A production big data interaction method based on smart big screen

Abstract

The present invention relates to the field of big data, and discloses a production big data interaction method based on a smart big screen, including: when a user performs a data kanban display operation, a production big data page is displayed in the smart big screen, and the production big data page includes multiple data kanban options, and the multiple data kanban options include production data kanban options, assembly data kanban options, and packaging data kanban options; when a user performs a selection operation for a packaging data kanban option, a corresponding monitoring video display window, a first user order sequence whose order status is being packaged, a second user order sequence whose order status is waiting for packaging, and a third user order sequence whose order status is completed packaging are displayed in the smart big screen; the monitoring video display window includes multiple fixed display windows and a mobile display window, and each fixed display window is used to display the real-time packaging video of the corresponding packaging station. Thus, the diversity of the interactive functions of the smart big screen is realized.

Description

Technical Field

[0001] The present invention relates to the field of big data, and in particular to a production big data interaction method based on a smart large screen. Background Art

[0002] Relying on the continuous maturity of big data technology, smart screens, as terminals for data display and interaction, are also widely used in the production process, especially in the production links of various electronic equipment such as servers and terminals. Through smart screens, various types of data can be viewed and interacted in a timely manner, thereby effectively improving production efficiency.

[0003] The existing smart large-screen interaction process often has the following technical problems:

[0004] First, the existing smart screens focus on display, while the interactive function is only to switch different data for display. The interactive function is single and has not been integrated with specific business scenarios, which makes it impossible to give full play to the functions of the smart screens.

[0005] Second, the existing smart screen display mode is single and interactive, and the efficiency of solving the problem of wrong orders displayed on the smart screen is low;

[0006] Third, there is no reasonable sampling process and sampling standards for the components of smart large screens, which leads to low sampling efficiency and random and accidental sampling results, which in turn affects the accuracy of the sampling results. Summary of the invention

[0007] The summary of the invention is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The summary of the invention is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0008] The present invention proposes a production big data interaction method based on a smart large screen to solve one or more of the technical problems mentioned in the above background technology part.

[0009] The present invention provides a production big data interaction method based on a smart big screen, comprising: when a user performs a data dashboard display operation, a production big data page is displayed in the smart big screen, the production big data page includes multiple data dashboard options, and the multiple data dashboard options include a production data dashboard option, an assembly data dashboard option, and a packaging data dashboard option; when a user performs a selection operation for a packaging data dashboard option, a packaging data display page corresponding to the packaging data dashboard option is displayed in the smart big screen, the packaging data display page includes a monitoring video display window, a first user order sequence whose order status is being packaged, a second user order sequence whose order status is waiting for packaging, and a third user order sequence whose order status is completed packaging, each user order in the third user order sequence includes an order number, a packaging station number, an order packaging time point, a name and quantity of purchased goods, and a shipping weight; the monitoring video display window includes multiple fixed display windows and a mobile display window, the multiple fixed display windows correspond to the multiple packaging stations one by one, and each fixed display window corresponds to the multiple packaging stations one by one. The display window is used to display the real-time packaging video of the corresponding packaging station; when a goods verification request is received, a match is performed in the third user order sequence according to the historical order number included in the goods verification request, and a user order matching the historical order number is obtained and determined as the target historical user order, and the verification category included in the goods verification request is determined. If the verification category is wrong goods verification, the corresponding packaging video clip is queried from the packaging video database according to the packaging station number and the order packaging time point included in the target historical user order and used as the target packaging video clip, and entity detection is performed on the target packaging video clip to obtain a video frame sequence containing an entity positioning frame, and the entity positioning frame is used to mark the entity appearing in each video frame in the target packaging video clip; the video frame sequence containing the entity positioning frame and the verification prompt information are displayed in the mobile display window, and the verification prompt information is used to prompt the user to enter the verification result information according to the entity positioning box; if the verification result information indicates that there is a wrong goods problem in the target historical user order, a reissue order for the target historical user order is generated.

[0010] Optionally, when the user performs a selection operation for an assembly data dashboard option, an assembly data display page corresponding to the assembly data dashboard option is displayed on the smart large screen, and the assembly data display page includes a fourth user order sequence whose order status is waiting for assembly. When the order status of the Nth user order in the fourth user order sequence changes from waiting for assembly to being assembled, the Nth user order is determined as the current assembly user order, and the current assembly user order includes the component model of each assembly component in the multiple assembly components;

[0011] For the Nth user order, if N is greater than or equal to 2, obtain the three-dimensional assembly model corresponding to the N-1th user order, and perform the following three-dimensional assembly model update steps: for each assembly component among the multiple assembly components included in the current assembly user order, determine whether the corresponding component model is consistent with the component model of the assembly component in the N-1th user order; if not, determine the component model of the assembly component in the N-1th user order as the component model before the update, determine the component model of the assembly component in the current assembly user order as the component model after the update, match the updated component model in a pre-built assembly component three-dimensional model library to determine the assembly component three-dimensional model that matches the updated component model and use it as the updated assembly component three-dimensional model; replace the assembly component three-dimensional model corresponding to the component model before the update in the three-dimensional assembly model with the updated assembly component three-dimensional model, and obtain the updated three-dimensional assembly model as the three-dimensional assembly model corresponding to the three-dimensional assembly model;

[0012] For the Nth user order, if N is equal to 1, the following three-dimensional assembly model construction steps are performed: according to the component model of each assembly component in the multiple assembly components included in the Nth user order, matching is performed in a pre-constructed assembly component three-dimensional model library to determine an assembly component three-dimensional model that matches the component model of each assembly component, and an assembly component three-dimensional model group corresponding to the multiple assembly components is obtained, wherein each assembly component three-dimensional model is associated with and displayed with the component model of the corresponding assembly component, and the three-dimensional models of each assembly component in the assembly component three-dimensional model group are combined to obtain a three-dimensional assembly model corresponding to the Nth assembly user order;

[0013] Display the three-dimensional assembly model corresponding to the Nth assembly user order on the assembly data display page;

[0014] The assembly data display page also includes multiple indicator values ​​of the three-dimensional assembly model, including the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model, multiple performance parameters of the assembly products corresponding to the three-dimensional assembly model, and the cost of the assembly products corresponding to the three-dimensional assembly model.

