Product history query method, device, equipment and medium

Abstract

The present application discloses a product history query method, device, equipment and medium. The method includes receiving a product query request, the product query request includes at least one product query parameter; querying a pre-created product map database according to the product query parameter to obtain product history data corresponding to the product to be queried, the product map database includes a relationship map constructed based on product entities, production entities, and relationship pairs between product entities and production entities, and the product history data is composed of production entities that have relationship pairs with the product to be queried and are obtained according to the relationship map according to time attributes. The technical solution provided by the embodiment of the present application obtains product history data by querying a pre-constructed product map database, which effectively saves the query time of product history data and improves the query efficiency of product history data.

Description

Technical Field

[0001] The present application relates to the technical field of industrial big data, and in particular to product history query methods, devices, equipment and media. Background Art

[0002] The Manufacturing Execution System (MES) stores the production history of products and records in detail the production information of products during the manufacturing process. The production history of products can be used to trace the source of problematic products, narrow the scope of product recalls, and thus reduce the losses caused by product recalls. The traceability data model can not only fully record production process data, but also be extended to quality traceability, procurement traceability, etc., which is of great significance to enterprise manufacturing process control and manufacturing process improvement.

[0003] Product history tracing is usually based on data stored in relational databases. However, product history tracing based on relational databases has problems such as a long query process or a complicated query process, resulting in low efficiency in tracing problematic products. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a product history query method, device, equipment and medium to improve the query efficiency of product history data.

[0005] In a first aspect, an embodiment of the present application provides a product history query method, the method comprising:

[0006] receiving a product query request, the product query request including at least one product query parameter of a product to be queried;

[0007] A pre-created product graph database is queried according to product query parameters to obtain product history data corresponding to the product to be queried. The product graph database includes a relationship graph constructed based on product entities, production entities, and relationship pairs between product entities and production entities. The product history data is composed of production entities that have relationship pairs with the product to be queried and are obtained according to time attributes based on the relationship graph.

[0008] In a second aspect, an embodiment of the present application provides a product history query system, the system comprising:

[0009] A product history query device is used to receive a product query request, the product query request includes at least one product query parameter of a product to be queried; construct a query statement based on the product query parameter, call the query statement to search a pre-created product graph database, and obtain product history data corresponding to the product to be queried, the product history data is formed by combining production entities that have a relationship with the product to be queried and are obtained according to the relationship graph according to a time attribute;

[0010] The product graph database is used to store a relationship graph constructed based on product entities, production entities, and the relationship pairs between product entities and production entities.

[0011] In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the method described in the embodiment of the present application when executing the program.

[0012] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and the computer program is used to implement the method described in the embodiment of the present application.

[0013] The product history query method, device, equipment and medium provided in the embodiment of the present application, the method receives a product query request, the product query request includes at least one product query parameter of the product to be queried; queries a pre-created product map database according to the product query parameter to obtain product history data corresponding to the product to be queried, the product map database includes a relationship map constructed based on product entities, production entities, and relationship pairs between product entities and production entities, the product history data is composed of production entities that have relationship pairs with the product to be queried and are obtained according to the relationship map according to the time attribute. The embodiment of the present application obtains product history data by querying a pre-constructed product map database, which effectively saves the query time of product history data and improves the query efficiency of product history data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0015] Figure 1 A schematic diagram showing an application scenario of the product resume query method provided in an embodiment of the present application is shown;

[0016] Figure 2 A schematic diagram showing a process flow of a product resume query method proposed in an embodiment of the present application is shown;

[0017] Figure 3 A schematic diagram of a process for constructing a product image database provided in an embodiment of the present application is shown;

[0018] Figure 4 A schematic diagram showing various entities and relationship pairs between entities in a product graph database proposed in an embodiment of the present application;

[0019] Figure 5 A schematic diagram showing a process flow of another product resume query method provided in an embodiment of the present application is shown;

[0020] Figure 6 The working principle diagram of the product resume query method provided by the embodiment of the present application is shown;

[0021] Figure 7 A schematic diagram showing a process flow of a product resume query method provided in an embodiment of the present application is shown;

[0022] Figure 8 A schematic diagram showing the structure of a product history query device provided in an embodiment of the present application is shown;

[0023] Fig. 9 A schematic diagram showing the structure of another product history query device provided in an embodiment of the present application

[0024] Fig.10 A schematic diagram of the structure of a computer system of a terminal device or server suitable for implementing an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant disclosure, rather than to limit the disclosure. It should also be noted that, for ease of description, only the parts related to the disclosure are shown in the accompanying drawings.

