Production line multi-process combined control system for forklift half shaft production

Abstract

The invention belongs to the technical field of forklift half shaft production management and control, and particularly relates to a production line multi-process combined control system for forklift half shaft production, which comprises an induction cooker heating module, a bar end upsetting machining module, a flange plate extrusion forming module, a mechanical arm transfer module, a multi-process combined control module and a production line supervision center, uniform heating of the heating end of a bar is achieved through an induction cooker heating module, a bar end upsetting machining module accurately applies axial pressure to guarantee the purpose that the heating end of the bar becomes thick and short, and a flange plate extrusion forming module pushes steel to completely fill a cavity through a customized mold to form a flange plate. Unified cooperative control of multiple working procedures of the production line of forklift half shaft production is achieved, manual operation is replaced, errors are reduced, potential hazards of all equipment are recognized in advance through the joint control risk early warning module, early warning is generated, continuous, safe and stable operation of the production line is effectively guaranteed, and the operation supervision difficulty of the production line of forklift half shaft production is remarkably reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forklift axle production control, in particular to a production line multi-process joint control system for forklift axle production. BACKGROUND

[0002] As the core force transmission component of the forklift drive system, the flange hot forming process of the forklift axle needs to go through electromagnetic heating, bar transfer, upsetting processing, extrusion forming and cooling and crack prevention, etc. Each process has strict requirements for temperature control, pressure parameters, transfer accuracy and collaborative rhythm, which directly affects the mechanical properties and forming quality of the axle.

[0003] As disclosed in the Chinese patent CN105063468A, a forklift axle forging process is involved. The patent document clearly states that in the traditional forklift axle forging and processing process, the multiple heating times lead to significant increase in forging and energy consumption, long forging time and low efficiency, and the forging precision is difficult to effectively control, and the labor intensity of the staff is large, which is not conducive to energy saving and emission reduction and high-quality production requirements.

[0004] At present, even if some production lines introduce automatic equipment, it is still difficult to realize the unified and collaborative control of the production line multi-process of the forklift axle production, and there is generally a lack of risk early warning and operation effect evaluation mechanism in the whole process, it is difficult to make reasonable improvement measures in advance and in time, at the same time, the isolation effectiveness evaluation link of the safety hidden danger of the production line area is missing, the risk overflow and diffusion situation cannot be grasped in time, which leads to the difficulty in meeting the large-scale and high-precision production requirements of the forklift axle in quality control, production efficiency and safety management. Therefore, a solution is proposed. SUMMARY

[0005] The purpose of the present application is to provide a production line multi-process joint control system for forklift axle production to solve the technical defects proposed in the background art.

[0006] To achieve the above purpose, the present application provides the following technical scheme: a production line multi-process joint control system for forklift axle production, comprising an electromagnetic oven heating module, a bar end upsetting processing module, a flange plate extrusion forming module, a mechanical arm transfer module, a multi-process joint control module and a production line supervision center. The multi-process joint control module controls the electromagnetic oven heating module, the bar end upsetting processing module, the flange plate extrusion forming module and the mechanical arm transfer module, and sends the control information and the operation monitoring information of each device module to the production line supervision center. The mechanical arm transfer module fixes the pretreated bar and places it in the electromagnetic oven heating module, and the electromagnetic oven heating module heats one end of the pretreated bar through electromagnetic heating. When the bar is heated to the standard, the mechanical arm transfer module transfers the bar to the bar end upset processing module, and the bar end upset processing module applies axial pressure to the heated end of the bar through a hydraulic press to cause plastic deformation of the heated end of the bar to achieve the effect of upsetting to thicken and shorten the bar; The mechanical arm transfer module transfers the upset bar to the flange plate extrusion forming module, and the flange plate extrusion forming module extrudes the upset segment of the bar through an extruder, so that the steel material plastically flows in the customized die of the extruder, completely fills the die cavity, and is formed into a preliminary shape of a flange plate.

[0007] Further, the multi-process joint control module is in communication connection with the joint control risk early warning module, the multi-process joint control module sends control information and operation monitoring information of each device module to the joint control risk early warning module, the joint control risk early warning module analyzes the operation control performance of each device, judges whether to generate a joint control early warning signal, and sends the joint control early warning signal to the production line supervision center when the joint control early warning signal is generated. When the production line supervision center receives the joint control early warning signal, the corresponding early warning is issued.

