Heat treatment industry data analysis system based on big data analysis

Abstract

The invention discloses a heat treatment industry data analysis system based on big data analysis, which relates to the field of big data, and comprises a data acquisition module, a data analysis module, a project setting module, a comprehensive evaluation module and a data storage module, classifying the collected industry information of the heat treatment industry; the data analysis module is used for periodically performing market analysis, product analysis and audience analysis on the data classified by the data acquisition module; according to the heat treatment industry data analysis system based on big data analysis, data in a heat treatment industry is collected in real time, analysis is carried out in combination with regional differences, user demands and market changes are known, enterprises can be helped to understand the development of the industry, and the analysis efficiency of the heat treatment industry is improved. Therefore, an enterprise can control the development trend of the industry, especially predict and grasp the risk, the development of the enterprise is facilitated, and the method has a good application prospect.

Description

Technical Field

[0001] The present invention relates to the field of heat treatment industry, and particularly to an analysis system for heat treatment industry data based on big data analysis. Background Art

[0002] Heat treatment refers to a metal hot working process in which materials in a solid state obtain the expected microstructure and properties through heating, holding, and cooling. In the process of progressing from the Stone Age to the Bronze Age and the Iron Age, the role of heat treatment has gradually been recognized by people.

[0003] With the increasing diversification and complexity of social industries, as well as the drastic changes and diverse and rapid changes in the external environment, it has become increasingly complex and important to control the development trend of industries, especially risk prediction and control. In response to the needs of social development and a stable economic environment, it is necessary to timely understand and adjust the risk trends faced by each industry. Effectively obtaining and avoiding risks is one of the important development elements for the development of the entire industry and even the whole society.

[0004] The invention patent with the publication number of CN115658757A and the patent name of a big data analysis system based on heat treatment equipment records a big data analysis system based on heat treatment equipment, including a time series data acquisition module, a data analysis and processing module, and a heat treatment data display module. The time series data acquisition module is used to collect on-site data of factory production. The data analysis and processing module is used to analyze the data of complex or repetitive work in workshop management. The heat treatment data display module is used to display the data analyzed in the data analysis and processing module. The time series data acquisition module and the data analysis and processing module are electrically connected, and the data analysis and processing module and the heat treatment data display module are electrically connected. The time series data acquisition module includes a sensor acquisition module, a time series data storage module, and a time series data transmission module. The data analysis and processing module includes a time series data receiving module, a database module, a data conversion module, and a transmission module. The present invention has the characteristics of reducing the data processing volume and improving the analysis speed.

[0005] The system described in the above patent has certain drawbacks when in use. The above solution mainly monitors the equipment data within the enterprise. However, during the daily operation of the enterprise, the understanding of external information is insufficient, and it is impossible to fully control the development trend of the industry, especially risk prediction and control. Therefore, it leads to insufficient ability to accurately judge industry risks, making it difficult to make risk judgments based on industry dynamic data and information, and unable to meet people's requirements.

[0006] Therefore, in view of the above, the inventor, based on rich experience in design, development and actual production in the relevant industry for many years, studied and improved the existing structure and deficiencies, and provided an analysis system for heat treatment industry data based on big data analysis, aiming to achieve a more practical value. Summary of the Invention

[0007] To solve the problem in the above-mentioned background technology that the existing solutions mainly supervise the equipment data within the enterprise, but during the daily operation of the enterprise, the understanding of external information is insufficient, and it is impossible to fully grasp the development trend of the industry, especially risk prediction and control. Therefore, the ability to accurately judge industry risks is insufficient, and it is difficult to make risk judgments based on industry dynamic data and information, which does not meet the usage requirements of people. The present invention provides an analysis system for heat treatment industry data based on big data analysis.

[0008] To achieve the above object, the present invention adopts the following technical solutions: An analysis system for heat treatment industry data based on big data analysis, including a data collection module, a data analysis module, a project establishment module, a comprehensive evaluation module, and a data storage module: Data collection module: used to periodically collect information in the heat treatment industry and classify the collected heat treatment industry information; Data analysis module: used to periodically conduct market analysis, product analysis, and audience analysis on the data classified by the data collection module; Project establishment module: used to assist enterprises in establishing new product projects according to the analysis results of the data analysis module; Comprehensive evaluation module: used to periodically score all established projects and sort the new product projects according to the scores from high to low; Data storage module: used to store the data collected by the data collection module, the new product projects established by the project establishment module, and the evaluation results of the comprehensive evaluation module.

