CN111831797B - Management and recommendation system for manufacturing industry processing equipment model - Google Patents
Management and recommendation system for manufacturing industry processing equipment model Download PDFInfo
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- CN111831797B CN111831797B CN201910319794.0A CN201910319794A CN111831797B CN 111831797 B CN111831797 B CN 111831797B CN 201910319794 A CN201910319794 A CN 201910319794A CN 111831797 B CN111831797 B CN 111831797B
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- 238000012545 processing Methods 0.000 title claims abstract description 35
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 31
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000000034 method Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 4
- 230000008520 organization Effects 0.000 claims 1
- 230000000007 visual effect Effects 0.000 abstract description 4
- 238000003754 machining Methods 0.000 abstract 2
- 239000003638 chemical reducing agent Substances 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 239000006185 dispersion Substances 0.000 description 2
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- 238000013473 artificial intelligence Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3344—Query execution using natural language analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/338—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
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Abstract
The invention relates to a management and recommendation system for manufacturing process equipment models, comprising: the knowledge management module and the knowledge retrieval module. According to regional or functional characteristics of networked cooperative machining, creating nodes of a machining equipment model; acquiring information of a user for using or designing the node, and identifying the node; analyzing the contact attribute among the nodes, and editing and storing; acquiring query information of a user for the processing equipment model; knowledge information corresponding to the query information is fed back to the user. The invention has visual and simple management mode and high management efficiency, and can effectively promote the progress of the networked manufacturing mode.
Description
Technical Field
The invention relates to the technical field of intelligent manufacturing, in particular to a management and recommendation system for manufacturing equipment models.
Background
Manufacturing modes always progress with the level of production and market development. Early manual workshops were inefficient and difficult to accomplish in large quantities. From the 19 th to the 20 th century, mass production modes are dominant in the manufacturing industry under the support of mechanical technology and electrification technology, so that the productivity is greatly improved, and the product cost is reduced. In the 21 st century, as computer technology and artificial intelligence technology advanced, more and more countries put forward concepts and strategies for intelligent manufacturing.
In a new generation of manufacturing modes, the informatization and intelligence degree of equipment is continuously improved, so that the networked cooperative processing equipment has the characteristics of regional dispersion, functional isomerism, management autonomy and knowledge evolution.
The inventor finds that in the prior networked manufacturing mode, the management of the equipment model processed by the manufacturing industry mainly depends on a form, but with the continuous development and upgrading of processing equipment, the attribute of the cooperative processing equipment is not limited to basic processing parameter information any more, and the number of the equipment attribute is increased, so that the traditional form model is difficult to meet the management requirements of inquiry, modification and the like, and therefore, an intuitive, simple and convenient management and recommendation system of the cooperative processing equipment model is required to be provided to promote the development of networked cooperative processing.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a system for managing and recommending a manufacturing process equipment model, which has a visual and simple management manner and high management efficiency, and can effectively promote the progress of a networked manufacturing mode.
A system for managing and recommending manufacturing process equipment models, comprising: a knowledge management module and a knowledge retrieval module;
The knowledge management module is used for creating nodes of the processing equipment model according to regional or functional characteristics of networked cooperative processing; acquiring information of a user for using or designing the node, and identifying the node; analyzing the contact attribute among the nodes, and editing and storing;
The knowledge retrieval module is used for acquiring query information of a user for the processing equipment model and feeding back knowledge information corresponding to the query information to the user.
The knowledge management module replaces the nodes of the traditional tabular form creating the processing equipment model with the nodes of the graphic database creating the processing equipment model.
The knowledge management module identifies the node as a system, subsystem, mechanism, part or element according to the regional or functional characteristics of the node.
The knowledge management module performs WHAT/HOW/WHY analysis on the connection between the nodes, represents product classification types, product production modes and product quality parameters, and stores analysis information in a map.
The system is also for presenting the map to a user.
The query information of the user for the processing equipment model is specifically a query problem for the processing equipment model.
The knowledge retrieval module acquires the query problem of a user aiming at the processing equipment model, and acquires the node and attribute information thereof corresponding to the query problem with the highest matching rate based on semantic analysis and classifier training algorithm.
The knowledge retrieval module is used for matching the query problem with the WHAT/HOW/WHY contact attribute between the nodes.
The management and recommendation system for the manufacturing equipment model is visual and simple in management mode, high in management efficiency and capable of effectively promoting progress of a networked manufacturing mode.
