Big data-based production line monitoring system for automobile parts production

Abstract

The application discloses a production line monitoring system for automobile accessory production based on big data, which comprises a data acquisition module, a monitoring precision adjustment module, a big data analysis module and a spraying adjustment module, characterized in that the data acquisition module is used for collecting data of automobile accessories and production lines, the monitoring precision adjustment module is used for controlling and adjusting the maximum precision of monitoring according to the line data, the big data analysis module is used for collecting shape data and analyzing and judging whether spraying is qualified, and the spraying adjustment module is used for automatically adjusting the angle, distance and spraying time of the spraying equipment according to the big data analysis result, so as to adapt to automobile accessories of different shapes. The data acquisition module is electrically connected with the monitoring precision adjustment module, and the data acquisition module and the monitoring precision adjustment module are both electrically connected with the big data analysis module. The big data analysis module is electrically connected with the spraying adjustment module. The application has the characteristics of strong practicability and accurate monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile manufacturing, in particular to a production line monitoring system for automobile parts production based on big data. BACKGROUND

[0002] Automobile parts are the units that make up the whole car and a product that serves the car. With the improvement of people's living standards, people's consumption of cars is also increasing, and the market for automobile parts is also becoming larger. However, due to the irregular shape of automobile parts, and the spraying process is greatly affected by external factors, leading to unstable spraying quality and low yield. The existing production line monitoring system for automobile parts production often only focuses on the overall spraying quality, and lacks adjustment and optimization strategies for specific shapes. Therefore, it is necessary to design a production line monitoring system for automobile parts production based on big data with strong practicability and accurate monitoring. SUMMARY

[0003] The purpose of the present application is to provide a production line monitoring system for automobile parts production based on big data to solve the problems raised in the background art.

[0004] In order to solve the above technical problems, the present application provides the following technical scheme: a production line monitoring system for automobile parts production based on big data, comprising a data acquisition module, a monitoring accuracy adjustment module, a big data analysis module and a spraying adjustment module, characterized in that: the data acquisition module is used for data acquisition of automobile parts and production line, the monitoring accuracy adjustment module is used for controlling and adjusting the maximum accuracy of monitoring according to the line data, the big data analysis module is used for collecting shape data and analyzing and judging whether the spraying is qualified, and the spraying adjustment module is used for automatically adjusting the angle, distance and paint spraying time of the spraying equipment according to the big data analysis result, so as to adapt to automobile parts of different shapes, the data acquisition module is electrically connected with the monitoring accuracy adjustment module, and the data acquisition module and the monitoring accuracy adjustment module are electrically connected with the big data analysis module, and the big data analysis module is electrically connected with the spraying adjustment module.

[0005] According to the above technical scheme, the data acquisition module comprises a camera acquisition module, a laser sensor unit, an environment data acquisition module and a monitoring data acquisition module, the camera acquisition module is used for real-time acquisition of image data of automobile parts, the laser sensor unit is used for measuring size and shape data of automobile parts, the environment data acquisition module is used for monitoring and collecting environmental temperature, humidity and wind speed data, and the monitoring data acquisition module is used for receiving feedback data of real-time monitoring.

[0006] According to the technical scheme, the monitoring precision adjustment module comprises a monitoring program database, a production line data receiving module and a complex environment judging module, the monitoring program database is used for storing monitoring data of a historical automobile accessory production line, the production line data receiving module is used for receiving processing product information of the production line, and the complex environment judging module is used for judging a production environment in an automobile accessory spraying process according to environment data.

[0007] According to the technical scheme, the big data analysis module comprises a data processing module, a feature extraction module and a data comparison module, the data processing module is used for processing and cleaning monitored data, so as to ensure accuracy and reliability of the data, the feature extraction module is used for extracting accessory image data of monitoring according to monitoring precision and current production accessory data, and the data comparison module is used for comparing the extracted accessory image features with preset standards, so as to judge whether the spraying quality meets requirements.

[0008] According to the technical scheme, the operation method of the automobile accessory production line monitoring system based on big data comprises the following steps.

