Homology system for factory operation parameters in manufacturing industry

Abstract

The invention discloses a manufacturing industry factory operation parameter coherence system, and belongs to the technical field of intelligent manufacturing industry, and the system comprises an operation station unit which provides a workbench and outputs current operation record data; the working environment can be provided, and data can be recorded and output. The intelligent tool unit collects contact point data of an operator; and the operation data of the operator is recorded, so that real-time analysis and subsequent improvement are facilitated. The operator parameter acquisition unit acquires operation associated data of an operator; and the working state of the current operator is known from the side, so that the reason and probability of abnormality can be calculated. A data acquisition unit acquires the contact point data, the current operation record data and the operation association data, and summarizes and outputs the data; data of the whole workshop are integrated, data analysis and utilization are carried out in a higher level, and the overall efficiency is improved. And the workshop data processing center acquires and processes the summarized data, and outputs operation guidance data to realize operation parameter coherence, so that the data processing capability can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent manufacturing, and in particular to a manufacturing plant operation parameter synchronization system. Background Art

[0002] Manufacturing is a vital pillar of social development, and its products support all aspects of society. This is particularly true of the production of large-scale equipment, which requires the use of numerous tools, such as hammers, pliers, files, and wrenches. While unmanned manufacturing has achieved considerable progress, manual operation of tools still exists.

[0003] During these manual operations, errors can occur due to habits, physical conditions, and other factors. These errors can cause significant damage to the large and precision equipment being produced. This risk does not meet the requirements of quality control, and existing technologies generally only rely on post-event accountability, which is inefficient and lacks control capabilities. Summary of the Invention

[0004] The present invention proposes a manufacturing factory operation parameter synchronization system to solve the problems of insufficient traceability, poor timeliness and low production line control capabilities in the existing technology.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] Manufacturing factory operation parameter synchronization system, including:

[0007] The workstation unit is used to provide a workbench and output current work record data;

[0008] Smart tool units, used to collect operator touchpoint data;

[0009] An operator parameter collection unit is used to collect operator operation-related data;

[0010] A data acquisition unit, configured to acquire, summarize and output the contact point data, the current operation record data and operation-related data;

[0011] The workshop data processing center is used to obtain and process summary data and output operation guidance data to achieve synchronization of operation parameters.

[0012] The intelligent tool unit includes a tool body, a pressure sensor group, a fingerprint recognition component, a displacement sensor and a posture sensor; correspondingly, the contact point data includes pressure data, displacement data and posture data; the pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor are based on an embedded design and are combined with the tool body; the work station unit is provided with a storage space matching the intelligent tool unit, which is used to place the intelligent tool unit and realize maintenance and communication connection; the work station unit is provided with a modification tool box for storing embedded components, which is used to provide different models of the pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor.

[0013] The work station units are designated to form a production line, and the operation compliance standards of different work station units are determined according to the objects to be processed corresponding to the current production line; correspondingly, the workshop data processing center is used to obtain the contact point data and parse the operator's tool usage data, and determine the operation compliance judgment data based on the tool usage data and the corresponding current operation record data; wherein, if the operation compliance judgment data is non-compliant, verification, traceability and corrective measures are performed; if the operation compliance judgment data is compliant, the corresponding data is saved normally.

[0014] The production line includes a quality inspection station for testing and recording tool usage traces; based on the test results of the tool usage traces, associated features are determined from the contact point data, and corresponding associated weights are assigned to establish an operation guidance decision model; the workshop data processing center obtains the test records output by the quality inspection station, and based on the operation guidance decision model, outputs the operation guidance data to the intelligent tool unit, and the intelligent tool unit outputs feedback information to guide the operator to use the tool body; testing the tool usage traces includes appearance recording and parameter reverse test verification, wherein the appearance recording includes obtaining the appearance of the operation target and determining scratches, color difference and background control object differences based on image recognition; the parameter reverse test verification includes using the corresponding tool to reverse the operation and record the tool usage parameters.

[0015] The workshop data processing center is used to: compare the tool usage data before and after the feedback information is output to obtain first comparison data; compare the test results of the tool usage traces before and after the feedback information is output to obtain second comparison data; calculate a first effect score corresponding to the feedback information based on the first comparison data and the second comparison data; share the feedback information corresponding to the first effect score with other production lines; and after sharing, calculate second effect scores corresponding to different production lines to modify the feedback information or update the operation guidance decision model.

[0016] The intelligent tool unit also includes a vibration component and an audio-visual component for outputting the feedback information; the operation-related data includes the operator's identity identification code, psychological judgment information and physical identification information; based on daily training, the exclusive feedback information of a single operator is determined to control the vibration component and the audio-visual component to output the feedback information.

