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 .
Status of the Application
This is a Non-Final Action in response to the claims submitted on 09/10/2025
Specification
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because of undue length. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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 following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
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.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
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:
“an artificial intelligence-based smart manufacturing collaboration platform”, “an artificial intelligence-based real-time demand prediction and big data analysis service unit” and “a company legacy system” in claim 1;
“a task processing unit” and “a service processing unit” in claim 2;
“a community and customer service module”, “a core service module” in claim 3;
“an input data processing unit”, “a data transmission unit”, “an artificial intelligence event processing unit”, “an artificial intelligence-based control unit”, “a task processing unit” in claim 5;
“a data collection agent”, “a data refinement and conversion processing unit”, “a data storage and search engine storage unit” in claim 6;
“an intelligence business service unit”, “a common service unit” in claim 7; and
“a business service module”, “an artificial intelligence (AI)-based engine module” in claim 8.
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 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.
Claim limitations:
“an artificial intelligence-based smart manufacturing collaboration platform”, “an artificial intelligence-based real-time demand prediction and big data analysis service unit” and “a company legacy system” in claim 1;
“a task processing unit” and “a service processing unit” in claim 2;
“a community and customer service module”, “a core service module” in claim 3;
“an input data processing unit”, “a data transmission unit”, “an artificial intelligence event processing unit”, “an artificial intelligence-based control unit”, “a task processing unit” in claim 5;
“a data collection agent”, “a data refinement and conversion processing unit”, “a data storage and search engine storage unit” in claim 6;
“an intelligence business service unit”, “a common service unit” in claim 7; and
“a business service module”, “an artificial intelligence (AI)-based engine module” in claim 8 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.
The specification is not clear regarding the corresponding structure, material or acts performing the claimed functions. After reviewing the specification in its totality, it is understood that there is not clear link between the claimed limitations and the structure, material or act to perform such functions.
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.
Claims 2-4 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 term “such as” in claims 2 and 3 is a relative term which renders the claim indefinite. The term “such as” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “such as” is rendering the limitations “a service processing unit configured to process services such as a security function, user management, and integrated management”, “a community and custom service module configured to support services such as community between manufacturing companies, template management, user management, and menu management” and “a core service module configured to support services such as real-time monitoring, integrated data sharing, and engine linkage” indefinite.
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 1-9 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the claims are directed to at least one potentially eligible category of subject matter (i.e., process and machine, respectively). Thus, Step 1 of the Subject Matter Eligibility test for claims 1-9 is satisfied.
With respect to Step 2A Prong One, it is next noted that the claims recite an abstract idea that falls under the “Mental Processes” group within the enumerated groupings of abstract ideas set forth in the MPEP 2106 since the claims set forth steps that recite observation and evaluation of gathered data.
Claim 1 recites the abstract idea of interconnecting all processes of the manufacturing industries through convergence between fields of manufacturing and soft power [001]. In claim 1, this idea is described by the following claim steps:
provide component manufacturing collaboration-related information or utilize the information;
collect manufacturing collaboration data through a plurality of channels;
process the manufacturing collaboration data, to model the manufacturing collaboration data to generate optimized manufacturing collaboration data, and to implement a manufacturing business service;
collect manufacturing collaboration raw to process the collected manufacturing collaboration raw data and to generate demand prediction information by analyzing the processed manufacturing collaboration data through data collection, conversion, and indexing processes using an analysis tool;
store, integrate, and manage the manufacturing collaboration data and the demand prediction information; and
implement a manufacturing collaboration service between companies by collaborating.
This idea falls within the certain methods of organizing human activity grouping of abstract ideas because it is directed towards concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
Because the above-noted limitations recite steps falling within the Mental Processes abstract idea groupings of the MPEP 2106, they have been determined to recite at least one abstract idea when evaluated under Step 2A Prong One of the eligibility inquiry.
