DETAILED ACTION
Acknowledgements
The present application is being examined under the pre-AIA first to invent provisions.
Claims 1, 6, 10, 11, 13-15, 17-23 are pending and have been examined.
Claim Objections
Claim 10, recites the term “synchronized stated” which appears to be a typographical error. The examiner believes that Applicant intended, similar to claim 1, to recite the term “synchronized state.” Appropriate correction is required.
Drawings
The drawings are objected to under 37 CFR 1.83(a) because they are incomplete. 37 CFR 1.83(a) reads as follows:
The drawing in a nonprovisional application must show every feature of the invention specified in the claims. However, conventional features disclosed in the description and claims, where their detailed illustration is not essential for a proper understanding of the invention, should be illustrated in the drawing in the form of agraphical drawing symbol or a labeled representation (e.g., a labeled rectangular box). In addition, tables and sequence listings that are included in the specification are, except for applications filed under 35 U.S.C. 371, not permitted to be included in the drawing.
The drawings must show every feature of the invention specified in the claims. Therefore, the method steps (claims 21-23) of the claimed invention must be shown or the feature(s) canceled from the claim(s). Applicants are requested to point out the corresponding support in the specification for each feature/ step in the to-be-submitted drawing. No new matter should be entered.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
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. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
a set of interfaces that are configured to access and configure features of the platform…as recited by at least claim 1.
a set of network connectivity facilities that are configured to direct a set of value chain network entities… as recited by at least claim 1.
a data collection layer that collects IOT sensor data…. as recited by at least claim 1.
a digital twin system configured to create digital twins… as recited by at least claim 1.
a set of adaptive intelligence facilities that are configured to automate…. as recited by at least claim 1.
a set of data storage facilities that are configured to store… as recited by at least claim 1.
a set of monitoring facilities that are configured to monitor the value chain network entities… as recited by at least claim 1.
a set of applications that are configured to direct an enterprise… as recited by at least claim 1.
a set of microservices layers including: an application layer supporting at least one supply chain application… as recited by at least claim 1.
a process automation system configured to execute the corrective action … as recited by at least claim 1.
a smart contract system that is configured to automate… as recited by at least claim 13.
a vibration sensor configured to measure vibration signatures… as recited by at least claim 18.
a temperature monitoring system configured to track environmental conditions… as recited by at least claim 18.
a motion sensor configured to track product throughput… as recited by at least claim 18.
an asset tracking sensor and at least one beacon configured to locate items in real-time… as recited by at least claim 18.
a machine vision system configured to perform automated quality inspection… as recited by at least claim 18.
an environmental sensor system configured to monitor chemical and biological parameters… as recited by at least claim 18.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 21-23 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
The specification lacks sufficient support for method claims 21-23. Specifically, the specification doesn’t appear to show the flow/timeline of the method steps as claimed. Appropriate correction is required.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 6, 10, 11, 13-15 & 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The claim limitations as shown above invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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, 10, 11, 13-15, 17-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: claims 21-23 are directed to a method and claims 1, 6, 10, 11, 13-15, 17-20 are directed to a product (system). Therefore, these claims fall within the four statutory categories of invention.
Claims 21-23
Step 2A, prong 1: Claim 21, for example, recites the abstract idea of identifying potential disruption in a supply chain facility or a demand management facility and implementing and validating a corrective action process. This idea is described by the following claim elements:
collecting IoT sensor data, from a set of […] resources operatively connected to at least one supply chain facility and at least one demand management facility;
[…];
[…];
continuing to collect IoT sensor data from the set of […] resources;
maintaining a synchronized stated between […] and the at least one supply chain facility and the at least one demand management facility using continually collected IoT sensor data;
simulating (modeling) facility operations of the at least one supply chain facility and the at least one demand management facility in real-time […];
analyzing the collected IoT sensor data;
detecting a supply chain disruption based, at least in part, on the analyzing of the collected IoT sensor data;
predicting, based at least in part on the simulated facility operations, a potential disruption to at least one of the supply chain facility or the demand management facility;
coordinating an […] workflow across the at least one supply chain facility and the at least one demand management facility;
optimizing an operation based on the […] facility simulations;
implementing a corrective action through […] processes; and
validating an effectiveness of the corrective action based, at least in part, the continued IoT sensor data collection and new facility operations simulations.