[0015] Optionally, the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model is generated by the following steps:

[0016] Obtain a pre-built compatibility test table, which includes multiple configuration schemes of the target electronic product and a compatibility score corresponding to each configuration scheme;

[0017] Matching the component models of multiple assembly components included in the current assembly user order in the compatibility test table to determine whether there is a configuration scheme matching the current assembly user order, and if there is a matching configuration scheme, determining the compatibility score of the matching configuration scheme as the comprehensive matching degree of the three-dimensional models of the multiple assembly components;

[0018] If there is no matching configuration scheme, obtain a historical user order configuration statistics table, which includes multiple historical configuration schemes corresponding to multiple historical user orders and the number of historical user orders corresponding to each historical configuration scheme; match the component models of multiple assembly components included in the current assembly user order in the historical user order configuration statistics table to determine whether there is a matching historical configuration scheme; if there is a matching historical configuration scheme, determine the comprehensive matching degree of the multiple assembly component three-dimensional models included in the three-dimensional assembly model according to the number of historical user orders corresponding to the matching historical configuration scheme;

[0019] If there is no matching historical configuration plan, the component model of each assembly component in the multiple assembly components included in the current assembly user order is sent to the audit terminal, so that the auditor corresponding to the audit terminal inputs the matching degree, and the input matching degree is determined as the comprehensive matching degree of the three-dimensional models of the multiple assembly components included in the three-dimensional assembly model.

[0020] Optionally, the smart large screen is configured with multiple display modes, each display mode corresponds to a comprehensive matching degree interval; and

[0021] The 3D assembly model corresponding to the Nth assembly user order is displayed on the assembly data display page, including:

[0022] A target display mode is determined from multiple display modes according to the comprehensive matching degree of multiple assembly component three-dimensional models included in the three-dimensional assembly model, and the three-dimensional assembly model corresponding to the Nth assembly user order is displayed in the assembly data display page according to the target display mode.

[0023] Optionally, when a simulation parameter adjustment request is received, each performance parameter of the assembled product after adjustment is determined according to the adjustment value of each performance parameter among the multiple performance parameters of the assembled product in the simulation parameter adjustment request; each performance parameter of the assembled product after adjustment is matched in a pre-built three-dimensional model library of assembly components to obtain a three-dimensional model corresponding to each performance parameter after adjustment; each performance parameter of the assembled product after adjustment is input into a pre-trained deep network model to obtain comprehensive analysis information of the assembled product;

[0024] The three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment are displayed in the assembly data display page. The assembly data display page also includes a main screen display window and multiple sub-screen display windows. A main screen display window is used to display the adjustment value of the performance parameter in the simulation parameter adjustment request, and each sub-screen display window is used to display the three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment.

[0025] The present invention has the following beneficial effects:

[0026] 1. By setting a monitoring video display window, and dividing the monitoring video display window into multiple fixed display windows and one mobile display window, it is possible to flexibly display the packaging video as needed. On this basis, when a cargo verification request is received, the target packaging video clip is automatically extracted and entity detection is performed, and the video frame containing the entity positioning box is displayed in the mobile display window. Therefore, the verification personnel can verify according to the content displayed in the mobile display window, and input the verification result information into the smart large screen. As a result, not only the interactive function of the smart large screen is expanded, and the problem of single interactive function in the prior art is overcome, but also the function of the smart large screen is fully utilized in combination with the cargo verification needs in business scenarios. In addition, by integrating the verification function in the smart large screen and through entity detection, the shortcomings of weighing verification are effectively compensated, and the different visual characteristics (such as color, shape, etc.) of goods of different models or types are used to achieve effective verification of wrong goods;

[0027] 2. The 3D assembly model of the previous user order is used to update the 3D assembly model of the next user order, thereby improving the efficiency and accuracy of the assembly process of each user order; determining the comprehensive matching degree of the 3D models of multiple assembly components through different channels is conducive to improving the accuracy of the data; in addition, the assembly data display page displays multiple indicator values ​​of the 3D assembly model, and the smart screen is configured with multiple display modes, which can improve the user's work efficiency and promote the accuracy of decision-making; the simulation parameter adjustment module improves the interactivity between the user and the smart screen;

[0028] 3. The score of the component model to be inspected is obtained by analyzing the parameter error of the component model to be inspected, thereby improving the accuracy and reliability of the score; the image score is obtained through the image type of the component model to be inspected, and the component model to be inspected is analyzed from the appearance, which is helpful for the appearance quality identification of the component model to be inspected and improves the inspection efficiency; the inspection results are made more comprehensive and objective by testing the parameters and appearance of the component model to be inspected; the inspection results are displayed in the production information display window to improve the efficiency of information transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The above and other features, advantages and aspects of the embodiments of the present invention will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0030] Figure 1 It is a flow chart of a production big data interaction method based on a smart large screen of the present invention. DETAILED DESCRIPTION

[0031] The present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0032] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0033] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0034] It should be noted that the modifications of "one" and "plurality" mentioned in the present invention are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0035] The names of the messages or information exchanged between multiple devices of the present invention are only for illustrative purposes, and are not used to limit the scope of these messages or information.

[0036] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0037] like Figure 1 As shown, it is a flow chart of a production big data interaction method based on a smart big screen of the present invention, which specifically includes the following steps:

[0038] Step 101, when the user performs a data dashboard display operation, a production big data page is displayed on the smart big screen, and the production big data page includes multiple data dashboard options, and the multiple data dashboard options include a production data dashboard option, an assembly data dashboard option, and a packaging data dashboard option;

[0039] In some embodiments, the execution subject of the production big data interaction method based on a smart large screen of the present invention can be a smart data display system composed of a background server for controlling the smart large screen and the smart large screen. Among them, the smart large screen is used for data display and interaction, and the background server is used to provide data support and control the smart large screen.

