Automobile chassis framework welding mistake-proofing identification system and method

Abstract

The invention relates to the technical field of automobile production and manufacturing, in particular to an automobile chassis framework welding mistake-proofing recognition system and method. The method comprises the following steps: designing an error-proofing scheme, and carrying out core component model selection; mounting a mistake proofing device, and establishing connection with the PLC control system; pLC programming and logic debugging are carried out; the standard component is calibrated and tested before production, and personnel are trained; mistake-proofing operation in the production process is carried out, and operation data are recorded in real time; the system comprises a building module, a linkage module, a programming and logic debugging module, a calibration module and a data recording module. By means of the mode, mistake-proofing recognition can be conducted, parts of two vehicle types are actively distinguished in the assembling stage, the vehicle type parts are prevented from being used mistakenly, and internal and external quality losses are reduced.

Description

Technical Field

[0001] This invention relates to the field of automobile manufacturing technology, and in particular to an error-proofing identification system and method for automobile chassis frame welding. Background Technology

[0002] In the automotive manufacturing industry, the chassis frame, as the core component for load-bearing and connection, directly determines the stability of the rear body structure and the overall vehicle safety performance through its welding quality. With the diversification of vehicle models, the chassis frame structures of models derived from the same platform are often highly similar. For example, the CN112 and CN115 models have completely identical stamping processes for their rear beam bodies, resulting in a very high degree of similarity in the shape, size, and tooling adaptability of the rear beams.

[0003] During the production process of the welding section in the stamping and welding workshop, the assembly of the rear beam usually relies on the pre-assembly tooling of the main frame to complete the positioning. The positioning hole design of the existing tooling is based on the common structure of the two models and adopts a shared mode, which aims to be compatible with the production of multiple models to improve equipment utilization.

[0004] However, in the production of the existing chassis frame, due to the relatively hidden differences in the rear beam features between the CN112 and CN115 models (whether or not the front leaf spring extension beam is punched), traditional tooling lacks a targeted error-proofing and identification mechanism, making it impossible to actively distinguish the parts of the two models during the assembly stage. This makes it difficult for operators to quickly identify the ownership of parts through vision or experience, which easily leads to the problem of incorrect installation of the rear beam. Summary of the Invention

[0005] The purpose of this invention is to provide a welding error prevention and identification system and method for automobile chassis frames, aiming to solve the technical problem that traditional tooling in the prior art lacks a targeted error prevention and identification mechanism, cannot actively distinguish parts of two different models during the assembly stage, and makes it difficult for operators to quickly identify the ownership of parts through vision or experience, which easily leads to the problem of incorrect installation of the rear beam.

[0006] To achieve the above objectives, the present invention provides a method for error prevention and identification in automobile chassis frame welding, comprising the following steps: Design error-proofing schemes and select core components; Install error-proofing devices and establish a connection with the PLC control system; Perform PLC programming and logic debugging; Standard parts are calibrated and tested before production, and personnel are trained accordingly. Implement error-proofing operations during the production process and record operational data in real time.

[0007] Among the steps involved in designing error-proofing schemes and selecting core components: By comparing and analyzing the rear beam structure of CN112 and CN115 models, the front leaf spring extension beam area was identified as the core identification part. The CN115 model has multiple weight reduction holes in the extension beam, while the CN112 model has no punched holes in the extension beam. The weight reduction holes were identified as the key difference in error prevention identification. An ifm photoelectric switch was selected as the laser sensor for detecting the leaf spring extension beam; The installation points were planned, and the laser sensors were installed in the corresponding area of ​​the front leaf spring extension beam of the rear beam, taking into account the structural characteristics of the pre-assembled tooling of the main frame. The sensor detection range completely covered the area with different characteristics and did not interfere with other assembly components.

