LED production intelligent management and control system and management and control method

Abstract

The invention relates to the technical field of monitoring equipment, in particular to an intelligent management and control system and method for LED production. The input unit is used for inputting material data, production procedures, equipment and personnel information of LED production products; the big data storage unit is used for storing data information and production process information of different LED products, and normal operation range information and operation step information of various current and voltage signals of production equipment; the data acquisition unit is used for acquiring data of various currents, voltages and equipment operation conditions in the operation process of the LED production equipment; the abnormity judgment unit is used for calling the normal operation data range of the corresponding LED product in the big data storage unit and acquiring the data acquired by the data acquisition unit in real time; by means of the device, the LED production equipment can be monitored, and whether abnormity exists in the production process or not is judged.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring equipment, and in particular to an intelligent control system and method for LED production. Background Art

[0002] At present, most LED companies separate production tracking and production results in the production process. The production process is recorded on a paper process card, and the production personnel write down everything that happens in the production process manually on the paper process card. The material content in the production process is reflected on this paper process card. After each process is completed, the production workers will feedback the production capacity through the computer to complete the process report.

[0003] Moreover, during the production and packaging process of LED products, various production data are recorded by production personnel. For some large-scale LED production sites, recording production data requires a lot of manpower, and different production personnel have different professional capabilities. It is easy to cause abnormal operation of production equipment due to operational errors or data setting errors. If there is no real-time supervision, it is easy for related abnormalities to go undetected, resulting in the final LED products not meeting product requirements.

[0004] Based on the above problems, there is an urgent need for an intelligent LED production control system and control method that can effectively monitor the LED production system in real time to prevent production anomalies. Summary of the invention

[0005] At present, it is difficult to effectively monitor production data in large-scale LED production sites, and production anomalies are prone to occur. The present invention provides an LED production intelligent management and control system and management and control method to solve the above problems.

[0006] To achieve the above object, the present invention is implemented through the following technical solutions: The present application embodiment discloses an LED production intelligent management and control system, including: Input unit: The material data, production process, equipment and personnel information of LED production products are input through the input unit; Big data storage unit: used to store data information of different LED products, production process information, normal operating range information of various current and voltage signals of production equipment, and operation steps information; Data acquisition unit: used to collect data on various currents, voltages and equipment operating conditions of LED production equipment during operation; Abnormality judgment unit: used to retrieve the normal operating data range of the corresponding LED product in the big data storage unit, and obtain the data collected by the data collection unit in real time; and compare and judge whether there is any abnormality; Exception processing unit: When the exception judgment unit determines that the collected data is abnormal, it can report the exception and handle it in the corresponding processing mode according to the exception type.

[0007] Adopt the above technical scheme: The above scheme sets up a production intelligent management and control system, which can record various data of LED production equipment during normal operation, and detect various data of the equipment during normal operation in real time. It can automatically judge whether the equipment has abnormalities through the detected data through the networked circuit equipment. It can be suitable for application scenarios in large-scale LED production workshops. It does not require manual supervision and can be monitored by corresponding sensor equipment. The judgment system can automatically judge whether the equipment has abnormal operation.

[0008] Preferably, the data acquisition unit comprises: Equipment operation process data collection module: used to monitor and collect the operation process of the equipment operated by the production staff in real time; Equipment operation parameter acquisition module: used to collect the current and voltage data of LED production equipment and LED packaging equipment in real time during operation; Material production quantity collection module: used to monitor and collect the production quantity of different types of LED products.

[0009] Adopting the above technical solution: the equipment provided by the above solution can realize automatic monitoring and recording of the equipment's operating process, equipment's operating parameters and material production volume.

[0010] Further preferably, the abnormality judgment unit includes: Equipment operation process abnormality judgment module: used to obtain the data collected by the equipment operation process data collection unit, and compare it with the process steps input by the big data storage unit and the input unit to determine whether an abnormality occurs; Equipment operation parameter abnormality judgment module: used to obtain the data collected by the equipment operation parameter acquisition module, and compare it with the current and voltage data stored in the big data storage unit to determine whether there is an abnormality; Material production anomaly judgment module: used to obtain production quantity data of different types of LED products, and compare it with the material data input by the input unit to determine whether there is an abnormality.