[0040] Among them, the smart big screen can be various electronic screens that support data display and interaction. The smart big screen can be used to display various data. For example, a "data dashboard" virtual button can be displayed. When the user performs a data dashboard display operation, that is, clicks the "data dashboard" virtual button, the production big data page is displayed in the smart big screen, and the production big data page includes multiple data dashboard options. In practice, each data dashboard option can correspond to a virtual button, and the user can select different data dashboard options by clicking the virtual button, so that the smart big screen can display different data. For example, when the user performs a selection operation for the packaging data dashboard option, the packaging data display page corresponding to the packaging data dashboard option is displayed in the smart big screen. Similarly, when the user performs a selection operation for the assembly data dashboard option and the production data dashboard option, the corresponding display page can be displayed.

[0041] Step 102, when the user performs a selection operation for a packaging data dashboard option, a packaging data display page corresponding to the packaging data dashboard option is displayed on the smart large screen, and the packaging data display page includes a monitoring video display window, a first user order sequence whose order status is being packaged, a second user order sequence whose order status is waiting for packaging, and a third user order sequence whose order status is completed packaging. Each user order in the third user order sequence includes an order number, a packaging station number, an order packaging time point, a name and quantity of purchased goods, and a shipping weight; the monitoring video display window includes a plurality of fixed display windows and a mobile display window, and the plurality of fixed display windows correspond to a plurality of packaging stations one by one, and each fixed display window is used to display a real-time packaging video of the corresponding packaging station;

[0042] In some embodiments, the fixed display window corresponds one-to-one to multiple packing stations. For example, the fixed display window 1 corresponds to packing station No. 1 and is fixedly used to display the real-time packing video of packing station No. 1, while the content displayed in the mobile display window can be adjusted according to actual needs.

[0043] In some embodiments, in the display page corresponding to each data dashboard option, user orders can be divided into different sequences according to different order statuses. For example, in the packaging data display page, it can be divided into three sequences, including: a first user order sequence whose order status is being packaged, a second user order sequence whose order status is waiting for packaging, and a third user order sequence whose order status is completed packaging.

[0044] Step 103, when a goods verification request is received, a match is performed in the third user order sequence according to the historical order number included in the goods verification request, a user order matching the historical order number is obtained and determined as the target historical user order, and the verification category included in the goods verification request is determined. If the verification category is wrong goods verification, a corresponding packaging video segment is queried from the packaging video database according to the packaging station number and the order packaging time point included in the target historical user order and used as the target packaging video segment, and entity detection is performed on the target packaging video segment to obtain a video frame sequence containing an entity positioning frame, and the entity positioning frame is used to mark the entity appearing in each video frame in the target packaging video segment; the video frame sequence containing the entity positioning frame and the verification prompt information are displayed in the mobile display window, and the verification prompt information is used to prompt the user to input the verification result information according to the entity positioning frame;

[0045] In practice, an entity detection model can be deployed in the background server, so that the target packaged video clip can be detected frame by frame to obtain the detection result of each frame. The detection result can be an entity positioning frame, which is used to mark the entity appearing in each video frame in the target packaged video clip. Among them, the entity includes various actual goods, including servers, terminal electronic devices, etc. In practice, the entity detection model can be pre-trained so that the entity detection model can identify the entities contained in each frame of the image. According to different usage scenarios or product categories, the entity detection model can be trained in a targeted manner. For example, if the products of a certain enterprise are mainly servers of different models, the entity detection model can be trained in a targeted manner to distinguish servers of different models. Specifically, the training samples can be composed of a large number of server images of different models. The verification prompt information is used to prompt the verification personnel to check the target historical user order according to the detection results, obtain the verification result information and input the verification result information into the smart screen. Among them, the verification result information represents whether there is a wrong product problem in the target historical user order, that is, whether the actual package acquisition is consistent with the goods involved in the order; if it is consistent, there is no wrong product, and if it is inconsistent, there is a wrong product.

[0046] Step 104: If the verification result information indicates that the target historical user order has a wrong product problem, a reissue order for the target historical user order is generated.

[0047] In some embodiments, the categories and quantities of goods involved in the target historical user orders can be compared with the categories and quantities of goods actually packaged to obtain the categories and quantities that need to be reissued, and a reissue order can be generated based on the categories and quantities that need to be reissued and the consignee information involved in the target historical user orders. Further, the priority of the reissue order is set to high priority.

[0048] In some embodiments, by setting a monitoring video display window and dividing the monitoring video display window into multiple fixed display windows and a mobile display window, it is possible to flexibly display the packaging video as needed. On this basis, when a cargo verification request is received, the target packaging video clip is automatically extracted and entity detection is performed, and the video frame containing the entity positioning frame is displayed in the mobile display window. Therefore, the verification personnel can verify according to the content displayed in the mobile display window, and input the verification result information into the smart screen. As a result, not only the interactive function of the smart screen is expanded, and the problem of single interactive function in the prior art is overcome, but also, combined with the cargo verification needs in the business scenario, the function of the smart screen is fully utilized. In addition, by integrating the verification function in the smart screen and through entity detection, the shortcomings of weighing verification are effectively compensated, and the different visual features (such as color, shape, etc.) of goods of different models or types are used to achieve effective verification of wrong goods.

[0049] In some embodiments, in order to further solve the second technical problem described in the background technology section, namely, "the existing smart large screen display mode is single, the interactivity is poor, and the efficiency of solving the problem of wrong orders displayed by the smart large screen is low", some embodiments of the present invention also include:

[0050] When the user performs a selection operation for an assembly data dashboard option, an assembly data display page corresponding to the assembly data dashboard option is displayed on the smart large screen, and the assembly data display page includes a fourth user order sequence whose order status is waiting for assembly. When the order status of the Nth user order in the fourth user order sequence changes from waiting for assembly to being assembled, the Nth user order is determined as the current assembly user order, and the current assembly user order includes the component model of each assembly component in the multiple assembly components;

[0051] In some embodiments, the current assembly user order includes the component model of each assembly component in the multiple assembly components. Specifically, the current assembly user order may be a computer assembly order of user 1, and the multiple assembly components in the computer assembly order of user 1 may be a processor, a motherboard, a memory bar, a solid-state drive, a power supply, and a chassis. The component model of each assembly component may be a component model of the processor i7-K, a component model of the motherboard B660M, a component model of the memory bar 3200MHz, a component model of the solid-state drive M.2, a component model of the power supply RM750x 750W, and a component model of the chassis NZXT.