[0009] Preferably, classifying the collected heat treatment industry information includes the following steps: S1. Establish a data warehouse and classify the data collected by the data collection module according to regions; S2. Establish a data sub-warehouse for secondary classification to obtain product information, and classify the data of the same model products into the data sub-warehouse; S3. Extract the product model data, parameter data, sales data, and evaluation data stored in the data sub-warehouse, and display the data in the data sub-warehouse in the form of charts.

[0010] Preferably, when the data analysis module conducts market analysis, it conducts sales volume analysis and price analysis. When conducting market analysis, it first divides the data sub-warehouse into levels, and analyzes the changing trend of the market share of the sales volume of products of different brands in different levels with price fluctuations and the market saturation.

[0011] Preferably, when the data analysis module conducts product analysis, it conducts product comparison analysis, product positioning analysis and product sales analysis. The product comparison analysis is the evaluation of all products of the same level by users to obtain user needs.

[0012] Preferably, the product positioning analysis is the inherent impression of users on products of different brands or products of the same level.

[0013] Preferably, the product sales analysis is the reason why users purchase or abandon the purchase of products.

[0014] Preferably, the audience analysis includes purchase channel analysis and purchase population analysis. The purchase population analysis is used to analyze the characteristic information of users and locate the characteristics of the audience population. The purchase channel analysis is used to analyze the ways for people in different regions to purchase the same type of products.

[0015] Preferably, the project establishment module counts the results analyzed by the data analysis module and displays them in the form of a table. The displayed content includes the sales plans of the N groups of existing products with the highest profits in different regions, the requirements for the same type of products in different regions, the acceptance degree of the same type of products in different regions, the reasons for users in different regions to purchase at different stages, the locations of the purchase population in different regions, and the sales ratios of different purchase channels of products in different regions.

[0016] Preferably, the comprehensive evaluation module uses the weighted scoring method for scoring. The weight indicators of the weighted scoring method include project cost, project success rate, project profit and project cycle. The calculation formula is as follows:

[0017] Among them, is the number of weight indicators, is the score of the i-th weight, is the proportion of the i-th weight.

[0018] Preferably, the data storage module periodically compares and checks for duplicate data and clears the duplicate data.

[0019] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention describes an analysis system for heat treatment industry data based on big data analysis, which collects data in the heat treatment industry in real time and conducts analysis in combination with regional differences to understand user needs and market changes. It can help enterprises gain in-depth understanding of this industry, thereby enabling enterprises to master the development trend of the industry, especially risk prediction and control, which is beneficial to the development of enterprises and has good application prospects.

[0020] 2. The present invention describes an analysis system for heat treatment industry data based on big data analysis, which records a data analysis module. The data analysis module conducts market analysis, product analysis, and audience analysis on the industry for comprehensive analysis, which can help enterprises understand industry changes and needs, and can help enterprises better formulate projects and make decisions, having good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is the system structure block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0024] Embodiment 1 Refer to Figure 1 , an analysis system for heat treatment industry data based on big data analysis, including a data acquisition module, a data analysis module, a project establishment module, a comprehensive evaluation module, and a data storage module: Data acquisition module: used to periodically collect information in the heat treatment industry and classify the collected heat treatment industry information; Data analysis module: used to periodically conduct market analysis, product analysis, and audience analysis on the data classified by the data acquisition module; Project establishment module: used to assist enterprises in new product project establishment according to the analysis results of the data analysis module; Comprehensive evaluation module: used to periodically score all established projects and sort the new product establishment projects according to the scores from high to low; Data storage module: used to store the data collected by the data collection module, the new product establishment established by the project establishment module, and the evaluation results of the comprehensive evaluation module.

[0025] The present invention describes an analysis system for heat treatment industry data based on big data analysis, which collects data in the heat treatment industry in real time, analyzes it in combination with regional differences, understands user needs and market changes, can help enterprises gain an in-depth understanding of this industry, so that enterprises can control the development trend of the industry, especially risk prediction and control, which is beneficial to the development of enterprises and has good application prospects.

[0026] The classification of the collected heat treatment industry information includes the following steps: S1. Establish a data warehouse and classify the data collected by the data collection module according to regions; S2. Establish a data sub-warehouse for secondary classification to obtain product information, and classify the data of the same model products into the data sub-warehouse; S3. Extract the product model data, parameter data, sales data and evaluation data stored in the data sub-warehouse, and display the data in the data sub-warehouse in the form of charts.