[0008] Among the steps, the installation of error-proofing devices and the establishment of a connection with the PLC control system are as follows: Based on the sensor size and installation location space requirements, a special mounting bracket is designed and manufactured. The bracket is made of high-strength metal and is fixed to the designated position of the pre-assembled tooling with bolts. Fix the laser sensor on the mounting bracket, adjust the sensor angle so that the laser beam is accurately aligned with the differential feature area of ​​the front leaf spring extension beam, connect the sensor power line and the signal transmission line, and connect one end of the signal line to the existing PLC control system in the workshop. An audible and visual alarm device is installed next to the pre-assembled tooling and a signal connection is established with the PLC control system for subsequent abnormal situation prompts. Status indicator lights are added to the tooling operation panel to display three states: normal, incorrect vehicle model, and sensor failure.

[0009] Among the steps involved in PLC programming and logic debugging: Based on the signal output rules of the laser sensor, a PLC program is written. When the sensor detects a hole in the extension beam, it outputs a high-level digital signal; when no hole is detected, it outputs a low-level digital signal. The PLC determines the current vehicle model based on the type of signal received. Link the vehicle model recognition results with the tooling clamping mechanism and write program instructions; The signal anomaly judgment logic is set up, including the sensor failing to output a valid signal twice in a row and the signal switching frequently within 1 second. If the signal is judged as a sensor failure or part positioning deviation, the PLC will immediately trigger the audible and visual alarm device, and the sensor fault indicator light will be lit on the operation panel to suspend the production process. Simulated signals were used to simulate the detection scenarios for CN112 and CN115 models. The PLC system was input to verify the accuracy of the recognition logic. Abnormal situations such as sensor failure and incorrect model installation were simulated. The interlocking function between the alarm device and the tooling was tested to ensure it was working properly. The program response speed was optimized based on the debugging results.

[0010] In the step of linking the vehicle model recognition result with the tooling clamping mechanism and writing program instructions: If the signal received by the PLC matches the vehicle model in the current production plan, the tooling clamping signal is triggered, the tooling is closed, and the welding process is allowed; if the signal does not match the planned vehicle model, the tooling clamping signal is immediately cut off, the tooling remains open, and production is prohibited.

[0011] Among the steps, the standard parts are calibrated and tested before production, and personnel are trained accordingly. Ten standard rear beam parts for CN112 and CN115 models were selected and installed sequentially into the pre-assembly fixture. The error prevention system was activated for testing, and the model identification result and fixture action status were recorded each time. Perform 50 consecutive cycles of standard part inspection and record the time taken from part positioning to tooling action for each inspection. Training was conducted for operators of welding section C in the stamping and welding workshop. The training covered the working principle of the error prevention system, the identification of the status of the control panel, and the handling procedures for abnormal alarms. Practical assessments were also conducted.

[0012] Among the steps involved in error-proofing operations during production and recording operational data in real time: After the rear beam parts are installed into the pre-installed fixture, the system automatically starts the laser sensor to scan and detect the front leaf spring extension beam area and transmits signals to the PLC in real time after confirming the part positioning through the operation panel. After receiving the signal, the PLC performs vehicle model identification and compares it with the production plan; The PLC system automatically records the time of each inspection, vehicle model recognition results, tooling action status, and whether an alarm is triggered, and uploads the data to the workshop production management system in real time to form a traceable production record.

[0013] Among them, in the step of PLC receiving signals and comparing vehicle model with production plan: If the parts match, the fixture will automatically close, the normal indicator light on the control panel will illuminate, and the operator can start the subsequent welding process; if the parts do not match, the fixture will not close, the audible and visual alarm will be activated, the incorrect model indicator light on the control panel will illuminate, and the operator will need to check and replace the parts.

[0014] This invention also provides an automotive chassis frame welding error prevention and identification system, including a construction module, a linkage module, a program writing and logic debugging module, a calibration module, and a data recording module; wherein: The construction module is used to design error prevention schemes and select core components; The linkage module is used to install error prevention devices and establish a connection with the PLC control system; The programming and logic debugging module is used for PLC programming and logic debugging. The calibration module is used to calibrate and test standard parts before production and to train personnel. The data recording module is used for error prevention during the production process and records the operation data in real time.