[0026] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0027] Please refer to Figure 1 , Figure 1 A schematic diagram of an application scenario of the product history query method provided in an embodiment of the present application is shown.

[0028] like Figure 1As shown, the user can use the terminal device 101 to query the pre-stored product history data. It can query the product history data of the corresponding product, or the product defect rate and other information through the query client pre-installed in the terminal device. The query client receives the query conditions input by the user, and then sends the query conditions to the server 103 through the network 102. The query conditions may include but are not limited to the query parameters of the product, target restriction conditions, etc. The query parameters of the product include but are not limited to the input product parameters such as product models, or pictures corresponding to defective products, etc. The target restriction conditions include but are not limited to query time parameters, such as query time range. The terminal device 101 can be a mobile device such as a smart phone, a tablet computer, smart glasses, etc., and can also be an electronic device such as a desktop computer, but is not limited to this.

[0029] The server 103 executes the query program according to the query conditions sent by the terminal device 101 to find the results related to the query conditions, which include but are not limited to product history data, product attention indicators, etc. The server 103 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0030] The network 102 includes but is not limited to a wireless network or a wired network, and standard communication technologies and / or protocols are used through the wireless network or the wired network. The network is usually the Internet, and can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network.

[0031] The server 103 may also include a database server, which is used to store relational data related to product queries. In related technologies, the database may be a relational database.

[0032] In the process of history tracing based on relational databases, it is necessary to interact with multiple data tables to query product history data and product defect information. When JOINing product defect information, the same panel may have multiple defect problems and each of the multiple defect problems may be caused by multiple different process steps, which may have as many as 3 to 4 hierarchical distribution relationships. If you search for product history data according to the relational database and then analyze the product defect information based on the product history data, the amount of query data will increase dramatically.

[0033] For example, there are 100,000 panels with compound input query conditions, each panel has M defects on average, there are N process sections, each process section has P EQPs on average, and each EQP has K UNITs. Then the amount of connection data generated may be 100,000*M*N*(P+K), and the number of records generated in the end is 100 to 1,000 times the number of panels. The entire query process requires the join operation of the database table to associate the data, which results in running a compound query statement based on the relational database, which takes a long time to query and leads to low query efficiency.

[0034] In order to solve the above problems, the present application proposes a technical solution for a product history data query method, which can effectively save query time and improve the query efficiency of product history data.

[0035] Please refer to the following Figure 2 , Figure 2 FIG. 1 is a flow chart showing a method for querying product history according to an embodiment of the present application. Figure 2 As shown, the method can be executed by a product history query device, which can be configured in a terminal device or a server. The method includes:

[0036] Step 201, receiving a product query request, the product query request including at least one product query parameter of a product to be queried;

[0037] Step 202, query the pre-created product map database according to the product query parameters to obtain the product history data corresponding to the product to be queried.

[0038] In the above steps, the product query request refers to a request message containing one or more query parameters received and inputted on the query client. The query parameters include, but are not limited to, a certain product defect, a time range, and a product arrival rate parameter. For example, the query parameters can be obtained by performing image analysis on the inspection image corresponding to the received defective product. Alternatively, a third party or user directly inputs the query parameters. The format and carrying form of the request message are not limited.

[0039] The query parameter may be an identifier corresponding to the query product.

[0040] The product graph database is a relational graph constructed based on multiple production entities, multiple product entities, relationship pairs between production entities, and relationship pairs between production entities and product entities, including the production process of the product. The product graph database includes a relational graph constructed based on product entities, production entities, and relationship pairs between product entities and production entities.

[0041] The relationship graph refers to a graph search structure built based on entities and triple arrays. Among them, the entity can be the above-mentioned production entity and product entity, and the triple array includes but is not limited to (named entity 1, relationship, named entity 2), that is, the triple array is used to represent the relationship between product entities and product entities, or the relationship between product entities and production entities, and the relationship between production entities and production entities.

[0042] A production entity refers to the implementation entity that a product goes through at each stage from raw materials to products in the industrial production process. The production entity includes but is not limited to the production factory (Factory), station (Station), the implementation equipment (Equipment) and chamber (Unit) corresponding to the process steps of the product, etc.

[0043] Product entities refer to products in different states. For example, product entities include but are not limited to large panels (Glass), half panels (HalfGlass), and panels (Panel); product entities can also include but are not limited to product attributes, such as defective (Defeat), product model (Product), etc.

[0044] The relationship between production entities refers to the relationship between various production entities, including but not limited to containment relationships, such as containment site (factory→site), containment equipment (site→equipment), containment chamber (equipment→chamber).