[0008] Further, the specific analysis process of the joint control risk early warning module includes: By capturing and analyzing the evaluation, it is judged whether there is a maintenance difficulty parameter in the corresponding module device within a unit time, if there is a maintenance difficulty parameter in the corresponding module device within a unit time, the corresponding module device is marked as a cooperative non-beneficial device; if there is no maintenance difficulty parameter in the corresponding module device within a unit time, the running normalization analysis is used to judge whether the corresponding module device is a cooperative non-beneficial device; if there is a cooperative non-beneficial device, a joint control early warning signal is generated.

[0009] Further, the specific process of the capturing and analyzing evaluation is as follows: After obtaining the parameters that need to be monitored in the working process of the corresponding device module, the real-time data of the corresponding parameters are compared with the corresponding set standard value requirements, if the real-time data of the corresponding parameters do not meet the corresponding set standard value requirements, it is judged that the corresponding parameters are in a non-matching state; The length of time that the corresponding parameters are in a non-matching state within a unit time is obtained and is compared with the total working time of the corresponding device module within a unit time to obtain a parameter matching abnormal time value, and if the corresponding parameters cannot be restored to a normal state within the corresponding standard time when it is judged that the corresponding parameters are in a non-matching state, an abnormal recovery symbol QK-1 is given, and the number of times that the corresponding parameters correspond to the abnormal recovery symbol QK-1 is obtained and is marked as a recovery abnormality frequency value; The parameter matching abnormal time value and the recovery abnormal frequency value are compared with the corresponding preset parameter matching abnormal time threshold value and the preset recovery abnormal frequency threshold value respectively, and if the parameter matching abnormal time value or the recovery abnormal frequency value exceeds the corresponding preset threshold value, the corresponding parameter is marked as a maintenance difficult parameter of the corresponding module device.

[0010] Further, the specific analysis process of the running normalization analysis is as follows: The parameter matching abnormal time value of the corresponding parameter is calculated by the ratio to obtain a first characteristic value, and the recovery abnormal frequency value of the corresponding parameter is calculated by the ratio to obtain a second characteristic value, and the first characteristic value and the second characteristic value are weighted and summed to obtain a characteristic weighted value; A set of preset weight values corresponding to each parameter is set in advance, the characteristic weighted value of the corresponding parameter is multiplied by the corresponding preset weight value to obtain a characteristic influence value, and the characteristic influence values of all parameters required to be monitored by the corresponding device module are summed to obtain a characteristic comprehensive coefficient, and the characteristic comprehensive coefficient is compared with the corresponding preset characteristic comprehensive coefficient threshold value, if the characteristic comprehensive coefficient exceeds the preset characteristic comprehensive coefficient threshold value, the corresponding module device is marked as a non-beneficial device.

[0011] Further, the joint control risk early warning module is communicatively connected to the production line running effect output module, if no joint control early warning signal is generated within a unit time, the production line running effect for forklift axle production within a unit time is analyzed through the production line running effect analysis module, whether a production line operation efficiency early warning signal is generated is determined through the analysis, and when the production line operation efficiency early warning signal is generated, it is sent to the production line supervision center, and the production line supervision center sends an appropriate early warning when receiving the production line operation efficiency early warning signal.

[0012] Further, the specific analysis process of the production line running effect analysis module is as follows: The number of forklift axle production scrap within a unit time is obtained and compared with the total number of forklift axles processed within a unit time to obtain a forklift axle scrap rate value, and the forklift axle scrap rate value is compared with the preset forklift axle scrap rate threshold value, if the forklift axle scrap rate value exceeds the preset forklift axle scrap rate threshold value, a production line operation efficiency early warning signal is generated; If the forklift axle scrap rate value does not exceed the preset forklift axle scrap rate threshold value, the number of production line running interruptions within a unit time is marked as a production line operation interruption detection frequency value, and the duration of the production line running interruption within a unit time is marked as a production line operation interruption detection time value, and the production line operation interruption detection frequency value and the production line operation interruption detection time value are compared with the preset production line operation interruption detection frequency threshold value and the preset production line operation interruption detection time threshold value respectively, if the production line operation interruption detection frequency value or the production line operation interruption detection time value exceeds the corresponding preset threshold value, a production line operation efficiency early warning signal is generated; If the production line operation detection frequency value and the production line operation detection time value do not exceed the corresponding preset threshold value, the processing time for each forklift half shaft in a unit time is calculated to obtain an efficiency fluctuation value, and the number of forklift half shafts whose processing time exceeds the preset processing time threshold value is compared with the total number of processed forklift half shafts in a unit time to obtain an efficiency buffer occupation value. The efficiency fluctuation value and the efficiency buffer occupation value are compared with the preset efficiency fluctuation threshold value and the preset efficiency buffer occupation threshold value, respectively. If the efficiency fluctuation value or the efficiency buffer occupation value exceeds the corresponding preset threshold value, a production line operation efficiency early warning signal is generated.

