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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/9/2025 has been entered.
Response to Amendment
The Amendments filed on 9/9/2025 have been entered. Claims 1-19 have been canceled. Claims 20-37 are new and pending in the application.
Claim Objections
Claim 20, 26, and 32 objected to because of the following informalities:
Claims 20, 26, and 32 recite “the components that the two of first plurality of nodes correspond to”; however, they should recite - - components that the two of the first plurality of nodes correspond to - - to provided consistent antecedent basis.
Claims 20, 26, and 32 recite “storing…managed by an information base engine.”; however, they should recite - - storing…managed by an information base engine;- - to correct the apparent typographical error of the period punctuation.
Appropriate correction is required.
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 20-37 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.
Regarding claim 20, claim 20 requires that each attribute of a component in a structure graph is represented using a "combination of text, a structure graph, and a flow graph".
Per the instant specification, clean copy of substitute specifications dated 6/8/2021: p. 4-5, Within the knowledge base, any product or process within an industrial setting may be represented using a special knowledge graph. When such a knowledge graph is used to represent a product, a resource, or a process, it is referred to as a product graph, a resource graph, or a process graph (i.e. a flow graph), respectively. The provisional application no. 63/027,947 contains detailed description of the product graph, resource graph and process graph. Such disclosure in the provisional application is hereby incorporated by reference. These graphs are usually interconnected. For instance, a product graph may contain in a vertex a reference to a process graph that represents the process for making a particular component of the product, and the product graph may also contain a reference to a resource graph that represents a supplier/ vendor of that component, a reference to resource graph that represents a partner for designing the product, or a reference to a resource graph that represents a component supplier or a customer of the product. (underlining added for emphasis)
Per the provisional application no. 63/027,947 incorporated by reference: p. 4, [0022] Every node in the structure graph contains an open set of properties/attributes/metadata. information about the component it represents. A property/attribute is expressed in the name value pair format, where the value field of a property/attribute may be a simple value, or a node in the structure graph, or another structure graph. For instance, in a structure graph representing a vehicle, a node representing the engine of the vehicle may contain properties such as name, serial number, model number, ISO number, schematics, suppliers, resources required for manufacturing the part including labor, machine and facility resources, pricing, warranty, reviews, complaints, and its compatible parts. The property describing the supplier may have its value field storing a link to an external structure graph that represents the supplier or the manufacturer of the engine. (underlining added for emphasis)
While the specification notes that a "process graph" is the same as a "flow graph", it does not explicitly state that a structure graph's attribute must or can be represented by a flow graph specifically. Furthermore, the claim requires a "combination" of all three (text, structure graph, and flow graph), whereas the specification presents these as alternatives ("or"). Thus, the claim 20 limitations “wherein each of the attributes is represented using a combination of text, a structure graph, and a flow graph” lacks written description and is considered new matter. For the purposes of examination the said claim limitation is interpreted as “wherein each of the attributes is represented using a first text, a first structure graph, or a first flow graph”.
Further, Claim 20 requires that each relationship (represented by an edge) in a structure graph is represented using "text and a structure graph".
Per the provisional application no. 63/027,947 incorporated by reference in the instant specification: p. 4, [0024] The relationship could be a structural relationship such as contains, comprises, connect to, bound to, derived from and the likes, or a functional relationship such as an action or a task that is performed by objects in one node to objects in the linked node. Examples of the action include "produce", "supplied by" and "made by", etc. [0025] As the relationship is directed and follows the RDF subject-verb-object format, we use a verb preceded by a symbol '>' or '<' to indicate that the direction of the relationship. For instance, in "A >contains B", A is the subject and B is the object. In other words, the relationship is "A contains B". For another instance, in "A <contains B' or "A contains< B", the symbol ' means that B is the subject and A is the object therefore the relationship is "B contains A". Furthermore, a link in a structure graph may contain one or more properties/attributes where a property may be represented in the form of a name value pair, and the value field of the name value pair a simple value, or another graph.
At best, instant specification describe relationships in structure graphs using "subject-verb-object syntax" and "RDF triples". While they mention that an edge can store attributes that refer to "one or more vertices and edges" or "another structure graph", there is no explicit disclosure in the provided sources that requires the relationship itself to be a combination of both text and a structure graph as a conjunctive requirement. Thus, the claim 20 limitations “wherein each of the one or more relationships is represented using text and a structure graph” lacks written description and is considered new matter. For the purposes of examination the said claim limitation is interpreted as “wherein each of the one or more relationships is represented using a second text or a second structure graph”.
Further, claim 20 requires that information in flow graph edges be represented using a "combination of text, structure graph, and a flow graph".
Per the provisional application no. 63/027,947 incorporated by reference in the instant specification: p. 7, [0047] A link may also represent the transition from one task to another, or indicate whether one task contains another as a subtask. The data produced by a first task and transmitted as input to a second task may be represented as a property of the node representing the first task, [0050] A link may also contain properties/attributes that store any information or data used by two tasks to coordinate the execution flow. Properties/attributes are expressed in the name value pair format, where the value field of a property/attribute may be a simple value, or another structure or flow graph, or another node in a structure graph or a flow graph.
While the sources provide support for the individual components of this limitation, they do not appear to describe them as a mandatory conjunctive "combination" for representing transition information in a single edge. The specification states that properties or attributes within a flow graph link (edge) are expressed in a name-value pair format. It explicitly states that the value field "may be a simple value, or another structure or flow graph, or another node in a structure graph or a flow graph". The use of the word "or" in the specification suggests that the information can be represented by one of these formats. The claim’s use of "combination" implies that all three must be present to represent the information, a requirement not explicitly found in the supporting text. Thus, the claim 20 limitations “wherein the information is represented using a combination of text, structure graph, and a flow graph” lacks written description and is considered new matter. For the purposes of examination the said claim limitation is interpreted as “wherein the second information is represented using a third text, a third structure graph, or a second flow graph”.
Regarding claims 26 and 32, these claims contain substantially similar limitations to those found in claim 20. Consequently, claims 26 and 32 are rejected for the same reasons.
Regarding claims 21-25, 27-31, and 33-37, these claims are also rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as being dependent on parent claims failing to comply with the written description requirement.
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 20-37 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.