Drawings
FIG. 1 is a schematic diagram of a map structure in a preferred embodiment of the present invention;
FIG. 2 is a schematic diagram of an application scenario of the present invention;
FIG. 3 is a schematic diagram of an application scenario for query and feedback in accordance with the present invention;
FIG. 4 is a schematic diagram of an interface for query and recommendation by the system knowledge retrieval module of the present invention.
Detailed Description
The invention provides a management and recommendation system for manufacturing process equipment models, comprising: a knowledge management module and a knowledge retrieval module;
The knowledge management module is used for creating nodes of the processing equipment model according to regional or functional characteristics of networked cooperative processing; acquiring information of a user for using or designing the node, and identifying the node; analyzing the contact attribute among the nodes, and editing and storing;
The knowledge retrieval module is used for acquiring query information of a user for the processing equipment model and feeding back knowledge information corresponding to the query information to the user.
Referring to fig. 1, the knowledge management module replaces the nodes that create the process equipment model in the form of a traditional table with nodes that create the process equipment model using a graphical database. Aiming at the characteristics of regional dispersion, functional isomerism, management autonomy, knowledge evolution and the like of networked cooperation of manufacturing processing equipment, the embodiment takes the enterprise as a whole as networked cooperation processing equipment resource, all processing equipment of the enterprise belongs to the enterprise to divide the system by processing product types, each system belongs to respective matched processing equipment, each processing equipment belongs to each matched part, each part belongs to each matched part, and SDN (SPRING DATA Neo4 j) provided by Neo4j is mainly used for creating nodes.
Specifically, as shown in fig. 1, the knowledge management module identifies the node, specifically:
the nodes are identified as systems, subsystems, mechanisms, parts or elements according to their geographical or functional characteristics.
In a specific application scenario, as shown in fig. 2, the "intelligent board sorting system" is identified as a system, and the "power system" and the "transmission system" subordinate to the system are identified as sub-systems; further, "harmonic reducer" is a mechanism, "flexspline" is a part, "demand", "function", "material" is a subordinate element.
In this embodiment, the steps of analyzing the contact attribute between the nodes, editing and storing include: and carrying out WHAT/HOW/WHY analysis on the connection between the nodes, representing the product classification type, the product production mode and the product quality parameters, and storing analysis information in a map. Taking the application scenario of fig. 2 as an example, in the element "maintenance", there are 3 sub-elements, "flexspline failure", "lubrication", and "gear wear", and there is a WHAT link attribute between the three sub-elements and the element "maintenance", which represents the classification type, i.e. "WHAT" problem. For example, under the sub-element "flexspline failure", there are "maintenance method" and "failure cause" which are adapted to the sub-element, respectively represent HOW contact attribute and what contact attribute. In summary, the embodiment may edit the nodes and the contact attributes between the nodes and store the edited contact attributes in the map.
In this embodiment, the edited map may be displayed to the user. The hierarchical nodes of the processing equipment and the links between the nodes are shown in the form of a graph.
Referring to fig. 3, the query information of the user for the processing equipment model is specifically a query problem for the processing equipment model.
The knowledge retrieval module is used for acquiring the query problem of the user aiming at the processing equipment model, and acquiring the node and attribute information thereof corresponding to the highest matching rate of the query problem based on semantic analysis and classifier training algorithm. Specifically, in this embodiment, the knowledge retrieval module is configured to match the query question with a WHAT/HOW/WHAT contact attribute between nodes.
Referring to fig. 4, in an application scenario, the knowledge retrieval module of the management and recommendation system for manufacturing process equipment models of the present invention relates to a naive bayes classifier of spark when performing knowledge recommendation, and the classifier can perform problem template probability matching through training a problem set, so that the use HanLP of functions for natural language processing in an industrial environment is perfect. The treatment process is as follows: first, taking the original sentence (usually a question) input by the user, for example, the user can input "ask for the part list of the harmonic reducer", further, the knowledge retrieval module abstracts the original sentence, replaces the names of the system, the subsystem, the component, the part, the element and the like with nr and abstracts the sentence, for example, ask for what the part list of the harmonic reducer is replaced with the list of nr, the knowledge retrieval module abstracts the sentence to match the question template (a pile of question data sets is trained and calculated by Spark), for example, nr list is restored to the final question by the question template, for example, nr list is replaced with nr=harmonic reducer, the final effect is that the harmonic reducer list is taken, after the question is taken, the answer of the question is found in the graphic database neo4j, and in fig. 4, the knowledge retrieval module feeds back "rigid wheel, flexible wheel and wave generator" to the user. The knowledge retrieval module in the system can rapidly distinguish the system, the subsystem, the parts and the elements, and find the common nodes and the relationship at the highest speed based on WHAT, HOW, WHY identification of the nodes, so that the problems of users are accurately and rapidly recommended.