[0011] Adopting the above technical solution: the module provided in the above solution can judge the data of the operation process, operation parameters and material production volume of the equipment, and judge whether corresponding abnormalities appear in each of the above parameters.

[0012] Further preferably, it also includes: an abnormality confirmation unit: when the abnormality judgment unit confirms that an abnormality occurs in the production process, the abnormality confirmation unit confirms whether an abnormality occurs in the production of the LED product.

[0013] By adopting the above technical solution, the abnormality confirmation unit provided in the above solution can further confirm whether the produced LED products will have corresponding abnormalities when it is determined that an abnormality occurs in the production process.

[0014] Further preferably, the abnormality confirmation unit includes: LED product image acquisition terminal: used to acquire production process images of different positions of abnormal LED products; Electrical signal test terminal: used to test the electrical signals of abnormal LED products; Abnormality judgment end: Compare and calculate the LED data information stored in the big data storage unit and the LED product image process and electrical signals to determine whether the LED product has any abnormality.

[0015] Adopting the above technical solution: the above solution can realize comprehensive judgment on whether the LED product has abnormality based on the relevant electrical signal detection data of the LED product and the LED product image process data.

[0016] Further preferably, the algorithm formula set in the abnormality judgment terminal is: , in is the abnormal determination coefficient, is the standard current, To detect the current, is the proportion of current in abnormal judgment, is the standard voltage, is the detection voltage, is the proportion of voltage in abnormal judgment, Standard image coefficients, To detect the image coefficients, It is the proportion of production process in abnormality judgment.

[0017] Adopt the above technical solution: the algorithm provided by the above solution can realize algorithm judgment based on the current, voltage and image coefficient of the LED, and automatically judge whether the produced LED products meet the standards based on the actual detected relevant data.

[0018] Further preferably, the abnormality determination coefficient thresholds of different types of LED products are Different LED products have different abnormality determination coefficient thresholds. The calculated abnormal determination coefficient Compare and judge whether there is any abnormality in the LED product.

[0019] By adopting the above technical solution, it is possible to determine whether there is any abnormality in the production of LED products according to the types of different LED products.

[0020] An intelligent management method for LED production, applied to any of the management systems described above, comprising: S110: Inputting material data, production process, equipment and personnel information of LED products through an input unit; S120: During the production process, data on various currents, voltages and equipment operating conditions during the operation of LED production equipment are collected; S130: Retrieve the normal operation data range of the corresponding LED product in the big data storage unit, and obtain the data collected by the data collection unit in real time; and compare and determine whether there is any abnormality; S140: When the abnormality judgment unit judges that the collected data is abnormal, an abnormality error is reported, and a corresponding processing mode is performed according to the abnormality type.

[0021] Adopt the above technical solution: The above solution provides a production intelligent management system, which can collect various data in the production process of LED products and determine whether there is any abnormality in the LED production process based on the collected data.

[0022] Further preferably, the step S3 comprises: S131: Acquire equipment operation process data, equipment operation parameters, and production quantity data of different types of LED products; S132: comparing the data acquired in step S31 with the standard data of the corresponding LED product input by the big data storage unit and the input unit; S133: Determine whether there are abnormalities in the operation process of the equipment, the operation parameters of the equipment, and the production quantity of the LED products.

[0023] Adopt the above technical solution: The solution provided by the above steps can detect and judge the operating data of the equipment to see whether there is any abnormality during the operation of the equipment.

[0024] Further preferably, it also includes an LED abnormality confirmation method, and the LED abnormality confirmation method includes: S210: Acquire production process images of different positions of abnormal LED products and obtain detection image coefficients; S220: Testing the electrical signal of the abnormal LED product to obtain a current detection signal and a voltage detection signal; S230: Obtaining an abnormality determination coefficient through the image coefficient and the current detection signal and the voltage detection signal; S240: Retrieve the corresponding determination coefficient threshold from the big data storage unit, and compare it with the abnormality determination coefficient to determine whether the LED product is abnormal.

[0025] Adopting the above technical solution: The technical solution provided in the above solution can detect the produced LED products to determine whether the LED products are abnormal. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 This is the connection diagram of the LED production intelligent management and control system for this application; Figure 2 This is a flow chart of the LED control method for this application; Figure 3 For this application Figure 2 Step S130 flow chart; Figure 4 This is a flow chart of the LED abnormality confirmation method for this application.

