Forging-heat treatment process data processing method based on ER relational model

Abstract

The present invention provides a forging-heat treatment process data processing method based on an E-R relationship model, analyzes the task relationship model based on the E-R relationship graph designed by the present invention, arranges the tasks of all task sets in layers for distributed processing, confirms whether the forging-heat processing process is an existing data process or a complex optimization process, and considers different parameter settings to design and process the heat processing process; the operation quality and data entry and processing efficiency of the heat processing process in the whole process of forging-heat treatment can be significantly improved, the process data allocation and resource scheduling of the most commonly used forging-heat treatment in the whole process of heat processing can be solved, and the low efficiency of compiling and entering the existing forging-heat treatment heat processing process quality data, historical data, and standard data, as well as the on-site process data such as process parameter analysis before and after forging and efficient resource allocation can be solved.

Description

Technical Field

[0001] The invention relates to the technical field of heat treatment process database, and in particular to a forging-heat treatment process data processing method based on an ER relational model. Background Art

[0002] Industry is the only sector that produces modern labor means. It determines the speed, scale and level of national economic modernization and plays a leading role in the national economies of contemporary countries in the world. It provides raw materials, fuel and power for itself and other sectors of the national economy, and provides industrial consumer goods for people's material and cultural life. In the process of industrial production reform, how to improve the level of industrial production management, ensure the reliability of industrial processes, improve product quality and visualize production process data are hindering the development of industrial modernization. The need to build a digital industry is imminent. The key role of technologies such as the Internet of Things, big data, and cloud computing in solving these problems is self-evident, but various companies in the industrial industry are still constantly exploring how to use these emerging technologies to better promote the development and advancement of industrial digitalization. The premise for realizing the application of information technology in industrial development is the real-time and accurate acquisition of industrial process data. The integration of data collection with cloud services, industrial Internet and other technologies is the key to the digitalization of industrial processes.

[0003] With the continuous expansion of industrial production scale and the integration of production processes, the demand for industrial automation and digitalization has increased, the number and types of equipment in industrial processes have continued to increase, and the data parameters that need to be monitored have become more and more complex. According to different industrial needs, industrial systems connect different types of equipment, controllers, sensors, etc. through the network to form a data interaction network.

[0004] On the basis of the hot working data interactive network, how to better construct the database model and establish the database for the collected data plays a very important role. Hot working processes include casting, forging, welding, and heat treatment. The current database information platform is basically a single database model of information islands. How to efficiently realize the database construction of the entire process of hot working process is of milestone significance to the entire hot working industry. As the forging-heat treatment process of the whole process of hot working process is a common process of hot working process, how to carry out the distributed scheduling method of ER data model construction is very important. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the above technical problems, propose a forging-heat treatment process data processing method based on the ER relational model, and use the hierarchical allocation method of forging process, heat treatment process and different elements to complete the hierarchical distributed scheduling of part of the full process hot processing process based on the ER relational model; the technical solution adopted by the present invention to solve the shortcomings of the above technical problems is:

[0006] A forging-heat treatment process data processing method based on an ER relational model comprises the following steps:

[0007] Step 1: The forging-heat treatment heat processing process data processing platform analyzes the heat processing process association relationship of the forging-heat treatment tasks, enters the forging-heat treatment heat processing process data, and arranges the tasks of all task sets in layers based on the ER relationship model;

[0008] Step 2: Forging-heat treatment The heat processing process data processing platform arranges the tasks in a hierarchical and distributed manner according to the association relationship based on the ER relationship model;

[0009] Step 3: Conduct a hierarchical distributed evaluation of the task complexity of the forging-heat treatment process, and allocate corresponding computing resources to the forging-heat treatment processes with different requirements;

[0010] Step 4: The forging-heat treatment heat processing process data processing platform executes the forging-heat treatment heat processing process tasks in a hierarchical and distributed manner according to the allocated computing resources. The specific steps are as follows:

[0011] S1: The forging-heat treatment heat processing process data processing platform determines whether it is the quality data, historical data, standard data and other existing data of the forging-heat treatment heat processing process. If so, enter the process selection option, enter the process card including the process node and process identification, and enter the heat treatment process link;

[0012] S2: The forging-heat treatment heat processing process data processing platform determines whether it is a simple forging-heat treatment mode of the forging-heat treatment heat processing process. If so, the forging-heat treatment link of the heat processing process is performed;

[0013] S3: The forging-heat treatment thermal processing process data processing platform determines whether it is the optimization mode of the forging-heat treatment thermal processing process. If so, it performs parameter setting and heat treatment process control.