Regarding claim 20, claim 20 recites each of the first plurality of nodes containing attributes using “text”, each of the one or more relationships of each of the first plurality of edges represented using “text”, and information associated with a second plurality of edges using “text”. It is unclear whether these are intended to be the same or different texts. Claim 20 recites “a structure graph”, “a structure graph” and “structure graph”. Claim 20 further recites “a flow graph” with respect to the first plurality of nodes and “a flow graph” with respect to the second plurality of edges. It is unclear whether these are intended to be the same or different graphs. For the purposes of examination, these limitations are interpreted as: a first text, a first structure graph, a first flow graph, a second text, a second structure graph, a third text, a second flow graph, and a third structure graph.
Claim 20 further recites “information associated with execution of the task”, “the information”, “information associated with transition between tasks”, “the information”. It is unclear which previous limitations “the information” is intended to refer. For the purposes of examination, this limitation is interpreted as: second information.
Regarding claims 26 and 32, these claims contain substantially similar limitations to those found in claim 20. Consequently, claims 26 and 32 are rejected for the same reasons.
Regarding claims 21-25, 27-31, and 33-37, these claims are also rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for depending on an indefinite parent claim.
Regarding claims 23, 29, and 35, these claims recite “routing data and commands between the knowledge entry”. The claims do not previously recite a knowledge entry and it is unclear what is meant by “between the knowledge entry”. For the purposes of examination, this claim is interpreted as:
providing a subscription/publication based real-time message routing platform for routing data and commands.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 20, 23-26, 29-32, and 35-37 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (hereinafter Wu), US 20200201875 A1 published 06/25/2020, in view of Martelaro et al. (hereinafter Martelaro), US 20210264296 A1 published 08/26/2021.
Regarding claim 20, Wu teaches an industrial knowledge management system comprising: one or more processors; memory for storing instructions executable by the one or more processors (Wu Figs. 1-16; [0028], the system circuitry 104 may include one or more instruction processors 118 and memories 120. The memories 120 stores, for example, control instructions 124 and an operating system 122. In one implementation, the instruction processors 118 executes the control instructions 124 and the operating system 122 to carry out any desired functionality related to the customized graph knowledge base);
an industrial knowledge repository that comprises one or more structure graphs and one or more flow graphs (Wu Figs. 1-16; [0019], This disclosure relates to a graph knowledge base customized for a specific industrial operation of a specific industrial setting. Chemical synthesis, petroleum refining, and electric power production, are all examples of different types of industries and different industrial settings. An industrial setting may exist for any specific industrial operation, and the industrial setting may include any type of industrial plant that carries our any type of industrial operation. Examples of industrial operations include synthesizing a particular set of chemicals, fabricating semiconductor wafers, and performing water treatment; [0020], domain processes, facilities, equipment, sensors/sensor parameters, personnel hierarchies, supply chains, raw materials, intermediate products, final products, key performance measures, customers, power consumptions, emissions, and regulation compliances. Data representing some or all of these entities and their relationships may be used to build a customized knowledge base for the plant; [0022], graph database may be used to store a collection of nodes, edges and attributes. These components of a graph database may be alternatively referred to as graph structural components. A node may represent any physical or abstract entity that plays a certain role in the industrial operation. An edge may be used to connect two nodes and may represent relationship between nodes. The relationships between the nodes, in the form the edges, may be directional; the organization of an industrial graph database customized to the specific industrial operation may also take a more structured form for achieving better data processing and querying efficiency; [0040], FIG. 6 illustrates an example categorization scheme predefined for a specific petroleum refinery plant. Under this example scheme, the operation of the refinery plant may be described by entities belonging to five categories including equipment 610, Key Performance Indicator (KPI) 620, industrial domain process 630, workforce 640, and facility and environment 650; [0045], FIG. 8 illustrates an example data template 800 for data elements belonging to the equipment category for the specific petroleum refinery plant; [0046], FIG. 9 illustrates an example domain process diagram 902 for the petroleum plant and an excerpt of an example domain process data template 930 for data elements belonging to the industrial domain process category; [0053], FIG. 13 shows a set of extracted types of inter-category relationships. In particularly, 1310 of FIG. 13 illustrates types of relationships between one of the categories (KPI) and all other categories; thus Wu teaches a graph knowledge base customized for industrial operations (e.g., petroleum refining) that stores entities and relationships in a structured graph database 130),
wherein each of the one or more structure graphs corresponds to an entity and comprises: a first plurality of nodes, wherein each of the first plurality of nodes corresponds to a component of the entity and contains attributes of the component, and wherein each of the attributes is represented using a combination of text, a structure graph, and a flow graph (interpreted as represented using a first text, a first structure graph, or a first flow graph per the 35 U.S.C. 112(a) and 112(b) rejections above), and a first plurality of edges connecting the first plurality of nodes, wherein each of the first plurality of edges connects two of the first plurality of nodes and represents one or more relationships between the components that the two of the first plurality of nodes correspond to, and wherein each of the one or more relationships is represented using text and a structure graph (interpreted as the one or more relationships is represented using a second text or a second structure graph per the 35 U.S.C. 112(a) and 112(b) rejections above) (Wu Figs. 1-16; [0034], FIG. 3 illustrates an example 300 of entities and relationships in a specific petroleum refinery operation extracted from the baseline; [0035], entities 324 and 326 may be determined as general products of entity 322. Likewise, entity 328 may be determined as a domain process of entity 322 and entity 329 may be determined as a general product of entity 322 as well as a direct product of the entity 328. Entities 332 (“equipment A01-01”), 334 (“equipment A01-02”), 336 (“John”), 338 (“equipment A02-01”), and their relationships may pertain to specific implementation of the particular petroleum refining plant and may be extracted from implementation-specific data sources collected by the petroleum refining plant. For example, entities 332, 334, and 338 may represent specific pieces of connected equipment in the specific petroleum refining plant for styrene production. Their relationships may be represented by “equipment connect”. Entity 336, however, may represent a particular operator of equipment entities 332 and 334. The relationships between entities may be directional, as shown by the arrows in FIG. 3. The relationships across baseline, domain-specific, and implementation-specific entities, such as relationships 340 and 350, may be determined from any of the baseline, domain-specific, and implementation-specific data sources; [0045], FIG. 8 illustrates an example data template 800 for data elements belonging to the equipment category for the specific petroleum refinery plant. Data elements in the equipment data template may be organized in multiple levels, as shown by unit system level (810), equipment level (820), and attributes and parameter level (840) illustrated in FIG. 8. Unit system level 810 may include various systems, such as 812 and 814, of the petroleum refinery plant. System 812, for example may denote the vacuum distillation system and system 814 may denote a catalytic reformer system of the petroleum plant. Each of the systems may include various equipment. For example, the vacuum distillation system 812 may include a furnace 822, and a pump assembly 824. Each of the levels 820 and 840 may in turn be organized as a hierarchy. For example, the furnace 822 may contain sub equipment 826, 828, and 830, and the pump assembly 824 may include sub equipment 832 and 834. Likewise, each equipment may be characterized by a set of attributes and types of parameters, such as specification 842 and operational parameter 844. The specification of an equipment may include parameters such as manufacturer 846, size/weight 848 and the like. Operational parameter 844 may further contains a hierarchical set of parameters 850, 852, 854, and 856; thus Wu teaches an equipment data template 800 where equipment (nodes) contains attributes/parameters level 840 (e.g., size, weight) as name-value pairs that can be a simple value or another graph (wherein each of the one or more structure graphs corresponds to an entity and comprises: a first plurality of nodes, wherein each of the first plurality of nodes corresponds to a component of the entity and contains attributes of the component, and wherein each of the attributes is represented using a first text, a first structure graph, or a first flow graph).