[0013] Further, the production line operation effect output module is communicatively connected to the isolation effectiveness evaluation module. If no production line operation efficiency early warning signal is generated in a unit time, the safety hazard degree of the production line to the peripheral space in a unit time is analyzed by the isolation effectiveness evaluation module to determine whether to generate an isolation effectiveness early warning signal. When the isolation effectiveness early warning signal is generated, it is sent to the production line supervision center, and the production line supervision center sends out a corresponding early warning when receiving the isolation effectiveness early warning signal.

[0014] Further, the specific analysis process of the isolation effectiveness evaluation module includes: The edge profile of the area involved in the production line is obtained and marked as a target profile. A plurality of target points are set on the target profile. The target points are used as starting positions to extend L1 meters outward to determine diffusion points. All diffusion points are connected to form a diffusion profile. The area surrounded by the diffusion profile and the target profile is marked as an isolation area. Environmental monitoring equipment is deployed at a plurality of positions in the isolation area. Whether there is an isolation vulnerability position in the isolation area is determined by analysis. If there is an isolation vulnerability position in the isolation area, an isolation effectiveness early warning signal is generated. If there is no isolation vulnerability position in the isolation area, the isolation effectiveness anomaly value of all positions in the isolation area is calculated to obtain an effectiveness characteristic value. The effectiveness characteristic value is compared with a preset effectiveness characteristic threshold value. If the effectiveness characteristic value exceeds the preset effectiveness characteristic threshold value, an isolation effectiveness early warning signal is generated.

[0015] Further, the analysis and determination method of the isolation vulnerability position is as follows: The average temperature of the corresponding position in a unit time is obtained and marked as a temperature risk characteristic value. The average dust concentration and average noise decibel value of the corresponding position in a unit time are marked as dust risk characteristic value and noise risk characteristic value, respectively. The types of harmful gases that need to be monitored in the isolation area are obtained. The concentrations of all types of harmful gases at the corresponding position are collected in real time and summed to obtain a harmful gas concentration sum coefficient. The average of all harmful gas concentration sum coefficients in a unit time is calculated to obtain a gas risk characteristic value. The isolation effectiveness anomaly value is obtained by weighted summation of temperature hazard characteristic value, dust hazard characteristic value, noise hazard characteristic value and air hazard characteristic value. The isolation effectiveness anomaly value is compared with the preset isolation effectiveness anomaly value threshold. If the isolation effectiveness anomaly value exceeds the preset isolation effectiveness anomaly value threshold, the corresponding location is marked as the isolation vulnerability location of the isolation area.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. In this invention, the heating end of the bar is uniformly heated by the induction cooker heating module, and the bar end upsetting module makes the heating end of the bar thicker and shorter. The flange extrusion forming module forms a flange at the heating end through extrusion. This realizes unified collaborative control of multiple processes in the forklift half-shaft production line, replaces manual operation and reduces errors. Furthermore, the joint control risk warning module identifies potential hazards of each piece of equipment in advance and generates warnings, effectively ensuring the continuous safe and stable operation of the production line and significantly reducing the difficulty of production line operation supervision for forklift half-shaft production.

[0017] 2. In this invention, the production line operation effect analysis module monitors the production effect from multiple dimensions and promptly detects quality decline and efficiency abnormalities when there is no joint control warning, ensuring the production line operation effect. In addition, the isolation effectiveness assessment module accurately judges the safety hazards caused by the production line to the surrounding space, avoiding the risk spillover from the production line area, which is conducive to ensuring personnel health and production environment compliance, and further reducing the difficulty of production line operation supervision for forklift half shaft production. Attached Figure Description

[0018] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiments 2 and 3 of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1: As Figure 1 As shown, the multi-process joint control system for forklift half-shaft production line proposed in this invention includes an induction cooker heating module, a bar end upsetting module, a flange extrusion forming module, a robotic arm transfer module, a multi-process joint control module, a joint control risk early warning module, and a production line monitoring center; The multi-process combined control module controls the electromagnetic stove heating module, the rod end upsetting processing module, the flange plate extrusion forming module and the mechanical arm transfer module, and sends control information and operation monitoring information of each device module to the production line supervision center, realizes full-process automatic control of the forklift half shaft production, replaces tedious operations such as repeated adjustment of temperature, pressure, transfer path and the like by manual, reduces operation errors caused by differences in manual experience, and can provide visual production state monitoring information for supervisors, guarantee the stable and coherent production rhythm of the production line, and reduce the difficulty of production management.