[0045] The relationship between product entities refers to the relationship between each product entity. It includes but is not limited to the product segmentation relationship and the relationship between products and product attributes. For example, related half-boards (panel->half-board), related large boards (half-board->large boards), related defects (panel->defects), product attributes (panel->product model), the relationship between products passing through equipment (large board->equipment, large board->chamber, half-board->equipment, half-board->chamber), etc.

[0046] After receiving the product query parameters, the product map database is queried according to the product query parameters, and the product history data associated with the product query parameters can be quickly and effectively queried. Compared with the query on the relational database, the query of product history data based on the product map database proposed in the embodiment of the present application can realize large-scale product history tracing and greatly improve the query speed of product history data.

[0047] Product query parameters refer to the relevant parameters used to query products. The above product query parameters include but are not limited to the product identification, time range parameters and product arrival rate parameters of the product to be queried. The time range parameters include, for example, the time start point, the time end point, or a preset query range set based on the time start point.

[0048] When the product ID of the product to be queried is input, the product map database is requested to perform a query of the history data according to the product ID to obtain the product history data corresponding to the product ID.

[0049] When the product arrival rate parameter, time range parameter and product ID of the product to be queried are input, the product map database is requested to perform a combined query through the parameter combination to obtain the product history data corresponding to the product that meets the product arrival rate parameter.

[0050] The above product arrival rate parameter refers to the ratio parameter of the product arriving at the inspection point, for example 90%.

[0051] After obtaining the product ID of the product to be queried, searching for the product entity corresponding to the product ID according to the product ID;

[0052] According to the product entity corresponding to the product identifier, a production entity having a relationship pair with the product entity corresponding to the product identifier is searched;

[0053] The production entities that have a relationship pair with the product entity corresponding to the product identifier are combined according to the time attribute to form the product history data corresponding to the product to be queried.

[0054] After obtaining the combination parameters of the product query parameters, the pre-created product map database is queried according to the product query parameters to obtain product history data including:

[0055] The first relationship pair between product entities and product entities in the product graph database is queried according to the time range parameter and the product arrival rate parameter to obtain the to-be-queried products that meet the product arrival rate parameter.

[0056] The first relationship pair is used to represent the relationship between the first-state product entity and the second-state product entity. The product to be queried that meets the product arrival rate parameter is the first-state product entity.

[0057] The first state product entity may be, for example, panel. The first relationship pair may be Glass←panel, or halfGlass←panel, halfGlass←Glass, that is, multiple panels are cut from the same large board or half board.

[0058] According to the first-state product entity, a second relationship pair between product entities and product entities in the product graph database is queried to obtain a second-state product entity.

[0059] The second-state product entity may be, for example, Glass. The second relationship pair is used to represent the relationship between the adverse result of the first-state product entity and the second-state product entity.

[0060] For example, the first-state product entity panel is determined based on the product arrival rate parameter. After a piece of Glass is divided into multiple panels, the ratio of the number of multiple panels that arrive at the detection point in batches or synchronously to the number of panels that Glass is divided into is called the product arrival rate parameter. Assuming that when the product arrival rate reaches 80%, it means that multiple panels are obtained from the same Glass, and 80% of the multiple panels have reached the detection point, then at this time, the second-state product entity Glass corresponding to the multiple panels is determined as the product to be queried based on the product arrival rate parameter. The product to be queried refers to the product used to query the product history parameters.

[0061] The second-state product entity Glass that meets the product arrival rate parameters may detect bad results when the panel arrives at the inspection point for product inspection after being split into panels. By pre-constructing a relationship pair between the bad results and the second-state product entity, the second-state product entity corresponding to the bad result can be traced back. The relationship pair between the bad results of the first-state product and the second-state product entity can be constructed by extracting data from the data relationship between the panels and Glass of multiple bad results. When multiple panels of bad results are obtained, the bad results can be aggregated to Glass to determine the bad Glass. The aggregation of this application is achieved through pre-constructed relationship pairs in the product graph database. There is no need to perform join operations between multiple data linked lists. The query speed is improved by about two orders of magnitude compared to the query of the relational database.

[0062] According to the second-state product entity, the relationship between the product entity and the production entity in the product graph database is queried to obtain the product history data corresponding to the second-state product entity.

[0063] Since the first-state product entity and the second-state product entity may be associated with each other through a simple process, when determining that the first-state product entity has a bad result, the possible cause of the bad result can be further found based on the second-state product entity associated with it. In the process of finding the possible cause of the bad result, it is necessary to obtain the product history data of the second-state product entity.

[0064] According to the second-state product entity, the relationship pair between the product entity and the production entity in the product map database is queried to obtain the product history data corresponding to the second-state product entity. The relationship pair between the product entity and the production entity is used to represent the relationship between the second-state product entity and the production entity.