[0017] The intelligent tool unit further includes an error compensation control component for controlling the tool body when the contact point data exceeds a threshold value so that the tool usage data complies with the operation compliance standard.

[0018] The operator is a disabled person; accordingly, the work limitations of the disabled person are determined through the physical recognition information to decide or modify the feedback information; the psychological judgment information is determined through language recognition and appearance recognition, and the testing method and frequency of the quality inspection station are determined based on the psychological judgment information; the feedback information is synchronized according to the identity identification code.

[0019] The work of the operator is assigned according to the exclusive feedback information and the specifications of the object to be processed; the work assignment includes: selection of the intelligent tool unit, allocation of the work station unit and adjustment of the exclusive feedback information.

[0020] The workshop data processing center includes: a production management software integration module, which is used to integrate the summary data into the production management software; an abnormality prediction module, which is used to set a prediction module based on machine learning and artificial intelligence to obtain abnormality prediction information based on the data output by the production management software; a visualization module, which is used to output visualization data; and a tool testing module, which is used to test and update the intelligent tool unit based on feedback.

[0021] Due to the adoption of the above technical solution, the present invention has the following beneficial effects:

[0022] 1. The present invention uses an operation station unit to provide a workbench and output current operation record data; it can provide an operation environment and record and output data. The intelligent tool unit is used to collect the operator's contact point data; it can be used to record the operator's operation data to facilitate real-time analysis and subsequent improvements. The operator parameter collection unit is used to collect the operator's operation-related data; it can understand the current operator's working status from the side to infer the cause and probability of abnormality. The data collection unit is used to obtain the contact point data, the current operation record data and the operation-related data, summarize and output them; it can integrate the data of the entire workshop, analyze and utilize data at a higher level, and improve overall efficiency. The workshop data processing center is used to obtain and process the summary information, output the operation instruction data to achieve operation parameter synchronization, and improve the data processing capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of the manufacturing factory operation parameter synchronization system proposed by the present invention. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] like Figure 1 The manufacturing plant operation parameter synchronization system shown includes:

[0026] The workstation unit is used to provide a workbench and output current work record data;

[0027] Smart tool units, used to collect operator touchpoint data;

[0028] An operator parameter collection unit is used to collect operator operation-related data;

[0029] A data acquisition unit, configured to acquire, summarize and output the contact point data, the current operation record data and operation-related data;

[0030] The workshop data processing center is used to obtain and process summary data and output operation guidance data to achieve synchronization of operation parameters.

[0031] Large-scale equipment and specialized equipment typically have complex mechanical structures that require processing for connection, fixation, and assembly. If these processing parameters do not meet standards, resonance may cause the structure to loosen or collapse, or poor contact may lead to loss of function. Using robotic arms for all processing can provide stable quality. However, some large-scale equipment and specialized equipment do not have specially designed robotic arms, or due to cost constraints, unmanned operation equipment has not been introduced. Therefore, many factories still rely on manual operations.

[0032] The factory operation parameter synchronization system of the manufacturing industry includes an operation station unit. The essence of the operation station unit is a work station, including a base for placing the object to be processed, a power socket for providing energy, a tool cabinet for providing various parts, etc. At the same time, various electronic devices / sensors are used to obtain various data, such as operation videos, various parameters generated / output when the tool is working, etc.

[0033] The factory operation parameter synchronization system for manufacturing includes an intelligent tool unit, which collects operator contact point data. This is because most tools are manually operated. When using tools, manual force is required, which creates contact points and pressure. Different tool types and usage habits also lead to changes in angle and position. Recording operator operation data facilitates real-time analysis and subsequent improvements.

[0034] Manufacturing factory operation parameter synchronization systems, including operator parameter collection units, require quality control to go beyond post-event traceability and also include pre-event predictions to mitigate risks. This is achieved through the operator's operation-related data collected by the operator parameter collection unit. Specifically, operator operation-related data is used to indirectly describe the operator's working status, such as mental state and physical condition, which directly affects whether the operator is performing according to regulations.

[0035] The manufacturing plant's operational parameter synchronization system includes a data acquisition unit for data aggregation and output. Manufacturing plants are large, encompassing numerous processes. Setting up independent data processing units for each process would be extremely costly. The data acquisition unit allows for centralized data processing, meeting cost requirements.

[0036] The factory operation parameter synchronization system of the manufacturing industry includes a workshop data processing center. Through a specially set up data processing center, it can concentrate processing capabilities, improve data processing efficiency and reduce hardware costs.