[0009] Step S1: The data acquisition module acquires data of automobile accessories and a production line; in order to obtain accurate data, image data of the automobile accessories are acquired in real time by using a camera acquisition module, a laser sensing unit is used for measuring size and shape data of the automobile accessories, and meanwhile, environment data acquisition modules monitor environment temperature, humidity and wind speed data;

[0010] Step S2: The monitoring program database stores monitoring data of a historical automobile accessory production line, and receives processing product information of the production line, so that the accuracy of monitoring can be dynamically adjusted according to historical data and real-time production line information;

[0011] Step S3: The big data analysis module acquires shape data and analyzes and judges whether spraying is qualified;

[0012] Step S4: The spraying adjustment module automatically adjusts the angle, distance and spraying time of the spraying equipment according to the big data analysis result, so as to adapt to automobile accessories of different shapes. According to the analyzed data result, shape features of each accessory can be accurately judged, and parameters of the spraying equipment are automatically adjusted, so that precise spraying operation is realized.

[0013] According to the technical scheme, the step S2 further comprises:

[0014] Step S21: A monitoring program database is established, monitoring results of a production line spraying process part are stored in the database, a good product rate of a nearest monitored accessory image process in the database is called, when the good product rate is lower than a historical average good product rate of a current accessory, the monitoring precision adjustment module adjusts precision;

[0015] Step S22: Real-time receiving production line data, adjusting the preset corresponding spraying monitoring precision according to the automobile parts batch and model standard of the production line, which is related to the part shape, process difficulty and color, and is preset for the parts, and the spraying monitoring result can be adjusted later;

[0016] Step S23: Obtain real-time monitored temperature, humidity and wind speed data, and judge the production line environment in combination with the environmental numerical standard, and automatically adjust the precision when the environment does not meet the requirements.

[0017] According to the above technical scheme, the step S3 further comprises:

[0018] Firstly, the data processing module processes and cleans the monitored data; then, the feature extraction module extracts the monitored part image data according to the monitoring precision and the current production part data; finally, the data comparison module compares the extracted part image features with the preset standard to judge whether the spraying quality meets the requirements.

[0019] Compared with the prior art, the present application has the following beneficial effects: through the organic combination of data acquisition, monitoring precision adjustment, big data analysis and spraying adjustment, the present application can timely find the problems in the production process and make adjustments, thereby realizing the function of simultaneous monitoring and local spraying repair, avoiding the problems found after traditional spraying, and improving the spraying quality and efficiency, and ensuring the consistency and reliability of each part. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with embodiments of the present application, and do not constitute a limitation on the present application. In the drawings:

[0021] Figure 1 is a schematic diagram of the system module composition of the present application. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0023] Please refer to Figure 1The application provides a technical scheme: a production line monitoring system for automobile part production based on big data, which comprises a data acquisition module, a monitoring precision adjustment module, a big data analysis module and a spraying adjustment module, and is characterized in that: the data acquisition module is used for acquiring data of automobile parts and a production line, the monitoring precision adjustment module is used for controlling and adjusting the maximum precision of monitoring according to production line data, the big data analysis module is used for acquiring shape data and analyzing and judging whether spraying is qualified, and the spraying adjustment module is used for automatically adjusting the angle, distance and paint spraying time of a spraying device according to the big data analysis result, so as to adapt to automobile parts of different shapes; the data acquisition module is electrically connected with the monitoring precision adjustment module, and the data acquisition module and the monitoring precision adjustment module are both electrically connected with the big data analysis module; and the big data analysis module is electrically connected with the spraying adjustment module.

[0024] The data acquisition module comprises a camera acquisition module, a laser sensor unit, an environment data acquisition module and a monitoring data acquisition module, the camera acquisition module is used for acquiring image data of automobile parts in real time, the laser sensor unit is used for measuring size and shape data of automobile parts, the environment data acquisition module is used for monitoring and acquiring environment temperature, humidity and wind speed data, and the monitoring data acquisition module is used for receiving feedback data of real-time monitoring.

[0025] The monitoring precision adjustment module comprises a monitoring program database, a production line data receiving module and a complex environment judgment module, the monitoring program database is used for storing monitoring data of a historical production line for automobile part production, the production line data receiving module is used for receiving processing product information of the production line, and the complex environment judgment module is used for judging a production environment in the spraying process of automobile parts according to environment data.