Therefore, because the limitations above set forth activities falling within the Mental Processes abstract idea groupings described in the MPEP 2106, the additional elements recited in the claims are further evaluated, individually and in combination, under Step 2A Prong Two and Step 2B below.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements that fail to integrate the abstract idea into a practical application are:
a user terminal;
a data channel;
an artificial intelligence-based smart manufacturing collaboration platform;
an edge computing technology;
an artificial intelligence-based model;
virtual simulation;
an artificial intelligence-based real-time demand prediction and big data analysis service unit;
an Internet of Things (IoT);
an artificial intelligence visualization;
an integrated database;
a company legacy system;
However, using a computer environment generically reciting artificial intelligence and virtual simulation amounts to no more than generally linking the use of the abstract idea to a particular technological environment. The examiner views these additional elements as results-oriented steps given that there is no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result are currently present such that this is viewed as equivalent to “apply it” for merely implementing the abstract idea using generic computing components (See Id). Interconnecting all processes of the manufacturing industries through convergence between fields of manufacturing and soft power can reasonably be performed by pencil and paper until limited to a computerized environment by requiring the recited elements to perform the steps.
These additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or computer-executable instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), and alternatively serve to link the use of the judicial exception to a particular technological environment. See MPEP 2106.05(f) and 2106.05(h).
In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As noted above, the claims as a whole merely describes a method, computer system, and computer program product that generally “apply” the concepts discussed in prong 1 above. (See MPEP 2106.05 f (II)) In particular applicant has recited the computing components at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. As the court stated in TLI Communications v. LLC v. AV Automotive LLC, 823 F.3d 607, 613 (Fed. Cir. 2016) merely invoking generic computing components or machinery that perform their functions in their ordinary capacity to facilitate the abstract idea are mere instructions to implement the abstract idea within a computing environment and does not add significantly more to the abstract idea. Accordingly, these additional computer components do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Therefore, even when viewed as a whole, nothing in the claim adds significantly more (i.e. an inventive concept) to the abstract idea and as a result the claim is not patent eligible.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
For the reasons identified with respect to Step 2A, prong 2, claims 1, 15 and 20 fail to recite additional elements that amount to an inventive concept. For example, use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a commercial or legal interaction or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more (see MPEP 2106.05(g)). In addition, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application (see MPEP 2106.05(h)).
Dependent claims 2-9 recite the same abstract idea as recited in the independent claims, and when evaluated under Step 2A Prong One are found to merely recite details that serve to narrow the same abstract idea recited in the independent claims accompanied by the same generic computing elements or software as those addressed above in the discussion of the independent claims, which is not sufficient to amount to a practical application or add significantly more, or other additional elements that fail to amount to a practical application or add significantly more, as noted above.
Dependent claim 2 further limits the abstract idea by introducing a task processing unit configured to monitor the data collected through the data channel, manage templates and users, and process integrated data sharing; and a service processing unit configured to process services such as a security function, user management, and integrated management. Processing and managing information is a process that could be performed manually until limited by computer elements. Further embellishing that the invention is capable of processing and sorting information in a generic computing environment does not integrate the abstract idea into a practical application or adds significantly more to the abstract idea. Therefore the claims are also non-statutory subject matter.
Dependent claims 3-4 further limits the abstract idea by linking the judicial exception to a particular field of use by introducing the limitation a community and custom service module configured to support services such as community between manufacturing companies, template management, user management, and menu management; and a core service module configured to support services such as real-time monitoring, integrated data sharing, and engine linkage and wherein the service processing unit processes an SSO/security service, processes the user management service, and supports the integrated management service. Processing and managing information is a process that could be performed manually until limited by computer elements. Further embellishing that the invention is capable of processing and sorting information in a generic computing environment does not integrate the abstract idea into a practical application or adds significantly more to the abstract idea. Therefore the claims are also non-statutory subject matter.