[0052] For the Nth user order, if N is greater than or equal to 2, obtain the three-dimensional assembly model corresponding to the N-1th user order, and perform the following three-dimensional assembly model update steps: for each assembly component among the multiple assembly components included in the current assembly user order, determine whether the corresponding component model is consistent with the component model of the assembly component in the N-1th user order; if not, determine the component model of the assembly component in the N-1th user order as the component model before the update, determine the component model of the assembly component in the current assembly user order as the component model after the update, match the updated component model in a pre-built assembly component three-dimensional model library to determine the assembly component three-dimensional model that matches the updated component model and use it as the updated assembly component three-dimensional model; replace the assembly component three-dimensional model corresponding to the component model before the update in the three-dimensional assembly model with the updated assembly component three-dimensional model, and obtain the updated three-dimensional assembly model as the three-dimensional assembly model corresponding to the three-dimensional assembly model;

[0053] In some embodiments, a three-dimensional assembly model corresponding to the N-1th user order is obtained from a model database. The three-dimensional assembly model refers to a digital representation created using three-dimensional computer graphics technology, which simulates the assembly process of a product or equipment and the three-dimensional spatial relationship of its components.

[0054] In some embodiments, for the second user order, the three-dimensional assembly model corresponding to the first user order is obtained. It is assumed that the multiple assembly components in the current assembly user order (the second user order) include a processor, a motherboard, and a memory stick. The component model corresponding to each assembly component is i7-K for the processor, B660M for the motherboard, and 3200MHz for the memory stick. Determine whether the component model corresponding to the second user order is consistent with the component model of the first user order. If not, determine the component model of the assembly component in the first user order as the component model before the update, and determine the component model of the assembly component in the second user order as the component model after the update. Match the updated component model in the pre-built assembly component three-dimensional model library to determine the assembly component three-dimensional model that matches the updated component model and use it as the updated assembly component three-dimensional model; replace the assembly component three-dimensional model corresponding to the component model before the update in the three-dimensional assembly model corresponding to the first user order with the updated assembly component three-dimensional model, and obtain the updated three-dimensional assembly model as the three-dimensional assembly model corresponding to the second user order. The 3D assembly model of the previous user order is used to update the 3D assembly model of the subsequent user order, thereby improving the efficiency and accuracy of the assembly process of each user order.

[0055] For the Nth user order, if N is equal to 1, the following three-dimensional assembly model construction steps are performed: according to the component model of each assembly component in the multiple assembly components included in the Nth user order, matching is performed in a pre-constructed assembly component three-dimensional model library to determine an assembly component three-dimensional model that matches the component model of each assembly component, and an assembly component three-dimensional model group corresponding to the multiple assembly components is obtained, wherein each assembly component three-dimensional model is associated with and displayed with the component model of the corresponding assembly component, and the three-dimensional models of each assembly component in the assembly component three-dimensional model group are combined to obtain a three-dimensional assembly model corresponding to the Nth assembly user order;

[0056] In some embodiments, if it is for the first user order, the following three-dimensional assembly model construction steps are performed: according to the first user order, multiple assembly components may include a processor, a power supply, and a chassis, and the component model of each assembly component may be a component model of the processor i5-K, a component model of the power supply 950W, and a component model of the chassis NZXT. Matching is performed in the pre-built assembly component three-dimensional model library to determine the assembly component three-dimensional models that match the component model of the processor, the component model of the power supply, and the component model of the chassis, respectively. Among them, each assembly component three-dimensional model is associated with the component model of the corresponding assembly component, and specifically, the processor three-dimensional model is associated with the component model of the processor. The processor three-dimensional model, the power supply three-dimensional model, and the chassis three-dimensional model are combined to obtain the three-dimensional assembly model corresponding to the first assembly user order.

[0057] Display the three-dimensional assembly model corresponding to the Nth assembly user order on the assembly data display page;

[0058] The assembly data display page also includes multiple indicator values ​​of the three-dimensional assembly model, including the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model, multiple performance parameters of the assembly products corresponding to the three-dimensional assembly model, and the cost of the assembly products corresponding to the three-dimensional assembly model.

[0059] In some embodiments, the assembly data display page also includes multiple index values ​​of the three-dimensional assembly model, and the multiple index values ​​include the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model, multiple performance parameters of the assembly product corresponding to the three-dimensional assembly model, and the cost of the assembly product corresponding to the three-dimensional assembly model. Specifically, among the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model in the multiple index values, the comprehensive matching degree of the three-dimensional models of multiple assembly components can be size matching, structure matching, and function matching. Among the multiple performance parameters of the assembly product corresponding to the three-dimensional assembly model, the multiple performance parameters of the assembly product can be size thickness, processing speed, power parameters, etc., and the multiple performance parameters of the assembly product directly affect the bearing capacity and service life of the product. The cost of the assembly product corresponding to the three-dimensional assembly model can be material cost, manufacturing cost, labor cost, etc. The assembly data display page facilitates users to intuitively understand the various aspects of performance and economic benefits of the assembly product.

[0060] Optionally, the comprehensive matching degree of the three-dimensional models of multiple assembly components included in the three-dimensional assembly model is generated by the following steps:

[0061] Obtain a pre-built compatibility test table, which includes multiple configuration schemes of the target electronic product and a compatibility score corresponding to each configuration scheme;

[0062] In some embodiments, a pre-built compatibility test table is obtained from an electronic product database, and the compatibility test table includes multiple configuration schemes of the target electronic product and the compatibility score corresponding to each configuration scheme. Specifically, the compatibility test table includes multiple configuration schemes of the target electronic product, and the multiple configuration schemes of the target electronic product can be configuration scheme 1 and configuration scheme 2. Configuration scheme 1 can be an operating system (Windows 10), a processor (Intel Core i5), a memory (8GB), and a graphics card (NVIDIA GTX 1050Ti). The compatibility score corresponding to configuration scheme 1 is 95 points. Configuration scheme 2 can be an operating system (macOS Catalina), a processor (Apple M1), a memory (8GB), and a graphics card (AMD Radeon RX5700XT). The compatibility score corresponding to configuration scheme 2 is 90 points.