[0065] The relationship between the product entity and the production entity includes: the relationship between the second-state product entity and the production entity. For example, the second-state product entity refers to a product generated according to the production process steps. Taking the second-state product entity as Glass as an example, the above-mentioned production entity refers to the process production equipment corresponding to the production of Glass, and the factory where the production equipment is located.

[0066] Assume that the product Glass to be queried can be determined according to the product identification and the above product arrival rate, that is, according to the product attribute relationship pairs pre-established in the product graph database, such as the relationship (panel->product model), the first state product entity corresponding to the product identification can be obtained. Then, according to the reverse process of the manufacturing process of the first state product entity, the second state product entity can be determined by searching the relationship pairs, that is, the relevant defective (panel->defective), the relevant large board (panel->large board), and the second state product entity is obtained. If there is a half board, the second state product entity can also be obtained according to the relevant defective (panel->defective), the relevant half board (panel->half board), and the relevant large board (half board->large board). That is, reversely search for Glass with the defective panel as the starting point to determine the Glass corresponding to the defective panel. Then, according to the second state product entity Glass, the production equipment passed through in the production process can be determined, and the product history data of the second state product entity can be obtained. Taking the direct segmentation of panel from Glass as an example, that is, large board->equipment, large board->chamber, the production process relationship between large board and production entity (i.e. equipment, chamber, etc.) can be determined. Assuming that the process of producing Glass involves multiple devices such as equipment A, B, C, and D, in the relationship graph, the second-state product entity establishes a star-shaped connection relationship with each production entity (i.e., the abstract entity of equipment A, B, C, and D). Each production entity is added with a time attribute, which is used to record the start time and end time of the second-state product entity passing through the generation entity.

[0067] After determining the second-state product entity, the set of production entities is obtained by searching for the connection relationship of the star structure, and then the order in which the second-state product entity passes through the production entity is determined according to the time attribute of each production entity. The set of production entities is output according to the time attribute to obtain the product history data of the second-state product entity.

[0068] When determining the second-state product entity based on the defect, the embodiment of the present application uses the pre-constructed relationship map between the second-state product entity and the production entity to obtain the set of production entities associated with the second-state product, and then obtains the product history data of the second-state product entity based on the time attribute of each production entity itself, which effectively shortens the time to obtain the product history data. Compared with the relational database, the process of searching for product defect information through join requires joining and associating multiple related data tables to search for product history data. The embodiment provided by the present application uses the relationship map of the product graph database to trace back and search for the product history data corresponding to the second-state product entity with defects, which can effectively save query time and can also present the product history data visually.

[0069] Based on the above embodiment, in order to more clearly describe the process of building a product map database, Figure 3 The construction method of the product graph database is further described. The construction process of the product graph database can be understood as two processes: offline construction and online update.

[0070] The offline build part may include:

[0071] Step 301, obtaining the original product history data generated by the production execution system MES;

[0072] Step 302, data processing is performed on the original product history data to obtain product entities and production entities, and a relationship pair between the product entity and the production entity is constructed based on the transfer relationship of the original product history data.

[0073] Step 303, construct a relationship graph based on product entities, production entities and relationship pairs to obtain a product graph database.

[0074] The above steps can be used to extract, transform, and load the original product history data generated by the manufacturing execution system MES (Manufacturing Execution Systems) to the destination (i.e., product map database) through the ETL module (full name in English: Extract-Transform-Load). That is, the source end is the metadata storage location and the operational data storage location. The operational data storage here is called Operational Data Store, abbreviated as ODS.

[0075] When building a product image database, by adding indexes to the characteristic attributes of entities, the ETL and query speed can be effectively improved. For example, when building relationship pairs between production entities, relationship pairs between production entities and product entities, and relationship pairs between product entities, the index value of the data transfer relationship is established in the attribute parameters of the ternary array to indicate the transfer status of the product. It is also possible to add identification attributes to the production entity, product entity, and each relationship pair, and the identification attribute is used to uniquely identify each production entity and product entity.

[0076] For example, each product entity and production entity creates a unique ID (full name Identifier, abbreviated ID), including but not limited to Panel.productID. Since a Panel.productID is created corresponding to each product entity, when querying the history data for Panel.productID, the query scope of the panel can be narrowed, the amount of query data can be reduced, and the query speed can be improved.

[0077] In the process of querying product history data based on bad demand, users can filter the panels that need to be tracked according to the time range. Since the characteristic attributes of the product entity pre-add the time attribute Panel.date, when users create an index through the time attribute Panel.date, they can effectively reduce the amount of data scanned in the time range, thereby improving the query time.