Dependent claim 5 further limits the abstract idea by linking the judicial exception to a particular field of use by introducing the limitation an input data processing unit configured to process the manufacturing collaboration data, which is collected through a plurality of data channels, through the edge computing technology, and to process a task; a data transmission unit configured to generate a process event for the data processed by the input data processing unit; an artificial intelligence event processing unit configured to process the event, which is transmitted through the data transmission unit, using the artificial intelligence-based model; an artificial intelligence-based control unit configured to provide an artificial intelligence- based processing model such that the artificial intelligence event processing unit processes the event; and a task processing unit configured to process the task by interworking with the artificial intelligence event processing unit. Further embellishing that the invention is capable of communicate data in a generic computing environment does not integrate the abstract idea into a practical application or adds significantly more to the abstract idea. The examiner views these additional elements as results-oriented steps given that there is no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result are currently present such that this is viewed as equivalent to “apply it” for merely implementing the abstract idea using generic computing components (See Id.). Therefore the claims are also non-statutory subject matter.
Dependent claim 6 further limits the abstract idea by introducing the limitations a data collection agent configured to collect manufacturing collaboration-related data through the edge computing technology; a data refinement and conversion processing unit configured to refine the manufacturing collaboration data collected through the data collection agent, and to convert the manufacturing collaboration data into data that is utilizable in the artificial intelligence-based model; a data storage and search engine storage unit configured to store the data processed by the data refinement and conversion processing unit, and to store a search engine; and a data visualization dashboard configured to display the processed data through visualization Processing and managing information is a process that could be performed manually until limited by computer elements. Further embellishing that the invention is capable of processing and sorting information in a generic computing environment does not integrate the abstract idea into a practical application or adds significantly more to the abstract idea. Therefore the claims are also non-statutory subject matter.
Dependent claims 7 further limits the abstract idea by introducing the limitations an intelligent business service unit configured to provide a manufacturing collaboration service and an artificial intelligence-based engine; and a common service unit configured to process common services between manufacturing companies, which include information management, user management, and log management. Transmitting data is a process that could be performed manually until limited by a processor. Further embellishing that the invention is capable of transmitting information in a generic computing environment does not integrate the abstract idea into a practical application or adds significantly more to the abstract idea. Therefore the claims are also non-statutory subject matter.
Dependent claim 8 further limits the abstract idea by linking the judicial exception to a particular field of use by introducing the limitation a business service module configured to support business services including task guidance, collaboration management, schedule management, contract/arbitration management, issue management, business management, and quality management; and an artificial intelligence (AI)-based engine module configured to provide a collaborative matching engine, a big data analysis engine, an arbitration management engine, a search engine, a performance management engine, and a demand prediction engine. The examiner views these additional elements as results-oriented steps given that there is no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result are currently present such that this is viewed as equivalent to “apply it” for merely implementing the abstract idea using generic computing components (See Id.). Therefore the claims are also non-statutory subject matter.
Dependent claim 9 further limits the abstract idea by introducing wherein the common service unit supports common services including reference information management, common management, user management, bulletin board management, company pool management, log management, and community. The examiner views these additional elements as results-oriented steps given that there is no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result are currently present such that this is viewed as equivalent to “apply it” for merely implementing the abstract idea using generic computing components (See Id.). Therefore the claims are also non-statutory subject matter.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and the collective functions merely provide high level of generality computer implementation. Therefore, whether taken individually or as an order combination, the claims are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
For more information see MPEP 2106.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-9 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cella (US 2023/0127651).