[0063] Matching the component models of multiple assembly components included in the current assembly user order in the compatibility test table to determine whether there is a configuration scheme matching the current assembly user order, and if there is a matching configuration scheme, determining the compatibility score of the matching configuration scheme as the comprehensive matching degree of the three-dimensional models of the multiple assembly components;

[0064] In some embodiments, if the current assembly user order is the second user order, the component models of multiple assembly components of the second user order are matched in the compatibility test table. If there is a matching configuration scheme and the compatibility score of the matching configuration scheme is 95 points, the comprehensive matching degree of the three-dimensional models of the multiple assembly components corresponding to the second user order is 95%.

[0065] If there is no matching configuration scheme, obtain a historical user order configuration statistics table, which includes multiple historical configuration schemes corresponding to multiple historical user orders and the number of historical user orders corresponding to each historical configuration scheme; match the component models of multiple assembly components included in the current assembly user order in the historical user order configuration statistics table to determine whether there is a matching historical configuration scheme; if there is a matching historical configuration scheme, determine the comprehensive matching degree of the multiple assembly component three-dimensional models included in the three-dimensional assembly model according to the number of historical user orders corresponding to the matching historical configuration scheme;

[0066] In some embodiments, if there is no configuration scheme matching the second user order in the compatibility test table, a historical user order configuration statistics table is obtained from the electronic product configuration database. The historical user order configuration statistics table includes multiple historical configuration schemes corresponding to multiple historical user orders and the number of historical user orders corresponding to each historical configuration scheme. Specifically, the historical user order configuration statistics table may include 60 historical user orders corresponding to historical configuration scheme 1 corresponding to historical user order 1, and 50 historical user orders corresponding to historical configuration scheme 2 corresponding to historical user order 1. The number of historical user orders corresponding to historical configuration scheme 1 corresponding to historical user order 2 is 80, and the number of historical user orders corresponding to historical configuration scheme 2 corresponding to historical user order 2 is 70. The component models of the multiple assembly components included in the second user order are matched in the historical user order configuration statistics table. If there is a historical user order 2 matching the second user order, and the number of historical user orders corresponding to the historical configuration scheme 1 corresponding to the matching historical user order 2 is 80, then the comprehensive matching degree of the three-dimensional models of the multiple assembly components is 80%.

[0067] If there is no matching historical configuration plan, the component model of each assembly component in the multiple assembly components included in the current assembly user order is sent to the audit terminal, so that the auditor corresponding to the audit terminal inputs the matching degree, and the input matching degree is determined as the comprehensive matching degree of the three-dimensional models of the multiple assembly components included in the three-dimensional assembly model.

[0068] In some embodiments, if there is no historical configuration scheme that matches the second user order, the component model of each assembly component in the multiple assembly components included in the second user order is sent to the audit terminal, so that the auditor corresponding to the audit terminal inputs the matching degree. If the matching degree input by the auditor is 70%, the input matching degree is determined as the comprehensive matching degree of 70% of the multiple assembly component three-dimensional models included in the three-dimensional assembly model. Determining the comprehensive matching degree of multiple assembly component three-dimensional models through different approaches is conducive to improving the accuracy of the data.

[0069] Optionally, the smart large screen is configured with multiple display modes, each display mode corresponds to a comprehensive matching degree interval; and

[0070] The 3D assembly model corresponding to the Nth assembly user order is displayed on the assembly data display page, including:

[0071] A target display mode is determined from multiple display modes according to the comprehensive matching degree of multiple assembly component three-dimensional models included in the three-dimensional assembly model, and the three-dimensional assembly model corresponding to the Nth assembly user order is displayed in the assembly data display page according to the target display mode.

[0072] In some embodiments, the smart large screen is configured with multiple display modes, and each display mode corresponds to a comprehensive matching degree interval. Specifically, the smart large screen can be configured with display mode 1, display mode 2, and display mode 3. The comprehensive matching degree interval of display mode 1 is 0%-70% (excluding 70%), the comprehensive matching degree interval of display mode 2 is 70%-90% (excluding 90%), and the comprehensive matching degree interval of display mode 3 is 90%-100%. The three-dimensional assembly model corresponding to the second assembly user order is displayed on the assembly data display page. If the comprehensive matching degree of the three-dimensional models of multiple assembly components in the second assembly user order is 91%, the target display mode is display mode 3, and the three-dimensional assembly model corresponding to the second assembly user order is displayed on the assembly data display page through display mode 3. The multiple display modes configured by the smart large screen can improve the work efficiency of users and promote the accuracy of decision-making.

[0073] Optionally, when a simulation parameter adjustment request is received, each performance parameter of the assembled product after adjustment is determined according to the adjustment value of each performance parameter among the multiple performance parameters of the assembled product in the simulation parameter adjustment request; each performance parameter of the assembled product after adjustment is matched in a pre-built three-dimensional model library of assembly components to obtain a three-dimensional model corresponding to each performance parameter after adjustment; each performance parameter of the assembled product after adjustment is input into a pre-trained deep network model to obtain comprehensive analysis information of the assembled product;

[0074] The three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment are displayed in the assembly data display page. The assembly data display page also includes a main screen display window and multiple sub-screen display windows. A main screen display window is used to display the adjustment value of the performance parameter in the simulation parameter adjustment request, and each sub-screen display window is used to display the three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment.

