply chain; in response to the identifying, formulating, based on a second analysis of the multi-tenant data and the change to the predicted state of the supply chain, a modification to a production schedule of the manufacturing entity predicted to cause a business metric of the manufacturing entity to satisfy an optimization criterion; and implementing the modification to the production schedule (See analysis in claim 1).
Regarding claim 20:
The non-transitory computer-readable medium of claim 19, wherein the multi-tenant data comprises at least one of production data from the manufacturing entity, the production schedule, an inventory level of a product manufactured by the manufacturing entity or a component part used to manufacture the product, customer demand data for the product, purchase order data for the manufacturing entity, transportation scheduling data from a transportation entity, shipping route information for the transportation entity, or a production schedule of a supplier entity that manufactures a component part or material used by the manufacturing entity to manufacture the product (See analysis in claim 3).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Chao in view of Chan and Cella, and further in view of U.S. Patent Application Publication No. 20220374402 to Hawkin et al. (“Hawkin”). (Hawkin was submitted in Applicant’s IDS of 05/19/2026).
Regarding claim 10:
The system of claim 1, wherein the analytics component is configured to group a subset of the multi-tenant data corresponding to manufacturing entities that operate within a common industrial vertical, determine, based on analysis of the subset of the multi-tenant data, business strategies that correlate with satisfaction of the optimization criterion by the business metric, and formulate the modification to the production schedule based on the business strategies (Chao in view of Chan and Cella do not explicitly disclose the claimed grouping. However, in a same filed of endeavor, cloud-based analytic system (and thus analogous art), Hawkin proposes, due to country specific regulatory requirements, “a multi-tenant in-country (“group a subset of the multi-tenant data corresponding to manufacturing entities that operate within a common industrial vertical”) hybrid cloud solution for deployment and automation of asset analytics.” See Hawkin at pars. [0034] and [0037]. The business metrics used for optimization, which are analyzed in claim 1, would then apply to the in-country multi-tenant group.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent No. 12,524,389 to Ubach et al. discloses an enterprise configuration framework for monitoring and control of systems located at multiple sites.
U.S. Patent No. 10,831,183 to Katti et al. discloses a system that enables decentralized manufacturing.
U.S. Patent No. 12,228,897 to Lamothe et al. discloses management of a process plant using compute fabric.
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/B.K./Examiner, Art Unit 2116
/KENNETH M LO/ Supervisory Patent Examiner, Art Unit 2116
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