[0021] The mechanical arm transfer module (which realizes stable clamping and transfer of the rod by precise posture adjustment and preset path planning, improves the connection efficiency and continuity of the whole process) fixes the pretreated rod by the mechanical arm and places it in the electromagnetic stove heating module. The electromagnetic stove heating module heats one end of the pretreated rod (the part that needs to be formed into a flange plate) by electromagnetic heating, provides qualified hot-state rods for subsequent upsetting and forming, reduces forming defects caused by uneven heating or temperature deviation from the source, and guarantees the quality of flange plate hot forming. It should be noted that, according to the temperature requirement of flange plate hot forming in the production and processing process of the forklift half shaft, a fixed heating temperature interval of 1100-1250°C is preset (this interval can make the steel reach the austenite state and have good plasticity); and the electromagnetic heating is realized by electromagnetic induction, which is uniform and efficient, can accurately control the heating area, and avoids overheating of the whole rod.

[0022] When the rod heating is up to standard, a "heating completion signal" is sent out, and the mechanical arm transfer module transfers the rod to the rod end upsetting processing module. Specifically, the rod is accurately clamped after adjusting the posture of the mechanical arm, and then transferred to the press table according to the preset path to ensure that the heated end of the rod (i.e. the part that needs to be upset) is aligned with the pressing position of the hydraulic press. After placing the rod on the press table, a "rod in place signal" is sent to the hydraulic press to trigger the upsetting process. The rod end upsetting processing module applies axial pressure to the heated end of the rod by the hydraulic press (usually with a tonnage of 1000-2000 tons) to make the heated end of the rod plastically deform, so as to realize the upsetting effect of "thickening and shortening" and reserve enough material volume for subsequent flange plate forming.

[0023] When the upsetting process is completed, a "upsetting completion signal" is sent out, the mechanical arm transfer module transfers the upset rod to the flange extrusion forming module through the mechanical arm, the flange extrusion forming module extrudes the upset section of the rod through the extruder, so that the steel material plastically flows in the customized die of the extruder (the die cavity is consistent with the shape of the finished flange, including the thickness of the flange and the preformed structure of the bolt hole), completely fills the die cavity, and finally forms the preliminary shape of the flange (forms the preliminary shape including the main body of the flange and the preformed groove of the connecting hole), effectively guarantees the integrity and size consistency of the preformed structure of the flange, greatly reduces the rework rate caused by structural loss or size out-of-tolerance after forming, and improves the stability of the flange forming quality.