[0015] This invention discloses a welding error prevention and identification system and method for automotive chassis frames. The system comprises the following steps using the aforementioned assembly module, linkage module, programming and logic debugging module, calibration module, and data recording module: designing an error prevention scheme and selecting core components; installing error prevention devices and establishing a connection with the PLC control system; programming and debugging the PLC program; calibrating and testing standard parts before production and training personnel; and conducting error prevention operation during production, recording operational data in real time. Through these methods, error prevention identification is achieved, proactively distinguishing parts from two different vehicle models during the assembly stage to prevent the use of incorrect parts and reduce internal and external quality losses. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the steps of the automobile chassis frame welding error prevention and identification method of the present invention.

[0018] Figure 2 This is a flowchart of steps S100 of the present invention.

[0019] Figure 3 This is a flowchart of steps S200 of the present invention.

[0020] Figure 4 This is a flowchart of steps S300 of the present invention.

[0021] Figure 5 This is a flowchart of steps S400 of the present invention.

[0022] Figure 6 This is a flowchart of steps S500 of the present invention.

[0023] Figure 7 This is a schematic diagram of the principle of the automotive chassis frame welding error prevention and identification system of the present invention.

[0024] 701-Building Module, 702-Linkage Module, 703-Programming and Logic Debugging Module, 704-Calibration Module, 705-Data Recording Module. Detailed Implementation

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0026] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0027] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0028] Please see Figures 1-6 This invention provides a method for error prevention and identification in automobile chassis frame welding, comprising the following steps: S100: Design error-proofing schemes and select core components.

[0029] In this embodiment, a fault-proofing scheme is designed and core components are selected. The specific process is as follows: S101: By comparing and analyzing the rear beam structure of CN112 and CN115 models, the front leaf spring extension beam area is identified as the core identification part. The CN115 model has multiple weight reduction holes in the extension beam, while the CN112 model has no punched holes in the extension beam. The weight reduction holes are taken as the key difference point for error-proof identification. S102: An ifm photoelectric switch is selected as the laser sensor for detecting the leaf spring extension beam; S103: Plan the installation points and, in combination with the structural characteristics of the pre-assembled fixtures of the main frame, install the laser sensor in the corresponding area of ​​the front leaf spring extension beam of the rear beam. The sensor's detection range completely covers the area with different characteristics and does not interfere with other assembly components.

[0030] In the above process, firstly, by comparing and analyzing the rear beam structure of CN112 and CN115 models, the front leaf spring extension beam area was identified as the core identification part. The CN115 model's extension beam has multiple weight-reduction holes, while the CN112 model's extension beam has no punched holes. The weight-reduction holes were used as the key difference point for error-proof identification. Then, an IFM photoelectric switch was selected as the laser sensor for detecting the leaf spring extension beam. Next, the installation point was planned. Combining the structural characteristics of the main frame pre-assembly fixture (the first process of assembling the beam), the laser sensor was installed in the corresponding area of ​​the front leaf spring extension beam of the rear beam. The sensor's detection range completely covers the difference feature area and does not interfere with other assembly parts.

[0031] S200: Install error prevention devices and establish a connection with the PLC control system.

[0032] In this embodiment, the error-proofing device is installed and connected to the PLC control system. The specific process is as follows: S201: Based on the sensor size and installation point space requirements, a special mounting bracket is designed and manufactured. The bracket is made of high-strength metal and is fixed to the designated position of the pre-assembled tooling with bolts. S202: Fix the laser sensor on the mounting bracket, adjust the sensor angle so that the laser beam is accurately aligned with the differential feature area of ​​the front leaf spring extension beam, connect the sensor power line and the signal transmission line, and connect one end of the signal line to the existing PLC control system in the workshop. S203: Install an audible and visual alarm device next to the pre-installed tooling and establish a signal connection with the PLC control system for subsequent abnormal situation prompts. Add status indicator lights to the tooling operation panel to display three states: normal, incorrect vehicle model, and sensor failure.