[0078] like Figure 4 As shown, Figure 4 A schematic diagram of the relationship between entities and entities in the product graph database constructed by the present application is shown. When querying the product graph database through a query statement, the product history data corresponding to the target product can be quickly and accurately found based on the pre-constructed index relationship.

[0079] The online update part may include:

[0080] Extract product entities, production entities, and relationship pairs between product entities and production entities that have undergone status changes from the original product history data after data processing;

[0081] The relationship graph is updated based on the product entities, production entities, and the relationship pairs between the product entities and the production entities that have undergone status changes.

[0082] In the above steps, the original product history data generated by the production execution system MES can be obtained periodically or by subscription push. That is, when the original product history data is updated, the ETL module can obtain the updated product history data from the MES system, and according to the index relationship of the pre-built entity, the ETL module searches for the production entity, product entity, the relationship between product entity and production entity, and the relationship between product entity and product entity in the product graph database corresponding to the index, thereby realizing the rapid update of the product database.

[0083] This application uses the product graph database to perform product history data queries. The relationship pairs between products and product attributes can be pre-built in the product graph database, and the relationship pairs can be stored as the relationship attribute features of the product. For example, the start time and end time of Glass passing through the production process equipment and chamber can be stored in the relationship attributes. When there is a defect in the panel detection, the relationship attributes such as the defect point coordinates and defect point count are stored in the relationship pair between the relevant defect result and the product.

[0084] When the embodiment of the present application uses the product database to perform related queries, the search scope can be effectively narrowed and the search accuracy can be improved by identifying the index.

[0085] Furthermore, the pre-established relationship attributes can be used to provide queries on product defects within a time range, thereby effectively improving query efficiency.

[0086] After obtaining product history data using the product map database, the process of using the product history data to analyze the focus index can further improve the analysis efficiency of the product history data in different applications. Figure 5 , Figure 5 A flowchart of another product history query method provided by an embodiment of the present application is shown. The method can be executed by a product history query device, which can be configured on a terminal device or a server. The method includes:

[0087] Step 501, receiving a product query request, the product query request including a plurality of product query parameters of products to be queried;

[0088] Step 502, query the pre-created product map database according to the product query parameters to obtain the product history data corresponding to the product to be queried.

[0089] Step 503: Calculate the attention index of the product to be queried based on the product history data.

[0090] In the above steps, the method of querying the product history data is the same as the above query process. After receiving the product query request, a query statement for querying the product map database can be constructed according to the product query parameters, and the product map database can be queried based on the query statement to obtain the product history data.

[0091] In the embodiment of the present application, by constructing a query statement for querying the product map database, a direct connection can be established in a multi-hop query to speed up the query speed. Among them, the query statement for querying the product map database can be constructed according to the query frequency of the query product.

[0092] For example, Panel-[relateHalfGlass]->HalfGlass-[relateGlass]->Glass. Considering that the query frequency of Glass's history data is relatively high, a query relationship statement can be directly established to realize the query connection between Panel-[R_Glass]->Glass. In actual tests, this query connection can speed up the query speed by 20%.

[0093] After obtaining the product history data through query, the attention index of the product to be queried can be calculated based on the product history data.

[0094] Step 503 may also include:

[0095] Read the pre-stored attention indicator calculation template;

[0096] The attention index of the product to be queried is calculated according to the attention index calculation template and the product history data of the product to be queried.

[0097] After obtaining the product history data, the attention index is calculated by reading the pre-stored attention index calculation module board combined with the product history data. Compared with the attention index calculation of related technologies, template processing saves the time of data call and further saves the processing time of query calculation. In addition, the calculation of attention index can also allow users to intuitively understand all product history data related to the attention index calculation, effectively improving user satisfaction with the product query terminal.

[0098] The following takes the display device production process as an example. Figure 6-7 The working principle of the product history query data method based on defective products proposed in this application is described below. Figure 6As shown, the query terminal is connected to the server through a communication network, and the query terminal sends a query request to the server, and the server feeds back the query result to the query terminal according to the query request. Figure 7 As shown, the method is executed by a server, and the method includes:

[0099] Input product query parameters on the product query terminal, such query parameters include, for example, the defective and time range values ​​of product A. The product arrival rate can be input by the user or preset by the system. The product query terminal encapsulates the product query parameters into a product query request and sends it to the server.

[0100] Step 601, the server receives a product query request;

[0101] Step 602: The server parses the product query request to obtain product query parameters.

[0102] Step 603: The server calls a pre-stored query statement template according to the product query parameters to construct a query statement for querying the product map database.

[0103] The product map database is completed in the creation part, and the creation part can be further divided into an offline creation part and an online update part of the product map database.