[0026] The big data analysis module comprises a data processing module, a feature extraction module and a data comparison module, the data processing module is used for processing and cleaning monitored data, so as to ensure the accuracy and reliability of the data, the feature extraction module is used for extracting monitored part image data according to monitoring precision and current production part data, and the data comparison module is used for comparing the extracted part image features with preset standards to judge whether the spraying quality meets the requirements.

[0027] The operation method of the production line monitoring system for automobile part production based on big data comprises the following steps:

[0028] Step S1: The data acquisition module acquires data of automobile parts and a production line; in order to obtain accurate data, a camera acquisition module is used to acquire image data of automobile parts in real time, a laser sensor unit is used to measure size and shape data of automobile parts, and an environment data acquisition module monitors environment temperature, humidity and wind speed data; through the acquisition of these data, comprehensive and multi-angle automobile part information can be acquired, thereby providing basic data for subsequent monitoring and analysis;

[0029] Step S2: The monitoring program database stores historical monitoring data of the production line for automobile parts production, and receives processing product information of the production line. Then, the accuracy of monitoring can be dynamically adjusted according to historical data and real-time production line information. This adjustment of accuracy can ensure that the monitoring results are more accurate and reliable, and improve the controllability and stability of the production process.

[0030] Step S3: The big data analysis module collects shape data and analyzes whether the spraying is qualified.

[0031] Step S4: The spraying adjustment module automatically adjusts the angle, distance and spraying time of the spraying equipment according to the big data analysis results to adapt to automobile parts of different shapes. According to the analysis data results, we can accurately judge the shape characteristics of each part, and realize precise spraying operation by automatically adjusting the parameters of the spraying equipment. Therefore, it can adapt to automobile parts of different shapes, ensure the consistency of the spraying quality of each part, and improve the consistency and reliability of the product.

[0032] Through the execution of the above steps, the method can realize real-time monitoring and adjustment of the production line for automobile parts production. Through the organic combination of data collection, monitoring accuracy adjustment, big data analysis and spraying adjustment, problems in the production process can be found and adjusted in time, and the function of monitoring and local spraying repair at the same time can be realized, avoiding the problem of finding problems after traditional spraying and returning to work after listing the parts in the bad area, improving the spraying quality and efficiency, and ensuring the consistency and reliability of each part. Therefore, the implementation of the current method can greatly improve the efficiency and quality level of automobile parts production, reduce the variation and error in the production process, and bring significant technical effects and economic benefits to the production enterprises.

[0033] Step S2 further comprises:

[0034] Step S21: Establish a monitoring program database to store the monitoring results of the spraying process part of the production line in the database. When the yield of the latest monitoring part drawing process in the database is lower than the historical average yield of the current part, the monitoring accuracy adjustment module adjusts the accuracy.

[0035] Step S22: Real-time receive production line data, adjust the preset spraying monitoring accuracy according to the automobile parts batch and model standard of the production line. This adjustment is related to the shape, process difficulty and color of the parts, and the preset value is adjusted according to the spraying monitoring results in the later period.

[0036] Step S23: Obtain real-time monitoring data of temperature, humidity and wind speed, combine with environmental numerical standard, judge the production line environment, when the environment does not meet, automatically adjust to increase the accuracy, avoid the influence of environment and lead to low monitoring accuracy, inaccurate monitoring results.

[0037] Step S3 further comprises:

[0038] Firstly, the data processing module processes and cleans the monitored data to ensure the accuracy and reliability of the data; secondly, the feature extraction module extracts the monitored accessory image data according to the monitoring accuracy and the current production accessory data; finally, the data comparison module compares the extracted accessory image features with the preset standard to determine whether the spraying quality meets the requirements; through such analysis and judgment, the spraying quality can be monitored in real time, the unqualified products can be avoided to flow out, and the production efficiency and the yield can be improved.

[0039] It should be noted that, in this document, the terms such as first and second are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between such entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover a non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements does not only include those elements, but also includes other elements not expressly listed or inherent to such process, method, article or apparatus.