[0033] In the above process, firstly, a special mounting bracket is designed and manufactured according to the sensor size and installation point space requirements. The bracket is made of high-strength metal and is fixed to the designated position of the pre-installed fixture with bolts. Then, the laser sensor is fixed on the mounting bracket, and the sensor angle is adjusted so that the laser beam is accurately aligned with the differential feature area of ​​the front leaf spring extension beam. The sensor power line and signal transmission line are connected, and one end of the signal line is connected to the existing PLC control system in the workshop. An audible and visual alarm device is installed next to the pre-installed fixture and a signal connection is established with the PLC control system for subsequent abnormal situation prompts. Status indicator lights are added to the fixture operation panel to display three states: normal, incorrect vehicle model, and sensor malfunction, so that operators can check in real time.

[0034] S300: Perform PLC programming and logic debugging.

[0035] In this embodiment, the PLC program is written and the logic is debugged. The specific process is as follows: S301: Based on the signal output rules of the laser sensor, a PLC program is written. When the sensor detects a hole in the extension beam, it outputs a high-level digital signal. When no hole is detected, it outputs a low-level digital signal. The PLC determines the current vehicle model based on the type of signal received. S302: Link the vehicle model recognition results with the tooling clamping mechanism and write program instructions; S303: Set signal abnormality judgment logic, including if the sensor fails to output a valid signal twice in a row and the signal switches frequently within 1 second, it is judged as a sensor failure or part positioning deviation. The PLC immediately triggers the audible and visual alarm device, lights up the sensor fault indicator on the operation panel, and suspends the production process. S304: Use analog signals to simulate the detection scenarios of CN112 and CN115 models, input the signals into the PLC system to verify the accuracy of the recognition logic, simulate abnormal situations such as sensor failure and incorrect model installation, test whether the alarm device and tooling interlock function are normal, and optimize the program response speed based on the debugging results.

[0036] In the above process, firstly, based on the signal output rules of the laser sensor, a PLC program is written. When the sensor detects a hole in the extension beam, it outputs a high-level digital signal; when no hole is detected, it outputs a low-level digital signal. The PLC determines the current vehicle model based on the received signal type. Then, the vehicle model recognition result is linked with the tooling clamping mechanism, and program instructions are written. If the signal received by the PLC matches the vehicle model in the current production plan, the tooling clamping signal is triggered, the tooling closes, and the welding process is allowed. If the signal does not match the planned vehicle model, the tooling clamping signal is immediately cut off, the tooling remains open, and production is prohibited. Next, signal anomaly judgment logic is set, including the sensor failing to output a valid signal (high / low level) twice consecutively and the signal switching frequently within 1 second, which is judged as a sensor failure or part positioning deviation. The PLC immediately triggers the audible and visual alarm device and illuminates the sensor fault indicator on the operation panel, pausing the production process. Analog signals are used to simulate the detection scenarios of CN112 and CN115 vehicle models, and the PLC system is input to verify the accuracy of the recognition logic. Abnormal situations such as sensor failure and incorrect vehicle model installation are simulated to test whether the alarm device and tooling interlock function are normal. The program response speed is optimized based on the debugging results.

[0037] S400: Standard parts are calibrated and tested before production, and personnel are trained accordingly.

[0038] In this embodiment, standard parts are calibrated and tested before production, and personnel are trained accordingly. The specific process is as follows: S401: Select 10 standard rear beam parts for CN112 and CN115 models, install them sequentially into the pre-installation fixture, activate the error prevention system for testing, and record the model identification result and fixture action status for each time. S402: Perform 50 consecutive standard part inspection cycles and record the time taken from part positioning to tooling action for each inspection; S403: Organize training for operators of welding section C in the stamping and welding workshop. The training content includes the working principle of the error prevention system, the identification of the status of the operation panel, and the abnormal alarm handling process, and conducts practical assessment.

[0039] In the above process, firstly, 10 standard rear beam parts for CN112 and CN115 models were selected and installed sequentially into the pre-assembled fixture. The error prevention system was then activated for testing, and the model identification results and fixture movement status were recorded for each test. Then, 50 consecutive standard part testing cycles were performed, and the time taken from part positioning to fixture movement was recorded for each test. Next, training was conducted for the operators of welding section C in the stamping and welding workshop. The training included the working principle of the error prevention system, operation panel status recognition, and abnormal alarm handling procedures, and a practical assessment was conducted.