[0046] FIG. 9 illustrates an example domain process diagram 902 for the petroleum plant and an excerpt of an example domain process data template 930 for data elements belonging to the industrial domain process category. The entire process flow of the petroleum plant is shown by 910. The process flow 910 may be divided into various component processes or sections. For example, component process 920 (enclosed by the dashed box) may be related to a particular processing section of the refinery plant. The connectivity between various equipment involved in component process 920 may be extracted, as shown by 922. The arrows in 910, 920, and 922 may represent the direction of material flow; thus Wu teaches relationships and inter-category relationships (e.g., equipment to KPI) using directional arrows and RDF subject-verb-object formats to represent these relationships (and a first plurality of edges connecting the first plurality of nodes, wherein each of the first plurality of edges connects two of the first plurality of nodes and represents one or more relationships between the components that the two of the first plurality of nodes correspond to, and wherein each of the one or more relationships is represented using a second text or a second structure graph));
wherein each of the one or more flow graphs corresponds to a process and comprises a second plurality of nodes, wherein each of the second plurality of nodes corresponds to a task in the process and stores information associated with execution of the task, wherein a portion of the information is ephemeral; a second plurality of edges connecting the second plurality of nodes, wherein each of the second plurality of edges stores information (interpreted as stores second information per the 35 U.S.C. 112(b) rejection above) associated with transition between tasks, wherein the information (interpreted as associated with transition between tasks, wherein the second information per the 35 U.S.C. 112(b) rejection above) is represented using a combination of text, structure graph, and a flow graph (interpreted as is represented using a third text, a third structure graph, or a second flow graph) (Wu Figs. 1-16; [0046], FIG. 9 illustrates an example domain process diagram 902 for the petroleum plant and an excerpt of an example domain process data template 930 for data elements belonging to the industrial domain process category. The entire process flow of the petroleum plant is shown by 910. The process flow 910 may be divided into various component processes or sections. For example, component process 920 (enclosed by the dashed box) may be related to a particular processing section of the refinery plant. The connectivity between various equipment involved in component process 920 may be extracted, as shown by 922. The arrows in 910, 920, and 922 may represent the direction of material flow. The example domain process data template 930 may include pairs of source and destination equipment 934 and 940, and their relationships 950. Each equipment may be identified by a unique ID as shown in 932 and 942. In one implementation, the IDs for the equipment may be constructed to identify the component process in which the equipment is used. For example, the first portion of the equipment IDs 932 and 942 contains “E010”, indicating that these pieces of equipment all belong to the component process 920; [0064], The customized industrial graph knowledge base may be updated as new knowledge is gained. For example, FIG. 15 illustrates a logic flow for updating the knowledge base when knowledge 1510 external to the current industrial knowledge base is introduced. The external new knowledge may be introduced from supplemental information via updates in any of the baseline, domain-specific, and implementation-specific data sources. For example, new equipment may be purchased and installed, existing equipment may be upgraded, operation manuals may be updated, and new facilities may be built; thus Wu teaches domain process diagrams (Fig. 9) where the process flow 910 is divided into component tasks. The "ephemeral" requirement is mapped to Wu’s logic for updating the knowledge base as new knowledge is gained, replacing or modifying existing data);
a knowledge entry module that comprises at least one interface for receiving raw information associated with one or more entities or one or more processes, wherein the raw information is received from a plurality of information sources, the raw information comprises at least one of a predefined set of commands, one or more keywords, one or more phrases, one or more sentences, one or more drawings, and one or more documents, and the at least one interface is selected from a plurality of interfaces including a text based interface, a graphical interface, and a communication network based interface (Wu Figs. 1-16; [0020], domain processes, facilities, equipment, sensors/sensor parameters, personnel hierarchies, supply chains, raw materials, intermediate products, final products, key performance measures, customers, power consumptions, emissions, and regulation compliances. Data representing some or all of these entities and their relationships may be used to build a customized knowledge base for the plant; Unstructured data sources may include, for example, freeform documents, operation manuals, and notes; [0026], The computers 101 of the customized graph knowledge base 100 may communicate with data sources 140 via the communication interface 102 and the communication network 111; [0027], The storage 109 may be used to store various initial, intermediate, or final data or model for building, updating, and operating the customized graph knowledge base 100. The graph database 130 may store the multi-dimensional nodes and edges representing entities and relationships for the specific industrial operation. The term entities with respect to the graph database may be alternatively referred to as data entities. The data sources 140 may contain baseline, domain-specific, and implementation specific industrial data items. The storage 109, the graph database 130, and the data sources 140 may be centralized or distributed; [0029], the logic flow includes data element extraction 210 for processing data from the data sources 140 and further includes establishing the customized industrial graph knowledge base 230; data sources 140 may include baseline data sources 202 embedded with baseline industrial data elements, domain-specific data sources 204 containing domain-specific industrial data elements, and implementation-specific data sources 206 containing implementation-specific data elements pertaining to the specific plant; he baseline industrial data elements may include data elements related to knowledge common to various types of industrial settings. The domain-specific data elements, on the other hand, may include data elements related to knowledge common to all industrial operations implementing the specific industrial setting; [0036], FIG. 4 illustrates an example implementation of the process 212 of FIG. 2 for extracting baseline and domain-specific data items from the baseline data sources 202 and the domain-specific data sources 204; an input document may be processed using text mining 412 and/or text extraction 414 techniques to identify texts in the input document. The identified texts may be further analyzed using various semantic recognition techniques 416. Word features in the text, may be, for example, extracted using word embedding techniques 418 for extracting baseline and domain-specific data elements from the text at 420; 0037], Unstructured implementation-specific data sources, for example, may be maintained in the forms of documents (e.g., operation manuals and other notes), videos, and image; [0038], natural language processing 534 for analyzing unstructured data sources; thus, Wu utilizes communication interfaces 102 and data sources 140. It employs text mining 412, text extraction 414, and semantic recognition 416 to identify word features and extract domain-specific elements);