These limitations collectively describe collecting, analyzing, simulating, predicting, and managing information for supply chain logistics. Such activities constitute a method of organizing human activity (business logistics, resource management) and/or mental processes (observation, evaluation, prediction).
Courts have consistently held these concepts abstract. See Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 219–20 (2014) (intermediated settlement = abstract); Electric Power Group v. Alstom, 830 F.3d 1350, 1354 (Fed. Cir. 2016) (collecting and analyzing data abstract); SAP America v. InvestPic, 898 F.3d 1161, 1164–65 (Fed. Cir. 2018) (statistical simulations abstract).
Step 2A, prong 2: claim 21, recite additional elements that fail to integrate the abstract idea into practical application.
Claim 21 recites the following additional limitations:
storing the collected IoT sensor data;
creating digital twins … based on stored IoT data;
a set of Internet of Things resources; and
an automated workflow/process.
These elements are additional elements considered under Step 2A, Prong 2.
However, they do not integrate the abstract idea into a practical application because the additional elements are being used merely as tools to implement the abstract idea. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on the locating system, or merely uses the locating system as a tool to perform an abstract idea, cannot provide an inventive concept. See MPEP 2106.05(f).
For example, “storing” is a generic data handling function performed by any conventional computer; “digital twins” represent mathematical modeling/simulation constructs invoked generically; IoT resources are claimed generically for collecting data; and “automated workflow” represents generic computer automation of human tasks. None of these elements improves the functioning of a computer, IoT hardware, or digital modeling technology itself.
Furthermore, the additional claimed elements, noted above, when viewed individually and as an ordered combination do not integrate the abstract idea into a practical application. The additional elements fail to provide a practical application because there are (1) no actual improvements to the functioning of a computer, (2) nor to any other technology or technical field, (3) nor do the claims apply the judicial exception with, or by use of, a particular machine, ( 4) nor do the claims provide a transformation or reduction of a particular article to a different state or thing, (5) nor provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of MPEP §2106.04, (6) nor do the claims apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, in view of MPEP §2106.04(d)(2).
Thus, the claim merely implements the abstract idea on generic computing components and does not integrate the exception into a practical application.
Step 2B: claim fails to recite additional elements that amount to an inventive concept.
For the reasons identified with respect to Step 2A, prong 2, claim 21 fails to recite additional elements that amount to significantly more.
Furthermore, the additional claimed elements, noted above, when viewed individually and as an ordered combination do not provide significantly more than the abstract idea. The additional elements fail to (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; ( 4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the fie Id; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of the MPEP 2106.0S(a-h).
Dependent claims 22 & 23 further describe the abstract idea of Identifying potential disruption in a supply chain facility or a demand management facility and implementing and validating a corrective action process. These claims do not include new additional elements that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. Therefore, these dependent claims are also not patent eligible.