Regarding claim 1, Cella discloses a smart consumer goods component manufacturing collaboration platform (abstract) comprising:
a user terminal configured to provide component manufacturing collaboration-related information or utilize the information ([0267] In embodiments, provided herein are methods, systems, components and other elements for an information technology system that may include a cloud-based management VCNP 604 with a micro-services architecture, a set of interfaces 702, a set of network connectivity facilities 642, adaptive intelligence facilities 614, data storage facilities 624, data collection systems 640, and monitoring facilities 614 that are coordinated for monitoring and management of a set of value chain network entities 652.);
a data channel configured to collect manufacturing collaboration data through the user terminal and a plurality of channels ([0267] In embodiments, provided herein are methods, systems, components and other elements for an information technology system that may include a cloud-based management VCNP 604 with a micro-services architecture, a set of interfaces 702, a set of network connectivity facilities 642, adaptive intelligence facilities 614, data storage facilities 624, data collection systems 640, and monitoring facilities 614 that are coordinated for monitoring and management of a set of value chain network entities 652.);
an artificial intelligence-based smart manufacturing collaboration platform configured to process the manufacturing collaboration data, which is collected through the data channel, through an edge computing technology, to model the manufacturing collaboration data into an artificial intelligence-based model, to generate optimized manufacturing collaboration data through virtual simulation, and to implement a manufacturing business service ([0669] In embodiments, the machine-learning system 6150 trains one or more models 6120 that are utilized by the artificial intelligence system 1160 to make classifications, predictions, and/or other decisions relating to risk management, including for products 650 and product components. In embodiments, may be equipment components. In example embodiments, a model 6120 is trained to mitigate risk and liability by detecting the condition of a set of components. The machine-learning system 6150 may train the models using n-tuples that include the features pertaining to components and one or more outcomes associated with the component condition. In this example, features for a component may include, but are not limited to, component material (plastic, glass, metal, or the like), component history (manufacturing dates, usage history, repair history), component properties, component dimensions, component thermal properties, component price, component supplier, and/or other relevant features. In this example, outcomes may include whether the digital twin of the component 6002 is in operating condition. In this example, one or more properties of the digital twins are varied for different simulations and the outcomes of each simulation may be recorded in a tuple with the proprieties. Other examples of training risk management models may include a model 6120 that is trained to optimize product safety, a model that is trained to identify components with a high likelihood of causing an undesired event, and the like. See also [1273]);
an artificial intelligence-based real-time demand prediction and big data analysis service unit configured to collect manufacturing collaboration raw data through an Internet of Things (IoT), to process the collected manufacturing collaboration raw data through the edge computing technology, and to generate demand prediction information by analyzing the processed manufacturing collaboration data through data collection, conversion, and indexing processes using an artificial intelligence visualization and analysis tool ([0169] This may involve taking any of the data that is flowing through or about any of these entities 652 and pull the data into a framework where other applications across supply and demand may interact with the entities 652. This may be a shared data pipeline coming from an IoT system and other external data sources, feeding into the monitoring layer, being stored in a common data schema in the storage layer, and then various intelligence may be trained to identify implications across these entities 652. [0200] In embodiments, providing coordinated intelligence for the set of demand management applications 824 may include configuring at least one of the adaptive intelligence systems 614 (e.g., through the user interface 3020 and the like) for at least one or more demand management applications selected from a list of demand management applications including a demand planning application, a demand prediction application, a sales application, a future demand aggregation application, a marketing application, an advertising application, an e-commerce application, a marketing analytics application, a customer relationship management application, a search engine optimization application, a sales management application, an advertising network application, a behavioral tracking application, a marketing analytics application, a location-based product or service-targeting application, a collaborative filtering application, a recommendation engine for a product or service, and the like. See also [1124], [1689], and [2069]);
an integrated database configured to store, integrate, and manage the manufacturing collaboration data that is processed by the artificial intelligence-based smart manufacturing collaboration platform and the demand prediction information that is generated by the artificial intelligence-based real-time demand prediction and big data analysis service unit ([0045] FIG. 31 is a block diagram showing components and relationships of a unified database in an embodiment of a value chain network management platform in accordance with the present disclosure. [0186] The adaptive intelligent systems layer 614 of the platform 604 may include one or more protocol adaptors 1110 for facilitating data storage, retrieval access, query management, loading, extraction, normalization, and/or transformation to enable use of the various other data storage architectures 1002, such as allowing extraction from one form of database and loading to a data system that uses a different protocol or data structure. ); and