[0024] Further, the multi-process joint control module sends control information and operation monitoring information of each device module to the joint control risk early warning module, the joint control risk early warning module analyzes the operation control performance of each device, and judges whether to generate a joint control early warning signal, and sends the joint control early warning signal to the production line supervision center when the joint control early warning signal is generated; When the production line supervision center receives the joint control early warning signal, the corresponding early warning is sent out, which can early warning and remind the supervisor to troubleshoot and repair, avoid the expansion of hidden dangers to cause equipment damage or safety accidents, effectively guarantee the continuous safe and stable operation of the production line, and reduce the waste rate and production loss caused by equipment problems; the specific analysis process of the joint control risk early warning module is as follows: After obtaining the parameters that need to be monitored in the working process of the corresponding device module (such as the heating temperature of the induction cooker heating module, the hydraulic pressure of the rod end upsetting processing module, and the extrusion pressure of the flange extrusion forming module), the real-time data of the corresponding parameters are compared with the corresponding set standard value requirements. If the real-time data of the corresponding parameters do not meet the corresponding set standard value requirements, it indicates that the operation of the corresponding parameters deviates, which is not conducive to the safe and stable operation of the corresponding module equipment, and then it is judged that the corresponding parameters are in a non-matching state; The time length of the corresponding parameter in the non-matching state in the unit time is obtained and compared with the total working time of the corresponding device module in the unit time to obtain the parameter matching abnormal time value. If the corresponding parameter cannot be restored to normal state within the corresponding standard time when it is judged that the corresponding parameter is in a non-matching state, it indicates that the control efficiency for the corresponding non-matching state is slow, and then the recovery abnormal symbol QK-1 is assigned, and the number of times the corresponding parameter is assigned to the recovery abnormal symbol QK-1 in the unit time is obtained and marked as the recovery abnormal symbol frequency value; The parameter matching abnormal time value and the recovery abnormal symbol frequency value are compared with the corresponding preset parameter matching abnormal time threshold value and the preset recovery abnormal symbol frequency threshold value, respectively. If the parameter matching abnormal time value or the recovery abnormal symbol frequency value exceeds the corresponding preset threshold value, it indicates that the maintenance control condition of the corresponding parameter in the unit time is not good, and then the corresponding parameter is marked as a difficult parameter of the corresponding module equipment; If the corresponding module equipment has parameters that are difficult to maintain within a unit of time, it indicates that the risk level of multi-process joint control of the forklift half shaft production line is high within a unit of time. In this case, the corresponding module equipment is marked as equipment that is not favorable for cooperation. If the corresponding module equipment does not have parameters that are difficult to maintain within a unit of time, the first feature value is obtained by comparing the parameter matching time-varying value of the corresponding parameter with the corresponding preset parameter matching time-varying threshold value. The second feature value is obtained by comparing the recovery anomaly standard frequency value of the corresponding parameter with the corresponding preset recovery anomaly standard frequency threshold value. The first feature value is obtained by weighted summation of the first and second feature values. Specifically, the first and second feature values ​​are assigned corresponding preset weight coefficients, and the first and second feature values ​​are multiplied by their respective preset weight coefficients. The sum of the two product results is then marked as the feature weight value. It should be noted that the larger the feature weight value, the worse the overall performance of the corresponding parameter. Each parameter is pre-set to correspond to a set of preset weight values ​​(all values ​​are greater than zero, and the more severe the adverse effect of the abnormality of the corresponding parameter on the module device, the larger the value of the preset weight value that matches it). The feature weight value of the corresponding parameter is multiplied by the corresponding preset weight value to obtain the feature influence value, and the feature influence values ​​of all parameters that the corresponding device module needs to monitor are summed to obtain the feature comprehensive coefficient. It should be noted that the larger the value of the feature comprehensive coefficient, the worse the overall performance of the corresponding module equipment in operation and control within a unit of time. The feature comprehensive coefficient is compared with the corresponding preset feature comprehensive coefficient threshold. If the feature comprehensive coefficient exceeds the preset feature comprehensive coefficient threshold, it indicates that the overall performance of the corresponding module equipment in operation and control within a unit of time is poor, and the corresponding module equipment is marked as non-cooperative equipment. If there is non-cooperative equipment within a unit of time, it indicates that the degree of hidden danger in the joint control of multiple processes in the forklift half shaft production line within a unit of time is high, and a joint control early warning signal is generated.

[0025] Example 2: Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that the joint control risk warning module is connected to the production line operation effect output module. If no joint control warning signal is generated within a unit time, the production line operation effect analysis module analyzes the production line operation effect used for forklift half shaft production within a unit time and determines whether to generate a production line operation effect warning signal. When a production line operation efficiency early warning signal is generated, it is sent to the production line monitoring center. Upon receiving the signal, the center issues a corresponding warning. The system analyzes the production line's operation from three dimensions: quality, stability, and efficiency. It comprehensively monitors the actual operational performance of the production line, promptly identifying issues such as quality decline, frequent interruptions, and efficiency fluctuations. This helps supervisors quickly pinpoint the causes and implement improvement measures, strengthening subsequent production line operation monitoring. Ultimately, this ensures the production line maintains a consistently high-efficiency and high-quality operating state, reducing cost waste and resource consumption. The specific analysis process of the production line operation efficiency analysis module is as follows: The number of forklift half shafts produced and scrapped within a unit time is obtained and the ratio is calculated with the total number of forklift half shafts processed within a unit time to obtain the forklift half shaft scrap rate value. The forklift half shaft scrap rate value is compared with the preset forklift half shaft scrap rate threshold. If the forklift half shaft scrap rate value exceeds the preset forklift half shaft scrap rate threshold, it indicates that the operating quality of the production line within a unit time is not good, and a production line operation efficiency warning signal is generated. If the scrap rate of the forklift half shaft does not exceed the preset scrap rate threshold, the number of production line interruptions per unit time is marked as the production line interruption detection frequency value, and the duration of production line interruptions per unit time is marked as the production line interruption detection time value. The production line interruption detection frequency value and the production line interruption detection time value are compared with the preset production line interruption detection frequency threshold and the preset production line interruption detection time threshold respectively. If the production line interruption detection frequency value or the production line interruption detection time value exceeds the corresponding preset threshold, it indicates that the operation stability of the production line is not good per unit time, and a production line operation efficiency warning signal is generated. If the production line downtime detection frequency and downtime value do not exceed the corresponding preset thresholds, the variance of the processing time for each forklift half-shaft per unit time is calculated to obtain the efficiency fluctuation value, and the ratio of the number of forklift half-shafts whose processing time exceeds the preset processing time threshold to the total number of forklift half-shafts processed per unit time is calculated to obtain the efficiency buffer value. The efficiency fluctuation value and efficiency buffer value are then compared with the preset efficiency fluctuation threshold and preset efficiency buffer threshold, respectively. If the efficiency fluctuation value or efficiency buffer value exceeds the corresponding preset threshold, it indicates that the production line's operating efficiency is poor per unit time, and a production line operation efficiency warning signal is generated.