[0040] S500: Performs error-proofing operation during the production process and records operational data in real time.

[0041] In this embodiment, error-proofing operation is performed during the production process, and operational data is recorded in real time. The specific process is as follows: S501: After installing the rear beam parts into the pre-installed fixture, confirm the part positioning through the operation panel. The system will automatically start the laser sensor to scan and detect the front leaf spring extension beam area and transmit signals to the PLC in real time. S502: After receiving the signal, the PLC performs vehicle model identification and production plan comparison; S503: The PLC system automatically records the time of each inspection, vehicle model recognition results, tooling action status, and whether an alarm is triggered, and uploads the data to the workshop production management system in real time to form a traceable production record.

[0042] In the above process, the rear beam parts are first installed onto the pre-assembled fixture. After confirming the part positioning is complete via the operation panel, the system automatically activates the laser sensor to scan and detect the front leaf spring extension beam area, transmitting signals to the PLC in real time. Then, after receiving the signal, the PLC performs vehicle model identification and comparison with the production plan. If they match, the fixture automatically closes, the normal indicator light on the operation panel illuminates, and the operator can start the subsequent welding process. If they do not match, the fixture does not close, the audible and visual alarm device is activated, the incorrect vehicle model indicator light on the panel illuminates, and the operator needs to check and replace the parts. The PLC system automatically records the time of each inspection, the vehicle model identification result, the fixture action status, and whether the alarm was triggered, and uploads this data to the workshop production management system in real time, forming a traceable production record.

[0043] Please see Figure 7This invention provides a welding error prevention and identification system for automotive chassis frames, comprising an assembly module 701, a linkage module 702, a program writing and logic debugging module 702, a calibration module 704, and a data recording module 705; wherein: The assembly module 701 is used to design error prevention schemes and select core components; The linkage module 702 is used to install error prevention devices and establish a connection with the PLC control system; The program writing and logic debugging module 702 is used for PLC program writing and logic debugging; The calibration module 704 is used to perform calibration tests on standard parts before production; The data recording module 705 is used for error prevention during the production process and records the operation data in real time.

[0044] In this embodiment, the construction module 701 is used to design a fault-proofing scheme and select core components; a fault-proofing device is installed, and the linkage module 702 is used to connect the fault-proofing device to the PLC control system; the program writing and logic debugging module 702 is used to write and debug the PLC program; the calibration module 704 performs calibration testing on standard parts before production; fault-proofing operation is carried out during production, and the data recording module 705 records the operation data in real time.

[0045] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0046] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. An automobile chassis frame welding mistake proofing recognition method, characterized by, The method comprises the following steps: Designing an error-proofing scheme and selecting core components; Installing error-proofing devices and connecting with PLC control system; Writing PLC program and logical debugging; Calibrating standard parts before production and training personnel; Error-proofing operation during production and recording operation data in real time.

2. The automobile chassis frame welding mistake proofing recognition method according to claim 1, characterized in that, In the step of designing an error-proofing scheme and selecting core components: By comparing and analyzing the rear beam structure of CN112 and CN115 models, the front leaf spring extension beam area is locked as the core identification part. There are multiple lightening holes in the extension beam of CN115 model, while there are no lightening holes in the extension beam of CN112 model. The lightening holes are used as the key difference for error-proofing identification; An ifm photoelectric switch is selected as the laser sensor for detecting the leaf spring extension beam; The installation point is planned, and the laser sensor is installed on the corresponding area of the rear beam front leaf spring extension beam according to the structure characteristics of the main line skeleton pre-installation tool. The sensor detection range completely covers the difference feature area and does not interfere with other assembly components.