a company legacy system configured to implement a manufacturing collaboration service between companies by collaborating the artificial intelligence-based smart manufacturing collaboration platform and the integrated database ([0200] In embodiments, providing coordinated intelligence for the set of demand management applications 824 may include configuring at least one of the adaptive intelligence systems 614 (e.g., through the user interface 3020 and the like) for at least one or more demand management applications selected from a list of demand management applications including a demand planning application, a demand prediction application, a sales application, a future demand aggregation application, a marketing application, an advertising application, an e-commerce application, a marketing analytics application, a customer relationship management application, a search engine optimization application, a sales management application, an advertising network application, a behavioral tracking application, a marketing analytics application, a location-based product or service-targeting application, a collaborative filtering application, a recommendation engine for a product or service, and the like. [0742] In embodiments, the EMP 8000 includes an enterprise configuration system 8002, a digital twin system 8004, a collaboration suite 8006, an expert agent system 8008, and an intelligence service system 8010. In embodiments, the EMP 8000 includes an API system 8014 that facilitates the transfer of data between one or more external systems and the EMP 8000. In some embodiments, the intelligence service system 8010 includes an enterprise data store 8012 that stores data relating to enterprises, whereby the enterprise data is used by the digital twin system 8004, the collaboration suite 8006, and/or the expert agent system 8008. The enterprise data store 8012 may store any of a wide variety of data, such as any data involved in the data pipeline described above and throughout this disclosure and the documents incorporated herein by reference. In embodiments, the enterprise data store 8012 may store data that is being used to update digital twins in real-time or substantially real time. In embodiments, the enterprise data store 8012 may store databases, file systems, folders, files, documents, transient data (e.g., real-time data or substantially real-time data), sensor data, and the like.).
Regarding claim 2, Cella discloses:
a task processing unit configured to monitor the data collected through the data channel ([0160] FIG. 6 illustrates a connected value chain network 668 in which a value chain network management platform 604 (referred to herein in some cases as a “value chain control tower,” the “VCNP,” or simply as “the system,” or “the platform”) orchestrates a variety of factors involved in planning, monitoring, controlling, and optimizing various entities and activities involved in the value chain network 668, such as supply and production factors, demand factors, logistics and distribution factors, and the like.), manage templates and users (See [0777]), and process integrated data sharing ([0163] In embodiments, the management platform 604 may include a set of data handling layers 608 each of which is configured to provide a set of capabilities that facilitate development and deployment of intelligence, such as for facilitating automation, machine learning, applications of artificial intelligence, intelligent transactions, state management, event management, process management, and many others, for a wide variety of value chain network applications and end uses. In embodiments, the data handling layers 608 are configured in a topology that facilitates shared data collection and distribution across multiple applications and uses within the platform 604 by a value chain monitoring systems layer 614.); and
a service processing unit configured to process services such as a security function, user management, and integrated management (See [0166]).
Regarding claim 3, Cella discloses:
a community and custom service module configured to support services such as community between manufacturing companies, template management, user management, and menu management ([0163] In embodiments, the management platform 604 may include a set of data handling layers 608 each of which is configured to provide a set of capabilities that facilitate development and deployment of intelligence, such as for facilitating automation, machine learning, applications of artificial intelligence, intelligent transactions, state management, event management, process management, and many others, for a wide variety of value chain network applications and end uses. In embodiments, the data handling layers 608 are configured in a topology that facilitates shared data collection and distribution across multiple applications and uses within the platform 604 by a value chain monitoring systems layer 614.); and
a core service module configured to support services such as real-time monitoring, integrated data sharing, and engine linkage ([0192] In embodiments, the value chain monitoring systems layer 614 and its data collection systems 640 may include a wide range of systems for the collection of data. This layer may include, without limitation, real time monitoring systems 1520).
Regarding claim 4, Cella discloses:
wherein the service processing unit processes an SSO/security service, processes the user management service, and supports the integrated management service ([1406] In embodiments, an authentication application may be provided to authenticate the identity of users of the platform through one or more authentication mechanisms including a simple username/password mechanism, biometric mechanism or cryptographic key exchange mechanism. Similarly, an authorization application may define the roles and access privileges of users of the platform such that users with different roles are provided different access privileges. For example, an “administrator” or “host” privilege may allow a user of the platform to make changes to platform configuration, add and remove programs, access any files and manage other users on the platform; an “engineer” privilege may allow a user of the platform to operate the platform; and a “service” privilege may allow a user of the platform to access a subset of administrator privileges to perform maintenance and repair activities.).