[0026] Example 3: Figure 2 As shown, the difference between this embodiment and Embodiment 1 and Embodiment 2 is that the production line operation effect output module is connected to the isolation effectiveness evaluation module. If no production line operation effect warning signal is generated within a unit time, the isolation effectiveness evaluation module analyzes the degree of safety hazards that the production line brings to the surrounding space within a unit time, and determines whether to generate an isolation effectiveness warning signal through analysis. And when generating the isolation effectiveness early warning signal, it is sent to the production line supervision center, when the production line supervision center receives the isolation effectiveness early warning signal, the corresponding early warning is issued, which can effectively control the safety hidden danger of the production line to the peripheral space, avoid the risk of the production line area to overflow and spread, protect the health and safety of the peripheral personnel, ensure that the production environment of the production line meets the safety specification requirements, improve the safety and compliance of the overall production scene, which is conducive to further reducing the difficulty of production line operation supervision; The specific analysis process of the isolation effectiveness evaluation module is as follows: The edge contour of the area involved in the production line is obtained and marked as the target contour. A plurality of target points are set on the target contour. The target points are used as the starting position to extend L1 meters outward to determine the diffusion points. Preferably, L1 is three meters. All diffusion points are connected to form a diffusion contour. The area surrounded by the diffusion contour and the target contour is marked as the isolation area. Environmental monitoring equipment is deployed at several positions in the isolation area. Based on the environmental monitoring equipment, monitoring and data collection are carried out. The average temperature of the corresponding position per unit time is obtained and marked as the temperature risk characteristic value. The average dust concentration and average noise decibel value of the corresponding position per unit time are marked as the dust risk characteristic value and the noise risk characteristic value, respectively. The types of harmful gases (such as carbon monoxide, sulfide, nitrogen oxide, etc.) that need to be monitored in the isolation area are obtained. The concentration of all types of harmful gases at the corresponding position is collected in real time and summed to obtain the harmful gas concentration coefficient. The average of all harmful gas concentration coefficients per unit time is calculated to obtain the gas risk characteristic value. The temperature risk characteristic value, the dust risk characteristic value, the noise risk characteristic value and the gas risk characteristic value are weighted and summed to obtain the isolation effectiveness anomaly value, that is, the temperature risk characteristic value, the dust risk characteristic value, the noise risk characteristic value and the gas risk characteristic value are respectively assigned corresponding preset weight coefficients, and the temperature risk characteristic value, the dust risk characteristic value, the noise risk characteristic value and the gas risk characteristic value are respectively multiplied by the corresponding preset weight coefficients, and the sum of the four product results is marked as the isolation effectiveness anomaly value. It should be noted that the larger the value of the isolation effectiveness anomaly value, the worse the isolation effect of the corresponding position per unit time; The isolation effectiveness anomaly value is compared with the preset isolation effectiveness anomaly threshold value. If the isolation effectiveness anomaly value exceeds the preset isolation effectiveness anomaly threshold value, it means that the isolation effect of the corresponding position per unit time is poor, and the corresponding position is marked as the isolation leakage position of the isolation area. If there is an isolation leakage position in the isolation area, it means that the isolation effectiveness of the production line processing area per unit time is not good, and the safety risk to the peripheral personnel is high, and the isolation effectiveness early warning signal is generated. If there is no isolation leakage position in the isolation area, the isolation effectiveness characteristic value of all positions in the isolation area is calculated by averaging the isolation effectiveness anomaly values of all positions in the isolation area, and the effectiveness characteristic value is compared with the preset effectiveness characteristic threshold value, if the effectiveness characteristic value exceeds the preset effectiveness characteristic threshold value, it indicates that the isolation effectiveness of the production line processing area in unit time is not good, and the safety risk to the peripheral personnel is higher, and an isolation effectiveness early warning signal is generated.