[0104] For example, Q1:”Match(panel:PANEL)-[:R_GLASS]->(glass:GLASS)

[0105] Optional match(panel)-[:relateDefeat]->(dft:DEFEAT)

[0106] where panel.productID={productID}and{startDate}<=panel.date<={endDate}and dft.ID={dftID}

[0107] with glass as glass,count(panel)as cnt,count(dft)as dftCnt match(glass)-[:PASS]->(eqp:EQP)

[0108] return eqp.group as group,eqp.ID as ID,sum(cnt)as total,sum(dftCnt)asdftCnt";

[0109] Q2:”Match(panel:PANEL)-[:R_GLASS]->(glass:GLASS)

[0110] Optional match(panel)-[:relateDefeat]->(dft:DEFEAT)

[0111] where panel.productID={productID}and{startDate}<=panel.date<={endDate}and dft.ID={dftID}

[0112] return count(panel)as totalPanel,count(dft)as totalDft";

[0113] Step 604: query the product database according to the constructed query statement to obtain product history data.

[0114] Then, the server can send the product history data to the product query client, which can display the product history data visually, thereby improving user satisfaction.

[0115] Optionally, the method executed by the server may further include:

[0116] Step 605, calculate the attention index of the queried product using the product history data and the pre-stored attention index calculation template. For example, query the attention index of defective Glass. The pre-stored attention index calculation template can be, for example:

[0117] {"total":Q2[0].totalPanel,

[0118] "dftTotal":Q2[0].totalDft,

[0119] "iv":{

[0120] "group":Q1.group,

[0121] "eqpID":Q1.ID,

[0122] "iv":Math.IV(Q2[0].totalPanel,Q2[0].totalDft,Q1[*].dftCnt,Q1[*].total)

[0123] }

[0124] }

[0125] Step 606: The server sends the attention index to the query terminal.

[0126] By calculating the product's attention indicators through the above-mentioned pre-built attention indicator calculation template, the complex steps of searching and calculating through data table association in related technologies can be avoided, which effectively improves the efficiency of querying attention indicators and saves the query time of attention indicators.

[0127] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0128] Please refer to the following Figure 8 , Figure 8 The structure diagram of the product resume query system provided by the embodiment of the present application is shown in FIG. The system may include

[0129] The product history query device 701 is used to receive a product query request, the product query request includes at least one product query parameter; construct a query statement based on the product query parameter, call the query statement to search a pre-created product graph database, and obtain product history data corresponding to the product to be queried, the product history data is obtained by searching the relationship graph, and the production entities that have a relationship with the product to be queried are combined according to time attributes;

[0130] The product graph database 702 is used to store a relationship graph constructed based on product entities, production entities, and the relationship pairs between product entities and production entities.

[0131] The product history query device provided in the embodiment of the present application can be used to perform the above Figure 2 Describe the method.

[0132] Product history query device is used for:

[0133] Search for a product entity corresponding to the product ID according to the product ID;

[0134] According to the product entity corresponding to the product identifier, a production entity having a relationship pair with the product entity corresponding to the product identifier is searched;

[0135] The production entities that have a relationship pair with the product entity corresponding to the product identifier are combined according to the time attribute to form the product history data corresponding to the product to be queried.

[0136] According to the time range parameter and the product arrival rate parameter, a first relationship pair between product entities in the product graph database is queried to obtain a product to be queried that meets the product arrival rate parameter, where the product to be queried is a first-state product entity, and the first relationship pair is used to represent an association relationship between the first-state product entity and the second-state product entity;

[0137] According to the queried product that meets the product arrival rate parameter, query the second relationship pair between the product entity and the product entity in the product graph database to obtain the second state product entity corresponding to the queried product, and the second relationship pair is used to represent the association relationship between the adverse result of the first state product entity and the second state product entity;

[0138] According to the second-state product entity, the relationship pair between the product entity and the production entity in the product graph database is queried to obtain the product history data corresponding to the second-state product entity. The relationship pair between the product entity and the production entity is used to represent the association relationship between the second-state product entity and the production entity.

[0139] The device also includes a database creation module for creating a product map database, which is configured to obtain original product history data generated by a manufacturing execution system MES;

[0140] Processing the original product history data to obtain product entities and production entities, and constructing a relationship pair between the product entity and the production entity based on the transfer relationship of the original product history data;

[0141] A relationship graph is constructed based on product entities, production entities and relationship pairs to obtain a product graph database.