[0040] Finally, it should be noted that: the above only describes the preferred embodiments of the present application, and does not limit the present application, although the foregoing embodiments of the present application are described in detail, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A line monitoring system for automobile parts production based on big data, comprising a data acquisition module, a monitoring precision adjustment module, a big data analysis module and a spraying adjustment module, characterized in that: The data acquisition module is used for data acquisition of automobile parts and production lines, the monitoring precision adjustment module is used for controlling and adjusting the maximum monitoring precision according to the line data, the big data analysis module is used for collecting shape data and analyzing and judging whether the spraying is qualified, and the spraying adjustment module is used for automatically adjusting the angle, distance and paint spraying time of the spraying equipment according to the big data analysis result, so as to adapt to automobile parts of different shapes. The data acquisition module is electrically connected with the monitoring precision adjustment module, and the data acquisition module and the monitoring precision adjustment module are electrically connected with the big data analysis module. The big data analysis module is electrically connected with the spraying adjustment module. The data acquisition module comprises a camera acquisition module, a laser sensing unit, an environment data acquisition module and a monitoring data acquisition module. The monitoring precision adjustment module comprises a monitoring program database, a line data receiving module and a complex environment judgment module. The operation method of the line monitoring system for automobile part production based on big data comprises the following steps: Step S1: the data acquisition module acquires data of automobile parts and production lines; in order to obtain accurate data, the camera acquisition module is used to acquire image data of automobile parts in real time, the laser sensing unit is used to measure size and shape data of automobile parts, and the environment data acquisition module monitors environment temperature, humidity and wind speed data; step S2: the monitoring data of the line for historical automobile part production is stored in the monitoring program database, and the processing product information of the line is received, and then the accuracy of monitoring can be dynamically adjusted according to the historical data and real-time line information; step S3: the big data analysis module collects shape data and analyzes and judges whether the spraying is qualified; Step S4: the spraying adjustment module automatically adjusts the angle, distance and paint spraying time of the spraying equipment according to the big data analysis result, so as to adapt to automobile parts of different shapes; Step S2 further comprises: Step S21: a monitoring program database is established, the monitoring results of the spraying process part of the line are stored in the database, the yield of the nearest monitored part process in the database is retrieved, when the yield is lower than the historical average yield of the current part, the monitoring precision adjustment module adjusts the precision; Step S22: real-time line data is received, and the preset corresponding spraying monitoring precision is adjusted according to the automobile part batch and model standard of the line. The adjustment is related to the shape, process difficulty and color of the part, and the preset value is adjusted according to the spraying monitoring result in the later period; Step S23: real-time monitoring temperature, humidity and wind speed data are obtained, the line environment is judged in combination with the environment value standard, when the environment does not meet the requirement, the precision is automatically adjusted to avoid the monitoring precision being reduced and the monitoring result being inaccurate due to the influence of the environment.

2. The big data based production line monitoring system for automobile component production as claimed in claim 1, wherein: The camera acquisition module is used for real-time acquisition of image data of automobile parts, the laser sensor unit is used for measurement of size and shape data of automobile parts, the environment data acquisition module is used for monitoring and collecting environment temperature, humidity and wind speed data, and the monitoring data acquisition module is used for receiving feedback data of real-time monitoring.

3. The big data based production line monitoring system for automobile component production as claimed in claim 2, wherein: The monitoring program database is used for storing historical monitoring data of automobile accessory production lines, the line data receiving module is used for receiving processing product information of the line, and the complex environment judging module is used for judging the production environment in the automobile accessory spraying process according to the environment data.

4. The big data based line monitoring system for automobile component production as claimed in claim 3, wherein: The big data analysis module comprises a data processing module, a feature extraction module and a data comparison module, the data processing module is used for processing and cleaning the monitored data, ensuring the accuracy and reliability of the data, the feature extraction module is used for extracting the monitored accessory image data according to the monitoring accuracy and the current production accessory data, and the data comparison module is used for comparing the extracted accessory image features with the preset standard to judge whether the spraying quality meets the requirements.

5. The big data based line monitoring system for automobile component production as claimed in claim 4, wherein: The step S3 further comprises: Firstly, the data processing module processes and cleans the monitored data; then, the feature extraction module extracts the monitored accessory image data according to the monitoring accuracy and the current production accessory data; finally, the data comparison module compares the extracted accessory image features with the preset standard to judge whether the spraying quality meets the requirements.

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