[0027] The working principle of the present application is as follows: when in use, the electromagnetic oven heating module is used to heat the rod heating end uniformly through electromagnetic induction, the rod end upsetting processing module precisely applies axial pressure through a hydraulic press to ensure that the rod heating end becomes thicker and shorter, the flange plate extrusion forming module relies on a customized die to push the steel to completely fill the cavity to form a flange plate, ensuring the forming quality of the flange plate and the continuity of the process, realizing unified and coordinated control of multiple processes of the forklift half shaft production line, replacing manual operation to reduce errors, and through the joint control risk early warning module, potential hazards of each device are identified in advance and early warning is generated, effectively ensuring the continuous safe and stable operation of the production line, and significantly reducing the difficulty of forklift half shaft production line operation supervision.

[0028] The threshold or preset value, preset range and the like in the technical scheme of the present application are set for result comparison and analysis, so as to determine whether it is good or not, and the size of the same is determined according to large model analysis of sample data and artificial experience, and is recorded and stored, and can be appropriately adjusted through seasonal or rational influence conditions; and the preset weight coefficient, influence factor and the like are set according to the influence of each parameter on the result, to allocate specific numerical values to finally reflect the influence of the result, and are recorded and stored through large model analysis of sample data and artificial experience, and can be appropriately adjusted through seasonal or rational influence conditions.

[0029] The preferred embodiments of the application disclosed above are only used to help explain the application, and the preferred embodiments do not describe all the details and do not limit the application to the specific embodiments. Obviously, many modifications and changes can be made according to the content of the present application. The embodiments are selected and described in the present application in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. A multi-process integrated control system for forklift half-shaft production lines, characterized in that, It includes an induction cooker heating module, a bar end upsetting module, a flange extrusion molding module, a robotic arm transfer module, a multi-process joint control module, and a production line monitoring center; The multi-process joint control module controls the induction cooker heating module, the bar end upsetting module, the flange extrusion forming module, and the robotic arm transfer module, and sends the control information and the operation monitoring information of each equipment module to the production line monitoring center. The robotic arm transfer module fixes the pre-treated bar and places it into the induction cooker heating module. The induction cooker heating module heats one end of the pre-treated bar through electromagnetic heating. Once the bar is heated to the required temperature, the robotic arm transfer module transfers the bar to the bar end upsetting module. The bar end upsetting module applies axial pressure to the heated end of the bar using a hydraulic press, causing the heated end of the bar to undergo plastic deformation. The robotic arm transfer module transfers the upset bar stock to the flange extrusion forming module. The flange extrusion forming module uses an extruder to extrude the upset section of the bar stock, causing the steel to flow plastically within the custom mold of the extruder, completely filling the mold cavity to form the preliminary shape of the flange.

2. The multi-process joint control system for forklift half-shaft production line according to claim 1, characterized in that, The multi-process joint control module communicates with the joint control risk early warning module. The joint control risk early warning module analyzes the operation and management performance of each piece of equipment and determines whether to generate a joint control early warning signal. When a joint control early warning signal is generated, it is sent to the production line monitoring center.

3. The multi-process joint control system for forklift half-shaft production line according to claim 2, characterized in that, The specific analysis process of the joint control risk early warning module includes: By capturing and analyzing the evaluation, it is determined whether there are maintenance difficulties parameters for the corresponding module equipment within a unit time. If maintenance difficulties parameters exist for the corresponding module equipment within a unit time, the corresponding module equipment is marked as a non-favorable cooperation device. If maintenance difficulties parameters do not exist for the corresponding module equipment within a unit time, normalization analysis is performed to determine whether the corresponding module equipment is a non-favorable cooperation device. If a non-favorable cooperation device exists, a joint control early warning signal is generated.