[0027] When the data analysis module conducts market analysis, it conducts sales analysis and price analysis. When conducting market analysis, it first divides the data sub-warehouse into levels, and analyzes the changing trends of the market share of the sales volume of different brand products in different levels with price fluctuations and the market saturation.

[0028] When the data analysis module conducts product analysis, it conducts product comparison analysis, product positioning analysis and product sales analysis. The product comparison analysis is the evaluation of all products at the same level by users to obtain user needs.

[0029] The product positioning analysis is the inherent impression of users on different brand products or products at the same level.

[0030] The product sales analysis is the reason why users buy or give up buying products.

[0031] The audience analysis includes purchase channel analysis and purchase population analysis. The purchase population analysis is used to analyze the characteristic information of users and locate the characteristics of the audience population. The purchase channel analysis is used to analyze the ways for people in different regions to purchase similar products.

[0032] The project establishment module counts the results analyzed by the data analysis module and understands them in the form of a table, so that enterprises can control the development trend of the industry, especially risk prediction and control, which is beneficial to the development of enterprises and has good application prospects.

[0033] Classifying the collected heat treatment industry information includes the following steps: S1. Establish a data warehouse and classify the data collected by the data collection module according to regions; S2. Establish a data sub-warehouse, conduct secondary classification, obtain product information, and classify the data of products of the same model into the data sub-warehouse; S3. Extract the product model data, parameter data, sales data, and evaluation data stored in the data sub-warehouse, and display the data in the data sub-warehouse in the form of charts.

[0034] When the data analysis module conducts market analysis, it conducts sales analysis and price analysis. When conducting market analysis, it first divides the data sub-warehouse into levels, and analyzes the changing trend of the market share of the sales volume of products of different brands in different levels with price fluctuations and the market saturation.

[0035] When the data analysis module conducts product analysis, it conducts product comparison analysis, product positioning analysis, and product sales analysis. The product comparison analysis is the evaluation of all products of the same level by users to obtain user needs.

[0036] The product positioning analysis is the inherent impression of users on products of different brands or products of the same level.

[0037] The product sales analysis is the reason why users purchase or give up purchasing products.

[0038] The audience analysis includes purchase channel analysis and purchase population analysis. The purchase population analysis is used to analyze the characteristic information of users and locate the characteristics of the audience population. The purchase channel analysis is used to analyze the ways for people in different regions to purchase the same type of products.

[0039] The project establishment module counts the results analyzed by the data analysis module and presents them in the form of a table

[0040] Among them, is the number of weight indicators, is the score of the i-th weight, is the proportion of the i-th weight.

[0041] The data storage module periodically conducts data comparison and duplicate checking to clear duplicate data.

[0042] The present invention describes an analysis system for heat treatment industry data based on big data analysis. It describes a data analysis module. The data analysis module conducts market analysis, product analysis, and audience analysis on the industry, conducts comprehensive analysis, can help enterprises understand the changes and needs of the industry, can help enterprises better formulate projects and make decisions, and has good application prospects.

[0043] Example 2 An analysis system for heat treatment industry data based on big data analysis. When in use, The data acquisition module periodically collects information of the heat treatment industry daily, classifies the collected heat treatment industry information, establishes a data warehouse during classification, classifies the data collected by the data acquisition module according to regions; establishes a data sub-warehouse for secondary classification to obtain product information, and classifies the data of the same model products into the data sub-warehouse; extracts the product model data, parameter data, sales data and evaluation data stored in the data sub-warehouse, and displays the data in the data sub-warehouse in the form of charts;

[0044] The project establishment personnel log in to the project establishment module to perform the project establishment steps. At this time, the data acquisition module displays the data in the data sub-warehouse in the form of charts for the project establishment personnel to view. At the same time, the data analysis module is started. When the data analysis module conducts market analysis, it conducts sales volume analysis and price analysis. When conducting market analysis, it first divides the data sub-warehouse into levels, and analyzes the changing trend of the market share of the sales volume of different brand products in different levels with price fluctuations and the market saturation; when the data analysis module conducts product analysis, it conducts product comparison analysis, product positioning analysis and product sales analysis. The product comparison analysis is the evaluation of all products of the same level by users to obtain user needs; the product positioning analysis is the inherent impression of users on different brand products or products of the same level; the product sales analysis is the reason why users buy or give up buying products; the audience analysis includes purchase channel analysis and purchase population analysis. The purchase population analysis is used to analyze the characteristic information of users and locate the characteristics of the target population. The purchase channel analysis is used to analyze the ways for people in different regions to purchase similar products;

[0045] The analysis results are displayed in the form of charts. At this time, the project establishment personnel can directly view the information, and then specify the corresponding area to sell products of the corresponding level according to the analysis results, and allocate the corresponding channels and product quantities to achieve the reasonable distribution of goods, thereby avoiding the accumulation of goods.