[0075] In some embodiments, it is assumed that the multiple performance parameters of the electronic device A in the simulation parameter adjustment request may include battery capacity, processor frequency, and screen brightness. On this basis, when the performance parameter is battery capacity, the adjustment value of the performance parameter may be that the battery capacity increases by 500mAh, and the original value of the battery capacity is 4000mAh. When the performance parameter is processor frequency, the adjustment value of the performance parameter may be that the processor frequency increases by 0.2GHz, and the original value of the processor frequency is 2.4GHz. When the performance parameter is screen brightness, the adjustment value of the performance parameter may be that the screen brightness increases by 0 nits, and the original value of the screen brightness is 500 nits. Specifically, each performance parameter of the electronic device A after adjustment is a battery capacity of 4500mAh and a processor speed of 2.6GHz. The three-dimensional model corresponding to each performance parameter of the electronic device A after adjustment is matched in the pre-built assembly component three-dimensional model library, each performance parameter after adjustment corresponds to a three-dimensional model, and multiple performance parameters after adjustment correspond to an overall adjusted three-dimensional model. The pre-trained deep network model is an algorithm based on an artificial neural network. The deep network model is pre-trained with a large number of performance parameters and is used to obtain comprehensive analysis information of the assembled product. The comprehensive analysis information of the assembled product can be the comprehensive advantages and disadvantages analysis information corresponding to each performance parameter after adjustment. The corresponding three-dimensional models after the performance parameters are adjusted can be three-dimensional model 1, three-dimensional model 2, and three-dimensional model 3. The comprehensive analysis information of the assembled product of the electronic device A corresponding to the three-dimensional model 1 can be a comprehensive text description, such as "battery life increased by 10%, battery weight increased by 3 grams, and cost increased by 15%". The comprehensive analysis information of the assembled product of the electronic device A corresponding to the three-dimensional model 2 can be "processor speed increased by 5%, battery life shortened by 7%, and cost increased by 10%". The three-dimensional model 3 corresponds to an overall adjusted three-dimensional model, and the comprehensive analysis information of the assembled product of the corresponding electronic device A can be "battery life increased by 3%, battery weight increased by 3 grams, cost increased by 25%, and processor speed increased by 5%".

[0076] In some embodiments, the three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment are displayed in the assembly data display page, and the assembly data display page also includes a main screen display window and multiple sub-screen display windows. Specifically, a main screen display window is used to display, for example, "When the performance parameter is battery capacity, the adjustment value of the performance parameter can be that the battery capacity increases by 500mAh, and the original value of the battery capacity is 4000mAh". Multiple sub-screen display windows may include sub-screen display window 1, sub-screen display window 2, and sub-screen display window 3. Sub-screen display window 1 can be used to display three-dimensional model 1 and "battery life increased by 10%, battery weight increased by 3 grams, and cost increased by 15%". Sub-screen display window 2 can be used to display three-dimensional model 2 and "processor speed increased by 5%, battery life shortened by 7%, and cost increased by 10%". Sub-screen display window 3 can be used to display three-dimensional model 3 and "battery life increased by 3%, battery weight increased by 3 grams, cost increased by 25%, and processor speed increased by 5%". Simulation parameter adjustment is the process of users adjusting the performance parameters of assembled products and observing the adjusted effects in real time, which enhances user participation and interactivity and helps users to have a deeper understanding of the complex relationship between product performance and structure.

[0077] In some embodiments, the three-dimensional assembly model of the previous user order is used to update the three-dimensional assembly model of the subsequent user order, thereby improving the efficiency and accuracy of the assembly process of each user order; determining the comprehensive matching degree of multiple three-dimensional models of assembly components through different approaches is conducive to improving the accuracy of the data; in addition, the assembly data display page displays multiple indicator values ​​of the three-dimensional assembly model, and the smart large screen is configured with multiple display modes, which can improve the user's work efficiency and promote the accuracy of decision-making; the simulation parameter adjustment module enhances the interactivity between the user and the smart large screen.

[0078] In some embodiments, in order to further solve the technical problem 3 described in the background technology section, that is, "the smart large screen has no reasonable sampling process and sampling standard for the sampling of components, resulting in low sampling efficiency, randomness and accidental sampling results, which in turn affects the accuracy of the sampling results", some embodiments of the present invention also include:

[0079] Step 1: When the user performs a selection operation on a production data dashboard option, a production data display page corresponding to the production data dashboard option is displayed on the smart screen, and the production data display page includes a production information display window and an information pop-up window;

[0080] Step 2: When a sampling inspection request for an assembly component is received, a query is made in the finished product information database according to the assembly component model corresponding to the production batch in the sampling inspection request to determine whether there is an assembly component model corresponding to the production batch in the sampling inspection request; wherein the assembly component information database includes multiple assembly component models, the production batch of each assembly component model, and the number of components corresponding to the production batch of each assembly component model; if not, a query error prompt message is generated, and an information pop-up window is used to display the query error prompt message; if so, the assembly component model corresponding to the production batch in the sampling inspection request is determined as the component model to be sampled; according to the number of components of the component model to be sampled, the sampling number of the component model to be sampled is determined; a target number of component models to be sampled are selected from the number of components of the component model to be sampled to form a component model group to be sampled, wherein the target number is equal to the sampling number;

[0081] Step three, obtaining multiple parameter values ​​of each component model to be inspected in the component model group to be inspected, calculating each parameter value in the multiple parameter values ​​and the standard parameter value corresponding to each parameter value, and obtaining a parameter error group of each component model to be inspected; obtaining a pre-configured first scoring table, the first scoring table including multiple parameter errors, and a score corresponding to each parameter error, obtaining a score group of each component model to be inspected by querying the parameter error group of each component model to be inspected in the first scoring table, calculating the score group of each component model to be inspected, and obtaining a comprehensive parameter score of each component model to be inspected;

[0082] Step 4: Obtain an image group of each component model to be inspected in the component model group to be inspected, input the image group of each component model to be inspected into a pre-trained deep learning network, obtain the image type of each component model to be inspected, and determine the image score of each component model to be inspected according to the image type of each component model to be inspected; configure weights for the comprehensive parameter score and image score of the component model to be inspected, respectively, calculate the comprehensive parameter score of each component model to be inspected and the image score of each component model to be inspected by the weights, and obtain the total score of each component model to be inspected;

[0083] Step five, comparing the total score of each component model to be inspected with the preset standard score threshold of each component model to be inspected; if the total score of the component model to be inspected is greater than or equal to the preset standard score threshold, generating qualified prompt information of the component model to be inspected; if the total score of the component model to be inspected is less than the preset standard score threshold, generating unqualified prompt information of the component model to be inspected; and respectively counting the first quantity of the component models to be inspected corresponding to the generated qualified prompt information and the second quantity of the component models to be inspected corresponding to the generated unqualified prompt information, and displaying the first quantity and the second quantity in the production information display window.