[0014] Furthermore, the process selection options in step three include allocation options, review options and approval options.

[0015] Furthermore, the forging-heat treatment process in step 4 includes the firing times and process details.

[0016] Furthermore, the parameter settings in step 4 include pre-forging heating parameter settings, furnace configuration parameter settings, forging process parameter settings, and post-forging process parameter settings.

[0017] The beneficial effects of the present invention are:

[0018] The present invention provides a data hierarchical distributed scheduling method based on a forging-heat treatment process big data platform, and utilizes the forging-heat treatment ER relationship model diagram provided by the patent of the present invention to realize a distributed and efficient scheduling method for the thermal processing technology of the forging-heat treatment process, thereby significantly improving the operation quality and data entry and processing efficiency of the thermal processing technology of the forging-heat treatment process.

[0019] The focus is on solving the process data allocation and resource scheduling methods of forging-heat treatment, the most commonly used process in the entire hot processing process. It solves the low efficiency of compiling and entering the existing forging-heat treatment hot processing process quality data, historical data, and standard data, as well as the on-site process data such as process parameter analysis before and after forging and efficient resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute an improper limitation of the present invention.

[0021] Figure 1 This is the forging-heat treatment ER relationship model diagram of the present invention;

[0022] Figure 2 The figure is a flow chart of the forging-heat treatment process data processing method of the present invention. DETAILED DESCRIPTION

[0023] The present invention is further described below in conjunction with specific embodiments. Specific implementation method:

[0025] Based on the forging-heat treatment process big data platform, using the forging-heat treatment ER relationship model diagram provided by the patent of this invention, the compilation and entry of the thermal processing process quality data, historical data, and standard data of forging-heat treatment is carried out, and the hierarchical allocation method of forging procedures, heat treatment processes and different elements is used to complete the hierarchical distributed scheduling of part of the full-process hot processing process based on the ER relationship model, laying the foundation for establishing an efficient forging-heat treatment full-process database.

[0026] Embodiment 1:

[0027] Forging-heat treatment The heat processing process data processing platform performs data platform task collection and task analysis and allocation according to forging requirements, such as Figure 2 As shown, the thermal processing relationship between forging and heat treatment tasks is analyzed, using Figure 1 The forging-heat treatment ER relationship model diagram shown is used to enter and allocate process tasks. The ER relationship model is used to form a data interaction network, break the single database model of information islands, realize the database construction of the entire process of hot processing technology, and better construct the database model of the collected data.

[0028] Forging-heat treatment The heat processing process data processing platform confirms whether the product to be forged is simple forging or complex optimized process forging, and performs data entry, task allocation and parameter setting.

[0029] The forging-heat treatment thermal processing data processing platform executes forging-heat treatment thermal processing tasks in a layered and distributed manner according to the allocated computing resources; it provides layered forging-heat treatment thermal processing according to different needs. This layered and simultaneous distributed processing can significantly improve the operation quality of the forging-heat treatment full-process thermal processing technology and complete the forging-heat treatment thermal processing tasks more efficiently.

[0030] When the forging-heat treatment thermal processing process data processing platform determines whether there is existing data such as quality data, historical data, standard data, etc. of the forging-heat treatment thermal processing process, if there is existing data, it enters the allocation / review / approval option, enters the process nodes, process identification and other process cards into the process steps, and enters the heat treatment process link; it solves the problem of low efficiency in the compilation and entry of existing forging-heat treatment thermal processing process quality data, historical data, and standard data, and accelerates the efficient allocation of resources.

[0031] The forging-heat treatment heat processing process data processing platform determines whether it is a simple forging-heat treatment mode of the forging-heat treatment heat processing process. If it is a simple forging-heat treatment mode, the forging-heat treatment link is carried out, and the heat processing process including the firing order and process details is carried out, and the process processing of the on-site operation is distinguished from the heat processing process processing using existing quality data, historical data, etc., to speed up the operation process and realize efficient allocation of resources.