claims 1, 6, 10, 11, 13, 14 15, 17, 18, 19 & 20
Step 2A, prong 1: Claim 1, for example, recites the abstract idea of identifying potential disruption in a supply chain facility or a demand management facility and implementing and validating a corrective action process. This idea is described by the following claim elements:
[…];
[…] direct a set of value chain network entities to connect to the features of the platform;
[…] collects IOT sensor data from a set of Internet of Things resources, each operatively connected to at least one supply chain facility of the set of value chain entities of the platform and at least one demand management facility related to the set of value chain network entities of the platform;
[…]
create digital twins corresponding to each of the at least one supply chain facility and the at least one demand management facility;
maintain synchronized state between each digital twins and the corresponding at least one supply chain facility and the corresponding at least one demand management facility represented by the digital twins, based on collected IoT sensor data; and
simulate facility operations in real-time based on collected IoT sensor data and at least a subset of a set of demand factors and a set of supply factors;
[…] automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform;
analyzing collected IoT sensor data;
predicting, based on the simulated facility operations, a potential disruption to at least one of the supply chain facility or the demand management facility; and
[…] initiating a corrective action;
[…] monitor the value chain network entities, wherein the interfaces, the network connectivity facilities, the adaptive intelligence facilities, the data storage facilities, and the monitoring facilities are coordinated for monitoring and management of the value chain network entities, and wherein the platform manages the set of demand factors, the set of supply factors and a set of supply chain infrastructure facilities;
[…] direct an enterprise to manage the value chain network entities of the platform from a point of origin to a point of customer use; and
[…] ; and,
[…] collects information IOT sensor data from the set of Internet of Things resources that collect information with respect to supply chain entities and demand management entities related to the value chain network entities of the platform; and
[…] execute the corrective action, wherein the corrective action includes at least one of:
coordinate an automated workflow across the at least one supply chain facility and the at least one demand management facility;
optimize an operation based on the digital twin facility simulations; and implement the corrective action through automated processes.
These limitations collectively describe collecting, analyzing, simulating, predicting, and managing information for supply chain logistics. Such activities constitute a method of organizing human activity (business logistics, resource management) and/or mental processes (observation, evaluation, prediction).
Courts have consistently held these concepts abstract. See Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 219–20 (2014) (intermediated settlement = abstract); Electric Power Group v. Alstom, 830 F.3d 1350, 1354 (Fed. Cir. 2016) (collecting and analyzing data abstract); SAP America v. InvestPic, 898 F.3d 1161, 1164–65 (Fed. Cir. 2018) (statistical simulations abstract).
Step 2A, prong 2: claim 21, recite additional elements that fail to integrate the abstract idea into practical application.
Claim 1 recites the following additional limitations:
a cloud-based management platform with a micro-services architecture, the platform having a set of interfaces
a set of network connectivity facilities
a data collection layer
a digital twin system:
a set of adaptive intelligence facilities that are configured to automate
automatically initiating a corrective action;
a set of data storage facilities that are configured to store data collected and handled by the platform, and a set of monitoring facilities
a set of applications
a set of microservices layers including: an application layer supporting at least one supply chain application and at least one demand management application, wherein the microservices layers include the data collection layer
a process automation system
These elements are additional elements considered under Step 2A, Prong 2. However, they do not integrate the abstract idea into a practical application because the additional elements are being used merely as tools to implement the abstract idea. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on the locating system, or merely uses the locating system as a tool to perform an abstract idea, cannot provide an inventive concept. See MPEP 2106.05(f).
Additionally, the additional elements are recited at a high level of generality and perform only generic computer functions. See examples below:
“IoT resources” are generic sensors performing generic data collection.
“Digital twins” represent generic simulation models, invoked broadly.
“Adaptive intelligence facilities” and “data storage facilities” are generic computing resources.
“Cloud-based management platform” is a generic computing environment, not a specific technological improvement.
Furthermore, the additional claimed elements, noted above, when viewed individually and as an ordered combination do not integrate the abstract idea into a practical application. The additional elements fail to provide a practical application because there are (1) no actual improvements to the functioning of a computer, (2) nor to any other technology or technical field, (3) nor do the claims apply the judicial exception with, or by use of, a particular machine, ( 4) nor do the claims provide a transformation or reduction of a particular article to a different state or thing, (5) nor provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of MPEP §2106.04, (6) nor do the claims apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, in view of MPEP §2106.04(d)(2).
Thus, the claim merely implements the abstract idea on generic computing components and does not integrate the exception into a practical application.
Step 2B: claim fails to recite additional elements that amount to an inventive concept.