[0028] In the figure: 1. Input unit; 2. Big data storage unit; 3. Data acquisition unit; 4. Abnormal judgment unit; 5. Abnormal processing unit; 6. Equipment operation process data acquisition module; 7. Equipment operation parameter acquisition module; 8. Material production volume acquisition module; 9. Equipment operation process abnormal judgment module; 10. Equipment operation parameter abnormal judgment module; 11. Material production abnormal judgment module; 12. Abnormal confirmation unit; 13. LED product image acquisition terminal; 14. Electrical signal testing terminal. DETAILED DESCRIPTION

[0029] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0030] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0031] See also Figure 1-Figure 4 For example, in the original LED product production workshop, there is no corresponding monitoring system for monitoring during the LED product production process. When an abnormality occurs in the LED production equipment, it is impossible to know and check it in time, which can easily lead to abnormalities in the LED product production and cause economic losses. Based on the above problems, this application provides an LED production intelligent management and control system, including: Input unit 1: Input material data, production process, equipment and personnel information of LED production products through input unit 1; Big data storage unit 2: used to store data information of different LED products, production process information, normal operating range information of various current and voltage signals of production equipment, and operation steps information; Data acquisition unit 3: used to collect data on various currents, voltages and equipment operating conditions of LED production equipment during operation; The abnormality judgment unit 4 is used to retrieve the normal operation data range of the corresponding LED product in the big data storage unit 2, and obtain the data collected by the data collection unit 3 in real time; and compare and judge whether there is an abnormality; Exception processing unit 5: When the exception judgment unit 4 judges that the collected data is abnormal, it can report the exception and handle it in a corresponding processing mode according to the exception type.

[0032] It is worth mentioning that the equipment provided in the above scheme can realize inputting relevant data of LED products through input unit 1, and compare the data stored in big data storage unit 2 with the data collected by data collection unit 3 during the operation of the equipment, so as to determine whether the operation of LED production equipment is abnormal. When the LED production equipment is abnormal during operation, the above device can be used to report the abnormality. The whole equipment can realize full monitoring of the LED production system without manual supervision, and can make corresponding abnormality reports based on the corresponding equipment operation data collected.

[0033] The data acquisition unit 3 comprises: Equipment operation process data collection module 6: used to monitor and collect the operation process of the equipment operated by the production staff in real time; Equipment operation parameter acquisition module 7: used for real-time acquisition of current and voltage data during the operation of LED production equipment and LED packaging equipment; Material production quantity collection module 8: used to monitor and collect the production quantity of different types of LED products.

[0034] Adopting the above technical solution: the data acquisition unit 3 provided by the above solution can realize the collection of equipment operation process data, equipment operation parameters, material production volume and other data for the corresponding abnormal judgment module to make judgment.

[0035] The abnormality judgment unit 4 includes: Equipment operation process abnormality judgment module 9: used to obtain the data collected by the equipment operation process data collection unit 3, and compare it with the process steps input by the big data storage unit 2 and the input unit 1 to determine whether an abnormality occurs; The equipment operation parameter abnormality judgment module 10 is used to obtain the data collected by the equipment operation parameter acquisition module 7, and compare it with the current and voltage data stored in the big data storage unit 2 to determine whether an abnormality occurs; The material production abnormality judgment module 11 is used to obtain the production quantity data of different types of LED products, and compare it with the material data input by the input unit 1 to determine whether an abnormality occurs.

[0036] The module provided in the above scheme can judge the data of the equipment's operation process, operation parameters and material production volume, and judge whether the above parameters have corresponding abnormalities. The abnormality confirmation unit 12 provided in the above scheme can further confirm whether the produced LED products have corresponding abnormalities when judging that the production process has abnormalities.

[0037] It also includes: an abnormality confirmation unit 12: when the abnormality judgment unit 4 confirms that an abnormality occurs in the production process, the abnormality confirmation unit 12 confirms whether an abnormality occurs in the production of the LED product.

[0038] The abnormality confirmation unit 12 includes: LED product image acquisition terminal 13: used to acquire production process images of different positions of abnormal LED products; Electrical signal test terminal 14: used to test the electrical signal of abnormal LED products; Abnormality judgment end: performs calculation and comparison on the LED data information stored in the big data storage unit 2 and the LED product image process and electrical signal to judge whether the LED product has abnormality.