Regarding claim 5, Cella discloses:
an input data processing unit configured to process the manufacturing collaboration data, which is collected through a plurality of data channels, through the edge computing technology, and to process a task (See Fig. 2 and [0156] In example embodiments a value chain control tower 260 (e.g., referred to herein in some cases as a “value chain network management platform”, a “VCNP”, or simply as “the system”, or “the platform”) may be connected to, in communication with, or otherwise operatively coupled with data processing facilities including, but not limited to, big data centers (e.g., big data processing 230) and related processing functionalities that receive data flow, data pools, data streams and/or other data configurations and transmission modalities received from, for example, digital product networks 21002, directly from customers (e.g., direct connected customer 250), or some other third party 220. );
a data transmission unit configured to generate a process event for the data processed by the input data processing unit ([0156] Communications related to market orchestration activities and communications 210, analytics 232, or some other type of input may also be utilized by the value chain control tower for demand enhancement 262, synchronized planning 234, intelligent procurement 238, dynamic fulfillment 240 or some other smart operation informed by coordinated and adaptive intelligence, as described herein.);
an artificial intelligence event processing unit configured to process the event, which is transmitted through the data transmission unit, using the artificial intelligence-based model ([0156] Communications related to market orchestration activities and communications 210, analytics 232, or some other type of input may also be utilized by the value chain control tower for demand enhancement 262, synchronized planning 234, intelligent procurement 238, dynamic fulfillment 240 or some other smart operation informed by coordinated and adaptive intelligence, as described herein.);
an artificial intelligence-based control unit configured to provide an artificial intelligence- based processing model such that the artificial intelligence event processing unit processes the event ([0156] Communications related to market orchestration activities and communications 210, analytics 232, or some other type of input may also be utilized by the value chain control tower for demand enhancement 262, synchronized planning 234, intelligent procurement 238, dynamic fulfillment 240 or some other smart operation informed by coordinated and adaptive intelligence, as described herein.); and
a task processing unit configured to process the task by interworking with the artificial intelligence event processing unit ([0156] Communications related to market orchestration activities and communications 210, analytics 232, or some other type of input may also be utilized by the value chain control tower for demand enhancement 262, synchronized planning 234, intelligent procurement 238, dynamic fulfillment 240 or some other smart operation informed by coordinated and adaptive intelligence, as described herein.).
Regarding claim 6, Cella discloses:
a data collection agent configured to collect manufacturing collaboration-related data through the edge computing technology ([0159] In example embodiments, the data aggregation facilities or layer may include, but is not limited to, modules for data normalization for common transmission and heterogeneous data collection from disparate devices);
a data refinement and conversion processing unit configured to refine the manufacturing collaboration data collected through the data collection agent, and to convert the manufacturing collaboration data into data that is utilizable in the artificial intelligence-based model ([009] The method may further include receiving, by the first device, additional data values of the data stream. The method may include refining, by the first device, the predictive model using the additional data values. In embodiments, refining the predictive model adjusts the model parameters. The method may include transmitting the adjusted model parameters to the second device. [2643] The modelling module 18064 may be responsible for various operations in a transmission role and/or in a receiver role. In a transmission role, the modelling module 18064 may continually receive data from various data sources 18004 (e.g., sensors 18022) and continually generate and/or refine models that predict future states of the incoming data. The various models may be, for example, classification models, behavioral analysis models, prediction models, data augmentation models, and/or any other types of model. Model parameters (e.g., neural network weights) from the generated/refined models may then be transmitted to receivers, which may use the parameters to perform classifications, behavior analysis, prediction, augmentation and/or the like without needing to have access to the data stream. Accordingly, in a receiver role, the modelling module 18064 may use various parameters received from another PMCP device interface to parameterize various types of models, then use the parameterized models to generate data for further use by the receiving device.);