For the reasons identified with respect to Step 2A, prong 2, claim 21 fails to recite additional elements that amount to significantly more.
Furthermore, the additional claimed elements, noted above, when viewed individually and as an ordered combination do not provide significantly more than the abstract idea. The additional elements fail to (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; ( 4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the fie Id; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of the MPEP 2106.0S(a-h).
Dependent claims 6, 10, 11, 13-15 & 17-20 further describe the abstract idea of Identifying potential disruption in a supply chain facility or a demand management facility and implementing and validating a corrective action process. These claims recite some new additional elements that also do not integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. Therefore, these dependent claims are also not patent eligible. See examples below:
Claim 6 (5G, cognitive networking, peer-to-peer): These are networking technologies that are recited generically, and do not improve computer functioning. See Two-Way Media v. Comcast, 874 F.3d 1329, 1338 (Fed. Cir. 2017) (generic network components).
Claims 10, 11 (edge intelligence, self-configuring data collection): Merely invoke generic distributed computing systems, without specific technological improvements.
Claim 13 (smart contract system): Generic use of blockchain/smart contracts is not a technologic improvement. See SEC v. Kik Interactive (S.D.N.Y. 2020) (blockchain transactions are general implementations).
Claim 14 (distributed data architecture, blockchain): generic computing technology that is claimed broadly. Secured Mail Solutions v. Universal Wilde, 873 F.3d 905 (Fed. Cir. 2017) (generic data structures).
Claim 15 (graph database): A generic database type, not a technological improvement.
Claim 17 (applications: supply chain, demand management, ERP): These are business software categories, not technological improvements.
Claim 18 (sensors: vibration, temperature, motion, asset tracking, vision, environmental): These are generic sensor types. Electric Power Group, 830 F.3d at 1354.
Claim 19 (adaptive intelligence facilities for tracking, maintenance, corrective actions, inventory optimization): These are general applications of data analysis and automation. FairWarning IP, 839 F.3d at 1095.
Subject Matter Free of Prior Art
Claims 1, 6, 10, 11, 13-15, 17-23 are believed to be free of prior art.
The closest prior art:
US 20200065759 A1- The analytical engine 712 can detect unreported events by identifying unexpected variations in collected performance information. For example, where one or more selected nodes of the supply chain and/or logistics operation(s) experience a sudden drop-in rate of on-time shipments or rise in rate of late shipments and the drop is sustained over a selected period, the analytical engine 712 can deduce that a disruptive event has occurred. The possibility of an occurrence of an unreported disruptive event can be reported to a system or supply chain and/or logistics operation(s) enterprise and/or organization administrator. Likewise, the severity of an event and/or shipment projections can be changed and rendered more accurate by observing actual behavior following creation of the event or estimate or projection. This information can also be used to refine temporally proximate estimates or projections. The analytical engine 712 can also calculate and update performance measures as information is collected by the data collection and maintenance module 700. In other words, the calculation and updating of performance measures is done substantially in real time. Alternatively, the analytical engine 712 can calculate the performance measures when and as requested by a user. In other words, the performance measures are not precalculated. This can obviate the need for an analytics database altogether.
US 20170286572 A1- An apparatus may implement a digital twin of a twinned physical system such that one or more sensors to sense values of one or more designated parameters of the twinned physical system. A computer processor may receive data associated with the sensors and, for at least a selected portion of the twinned physical system, monitor a condition of the selected portion of the twinned physical system and/or assess a remaining useful life of the selected portion based at least in part on the sensed values of the one or more designated parameters. A communication port may transmit information associated with a result generated by the computer processor. The one or more sensors may sense values of the one or more designated parameters, and the computer processor may perform the monitoring and/or assessing, when the twinned physical system is not operating.