an information base for storing the raw information associated with one or more entities or one or more processes, wherein the information base is managed by an information base engine; a semantic engine configured to process the received raw information to generate a first set of structured data associated with one or more entities and a second set of structured data associated one or more processes; a knowledge base engine configured to provide an interface to the industrial knowledge repository; and process the first set of structured data and the second set of structured data to update the one or more structure graphs and the one or more flow graphs in the industrial knowledge base repository (Wu Figs. 1-16; [0026], The computers 101 of the customized graph knowledge base 100 may communicate with data sources 140 via the communication interface 102 and the communication network 111; [0029], the logic flow includes data element extraction 210 for processing data from the data sources 140 and further includes establishing the customized industrial graph knowledge base 230; data sources 140 may include baseline data sources 202 embedded with baseline industrial data elements, domain-specific data sources 204 containing domain-specific industrial data elements, and implementation-specific data sources 206 containing implementation-specific data elements pertaining to the specific plant; he baseline industrial data elements may include data elements related to knowledge common to various types of industrial settings. The domain-specific data elements, on the other hand, may include data elements related to knowledge common to all industrial operations implementing the specific industrial setting; [0031], Data elements extracted from the baseline, domain-specific, and implementation specific may be used to build the customized industrial graph knowledge base 230 for providing data services. As shown by the example implementation of FIG. 2, the customized industrial graph knowledge base may include a graph database 232; [0035], entities 324 and 326 may be determined as general products of entity 322. Likewise, entity 328 may be determined as a domain process of entity 322 and entity 329 may be determined as a general product of entity 322 as well as a direct product of the entity 328. Entities 332 (“equipment A01-01”), 334 (“equipment A01-02”), 336 (“John”), 338 (“equipment A02-01”), and their relationships may pertain to specific implementation of the particular petroleum refining plant and may be extracted from implementation-specific data sources collected by the petroleum refining plant. For example, entities 332, 334, and 338 may represent specific pieces of connected equipment in the specific petroleum refining plant for styrene production. Their relationships may be represented by “equipment connect”. Entity 336, however, may represent a particular operator of equipment entities 332 and 334. The relationships between entities may be directional, as shown by the arrows in FIG. 3. The relationships across baseline, domain-specific, and implementation-specific entities, such as relationships 340 and 350, may be determined from any of the baseline, domain-specific, and implementation-specific data sources; [0036], FIG. 4 illustrates an example implementation of the process 212 of FIG. 2 for extracting baseline and domain-specific data items from the baseline data sources 202 and the domain-specific data sources 204; an input document may be processed using text mining 412 and/or text extraction 414 techniques to identify texts in the input document. The identified texts may be further analyzed using various semantic recognition techniques 416. Word features in the text, may be, for example, extracted using word embedding techniques 418 for extracting baseline and domain-specific data elements from the text at 420; [0038], natural language processing 534 for analyzing unstructured data sources; [0064-0065], The customized industrial graph knowledge base may be updated as new knowledge is gained. For example, FIG. 15 illustrates a logic flow for updating the knowledge base when knowledge 1510 external to the current industrial knowledge base is introduced; The external new knowledge may be introduced from supplemental information via updates in any of the baseline, domain-specific, and implementation-specific data sources; new nodes may further be added to the graph database with appropriate categories and the new relationships may be added to the graph database with appropriate inter-category and intra-category designation; [0045], FIG. 8 illustrates an example data template 800 for data elements belonging to the equipment category for the specific petroleum refinery plant; [0046], FIG. 9 illustrates an example domain process diagram 902 for the petroleum plant and an excerpt of an example domain process data template 930 for data elements belonging to the industrial domain process category; [0053], FIG. 13 shows a set of extracted types of inter-category relationships. In particularly, 1310 of FIG. 13 illustrates types of relationships between one of the categories (KPI) and all other categories; see also [0020], [0027]);
a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing based on information stored in the industrial knowledge repository (Wu Figs. 1-16; [0002], A graph database is a foundational component for a graph knowledge base. The graph knowledge base includes the graph database, a processing platform and interface to issue queries and analyze query results, and procedures to build, expand, and update the graph database; [0022], a more structured form for achieving better data processing and querying efficiency; [0026], The operators and controllers of the industrial plant may access the customized graph knowledge base 100 via the communication network 111 for submitting queries and obtaining queried and analyzed data; [0051], queries into the graph database may be conducted conveniently within any of the predefined categories):
Wu fails to expressly disclose a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing training materials associated with the one or more entities and the one or more processes based on information stored in the industrial knowledge repository; designing a new product based on information associated with the one or more entities and the one or more processes; and building a simulation tool based on the structured data associated with the one or more products and the one or more processes.
However, Martelaro teaches a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing training materials associated with the one or more entities and the one or more processes based on information stored in the industrial knowledge repository; designing a new product based on information associated with the one or more entities and the one or more processes; and building a simulation tool based on the structured data associated with the one or more products and the one or more processes (Martelaro Figs. 1-4; [0016], A user can provide a natural-language query to a component recommendation engine, where the query includes terms defining at least one desired function of a component or multiple components, e.g., one or more actions performed by the component. Additional contextual information for the design problem can be determined by the recommendation engine, providing constraints and/or further specifying the desired functions of the desired component(s); [0017], The additional contextual information can be generated through an intelligent dialog process and/or interactive process between the recommendation engine and the user; [0018], The knowledge graph can include a known set of parts with connections to functions, use cases, and industries. For example, a known set of accelerometers can be linked in the knowledge graph to 1) functions such as motion detection, impact detection, motion tracking, and orientation detection, 2) use cases such as robotics, mobile phones, and flight controllers, and 3) industrial sectors such as automotive, military, and consumer electronics; [0020], Any known parts used in the product's design (extracted from the documentation) can be associated with the descriptions given in the text about the function of a product, the use-case, and the industry (also extracted from a relevant document). A further method of populating the knowledge graph is through part manufacturers explicitly adding relevant information when they upload their part to the database; [0053], As depicted in FIG. 2, design recommendation interface 130 includes a query entry bar 202, intelligent component design assistant window 204, a requirements list window 206, and a recommended design options window 208; [0084], As illustrated in FIG. 5B, the access mechanisms 425 provided by the edge-facing component 400 includes one or more APIs 428 which serve as direct access mechanisms to information stored in the contextual knowledge repository 420. The one or more direct access APIs 428 may be implemented in accordance with, for example, the REST (REpresentational State Transfer) architecture, GraphQL or other suitable query language).