[0142] The device also includes an updating module, which is used to update the product map database and is configured to: extract product entities, production entities, and relationship pairs between product entities and production entities that have undergone status changes from the original product history data after data processing;

[0143] The relationship graph is updated based on the product entities, production entities, and the relationship pairs between the product entities and the production entities that have undergone status changes.

[0144] The product history query device is also used for:

[0145] Constructing a query statement for querying a product graph database based on product query parameters;

[0146] The product graph database is queried based on the query statement to obtain the product history data corresponding to the product to be queried.

[0147] The product history query device is also used to calculate the attention index of the product to be queried based on the product history data.

[0148] The product resume query device is also used to: read a pre-stored attention index calculation template;

[0149] The attention index of the product to be queried is calculated according to the attention index calculation template and the product history data of the product to be queried.

[0150] The embodiment of the present application queries the product history data by pre-building a product map database. It directly aggregates negative information to the primary-state products through multiple relationship pairs contained between the product to be queried and the primary-state products, thereby shortening the time for obtaining the product history data of the primary-state products.

[0151] The aggregation of this application is achieved through pre-built relationship pairs in the product graph database, without the need to perform join operations between multiple data linked tables. The query speed is improved by about two orders of magnitude compared to the query of relational databases.

[0152] Please refer to Fig. 9 , Fig. 9 The schematic diagram of the structure of the product resume query device provided in the embodiment of the present application is shown. The device can be configured in a query terminal or a server, and the device includes:

[0153] The query submodule 7011 is used to receive a product query request, and request a query statement template from the indicator storage submodule according to the product query parameters, construct a query statement according to the query statement template and the product query parameters, and request the product map database to execute a query according to the query statement, and receive the product history data corresponding to the product to be queried returned by the product map database;

[0154] The indicator storage submodule 7012 is used to store query statement templates and attention indicator calculation templates;

[0155] The result parsing submodule 7013 is used to receive the product history data of the product to be queried sent by the query submodule; request the attention index calculation template from the index storage submodule, and calculate the attention index of the product to be queried according to the product history data and the attention index calculation template.

[0156] The result parsing submodule 7013 is also used to send the attention index of the queried product to the query client.

[0157] The file processing device provided in the embodiment of the present application can be used to perform the above Figure 2 Describe the method.

[0158] It should be understood that the units or modules described in the above device are similar to those described in the reference Figure 2 The steps in the described method correspond to each other. Therefore, the operations and features described above for the method are also applicable to the above-mentioned device and the units contained therein, and will not be repeated here. The above-mentioned device can be pre-implemented in the browser or other security application of the electronic device, and can also be loaded into the browser or its security application of the electronic device by downloading or the like. The corresponding units in the above-mentioned device can cooperate with the units in the electronic device to implement the solution of the embodiment of the present application.

[0159] For the several modules or units mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0160] Reference below Fig.10 , Fig.10 A schematic diagram of the structure of a computer system of a terminal device or server suitable for implementing an embodiment of the present application is shown.

[0161] like Fig.10 As shown, the computer system includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the system 900 are also stored. The CPU 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0162] The following components are connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage section 908 as needed.

[0163] In particular, according to an embodiment of the present disclosure, the above reference flow chart Figure 2 The described process can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part 909, and / or installed from a removable medium 911. When the computer program is executed by a central processing unit (CPU) 901, the above-mentioned functions defined in the system of the present application are executed.

[0164] It should be noted that the computer-readable medium shown in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0165] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of the code, and the aforementioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0166] The units or modules involved in the embodiments described in the present application may be implemented by software or hardware. The units or modules described may also be provided in a processor, for example, may be described as: a processor includes a query submodule. The names of these units or modules do not, in certain cases, constitute limitations on the units or modules themselves, for example, the query submodule may also be described as a "module for receiving product query requests".

[0167] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently and not be assembled into the electronic device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the product history query method described in the present application.

[0168] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A product history query method, characterized in that: The method includes: receiving a product query request, wherein the product query request includes at least one product query parameter; According to the product query parameters, a pre-created product graph database is queried to obtain product history data corresponding to the product to be queried, wherein the product graph database includes a relationship graph constructed based on product entities, production entities, and relationship pairs between product entities and production entities, and the product history data is formed by combining production entities that have relationship pairs with the product to be queried and are obtained according to the relationship graph according to time attributes; Wherein, the product query parameter includes: one or more of a time range parameter, a product arrival rate parameter, and a product identifier of the product to be queried. The method of querying a pre-created product map database according to the product query parameter to obtain product history data includes one or more of the following: According to the time range parameter and the product arrival rate parameter, a first relationship pair between product entities and product entities in the product graph database is searched to obtain a product to be queried that meets the product arrival rate parameter, wherein the product to be queried is a first-state product entity, and the first relationship pair is used to represent an association relationship between the first-state product entity and the second-state product entity; According to the product to be queried that meets the product arrival rate parameter, query the second relationship pair between the product entity and the product entity in the product graph database to obtain the second state product entity corresponding to the product to be queried, wherein the second relationship pair is used to represent the association relationship between the adverse result of the first state product entity and the second state product entity; According to the second-state product entity, the relationship pair between the product entity and the production entity in the product map database is queried to obtain the product history data corresponding to the second-state product entity, and the relationship pair between the product entity and the production entity is used to represent the association relationship between the second-state product entity and the production entity.