[0084] In some embodiments, assuming that the sampling request is to sample terminal electronic device A with a production batch of 2024-5-25, the terminal electronic device A with a production batch of 2024-5-25 is queried in the finished product information library. If it does not exist, a query error prompt message is generated, and the error prompt message may be "query error, the terminal electronic device A with a production batch of 2024-5-25 is not found". If it exists, the terminal electronic device A with a production batch of 2024-5-25 is determined as the component model to be sampled, and the number of components of the component model to be sampled is queried at the same time. If the number of components is 500, 50 component models to be sampled are sampled according to the preset sampling rule (10%) to form a component model group to be sampled, wherein the target number corresponds to the sampling number, for example, if the sampling number is 50, then the target number is also 50.

[0085] In some embodiments, multiple parameter values ​​of each component model to be sampled are obtained from the component model parameter record, assuming that the component model group to be sampled includes but is not limited to terminal electronic device A1 and terminal electronic device A2. The multiple parameter values ​​of terminal electronic device A1 include parameter value 1 of 99.8, parameter value 2 of 20.45, and parameter value 3 of 0.045. The multiple parameter values ​​of terminal electronic device A2 include parameter value 1 of 100, parameter value 2 of 20.5, and parameter value 3 of 0.05. The standard parameter value of parameter value 1 is 100, the standard parameter value of parameter value 2 is 20.5, and the standard parameter value of parameter value 3 is 0.05. The calculation process of the terminal electronic device A1 is: the error of parameter value 1 is equal to 0.2 (|99.8-100|=0.2), the error of parameter value 2 is equal to 0.05 (|20.45-20.5|=0.05), and the error of parameter value 3 is equal to 0.005 (|0.045-0.05|=0.005). The parameter error group of the terminal electronic device A1 is parameter value 1 is 0.2, parameter value 2 is 0.05, and parameter value 3 is 0.005. Similarly, the terminal electronic device A2 is calculated to obtain the parameter error group of the terminal electronic device A2. A pre-configured first scoring table is obtained from the standard scoring database. The first scoring table includes multiple parameter errors, and the score corresponding to each parameter error, for example, the parameter error of parameter value 1 is 0 and the score corresponding to the parameter error is 100 points, the parameter error of parameter value 1 is 0.2 and the score corresponding to the parameter error is 90 points, and the parameter error of parameter value 2 is 0.02 and the score corresponding to the parameter error is 90 points. The scoring group of terminal electronic device A1 and the scoring group of terminal electronic device A2 are obtained by query. Assuming that the scoring group of terminal electronic device A1 is 90, 98, and 97, the comprehensive parameter score of terminal electronic device A1 is 95 points (90+98+97=285÷3=95). Similarly, the comprehensive parameter score of terminal electronic device A2 is calculated to be 99.7 points.

[0086] In some embodiments, an image group of each component model to be sampled in the component model group to be sampled is obtained from the finished component image library, and the image group of the terminal electronic device A1 and the image group of the terminal electronic device A2 are input into a pre-trained deep learning network, which is a convolutional neural network, which has been pre-trained with a large number of component models, and is used to obtain the image type of the component model, and the image type includes slight flaws, flawless, and defects. The image scores corresponding to slight flaws, flawless, and defects are 98, 100, and 92, respectively. A weight of 45% is configured for the comprehensive parameter score of the component model to be sampled, and a weight of 55% is configured for the image score of the component model to be sampled. If the image type of the terminal electronic device A1 is flawless and the image type of the terminal electronic device A2 is slightly flawed, the total score of the terminal electronic device A1 is 97.75 points (45%×95+55%×100=97.75), and similarly, the total score of the terminal electronic device A2 is 98.765 points. In some embodiments, if the standard score of terminal electronic device A is 98.5 points, terminal electronic device A2 generates qualified prompt information of terminal electronic device A2, and the qualified prompt information may be "terminal electronic device A2 is qualified". Terminal electronic device A1 generates unqualified prompt information of terminal electronic device A1, and the unqualified prompt information may be "terminal electronic device A1 is unqualified". Assuming that there are 50 component models to be inspected in the group of component models to be inspected, the number of qualified prompt information generated is 48, and the number of unqualified prompt information generated is 2, the content of the production information display window may be "the number of terminal electronic devices A sampled for production batch 2024-5-25 is 50, 48 are qualified, and 2 are unqualified".

[0087] In these embodiments, the score of the component model to be inspected is obtained by analyzing the parameter error of the component model to be inspected, thereby improving the accuracy and reliability of the score; the image score is obtained by the image type of the component model to be inspected, and the component model to be inspected is analyzed from the appearance, which helps to identify the appearance quality of the component model to be inspected and improves the inspection efficiency; the inspection results are made more comprehensive and objective by testing the parameters and appearance of the component model to be inspected; the inspection results are displayed in the production information display window to improve the efficiency of information transmission.

[0088] The above descriptions are only some preferred embodiments of the present invention and the explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but also should cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) to form a technical solution.