4. The multi-process joint control system for forklift half-shaft production line according to claim 3, characterized in that, The specific process of capturing, parsing and evaluating is as follows: obtain the duration of the corresponding parameter being in a non-matching state within a unit time and calculate the ratio with the total working time of the corresponding device module within a unit time to obtain the parameter matching time value; and obtain the number of times the recovery anomaly symbol QK-1 corresponding to the corresponding parameter is assigned within a unit time and mark it as the recovery anomaly standard frequency value. If the parameter matches an out-of-time value or recovers an abnormal standard frequency value exceeding the corresponding preset threshold, the corresponding parameter will be marked as a maintenance difficulty parameter for the corresponding module device.

5. The multi-process joint control system for forklift half-shaft production line according to claim 3, characterized in that, The specific analysis process for performing normalization analysis is as follows: The first feature value and the second feature value are weighted and summed to obtain the feature weight value. The feature weight value of the corresponding parameter is multiplied by the corresponding preset weight value to obtain the feature influence value. The feature influence values ​​of all parameters that the corresponding device module needs to monitor are summed to obtain the feature comprehensive coefficient. If the feature comprehensive coefficient exceeds the preset feature comprehensive coefficient threshold, the corresponding module device is marked as a non-advantageous device.

6. The multi-process joint control system for forklift half-shaft production line according to claim 2, characterized in that, The joint control risk warning module communicates with the production line operation effect output module. If no joint control warning signal is generated within a unit of time, the production line operation effect analysis module analyzes the production line operation effect used for forklift half shaft production within a unit of time. The analysis determines whether to generate a production line operation efficiency warning signal. When a production line operation efficiency warning signal is generated, it is sent to the production line monitoring center.

7. The multi-process joint control system for forklift half-shaft production line according to claim 6, characterized in that, The specific analysis process of the production line operation effect analysis module is as follows: If the scrap rate of the forklift half shaft exceeds the preset scrap rate threshold, a production line operation efficiency warning signal is generated; if the scrap rate of the forklift half shaft does not exceed the preset scrap rate threshold, the production line operation interruption detection frequency value and production line operation interruption detection time value are compared with the preset production line operation interruption detection frequency threshold and preset production line operation interruption detection time threshold respectively. If the production line operation interruption detection frequency value or the production line operation interruption detection time value exceeds the corresponding preset threshold, a production line operation efficiency warning signal is generated. If the production line operation interruption detection frequency and the production line operation interruption detection time do not exceed the corresponding preset threshold, the efficiency fluctuation value and the efficiency buffer value are compared with the preset efficiency fluctuation threshold and the preset efficiency buffer threshold respectively. If the efficiency fluctuation value or the efficiency buffer value exceeds the corresponding preset threshold, a production line operation efficiency warning signal is generated.

8. The multi-process joint control system for forklift half-shaft production line according to claim 6, characterized in that, The production line operation effect output module communicates with the isolation effectiveness assessment module. If no production line operation effect warning signal is generated within a unit of time, the isolation effectiveness assessment module analyzes the degree of safety hazards that the production line poses to the surrounding space within a unit of time. The analysis determines whether to generate an isolation effectiveness warning signal, and when an isolation effectiveness warning signal is generated, it is sent to the production line monitoring center.

9. The multi-process joint control system for forklift half-shaft production line according to claim 8, characterized in that, The specific analysis process of the isolation effectiveness assessment module includes: The edge contour of the area involved in the production line is obtained and marked as the target contour. The area enclosed by the diffusion contour and the target contour is marked as the isolation area. If there is an isolation gap in the isolation area, an isolation effectiveness warning signal is generated. If there is no isolation gap in the isolation area, the average value of the isolation effectiveness anomalies of all locations in the isolation area is calculated to obtain the effectiveness feature value. If the effectiveness feature value exceeds the preset effectiveness feature threshold, an isolation effectiveness warning signal is generated.

10. The multi-process joint control system for forklift half-shaft production line according to claim 9, characterized in that, The specific methods for analyzing and determining the location of isolation vulnerabilities are as follows: The isolation effectiveness anomaly value is obtained by weighted summation of temperature hazard characteristic value, dust hazard characteristic value, noise hazard characteristic value and air hazard characteristic value. If the isolation effectiveness anomaly value exceeds the preset isolation effectiveness anomaly value threshold, the corresponding location is marked as the isolation vulnerability location of the isolation area.

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