Method for generating visual board according to individual requirements of industrial user and storage medium

Abstract

The invention relates to a method for generating a visual billboard according to personalized requirements of enterprise users. The method comprises the following steps: receiving a component creation instruction issued by a user and generating a corresponding component to a corresponding position of a billboard simulation display area; receiving a component editing instruction issued by a user, and associating a data source corresponding to the user to the component according to the component display data editing instruction; and receiving a visual board generation instruction and generating the component entity in the visual board, so that the data on the component entity and the corresponding data source file are associated in real time so as to be updated in real time according to the data change in the data source file. According to the invention, different components are dragged to the working area, data source setting, appearance setting and width and height setting are carried out on the components, enterprise data visualization billboards are rapidly achieved with extremely low cost, billboard business appeals and personalized configuration requirements of different enterprises can be met, and the invention has the advantages of fast deployment, low cost and high convenience, and has wide application prospect.

Description

technical field [0001] The invention belongs to the technical field of intelligent manufacturing, and relates to a method and a storage medium for generating a visual kanban according to individual needs of industrial users. Background technique [0002] Intelligent manufacturing, also known as Industry 4.0, is Internet + manufacturing; under the background of Industry 4.0, enterprises use the cloud platform to improve production management efficiency; enterprise visual kanban is one of the important performances of traditional enterprises after the cloud platform, With the development of the enterprise, the data grows exponentially. Through data analysis, the historical data of the enterprise and the increasing incremental data can be analyzed in real time, data mining, and market forecasting, and then the correct decision-making ahead of competitors can be made, which is enough to give Enterprises bring huge benefits. At the same time, the process of data visualization ca...

AI Technical Summary

Problems solved by technology

[0006] However, if an enterprise wants to build a set of data visualization Kanban: it needs to invest a lot of R&D personnel, designers, data analysts, time costs, and high technical threshold. After the Kanban is developed, the model is relatively fixed and inflexible. It is difficult to meet the different needs of various enterprises at the same time

In addition, building a data visualization kanban is a very complicated task that requires very professional personnel to build. The data, programs, and underlying technologies involved are very complicated. General industrial enterprise personnel usually do not have these professionals, and even if they are built, it is very difficult. It may not be the ideal visual kanban for users, that is, the supply is not what they want, and different types of digital kanbans with different data cannot be built according to the needs of enterprise users. Change the type, form, layout, etc. of the visual kanban according to the different requirements of the segment, making the data visualization kanban extremely mechanical

In addition, since the data visualization Kanban is built by the corresponding software company A for enterprise user B, software enterprise A is not familiar with the usage and habits of enterprise user B, so software enterprise A cannot well build a more accurate version according to the operating habits of enterprise user B. The data visualization kanban that fits enterprise user B leads to a low degree of fit between enterprise user B and the data visualization kanban, which in turn leads to poor experience and satisfaction of enterprise user B, and enterprise user B cannot feel the sense of accomplishment built by himself

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