2. The method according to claim 1, characterized in that The product query parameters include: product identification of the product to be queried, and querying a pre-created product map database according to the product query parameters includes: Searching for a product entity corresponding to the product identifier according to the product identifier; Searching, according to the product entity corresponding to the product identifier, for a production entity that has a relationship pair with the product entity corresponding to the product identifier; The production entities that have a relationship pair with the product entity corresponding to the product identifier are combined according to the time attribute to form the product history data corresponding to the product to be queried.

3. The method according to claim 1, characterized in that The steps of creating the product map database include: Obtain the original product history data generated by the manufacturing execution system MES; Processing the original product history data to obtain a product entity and a production entity, and constructing a relationship pair between the product entity and the production entity based on the transfer relationship of the original product history data; A relationship graph is constructed based on the product entity, the production entity and the relationship pair to obtain the product graph database.

4. The method according to claim 3, characterized in that The method further includes updating the product map database, wherein updating the product map database includes: Extract product entities, production entities, and relationship pairs between product entities and production entities that have undergone status changes from the original product history data after data processing; The relationship graph is updated based on the product entity, the production entity, and the relationship between the product entity and the production entity whose status has changed.

5. The method according to claim 1, characterized in that Before querying the pre-created product map database according to the product query parameter, the method includes: Constructing a query statement for querying the product map database based on the product query parameters; The product map database is queried based on the query statement to obtain the product history data corresponding to the product to be queried.

6. The method according to claim 2, characterized in that The method further includes: The attention index of the product to be queried is calculated based on the product history data.

7. The method according to claim 6, characterized in that The calculating the attention index of the product to be queried based on the product history data includes: Read the pre-stored attention indicator calculation template; The attention index of the product to be queried is calculated according to the attention index calculation template and the product history data of the product to be queried.

8. A product history query system, characterized in that: The system includes: A product history query device is used to receive a product query request, the product query request includes at least one product query parameter; construct a query statement based on the product query parameter, call the query statement to search a pre-created product graph database, and obtain product history data corresponding to the product to be queried, the product history data is formed by combining production entities that have a relationship with the product to be queried and are obtained according to a relationship graph according to a time attribute; A product graph database, used to store a relationship graph constructed based on product entities, production entities, and the relationship between product entities and production entities; Wherein, the product query parameters include: time range parameters, product identification of the product to be queried, and the pre-created product map database is queried according to the product query parameters to obtain product history data including: According to the time range parameter and the product arrival rate parameter, a first relationship pair between product entities and product entities in the product graph database is searched to obtain a product to be queried that meets the product arrival rate parameter, wherein the product to be queried is a first-state product entity, and the first relationship pair is used to represent an association relationship between the first-state product entity and the second-state product entity; According to the product to be queried that meets the product arrival rate parameter, query the second relationship pair between the product entity and the product entity in the product graph database to obtain the second state product entity corresponding to the product to be queried, wherein the second relationship pair is used to represent the association relationship between the adverse result of the first state product entity and the second state product entity; According to the second-state product entity, the relationship pair between the product entity and the production entity in the product map database is queried to obtain the product history data corresponding to the second-state product entity, and the relationship pair between the product entity and the production entity is used to represent the association relationship between the second-state product entity and the production entity.

9. The system according to claim 8, characterized in that The product history query device comprises: A query submodule, configured to receive the product query request, and request a query statement template from the indicator storage submodule according to the product query parameters, construct a query statement according to the query statement template and the product query parameters, and request the product map database to execute a query according to the query statement, and receive product history data corresponding to the product to be queried returned by the product map database; The indicator storage submodule is used to store query statement templates and attention indicator calculation templates; The result parsing submodule is used to receive the product history data of the product to be queried sent by the query submodule; request the attention index calculation template from the index storage submodule, and calculate the attention index of the product to be queried according to the product history data and the attention index calculation template.

10. An electronic device, characterized in that: The device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the method according to any one of claims 1 to 7 when executing the program.

11. A computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to implement the method according to any one of claims 1 to 7.

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