3. The automobile chassis frame welding mistake proofing recognition method according to claim 1, characterized in that, In the step of installing error-proofing devices and connecting with PLC control system: According to the size of the sensor and the space requirement of the installation point, a special installation bracket is designed and made. The bracket is made of high-strength metal material and is fixed on the specified position of the pre-installation tool by bolts; The laser sensor is fixed on the installation bracket, the sensor angle is adjusted to make the laser beam accurately align with the difference feature area of the front leaf spring extension beam, the sensor power line and signal transmission line are connected, and one end of the signal line is connected to the existing PLC control system in the workshop; A sound and light alarm device is installed beside the pre-installation tool and connected with the PLC control system for subsequent abnormal situation prompt. A status indicator light is added to the tool operation panel to display three states: normal, model error and sensor failure.

4. The automobile chassis frame welding mistake proofing recognition method according to claim 1, characterized in that, In the step of writing PLC program and logical debugging: Based on the signal output rule of the laser sensor, the PLC program is written. When the sensor detects holes in the extension beam, it outputs a high-level digital signal. When no holes are detected, it outputs a low-level digital signal. The PLC determines the current model by receiving the signal type; The model recognition result is linked with the tool clamping mechanism, and the program instruction is written; The signal abnormality judgment logic is set, including 2 times of continuous sensor output of invalid signal and frequent switching of signal within 1 second, which is determined as sensor failure or part positioning deviation. The PLC immediately triggers the sound and light alarm device, lights up the sensor failure indicator light on the operation panel, and suspends the production process; An analog signal is used to simulate the detection scenarios of CN112 and CN115 models, which are input into the PLC system to verify the accuracy of the identification logic. The abnormal situations such as sensor failure and model misinstallation are simulated to test whether the alarm device and tool interlock function are normal. The program response speed is optimized according to the debugging results.

5. The automobile chassis frame welding mistake proofing recognition method according to claim 4, characterized in that, In the step of linking the model recognition result with the tool clamping mechanism and writing program instruction: If the signal received by the PLC is consistent with the model in the current production plan, the tool clamping signal is triggered, the tool is closed, and the welding process is allowed to proceed. If the signal is not consistent with the planned model, the tool clamping signal is immediately cut off, the tool remains open, and production is prohibited.

6. The automobile chassis frame welding mistake proofing recognition method according to claim 1, characterized in that, In the step of calibrating the standard parts before production and training the personnel: Select 10 standard rear frame parts for each of the CN112 and CN115 models, install them in turn to the pre-assembly tool, start the error-proofing system for detection, and record the model recognition result and tool action state each time; Perform 50 consecutive standard part detection cycles, and record the time consumed from part positioning to tool action each time; Organize the welding C section operators in the punch-welding workshop to carry out training, including the working principle of the error-proofing system, operation panel state recognition, abnormal alarm processing flow, and practical operation examination.

7. The automobile chassis frame welding mistake proofing recognition method according to claim 1, characterized in that, In the step of running the error-proofing during production and recording the running data in real time: After installing the rear frame part into the pre-assembly tool, confirm the completion of part positioning through the operation panel, the system automatically starts the laser sensor to scan and detect the front spring extension beam area, and transmits signals to the PLC in real time; After the PLC receives the signals, perform model recognition and production plan comparison; Through the PLC system, automatically record the time of each detection, model recognition result, tool action state, and whether the alarm is triggered, and upload the data to the workshop production management system in real time to form traceable production records.

8. The automobile chassis frame welding mistake proofing recognition method according to claim 7, characterized in that, In the step of model recognition and production plan comparison after the PLC receives the signals: If matched, the tool automatically closes the clamp, the normal indicator light on the operation panel is lit, and the operator can start the subsequent welding process; if not matched, the tool does not close the clamp, the sound and light alarm device is started, the model error indicator light on the panel is lit, and the operator needs to check and replace the parts.

9. A chassis frame welding mistake identification system applied to the chassis frame welding mistake identification method of claim 1, characterized in that, It includes a building module, a linkage module, a program writing and logic debugging module, a calibration module, and a data recording module; among them: The building module is used to design the error-proofing scheme and select the core components; The linkage module is used to install the error-proofing device and establish a connection with the PLC control system; The program writing and logic debugging module is used for PLC program writing and logic debugging; The calibration module is used to calibrate the standard parts before production and train personnel; The data recording module is used to run the error-proofing during production and record the running data in real time.

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