[0032] The forging-heat treatment heat processing process data processing platform determines whether it is the optimization mode of the forging-heat treatment heat processing process. If the optimization mode of the forging-heat treatment heat processing process is required, parameter setting and heat treatment process control are performed. The parameter setting includes pre-forging heating parameter setting, furnace matching parameter setting, forging process parameter setting, and post-forging process parameter setting; the forging-heat treatment process data allocation and resource efficient scheduling method are realized, and the hierarchical allocation method of forging procedures, heat treatment processes and different elements is used to improve accuracy, and the hierarchical distributed scheduling of part of the full-process hot processing process based on the ER relationship model is completed.

[0033] like Figure 1 :

[0034] The user adds technical parameters in the heat treatment module, edits the part size, sets the process parameters, and enters the process card such as process node and process identification into the process. The process card contains multiple parts. The user enters the material number, version, and process route node of each part and enters the heat treatment process link.

[0035] If the optimization mode of forging-heat treatment heat processing technology is required, parameter setting and heat treatment process control are carried out. The component is bound with the ingot program. The user edits the pre-forging heating, furnace matching and post-forging heat treatment processes, submits them for approval, and compiles the furnace matching including pre-forging fire process parameter setting, post-forging fire process parameter setting and heat treatment process parameter setting;

[0036] Post-forging fire process parameter settings include post-forging fire heating methods; heat treatment process parameter settings include heat treatment heating methods;

[0037] If entering the second forging process, hot processing technology is carried out on the contents including the firing times and process details, and process processing is carried out on the on-site operation.

[0038] MN: A left-end object can be associated with multiple right-end objects, and a right-end object can also be associated with multiple right-end objects;

[0039] 1M: A left-end object can be associated with multiple right-end objects, and a right-end object can only be associated with one left-end object;

[0040] 1N: One left-end object can be associated with multiple right-end objects, and one right-end object can only be associated with one left-end object;

[0041] 11: A left-end object can only be associated with one right-end object, and a right-end object can only be associated with one left-end object;

[0042] The above description of the disclosed embodiments is intended only to enable those skilled in the art to implement or use the present invention. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A forging-heat treatment process data processing method based on an ER relational model, characterized in that: The method comprises the following steps: Step 1: The forging-heat treatment heat processing process data processing platform analyzes the heat processing process association relationship of the forging-heat treatment tasks, enters the forging-heat treatment heat processing process data, and arranges the tasks of all task sets in layers based on the ER relationship model; Step 2: Forging-heat treatment The heat processing process data processing platform arranges the tasks in a hierarchical and distributed manner according to the association relationship based on the ER relationship model; Step 3: Conduct a hierarchical distributed evaluation of the task complexity of the forging-heat treatment thermal processing process, and allocate corresponding computing resources to the forging-heat treatment thermal processes with different requirements; Step 4: The forging-heat treatment heat processing process data processing platform executes the forging-heat treatment heat processing process tasks in a hierarchical and distributed manner according to the allocated computing resources. The specific steps are as follows: S1: The forging-heat treatment heat processing process data processing platform determines whether it is the quality data, historical data, and standard data of the forging-heat treatment heat processing process. If so, enter the process selection option, enter the process card including the process node and process identification, and enter the heat treatment process link; S2: The forging-heat treatment heat processing process data processing platform determines whether it is a simple forging-heat treatment mode of the forging-heat treatment heat processing process. If so, the forging-heat treatment link of the heat processing process is performed; S3: The forging-heat treatment thermal processing process data processing platform determines whether it is the optimization mode of the forging-heat treatment thermal processing process. If so, it performs parameter setting and heat treatment process control.

2. The forging-heat treatment process data processing method based on the ER relational model according to claim 1 is characterized in that: The process selection options in step S1 include an allocation option, a review option and an approval option.

3. The forging-heat treatment process data processing method based on the ER relational model according to claim 1 is characterized in that: The forging-heat treatment process in step S2 includes the firing times and process details.

4. The forging-heat treatment process data processing method based on the ER relational model according to claim 3 is characterized in that: The parameter settings in step S3 include pre-forging heating parameter settings, furnace matching parameter settings, forging process parameter settings, and post-forging process parameter settings.

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