[0039] The algorithm formula set in the abnormal judgment terminal is: , in is the abnormal determination coefficient, is the standard current, To detect the current, is the proportion of current in abnormal judgment, is the standard voltage, To detect the voltage, is the proportion of voltage in abnormal judgment, Standard image coefficients, To detect the image coefficients, It is the proportion of production process in abnormality judgment.

[0040] It is worth mentioning that the abnormality confirmation unit 12 provided in the above scheme can further acquire relevant parameters of the LED product when an abnormality is detected in the operation of the LED production equipment, including the production process images of different positions of the LED, to determine whether the LED product has an abnormality in the production process, and to judge the current detection data and voltage detection data of the LED product. It calculates whether the abnormality of the LED product is within the set abnormality range through the corresponding algorithm, so as to further determine whether the production of the LED product meets the actual needs.

[0041] Abnormality determination coefficient thresholds for different types of LED products Different LED products have different abnormality determination coefficient thresholds. The calculated abnormal determination coefficient Compare and judge whether the LED product is abnormal. In the above scheme, different LED products have corresponding abnormality determination coefficient thresholds, and for different LED product types, it is possible to effectively detect whether the LED product is qualified.

[0042] An intelligent management method for LED production, applied to any one of the management systems described above, characterized in that it includes: S110: Inputting material data, production process, equipment and personnel information of LED products through input unit 1; S120: During the production process, data on various currents, voltages and equipment operating conditions during the operation of LED production equipment are collected; S130: Retrieve the normal operation data range of the corresponding LED product in the big data storage unit 2, and obtain the data collected by the data collection unit 3 in real time; and compare and judge whether there is any abnormality; S140: When the abnormality judgment unit 4 judges that the collected data is abnormal, an abnormality error is reported, and a corresponding processing mode is performed according to the abnormality type.

[0043] The above solution provides an intelligent production management system, which can collect various data in the production process of LED products and determine whether there is any abnormality in the LED production process based on the collected data.

[0044] The step S3 comprises: S131: Acquire equipment operation process data, equipment operation parameters, and production quantity data of different types of LED products; S132: comparing the data acquired in step S31 with the standard data of the corresponding LED product input by the big data storage unit 2 and the input unit 1; S133: Determine whether there are abnormalities in the operation process of the equipment, the operation parameters of the equipment, and the production quantity of the LED products.

[0045] The solution provided by the above steps can detect and judge the operating data of the equipment to see whether there is any abnormality during the operation of the equipment.

[0046] Also included is an LED abnormality confirmation method, the LED abnormality confirmation method comprising: S210: Acquire production process images of different positions of abnormal LED products and obtain detection image coefficients; S220: Testing the electrical signal of the abnormal LED product to obtain a current detection signal and a voltage detection signal; S230: Obtaining an abnormality determination coefficient through the image coefficient and the current detection signal and the voltage detection signal; S240: Retrieve the corresponding determination coefficient threshold from the big data storage unit 2, and compare it with the abnormality determination coefficient to determine whether the LED product is abnormal.

[0047] The technical solution provided in the above scheme can detect the produced LED products to determine whether the LED products are abnormal.

[0048] Unless otherwise specified, the device components involved in the above embodiments are all conventional device components, and the connection methods and control methods involved are all conventional connection methods and control methods unless otherwise specified.

[0049] The present invention has been described in detail above in conjunction with the embodiments. However, those skilled in the art will appreciate that, without departing from the spirit of the present invention, the specific parameters in the above embodiments may be changed to form a plurality of specific embodiments, which are all within the common variation range of the present invention and will not be described in detail herein.

Claims

1. An intelligent management and control system for LED production, characterized in that: include: Input unit: The material data, production process, equipment and personnel information of LED production products are input through the input unit; Big data storage unit: used to store data information of different LED products, production process information, normal operating range information of various current and voltage signals of production equipment, and operation steps information; Data acquisition unit: used to collect data on various currents, voltages and equipment operating conditions of LED production equipment during operation; Abnormal judgment unit: used to retrieve the normal operating data range of the corresponding LED product in the big data storage unit, and obtain the data collected by the data collection unit in real time; And compare and judge whether there is any abnormality; Exception processing unit: When the exception judgment unit determines that the collected data is abnormal, it can report the exception and handle it in the corresponding processing mode according to the exception type.