Claims

1. A production big data interaction method based on a smart big screen, characterized in that: include: When the user performs a data dashboard display operation, a production big data page is displayed on the smart big screen, and the production big data page includes multiple data dashboard options, including a production data dashboard option, an assembly data dashboard option, and a packaging data dashboard option; When the user performs a selection operation for the packaging data dashboard option, the packaging data display page corresponding to the packaging data dashboard option is displayed on the smart large screen, and the packaging data display page includes a monitoring video display window, a first user order sequence whose order status is being packaged, a second user order sequence whose order status is waiting for packaging, and a third user order sequence whose order status is completed packaging. Each user order in the third user order sequence includes an order number, a packaging station number, an order packaging time point, a name and quantity of purchased goods, and a shipping weight; the monitoring video display window includes a plurality of fixed display windows and a mobile display window, and the plurality of fixed display windows correspond to a plurality of packaging stations one by one, and each fixed display window is used to display a real-time packaging video of the corresponding packaging station; When a goods verification request is received, a match is performed in the third user order sequence according to the historical order number included in the goods verification request, a user order matching the historical order number is obtained and determined as the target historical user order, and the verification category included in the goods verification request is determined. If the verification category is wrong goods verification, a corresponding packaging video segment is queried from a packaging video database according to the packaging station number and the order packaging time point included in the target historical user order and used as the target packaging video segment, and entity detection is performed on the target packaging video segment to obtain a video frame sequence containing an entity positioning frame, wherein the entity positioning frame is used to mark the entity appearing in each video frame in the target packaging video segment; the video frame sequence containing the entity positioning frame and verification prompt information are displayed in the mobile display window, wherein the verification prompt information is used to prompt the user to input verification result information according to the entity positioning frame; If the verification result information indicates that the target historical user order has a wrong product problem, a reissue order for the target historical user order is generated; When the user performs a selection operation for an assembly data dashboard option, an assembly data display page corresponding to the assembly data dashboard option is displayed on the smart large screen, wherein the assembly data display page includes a fourth user order sequence whose order status is waiting for assembly, and when the order status of the Nth user order in the fourth user order sequence changes from waiting for assembly to being assembled, the Nth user order is determined as the current assembly user order, and the current assembly user order includes the component model of each assembly component in the plurality of assembly components; For the Nth user order, if N is greater than or equal to 2, obtain the three-dimensional assembly model corresponding to the N-1th user order, and perform the following three-dimensional assembly model update steps: for each assembly component among the multiple assembly components included in the current assembly user order, determine whether the corresponding component model is consistent with the component model of the assembly component in the N-1th user order; if not, determine the component model of the assembly component in the N-1th user order as the component model before the update, determine the component model of the assembly component in the current assembly user order as the component model after the update, match the updated component model in a pre-built assembly component three-dimensional model library to determine the assembly component three-dimensional model that matches the updated component model and use it as the updated assembly component three-dimensional model; replace the assembly component three-dimensional model corresponding to the component model before the update in the three-dimensional assembly model with the updated assembly component three-dimensional model, and obtain the updated three-dimensional assembly model as the three-dimensional assembly model corresponding to the three-dimensional assembly model of the Nth user order; For the Nth user order, if N is equal to 1, the following three-dimensional assembly model construction steps are performed: according to the component model of each assembly component in the multiple assembly components included in the Nth user order, matching is performed in a pre-constructed assembly component three-dimensional model library to determine an assembly component three-dimensional model that matches the component model of each assembly component, and an assembly component three-dimensional model group corresponding to the multiple assembly components is obtained, wherein each assembly component three-dimensional model is associated with and displayed with the component model of the corresponding assembly component, and the respective assembly component three-dimensional models in the assembly component three-dimensional model group are combined to obtain a three-dimensional assembly model corresponding to the Nth user order; Displaying the three-dimensional assembly model corresponding to the Nth user order on the assembly data display page; The assembly data display page also includes multiple index values ​​of the three-dimensional assembly model, wherein the multiple index values ​​include comprehensive matching degrees of three-dimensional models of multiple assembly components included in the three-dimensional assembly model, multiple performance parameters of assembly products corresponding to the three-dimensional assembly model, and costs of assembly products corresponding to the three-dimensional assembly model; When the user performs a selection operation on a production data dashboard option, the production data display page corresponding to the production data dashboard option is displayed on the smart large screen, and the production data display page includes a production information display window and an information pop-up window.

2. The production big data interaction method based on the smart big screen according to claim 1 is characterized in that: The comprehensive matching degree of the multiple assembly component three-dimensional models included in the three-dimensional assembly model is generated by the following steps: Obtaining a pre-built compatibility test table, wherein the compatibility test table includes multiple configuration schemes of the target electronic product and a compatibility score corresponding to each configuration scheme; Matching the component models of the multiple assembly components included in the current assembly user order in the compatibility test table to determine whether there is a configuration scheme that matches the current assembly user order, and if there is a matching configuration scheme, determining the compatibility score of the matching configuration scheme as the comprehensive matching degree of the three-dimensional models of the multiple assembly components; If there is no matching configuration scheme, obtain a historical user order configuration statistics table, wherein the historical user order configuration statistics table includes multiple historical configuration schemes corresponding to multiple historical user orders and the number of historical user orders corresponding to each historical configuration scheme; Matching the component models of multiple assembly components included in the current assembly user order in the historical user order configuration statistics table to determine whether there is a matching historical configuration scheme, and if there is a matching historical configuration scheme, determining the comprehensive matching degree of the multiple assembly component three-dimensional models included in the three-dimensional assembly model according to the number of historical user orders corresponding to the matching historical configuration scheme; If there is no matching historical configuration plan, the component model of each assembly component in the multiple assembly components included in the current assembly user order is sent to the review terminal, so that the reviewer corresponding to the review terminal inputs the matching degree, and the input matching degree is determined as the comprehensive matching degree of the multiple assembly component three-dimensional models included in the three-dimensional assembly model.

3. The production big data interaction method based on the smart big screen according to claim 2 is characterized in that: The smart large screen is configured with multiple display modes, and each display mode corresponds to a comprehensive matching degree interval; as well as The displaying of the three-dimensional assembly model corresponding to the Nth user order on the assembly data display page includes: A target display mode is determined from multiple display modes according to the comprehensive matching degree of multiple assembly component three-dimensional models included in the three-dimensional assembly model, and the three-dimensional assembly model corresponding to the Nth user order is displayed in the assembly data display page according to the target display mode.

4. The production big data interaction method based on the smart big screen according to claim 1 is characterized in that: Also includes: When a simulation parameter adjustment request is received, each performance parameter of the assembly product after adjustment is determined according to the adjustment value of each performance parameter among the multiple performance parameters of the assembly product in the simulation parameter adjustment request; each performance parameter of the assembly product after adjustment is matched in the pre-built assembly component three-dimensional model library to obtain a three-dimensional model corresponding to each performance parameter after adjustment; each performance parameter of the assembly product after adjustment is input into a pre-trained deep network model to obtain comprehensive analysis information of the assembly product; The three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment are displayed in the assembly data display page, and the assembly data display page also includes a main screen display window and multiple sub-screen display windows. The main screen display window is used to display the adjustment value of the performance parameter in the simulation parameter adjustment request, and each sub-screen display window is used to display the three-dimensional model and comprehensive analysis information of the assembly product corresponding to each performance parameter after adjustment.

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