The management and recommendation system for the manufacturing equipment model is visual and simple in management mode, high in management efficiency and capable of effectively promoting progress of a networked manufacturing mode.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (7)
1. A system for managing and recommending manufacturing process equipment models, comprising: a knowledge management module and a knowledge retrieval module;
the knowledge management module is used for creating nodes of the processing equipment model in a traditional form according to regional or functional characteristics of networked collaborative processing and replacing the nodes of the processing equipment model in a traditional form with nodes of the processing equipment model by using a graphic database; acquiring information of a user for using or designing the node, and identifying the node; analyzing the contact attribute among the nodes, and editing and storing;
The knowledge retrieval module is used for acquiring query information of a user for the processing equipment model and feeding back knowledge information corresponding to the query information to the user.
2. The system of claim 1, wherein the knowledge management module identifies the node as a system, subsystem, organization, part, or element based on a regional or functional characteristic of the node.
3. The system for managing and recommending manufacturing process equipment models according to claim 2, wherein the knowledge management module performs a WHAT/HOW/WHY analysis of the connections between the nodes, represents product classification type, product production mode, and product quality parameters, and stores analysis information in a map.
4. A system for managing and recommending manufacturing process equipment models in accordance with claim 3, wherein said system is further for presenting said map to a user.
5. The system of claim 1, wherein the user query information for the process equipment model is specifically a query question for the process equipment model.
6. The system of claim 5, wherein the knowledge retrieval module obtains a query problem for the manufacturing process equipment model by a user, and obtains a node and attribute information thereof corresponding to the highest matching rate of the query problem based on semantic analysis and classifier training algorithm.
7. The system of claim 6, wherein the knowledge retrieval module is configured to match the query question to a WHAT/HOW/WHY contact attribute between nodes.
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| CN108920716A (en) * | 2018-07-27 | 2018-11-30 | 中国电子科技集团公司第二十八研究所 | The data retrieval and visualization system and method for knowledge based map |
| CN109144007A (en) * | 2018-09-12 | 2019-01-04 | 机械工业仪器仪表综合技术经济研究所 | A kind of automatic construction system for integrating and interconnecting towards digitlization workshop manufacturing equipment |
| CN109446385A (en) * | 2018-11-14 | 2019-03-08 | 中国科学院计算技术研究所 | A kind of method of equipment map that establishing Internet resources and the application method of the equipment map |
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| CN106453097B (en) * | 2016-11-15 | 2019-04-30 | 中国科学院计算技术研究所 | The method and system of routing table are obtained in a kind of data center |
| CN106713083B (en) * | 2016-11-24 | 2020-06-26 | 海信集团有限公司 | Intelligent household equipment control method, device and system based on knowledge graph |
| CN106919655B (en) * | 2017-01-24 | 2020-05-19 | 网易（杭州）网络有限公司 | Answer providing method and device |
| CN107222339B (en) * | 2017-05-27 | 2020-06-05 | 全球能源互联网研究院有限公司 | Graph database-based fault analysis method and device for power information communication system |
| CA3007166C (en) * | 2017-06-05 | 2024-04-30 | 9224-5489 Quebec Inc. | Method and apparatus of aligning information element axes |
| CN109033063B (en) * | 2017-06-09 | 2022-02-25 | 微软技术许可有限责任公司 | Machine inference method based on knowledge graph, electronic device and computer readable storage medium |
| CN109522420B (en) * | 2018-11-16 | 2022-04-22 | 广东小天才科技有限公司 | Method and system for acquiring learning demand |
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| CN108920716A (en) * | 2018-07-27 | 2018-11-30 | 中国电子科技集团公司第二十八研究所 | The data retrieval and visualization system and method for knowledge based map |
| CN109144007A (en) * | 2018-09-12 | 2019-01-04 | 机械工业仪器仪表综合技术经济研究所 | A kind of automatic construction system for integrating and interconnecting towards digitlization workshop manufacturing equipment |
| CN109446385A (en) * | 2018-11-14 | 2019-03-08 | 中国科学院计算技术研究所 | A kind of method of equipment map that establishing Internet resources and the application method of the equipment map |
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