[0046] After the project establishment personnel formulate a complete project, at this time, the comprehensive evaluation module uses the weight scoring method for scoring, and sends the scoring results and project content to the corresponding decision-making personnel for final decision-making.

[0047] Conducting a comprehensive analysis of the entire industry can help enterprises understand the changes and needs of the industry, help enterprises better formulate projects and make decisions, and has good application prospects.

[0048] The above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, making equivalent substitutions or changes, shall be covered by the protection scope of the present invention.

Claims

1. An analysis system for heat treatment industry data based on big data analysis, characterized in that: include: Data collection module: used to periodically collect information about the heat treatment industry and classify the collected information about the heat treatment industry; Data analysis module: used to periodically conduct market analysis, product analysis and audience analysis on the data classified by the data collection module; Project establishment module: used to assist enterprises in establishing new product projects based on the analysis results of the data analysis module; Comprehensive evaluation module: used to periodically score all projects and sort new product projects according to their scores; Data storage module: used to store the data collected by the data acquisition module, the new product projects established by the project establishment module, and the evaluation results of the comprehensive evaluation module.

2. The heat treatment industry data analysis system based on big data analysis according to claim 1, characterized in that: Classifying the collected heat treatment industry information includes the following steps: S1. Establish a data warehouse and classify the data collected by the data collection module according to regions; S2. Establish a data sub-warehouse, perform secondary classification, obtain product information, and classify the data of products of the same model into the data sub-warehouse; S3. Extract product model data, parameter data, sales data and evaluation data stored in the data sub-warehouse, and display the data in the data sub-warehouse in the form of charts.

3. The heat treatment industry data analysis system based on big data analysis according to claim 2, characterized in that: The data analysis module conducts sales volume analysis and price analysis when conducting market analysis. When conducting market analysis, the data sub-warehouse is first divided into levels, and the market share of sales volume of different brands of products at different levels is analyzed as the price fluctuates and the market saturation.

4. The analysis system for heat treatment industry data based on big data analysis according to claim 1, characterized in that: The data analysis module performs product comparison analysis, product positioning analysis and product sales analysis when performing product analysis. The product comparison analysis is the user's evaluation of all products of the same level to obtain user needs.

5. The heat treatment industry data analysis system based on big data analysis according to claim 4, characterized in that: The product positioning analysis is the user's inherent impression of products of different brands or products of the same level.

6. The heat treatment industry data analysis system based on big data analysis according to claim 4, characterized in that: The product sales analysis is the reasons why users purchase or give up purchasing products.

7. The heat treatment industry data analysis system based on big data analysis according to claim 4, characterized in that: The audience analysis includes purchase channel analysis and purchase population analysis. The purchase population analysis is used to analyze user feature information and locate audience population features. The purchase channel analysis is used to analyze the ways in which people in different regions purchase similar products.

8. The heat treatment industry data analysis system based on big data analysis according to claim 1, characterized in that: The project establishment module statistics data analysis module analyzes the results and displays them in a table, including the N groups of existing product sales plans with the highest profits in different regions, the requirements of different regions for similar products, the acceptance of similar products in different regions, the purchase reasons of users in different regions at different stages, the locations of purchasing groups in different regions, and the sales proportions of different purchasing channels for products in different regions.

9. The heat treatment industry data analysis system based on big data analysis according to claim 1, characterized in that: The comprehensive evaluation module adopts a weighted scoring method for scoring. The weighted indicators of the weighted scoring method include project cost, project success rate, project profit and project cycle. The calculation formula is as follows: in, is the number of weight indicators, is the score of the i-th item weight, is the proportion of the weight of item i.

10. The heat treatment industry data analysis system based on big data analysis according to claim 1, characterized in that: The data storage module periodically performs data comparison and duplication checking to remove duplicate data.

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