2. According to claim 1, the LED production intelligent management and control system is characterized in that: The data acquisition unit comprises: Equipment operation process data collection module: used to monitor and collect the operation process of the equipment operated by the production staff in real time; Equipment operation parameter acquisition module: used to collect the current and voltage data of LED production equipment and LED packaging equipment in real time during operation; Material production quantity collection module: used to monitor and collect the production quantity of different types of LED products.

3. According to claim 2, the LED production intelligent management and control system is characterized in that: The abnormality judgment unit comprises: Equipment operation process abnormality judgment module: used to obtain the data collected by the equipment operation process data collection unit, and compare it with the process steps input by the big data storage unit and the input unit to determine whether an abnormality occurs; Equipment operation parameter abnormality judgment module: used to obtain the data collected by the equipment operation parameter acquisition module, and compare it with the current and voltage data stored in the big data storage unit to determine whether there is an abnormality; Material production anomaly judgment module: used to obtain production quantity data of different types of LED products, and compare it with the material data input by the input unit to determine whether there is an abnormality.

4. The LED production intelligent management and control system according to claim 1, characterized in that: Also includes: Abnormality confirmation unit: After the abnormality judgment unit confirms that an abnormality has occurred in the production process, the abnormality confirmation unit confirms whether an abnormality has occurred in the production of LED products.

5. The LED production intelligent management and control system according to claim 4, characterized in that: The abnormality confirmation unit comprises: LED product image acquisition terminal: used to acquire production process images of different positions of abnormal LED products; Electrical signal test terminal: used to test the electrical signals of abnormal LED products; Abnormality judgment end: Compare and calculate the LED data information stored in the big data storage unit and the LED product image process and electrical signals to determine whether the LED product has any abnormality.

6. The LED production intelligent management and control system according to claim 5, characterized in that: The algorithm formula set in the abnormal judgment terminal is: ， in is the abnormal determination coefficient, is the standard current, To detect the current, is the proportion of current in abnormal judgment, is the standard voltage, is the detection voltage, is the proportion of voltage in abnormal judgment, Standard image coefficients, To detect the image coefficients, It is the proportion of production process in abnormality judgment.

7. The LED production intelligent management and control system according to claim 6, characterized in that: Abnormality determination coefficient thresholds for different types of LED products Different LED products have different abnormality determination coefficient thresholds. The calculated abnormal determination coefficient Compare and judge whether there is any abnormality in the LED product.

8. An intelligent management method for LED production, applied to an intelligent management and control system for LED production as claimed in any one of claims 1 to 7, characterized in that: include: S110: Inputting material data, production process, equipment and personnel information of LED products through an input unit; S120: During the production process, data on various currents, voltages and equipment operating conditions during the operation of LED production equipment are collected; S130: Retrieving the normal operation data range of the corresponding LED product in the big data storage unit, and acquiring the data collected by the data collection unit in real time; And compare and judge whether there is any abnormality; S140: When the abnormality judgment unit judges that the collected data is abnormal, an abnormality error is reported, and a corresponding processing mode is performed according to the abnormality type.

9. The LED production intelligent management method according to claim 8, characterized in that: The S3 includes: S131: Acquire equipment operation process data, equipment operation parameters, and production quantity data of different types of LED products; S132: comparing the data acquired in step S31 with the standard data of the corresponding LED product input by the big data storage unit and the input unit; S133: Determine whether there are abnormalities in the operation process of the equipment, the operation parameters of the equipment, and the production quantity of the LED products.

10. The LED production intelligent management method according to claim 8, characterized in that: Also included is an LED abnormality confirmation method, the LED abnormality confirmation method comprising: S210: Acquire production process images of different positions of abnormal LED products and obtain detection image coefficients; S220: Testing the electrical signal of the abnormal LED product to obtain a current detection signal and a voltage detection signal; S230: Obtaining an abnormality determination coefficient through the image coefficient and the current detection signal and the voltage detection signal; S240: Retrieve the corresponding determination coefficient threshold from the big data storage unit, and compare it with the abnormality determination coefficient to determine whether the LED product is abnormal.

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