Because Wu and Martelaro address the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing training materials associated with the one or more entities and the one or more processes based on information stored in the industrial knowledge repository; designing a new product based on information associated with the one or more entities and the one or more processes; and building a simulation tool based on the structured data associated with the one or more products and the one or more processes as suggested in Martelaro into Wu. Doing so would be desirable because as new parts and components become available, there are limited channels for designers to become aware of them and, particularly, know how to use them. The burden for designers is sufficiently large such that a search process is typically limited to searching for specific parts based on specifications to meet a function that has already been determined by a human user. Designers becoming aware of new parts with new functionality is achieved mostly in an ad hoc way, e.g., through experience in a field that uses such new parts (see Martelaro [0002]). Implementations of the present disclosure are generally directed towards capturing the context of a design problem posed by the user. Implementations can elicit context from a user via an interactive user interface to provide better recommendations (in terms of satisfying a need expressed by a user) than are provided by current systems (see Martelaro [0002]). Allowing designers to search for unknown component based on function can reduce the burden of discovery for as-of-yet unknown components to the designer and can result in better part selection. By creating a searchable recommendation repository that is updated with new components, component function, and applications, the component recommendation engine can save time and effort required to learn new markets and parts, and create better solutions based on a more robust product database (see Martelaro [0009]).
Regarding claims 26 and 32, claims 26 and 32 contain substantially similar limitations to those found in claim 20, except for maintaining, via an interface provided by a knowledge base engine (Wu Figs. 1-16; [0026] The computers 101 of the customized graph knowledge base 100 may communicate with data sources 140 via the communication interface 102 and the communication network 111. The computers 101 of the customized graph knowledge base 100 may communicate with the specific industrial operation, or industrial plant 150 via the communication interfaces 102 and the communication network 111. The data sources 140 may further communicate with the industrial plant 150 either directly or via the communication network 111. For example, the data sources 140 may obtain updates of implementation-specific data elements from the industrial plant 150, as shown by arrows 152 and alternatively 154). Claim 32 additionally recites wherein each of the second plurality of edges connect two nodes of the second plurality of nodes and stores information associated with transition between tasks that the two nodes correspond to (Wu Figs. 1-16; [0046], FIG. 9 illustrates an example domain process diagram 902 for the petroleum plant and an excerpt of an example domain process data template 930 for data elements belonging to the industrial domain process category. The entire process flow of the petroleum plant is shown by 910. The process flow 910 may be divided into various component processes or sections. For example, component process 920 (enclosed by the dashed box) may be related to a particular processing section of the refinery plant. The connectivity between various equipment involved in component process 920 may be extracted, as shown by 922. The arrows in 910, 920, and 922 may represent the direction of material flow. The example domain process data template 930 may include pairs of source and destination equipment 934 and 940, and their relationships 950. Each equipment may be identified by a unique ID as shown in 932 and 942. In one implementation, the IDs for the equipment may be constructed to identify the component process in which the equipment is used. For example, the first portion of the equipment IDs 932 and 942 contains “E010”, indicating that these pieces of equipment all belong to the component process 920; [0064], The customized industrial graph knowledge base may be updated as new knowledge is gained. For example, FIG. 15 illustrates a logic flow for updating the knowledge base when knowledge 1510 external to the current industrial knowledge base is introduced. The external new knowledge may be introduced from supplemental information via updates in any of the baseline, domain-specific, and implementation-specific data sources. For example, new equipment may be purchased and installed, existing equipment may be upgraded, operation manuals may be updated, and new facilities may be built). Consequently, claims 26 and 32 are rejected for the same reasons.
Regarding claim 29, Wu in view of Martelaro teaches all the limitations of claim 26, further comprising:
providing a subscription/publication based real-time message routing platform for routing data and commands between the knowledge entry (interpreted as providing a subscription/publication based real-time message routing platform for routing data and commands per the 35 U.S.C. 112(b) rejection above) (Wu Figs. 1-16; [0020], domain processes, facilities, equipment, sensors/sensor parameters, personnel hierarchies, supply chains, raw materials, intermediate products, final products, key performance measures, customers, power consumptions, emissions, and regulation compliances. Data representing some or all of these entities and their relationships may be used to build a customized knowledge base for the plant; Unstructured data sources may include, for example, freeform documents, operation manuals, and notes; [0025], The communication interfaces 102 may include wireless transmitters and receivers (“transceivers”) 112 and any antennas 114 used by the transmitting and receiving circuitry of the transceivers 112. The transceivers 112 and antennas 114 may support Wi-Fi network communications, for instance, under any version of IEEE 802.11, e.g., 802.11n or 802.11ac. The communication interfaces 102 may also include wireline transceivers 116. The wireline transceivers 116 may provide physical layer interfaces for any of a wide range of communication protocols, such as any type of Ethernet, data over cable service interface specification (DOCSIS), digital subscriber line (DSL), Synchronous Optical Network (SONET), or other protocol; [0026], The computers 101 of the customized graph knowledge base 100 may communicate with data sources 140 via the communication interface 102 and the communication network 111. The computers 101 of the customized graph knowledge base 100 may communicate with the specific industrial operation, or industrial plant 150 via the communication interfaces 102 and the communication network 111; [0027], The storage 109 may be used to store various initial, intermediate, or final data or model for building, updating, and operating the customized graph knowledge base 100; [0033], The platform and application interface 234 built on top of the graph database 232 may be used for external applications 240 for accessing the graph database 232 and the intermediate data repositories 220, for processing queries and data service requests, for performing analytics on query results, and for providing other data services. Examples of services and applications that may be obtained from the customized industrial graph knowledge base 230 may include searching 242, equipment profiling 244, real-time prediction of performance of the plant 246, and other intelligent analytics 248; [0037], Unstructured implementation-specific data sources, for example, may be maintained in the forms of documents (e.g., operation manuals and other notes), videos, and image; see also [0028-0029], [0036-0038])
Regarding claims 23 and 35, claims 23 and 35 contain substantially similar limitations to those found in claim 29. Consequently, claims 23 and 35 are rejected for the same reasons.