US 20170323240 A1- A method of presenting a recommendation in a user interface for use in optimization operation of industrial assets. Digital twins are generated for a set of industrial assets. The digital twins include data structures representing estimated states of each of a plurality of subsystems of the set of industrial assets over a time period based on an application of simulations using cumulative damage models. The cumulative damage models modeling the effects of exogenous factors on the operation of the set of industrial assets over the time period. Based on an uncertainty level of at least one of the estimated states transgressing an uncertainty threshold, directed actual state data is requested from an inspection system deployed in a field of at least one of the industrial assets. Based on a receiving of the actual state data, the data structures are updated to include the actual state data. The uncertainty level of the estimated states of each of the plurality of subsystems is also updated. The digital twins are continuously analyzed to determine a recommendation pertaining to operation of the industrial assets. The optimization is calculated to increase a net present value of the industrial assets or decrease an economic risk associated with the operation of the industrial assets.
Barni et al (Exploiting the Digital Twin in the Assessment and Optimization of Sustainability Performances), 2018. Digitalization has shown the potential to disrupt industrial value chains by supporting real-time, risk-free and inexpensive inputs to decision making towards enhanced companies' productivity and value networks flexibility. Developing a reliable and robust digital replica of the physical systems of the value chain is one of the most advanced (and challenging) approaches to digitalization, condensed in the concept of Digital Twin (DT). DT plays a fundamental role in creating a data-rich environment where simulation and optimization procedures can be run. With DT expected to become a commodity in the coming years, simulation and optimization become therefore a more accessible instrument for the improvement of manufacturing and business processes also in small enterprises with limited investment capacity. While scientific literature has analysed the adoption of DT in the optimization of products lifecycle, no contributions have yet focused on the exploitation of DT to improve the sustainability performances of whole value chains. In this paper we propose a reference framework where DTs built upon process and system data gathered from the field, allow to quickly assess the sustainability performances of both existing and planned production mixes and to compare achievable impacts with changing processes and technologies, thus enabling advisory features for sustainability-aware decision making in structured, multi-entity value networks. Internal validation will be deployed referring to real case studies.
US 20080133960 A1- An inconsistency in the supply chain data may be automatically identified to enable management of the potential disruption in the flow of materials in the supply chain. Moreover, A violation of the validation rules, a violation of the replenishment rules, and/or a violation of the policies of the supply chain data may be automatically identified to enable management of the potential disruption in the flow of materials in the supply chain. A conflict in the supply chain data may be automatically identified when a particular item exceeds a customizable threshold parameter to enable management of the potential disruption in the flow of materials in the supply chain.
US 12093888 B2- After the model has been trained, it may be deployed to a live environment where it can make predictions/decisions based on the execution of the final trained machine learning model. For example, in 704, the machine learning model may be used for condition-based maintenance (CBM) for an asset such as an aircraft, a wind turbine, a healthcare machine, and the like. In this example, data fed back from the asset 730 may be input the machine learning model and used to make event predictions such as failure events, error codes, and the like. Determinations made by the execution of the machine learning model at the host platform 720 may be stored on the blockchain 710 to provide auditable/verifiable proof. As one non-limiting example, the machine learning model may predict a future breakdown/failure to a part of the asset 730 and create alert or a notification to replace the part. The data behind this decision may be stored by the host platform 720 on the blockchain 710. In one embodiment the features and/or the actions described and/or depicted herein can occur on or with respect to the blockchain 710.