a data storage and search engine storage unit configured to store the data processed by the data refinement and conversion processing unit, and to store a search engine ([2649] In embodiments, a storage module 18068 may provide various operations for processing data for storage and/or storing data. An ETL interface 18088 may be configured to perform exchange, transform, and load (ETL) operations for storing data in a PMCP database 18090. The PMCP database 18090 may be used to store various data, including data received from data sources 18004 (e.g., such that historical data may be used to generate/refine various models), as well as the models themselves, model parameters, and/or the like.); and
a data visualization dashboard configured to display the processed data through visualization ([2420] In some embodiments, the intelligence layer 14320 includes a graphical user interface (GUI) module 14340 and a proximity module 14342. The GUI module may generate at least one user interface display for presentation on the display 14311. The GUI module 14340 may generate the parameters of at least one digitally enabled product of the set of digital products in the at least one user interface display and may generate a proximity display of proximal digital products of the set of digital products in the at least one user interface display. In some embodiments, generating the proximity display includes generating the proximity display of proximal products that are geographically proximate, where the digital product network is further programmed to filter the proximal products by at least one of product type, product capability, or product brand. In some embodiments, generating the proximity display includes generating the proximity display of proximal products that are proximate to one of the set of digital products by product type proximity, product capability proximity, or product brand proximity.).
Regarding claim 7, Cella discloses:
an intelligent business service unit configured to provide a manufacturing collaboration service and an artificial intelligence-based engine; and a common service unit configured to process common services between manufacturing companies, which include information management, user management, and log management (See Fig. 7 and [0163]-[0164]).
Regarding claim 8, Cella discloses:
a business service module configured to support business services including task guidance, collaboration management, schedule management, contract/arbitration management, issue management, business management, and quality management (See Fig. 7 and [0163]-[0164]); and
an artificial intelligence (AI)-based engine module configured to provide a collaborative matching engine, a big data analysis engine, an arbitration management engine, a search engine, a performance management engine, and a demand prediction engine (See also [0356] One set of solutions to these challenges is an artificial intelligence store 3504 that is configured to enable collection, organization, recommendation and presentation of relevant sets of artificial intelligence systems based on one or more attributes of a domain and/or a domain-related problem.).
Regarding claim 9, Cella discloses:
wherein the common service unit supports common services including reference information management, common management, user management, bulletin board management, company pool management, log management, and community ([0062] FIG. 48 is a block diagram showing components and relationships in embodiments of a value chain network management platform that uses a microservices architecture. [0090] FIG. 104 is a schematic illustrating an example intelligence services system according to some embodiments of the present disclosure. [0105] FIG. 119 is a schematic illustrating an example implementation of an autonomous additive manufacturing platform for automating and managing manufacturing functions and sub-processes including process and material selection, hybrid part workflows, feedstock formulation, part design optimization, risk prediction and management, marketing and customer service according to some embodiments of the present disclosure.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
BEAVER, US 2022/0391846, MOMENT-BASED GIFTS AND DESIGNS GENERATED USING A DIGITAL PRODUCT COLLABORATION PLATFORM. One technical field of the disclosure pertains to generating moment-based gifts and designs using a digital product collaboration platform. Another technical field pertains to determining context information for interactions between users and the collaboration platform and based on the information content and various constraints, generating suggestions for additional gifts and designs to memorialize various events. Yet another technical field pertains to determining digital descriptions of the designs and based on the digital descriptions, determining manufacturing instructions for manufacturing corresponding digital and physical products.
H. Xia, J. Zhao, X. Ma, Y. Chen, H. Lv and Z. Wang, "Research on Data-Driven Industrial Internet Solutions," 2018 International Conference on Networking and Network Applications (NaNA), Xi'an, China, 2018, pp. 366-371, doi: 10.1109/NANA.2018.8648782.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIA C SANTOS-DIAZ whose telephone number is (571)272-6532. The examiner can normally be reached Monday-Friday 8:00AM-5:00PM.
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/MARIA C SANTOS-DIAZ/ Primary Examiner, Art Unit 3629
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