Regarding claim 24, Wu in view of Martelaro teaches all the limitations of claim 20, further comprising:
wherein the plurality of information sources include at least one of user inputs, brochures, manuals, research publications, design documents, requirement documents, trouble reports, diagnosis logs, meeting minutes, customer reviews, Web articles, encyclopedia, dictionaries, books, catalogs, publication of rules and regulations, and legal documents, and third-party knowledge bases (Wu Figs. 1-16; [0020], domain processes, facilities, equipment, sensors/sensor parameters, personnel hierarchies, supply chains, raw materials, intermediate products, final products, key performance measures, customers, power consumptions, emissions, and regulation compliances. Data representing some or all of these entities and their relationships may be used to build a customized knowledge base for the plant; Unstructured data sources may include, for example, freeform documents, operation manuals, and notes; [0027], The storage 109 may be used to store various initial, intermediate, or final data or model for building, updating, and operating the customized graph knowledge base 100; [0037], Unstructured implementation-specific data sources, for example, may be maintained in the forms of documents (e.g., operation manuals and other notes), videos, and image; see also [0028-0029], [0036-0038])
Regarding claims 30 and 36, claims 30 and 36 contain substantially similar limitations to those found in claim 24. Consequently, claims 30 and 36 are rejected for the same reasons.
Regarding claim 25, Wu in view of Martelaro teaches all the limitations of claim 20, further comprising:
wherein the system communicates with a user collaboration platform to support knowledge entry, knowledge query and knowledge presentation (Wu Figs. 1-16; [0002], A graph database is a foundational component for a graph knowledge base. The graph knowledge base includes the graph database, a processing platform and interface to issue queries and analyze query results, and procedures to build, expand, and update the graph database; [0022], a more structured form for achieving better data processing and querying efficiency; [0024], display circuitry 108 that generates machine interfaces 110 locally or for remote display, e.g., in a web browser running on a local or remote machine. The machine interfaces 110 and the I/O interfaces 106 may include GUIs; [0026], The operators and controllers of the industrial plant may access the customized graph knowledge base 100 via the communication network 111 for submitting queries and obtaining queried and analyzed data; [0043], The graph model repository 720 may store a graphic representation of the entities and relationships contained in the graph database. For example, the graphic representation stored in the graph model repository 720 may be in the form of Scalable Vector Graphics (SVG). The SVG model may be XML-based and may support interactivity and animation. The SVG model may be directly supported by and viewed on a web browser; Users may create or modify the labels of entities, redefine the information of entities in the taxonomy repository via a taxonomy management tool/software and interface; [0048], each of the KPI indicator may either be calculated based on parameters 1060 or estimated by domain experts, as indicated by the column 1080 of the data template; [0051], queries into the graph database may be conducted conveniently within any of the predefined categories).
Regarding claims 31 and 37, claims 31 and 37 contain substantially similar limitations to those found in claim 25. Consequently, claims 31 and 37 are rejected for the same reasons.
Claims 21, 27, and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Martelaro, as applied in the rejections of claims 20, 26, and 32 above, and further in view of Nixon et al. (hereinafter Nixon), US 20210089526 A1 published 03/25/2021.
Regarding claim 21, Wu in view of Martelaro teaches all the limitations of claim 20, further comprising:
wherein the knowledge base management system further comprises: an access control module that provides access control to the industrial knowledge repository and the knowledge management system (Wu Figs. 1-16; [0002], A graph database is a foundational component for a graph knowledge base. The graph knowledge base includes the graph database, a processing platform and interface to issue queries and analyze query results, and procedures to build, expand, and update the graph database; [0026], The operators and controllers of the industrial plant may access the customized graph knowledge base 100 via the communication network 111 for submitting queries and obtaining queried and analyzed data; [0033], The platform and application interface 234 built on top of the graph database 232 may be used for external applications 240 for accessing the graph database 232 [0043], The graph model repository 720 may store a graphic representation of the entities and relationships contained in the graph database. For example, the graphic representation stored in the graph model repository 720 may be in the form of Scalable Vector Graphics (SVG). The SVG model may be XML-based and may support interactivity and animation. The SVG model may be directly supported by and viewed on a web browser)
However, Wu in view of Martelaro fails to expressly disclose security control. In the same field of endeavor, Nixon teaches:
security control (Nixon Fig. 1-59; [0016], Securing process plants and process control systems against cyber intrusions and malicious cyber attacks typically utilizes a layered or leveled security hierarchy, with at least some of the layers or levels secured by using firewalls and other security mechanisms; [0017], the novel systems, components, apparatuses, methods, and techniques described herein address these and other security issues related to process plants and their networks, and in particular are directed to the secure delivery of process plant-related data to one or more external systems that are consumers of the process plant-related data; [0018], To illustrate, FIG. 1 is a block diagram of an example edge gateway system 1 which securely delivers process plant-related data (e.g., field data) from a process plant 5 to one or more external, data-consuming applications and/or systems, which may include enterprise applications and/or systems (e.g., at IT levels of security, such as security levels 3-5), and/or third-party applications and/or systems; [0022], Generally speaking, the edge gateway system 1 securely connects and/or bridges the process plant 5 and associated systems at lower-numbered security levels with one or more data-consuming systems 8 at higher-numbered security levels; [0027], the contextual knowledge repository 48 stores both process plant-related or field content data (e.g., run-time data, event data, historical data, and/or other types of data provided by the process plant 5, as well as contextual information that is indicative of relationships between provided process plant-related/field content data, conditions corresponding to the generation, delivery, and/or reception of the process plant-related/field content data within the process plant 5, and/or other types of contexts of the process plant-related/field content data. Knowledge (e.g., content data and associated contextual information, and optionally other data) that is stored in the contextual knowledge repository 48 is exposable (e.g., is made available) to the one or more external, data-consuming systems 8; [0028], preventing external systems from unauthorized access of the contextual knowledge repository 48; [0029], the features, components, and architecture of the edge gateway system 1 provide almost unlimited access of external, data-consuming systems 8 to process plant-related data in a highly secure manner and without impacting the performance of the process plant 5; [0088], the services 435 may include other types of services such as authentication and/or authorization services to authenticate and/or data-consuming applications and/or systems 422).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated security control as suggested in Nixon into Wu in view of Martelaro. Doing so would be desirable because the interconnection of process plants and/or process control systems to enterprise and/or external networks and systems increases the risk of cyber intrusions and/or malicious cyber attacks that may arise from expected vulnerabilities in commercial systems and applications, such as those used in enterprise and/or external networks. Cyber intrusions and malicious cyber attacks of process plants, networks, and/or control systems may negatively affect the confidentiality, integrity, and/or availability of information assets, which, generally speaking, are vulnerabilities similar to those of general purpose computing networks. However, unlike general purpose computer networks, cyber intrusions of process plants, networks, and/or control systems may also lead to damage, destruction, and/or loss of not only plant equipment, product, and other physical assets, but also to the loss of human life. For example, a cyber intrusion may cause a process to become uncontrolled, and thereby produce explosions, fires, floods, exposure to hazardous materials, etc. Thus, securing communications related to process control plants and systems is of paramount importance (see Nixon [0007]). As more and more services and applications that operate on process plant data are moved to execute remotely, e.g., on networks and systems outside of or external to the process plant (e.g., at security levels 4 and/or 5 within the enterprise or business with which the process plant is associated, owned, and/or operated), and/or even on networks and systems that are external to the enterprise or business (e.g., above security level 5, via the Internet or other public network), stronger techniques for preventing process plant systems, networks, and devices from being compromised are needed (see Nixon [0016]). The features, components, and architecture of the edge gateway system 1 provide almost unlimited access of external, data-consuming systems 8 to process plant-related data in a highly secure manner and without impacting the performance (see Nixon [0029]).