US 20140019471 A1- discloses the accessible information source(s) 224 include any source of information relevant to supply chain performance, including, without limitation, news sources and/or aggregators (to provide news on current events that may impact positively or negatively the supply chain performance, such as political coup d'etates, changes or upheavals, environmental conditions and events (e.g., storms, floods, earthquakes, tsunamis, typhoons, volcanic eruptions, forest fires, and other natural disasters, and the like), criminal acts (e.g., piracy, hijacking, theft, arson, vandalism, and the like), acts of violence (e.g., terrorism, war, political upheaval, military action, and the like), news reports on and announcements by a partner or competitor, scheduled events or holidays (e.g., religious, political, or other holidays), freight disruptions (e.g., train derailment, oceangoing vessel sinking, airplane crash, freight embargos, naval blockades, and the like), energy shortages, disruptions, or blackouts, and labor disruptions (e.g., strikes or threatened strikes)), weather data sources (e.g., the National Weather Service, national and local news sources, the Weather Channel.TM., Weather Source.TM., worldweatheronline.com, and the like), governmental entities (such as courts, law enforcement authorities, geological surveys, disaster relief agencies, and the like to provide legal or regulatory changes or requirements, lawsuits, bankruptcy filings, and the like, and other information), law enforcement or military authorities (e.g., to provide information on criminal acts (e.g., piracy, hijacking, theft, arson, vandalism, and the like), and acts of violence (e.g., terrorism, war, revolution, political upheaval, military action, and the like). Such information sources can be monitored using word cloud techniques, which graphically represent word usage frequency. Generally, the more frequent a word or group of words is used the greater the likelihood that the fact or event described by the words or group of words exists. The words or group of words can further be weighted for reliability by the source, with law enforcement and military authorities being given a higher or more reliable weighting than news sources.
US 20140278728 A1 discloses- a first step in determining the risk of a supply chain disruption may be to map a production process for each product (e.g., a chemical) being monitored by generating a process map. The process map illustrates relationships between upstream and downstream drivers for the chemical being monitored. The process map thereby facilitates assessing the components of the manufacturing process, and evaluating the impact each driver component may have on the availability of the product being produced. The factors assessed may include: (1) general market availability and intelligence of the components or suppliers, (2) supply and demand dynamics of the component by industry and application, and (3) special quality concerns needed in the component to make the quality of raw material used in the targeted industry.
US 20210356576 A1- discloses, to prevent disruptions, the sensor system 100 may detect information useful to a value chain network (e.g., a logistics value chain network) for preventing disruptions. For example, occupancy signals may indicate that a certain number of workers are present over a predetermined threshold causing impact to workflow, that an animal is present, that a window has opened, that a door has opened, that at least one person is present but not moving, that a person has fallen, that a person has moved to a different space 105, or any other condition of the space 105 that may impact the logistics value chain network. The sensor system 100 may determine a value chain recommendation based on these disruptions. The sensor system 100 may determine that these conditions are disruptions based on a combination of workflow results and/or occupancy information indicating disruption to workflow operations such that an action may be suggested to either eliminate or at least minimize the disruption. For example, it may be determined that when a particular door is opened as often as it is on some days, this action may be impacting worker productivity in the vicinity such that recommendation may be to use a different door or use the particular door at specific times of day thereby eliminating or at least minimizing this disruption.
The closes prior art noted above, however, do not fairly teach/suggest at least: collecting IoT sensor data, from a set of Internet of Things resources operatively connected to at least one supply chain facility and at least one demand management facility; storing the collected IoT sensor data; creating digital twins of the at least one supply chain facility and the at least one demand management facility based on the stored IoT sensor data; continuing to collect IoT sensor data from the set of Internet of Things resources; maintaining a synchronized stated between the digital twins and the at least one supply chain facility and the at least one demand management facility using continually collected IoT sensor data; simulating facility operations of the at least one supply chain facility and the at least one demand management facility in real-time using the digital twins; analyzing the collected IoT sensor data; detecting a supply chain disruption based, at least in part, on the analyzing of the collected IoT sensor data; predicting, based at least in part on the simulated facility operations, a potential disruption to at least one of the supply chain facility or the demand management facility; coordinating an automated workflow across the at least one supply chain facility and the at least one demand management facility; optimizing an operation based on the digital twin facility simulations; implementing a corrective action through automated processes; and validating an effectiveness of the corrective action based, at least in part, the continued IoT sensor data collection and new facility operations simulations.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/MAMON OBEID/Supervisory Patent Examiner, Art Unit 3687