Regarding claims 27 and 33, claims 27 and 33 contain substantially similar limitations to those found in claim 21. Consequently, claims 27 and 33 are rejected for the same reasons.
Claims 22, 28, and 34 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Martelaro in further view of Nixon in further view of B R et al. (hereinafter B R), US 20220366103 A1 published 11/17/2022.
Regarding claim 22, Wu in view of Martelaro and Nixon teaches all the limitations of claim 21, further comprising:
further comprising a simulation tool comprising a user interface, the simulation tool configured to retrieve a third set of structured data associated with a product or a process from the industrial knowledge repository; display the third set of structured data on the user interface; receive a request from a user to modify the third set of structured data; modify the third set of structured data; retrieve a set of data from the information base (Wu Figs. 1-16; [0002], A graph database is a foundational component for a graph knowledge base. The graph knowledge base includes the graph database, a processing platform and interface to issue queries and analyze query results, and procedures to build, expand, and update the graph database; [0024], display circuitry 108 that generates machine interfaces 110 locally or for remote display, e.g., in a web browser running on a local or remote machine. The machine interfaces 110 and the I/O interfaces 106 may include GUIs, touch sensitive displays, voice or facial recognition inputs, buttons, switches, speakers and other user interface elements; [0026], The operators and controllers of the industrial plant may access the customized graph knowledge base 100 via the communication network 111 for submitting queries and obtaining queried and analyzed data; [0033], The platform and application interface 234 built on top of the graph database 232 may be used for external applications 240 for accessing the graph database 232; [0043], The graph model repository 720 may store a graphic representation of the entities and relationships contained in the graph database. For example, the graphic representation stored in the graph model repository 720 may be in the form of Scalable Vector Graphics (SVG). The SVG model may be XML-based and may support interactivity and animation. The SVG model may be directly supported by and viewed on a web browser; Users may create or modify the labels of entities, redefine the information of entities in the taxonomy repository via a taxonomy management tool/software and interface; [0064-0065], The customized industrial graph knowledge base may be updated as new knowledge is gained)
However, Wu in view of Martelaro and Nixon, fails to expressly disclose further comprising a simulation tool comprising a user interface, the simulation tool configured to retrieve a third set of structured data associated with a product or a process from the industrial knowledge repository; construct a digital model of the entity or the process based on the modified third set of structured data; retrieve a set of data from the information base; activate a simulation of the entity or the process using the set of data retrieved from the information base and the constructed digital model of the entity or the process to produce outputs; present the outputs on the user interface; retrieving a set of data from the information base; activating a simulation of the entity or the process using the set of data retrieved from the information base and the digital model of the entity or the process and producing outputs; present the outputs on the user interface.
In the same field of endeavor, B R teaches:
further comprising a simulation tool comprising a user interface, the simulation tool configured to retrieve a third set of structured data associated with a product or a process from the industrial knowledge repository; construct a digital model of the entity or the process based on the modified third set of structured data; retrieve a set of data from the information base; activate a simulation of the entity or the process using the set of data retrieved from the information base and the constructed digital model of the entity or the process to produce outputs; present the outputs on the user interface; retrieving a set of data from the information base; activating a simulation of the entity or the process using the set of data retrieved from the information base and the digital model of the entity or the process and producing outputs; present the outputs on the user interface (B R Fig. 1-7; [0043], a user of the electronic device 107.1 may send a request to the server 101 to generate a design of a product (e.g., a car, a bottle, a rotary blade of a turbine and so on) via a graphical user interface provided to the user. The server 101 may prompt the user to provide various parameters of the product on the graphical user interface. Accordingly, the user may input the parameters of the product which can include design requirements, and the parameters which can include environmental sustainability indicators related to the product, via the graphical user interface. The electronic device 107.1 sends the parameters of the product to the server 101 via the network 105. Accordingly, the processor in the server 101 obtains a model of the product, for example from the product environmental database. The model can be a computer-aided design model, a geometrical shape, a pre-determined shape, an engineering model and the like. Further, the processor performs simulation of the model of the product with respect to the environmental sustainability of the product. The simulation can be performed with the obtained one or more parameters and the information received from the one or more knowledge sources which include but not limited to knowledge graphs, historical data, unstructured data, domain knowledge related to designs and the like; [0044], Additionally, the processor outputs the generated design on the display unit of the electronic device 107.1. For example, the graphical user interface on the electronic device 107.1 may display the generated design along with the computed values of performance, reliability, cost functionality and environmental sustainability index of the design).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated further comprising a simulation tool comprising a user interface, the simulation tool configured to retrieve a third set of structured data associated with a product or a process from the industrial knowledge repository; construct a digital model of the entity or the process based on the modified third set of structured data; retrieve a set of data from the information base; activate a simulation of the entity or the process using the set of data retrieved from the information base and the constructed digital model of the entity or the process to produce outputs; present the outputs on the user interface; retrieving a set of data from the information base; activating a simulation of the entity or the process using the set of data retrieved from the information base and the digital model of the entity or the process and producing outputs; present the outputs on the user interface as suggested in B R into Wu in view of Martelaro and Nixon. Doing so would be desirable because the following relates to computer-aided design and analysis and more particularly relates to a method and system for generating a design of a product (see B R [0002]). In general, various environmental impacts such as energy, water, climate change, human health and ecological toxicity, and other unknown emerging environmental risks are major challenges. With an intention to address these challenges, various environmental and sustainable policies have been applied and/or considered by many companies to ensure that environmental impact from their products are controlled (see B R [0003]). An environmental sustainability measurement of the product can be used to indicate the environmental impacts of the product. However, in existing systems, environmental sustainability is typically evaluated after the product is towards the end of its life cycle. For example, various mechanisms are available for handling wastes produced by a product after usage of the product. Further, conventionally, the product is manufactured and then the environmental assessment is performed, e.g., when required for some approvals. Thus, the product may be launched without a proper understanding of its environmental impact (see B R [0004]). In light of above, there is a need for generating design(s) of a product by having environmental sustainability considerations (see B R [0006]). The proposed method and system provides suggestions such as efficient ways of disassembly of components, alternative materials to be used for designs, surface painting alternatives and alternatives for material sourcing, region for manufacturing, alternative processes for manufacturing and transportation and sources of energy and so on (see B R [0013]).
Regarding claims 28 and 34, claims 28 and 34 contain substantially similar limitations to those found in claim 22, except for retrieving, via a user interface provided by a simulation tool (Wu Figs. 1-16; [0024], display circuitry 108 that generates machine interfaces 110 locally or for remote display, e.g., in a web browser running on a local or remote machine. The machine interfaces 110 and the I/O interfaces 106 may include GUIs, touch sensitive displays, voice or facial recognition inputs, buttons, switches, speakers and other user interface elements; [0026], The operators and controllers of the industrial plant may access the customized graph knowledge base 100 via the communication network 111 for submitting queries and obtaining queried and analyzed data; [0043], The graph model repository 720 may store a graphic representation of the entities and relationships contained in the graph database. For example, the graphic representation stored in the graph model repository 720 may be in the form of Scalable Vector Graphics (SVG). The SVG model may be XML-based and may support interactivity and animation. The SVG model may be directly supported by and viewed on a web browser; Users may create or modify the labels of entities, redefine the information of entities in the taxonomy repository via a taxonomy management tool/software and interface; [0064-0065], The customized industrial graph knowledge base may be updated as new knowledge is gained; see also [0002], [0033]). Consequently, claims 28 and 34 are rejected for the same reasons.
Response to Arguments
The Examiner acknowledges the cancellation of claims 1-19 and the addition of claims 20-37. The rejections of claims 1-19 are hereby withdrawn.
Regarding independent claims 20-37, the Applicant alleges that Wu in view of Martelaro as described in the previous Office action, does not explicitly teach novel aspects of the instant application's "knowledge base management system" (see remarks p. 16). Examiner respectfully disagrees.
As discussed above, Wu is considered to teach an industrial knowledge repository that comprises one or more structure graphs and one or more flow graphs (Wu Figs. 1-16; [0019], [0020], [0022], [0040], [0045], [0046], [0053]), wherein each of the one or more structure graphs corresponds to an entity and comprises: a first plurality of nodes, wherein each of the first plurality of nodes corresponds to a component of the entity and contains attributes of the component, and wherein each of the attributes is represented using a combination of text, a structure graph, and a flow graph, and a first plurality of edges connecting the first plurality of nodes, wherein each of the first plurality of edges connects two of the first plurality of nodes and represents one or more relationships between the components that the two of first plurality of nodes correspond to, and wherein each of the one or more relationships is represented using text and a structure graph (Wu Figs. 1-16; [0034], [0035], [0045], [0046]); wherein each of the one or more flow graphs corresponds to a process and comprises a second plurality of nodes, wherein each of the second plurality of nodes corresponds to a task in the process and stores information associated with execution of the task, wherein a portion of the information is ephemeral; a second plurality of edges connecting the second plurality of nodes, wherein each of the second plurality of edges stores information associated with transition between tasks, wherein the information is represented using a combination of text, structure graph, and a flow graph (Wu Figs. 1-16; [0046], [0064]); a knowledge entry module that comprises at least one interface for receiving raw information associated with one or more entities or one or more processes, wherein the raw information is received from a plurality of information sources, the raw information comprises at least one of a predefined set of commands, one or more keywords, one or more phrases, one or more sentences, one or more drawings, and one or more documents, and the at least one interface is selected from a plurality of interfaces including a text based interface, a graphical interface, and a communication network based interface (Wu Figs. 1-16; [0020], [0026-0027], [0029], [0036-0038]); an information base for storing the raw information associated with one or more entities or one or more processes, wherein the information base is managed by an information base engine; a semantic engine configured to process the received raw information to generate a first set of structured data associated with one or more entities and a second set of structured data associated one or more processes; a knowledge base engine configured to provide an interface to the industrial knowledge repository; and process the first set of structured data and the second set of structured data to update the one or more structure graphs and the one or more flow graphs in the industrial knowledge base repository; (Wu Figs. 1-16; [0026], [0029], [0031], [0035], [0036], [0038], [0064-0065], [0045-0046], [0053], see also [0020], [0027]); a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing based on information stored in the industrial knowledge repository; designing a new product based on information associated with the one or more entities and the one or more processes; and building a simulation tool based on the structured data associated with the one or more products and the one or more processes (Wu Figs. 1-16; [0002], [0022], [0026], [0051]). Martelaro cited to clarify a query engine that in response to receiving an information request structured according to a query language, queries the industrial knowledge repository and returns a response, wherein the information request is associated with at least one of a plurality of tasks including: producing training materials associated with the one or more entities and the one or more processes based on information stored in the industrial knowledge repository; designing a new product based on information associated with the one or more entities and the one or more processes; and building a simulation tool based on the structured data associated with the one or more products and the one or more processes (Martelaro Figs. 1-4; [0016-0020], [0053], [0084]). Thus, Wu in view of Martelaro are considered to teach the independent claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Reinhart (US 20200264589 A1) see Figs. 1-7 and [0020-0031].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KUANG FU CHEN whose telephone number is (571)272-1393. The examiner can normally be reached M-F 9:00-5:30pm ET.
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/KC CHEN/Primary Patent Examiner, Art Unit 2143