[0037] The intelligent tool unit includes a tool body, a pressure sensor group, a fingerprint recognition component, a displacement sensor and a posture sensor; correspondingly, the contact point data includes pressure data, displacement data and posture data; the pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor are based on an embedded design and are combined with the tool body; the work station unit is provided with a storage space matching the intelligent tool unit, which is used to place the intelligent tool unit and realize maintenance and communication connection; the work station unit is provided with a modification tool box for storing embedded components, which is used to provide different models of the pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor.

[0038] The tool body is a conventional tool. Fixing parts can be set on the surface / gaps / holes that do not affect its normal use to install the pressure sensor group, fingerprint recognition component, displacement sensor and posture sensor on the tool body, and perform corresponding data transmission and processing capabilities. Transformation, that is, embedded transformation.

[0039] Multiple pressure sensors are installed where the tool is gripped to measure pressure, as different pressures at different locations will have different effects on the tool. A fingerprint recognition component ensures that the tool is being used by the operator, facilitating individual tracing while also preventing others from damaging the tool. Ensuring that the individual is familiar with the tool improves efficiency.

[0040] When a tool is in use, it sometimes opens, such as pliers, and sometimes moves back and forth, left and right, such as a wrench. Sensors placed on the various moving parts of the tool can sense the displacement changes between these components, known as displacement sensors. These sensors can reveal tool usage, such as the opening angle of pliers or the length of a wrench's opening. Specific analysis is performed based on the tool type and usage.

[0041] When in use, tools are not necessarily confined to a specific plane; they are three-dimensional. By measuring the tool's speed and acceleration, its posture can be determined, which is achieved through posture sensors. This posture testing can determine the tool's usage. For example, if the tool is used in the wrong range, it may hit other components, causing damage or injury. Or, if it is used at the wrong angle, it may not be able to complete the work properly, such as screws not being tightened properly or nails not being driven into place.

[0042] The work station units are designated to form a production line, and the operation compliance standards of different work station units are determined according to the objects to be processed corresponding to the current production line; correspondingly, the workshop data processing center is used to obtain the contact point data and parse the operator's tool usage data, and determine the operation compliance judgment data based on the tool usage data and the corresponding current operation record data; wherein, if the operation compliance judgment data is non-compliant, verification, traceability and corrective measures are performed; if the operation compliance judgment data is compliant, the corresponding data is saved normally.

[0043] Most mainstream factories today utilize assembly lines, which are composed of several designated workstations. These lines typically produce fixed, fixed-size objects, but sometimes also different types of objects. These different objects have different processing requirements, often referred to as operational compliance standards. For example, process A has rules, while process B has rules.

[0044] Contact point data cannot directly reveal machining conditions; it requires analysis. For example, different pressure combinations correspond to different tool usage data, which needs to be verified based on the actual tool type and operation type. Based on the contact point data's values, ranges, and trends, tool usage data can be derived using pre-defined formulas or data processing models. These pre-defined formulas or data processing models can be summarized or trained based on actual needs.

[0045] The operation compliance judgment data is determined based on the tool usage data and the corresponding current operation record data. If the operation compliance judgment data indicates non-compliance, verification, tracing, and corrective measures are performed; if the operation compliance judgment data indicates compliance, the corresponding data is stored normally.

[0046] The production line includes a quality inspection station for testing and recording tool usage traces; based on the test results of the tool usage traces, associated features are determined from the contact point data, and corresponding associated weights are assigned to establish an operation guidance decision model; the workshop data processing center obtains the test records output by the quality inspection station, and based on the operation guidance decision model, outputs the operation guidance data to the intelligent tool unit, and the intelligent tool unit outputs feedback information to guide the operator to use the tool body; testing the tool usage traces includes appearance recording and parameter reverse test verification, wherein the appearance recording includes obtaining the appearance of the operation target and determining scratches, color difference and background control object differences based on image recognition; the parameter reverse test verification includes using the corresponding tool to reverse the operation and record the tool usage parameters.

[0047] Quality inspection stations, typically QA or QE stations, are used to perform functional tests on products using functional fixtures, as well as to test the product's appearance. Specifically for this solution, tool usage traces primarily include tool parameters involved in use, such as torque, pressure, depth, and angle, as well as appearance, such as scratches or compression marks caused by contact between the tool and the product.

[0048] First, the product, i.e., the object to be processed, must have corresponding specification numbers / structural diagrams / parameter tables for its specifications; otherwise, industrial production would be impossible. Products are generally fixed in a specified position during the production process. At this point, the influence on tool usage marks can be determined to be human, that is, the influence of the operator using the tool. Since the positional relationship of the product is relatively stable, the corresponding tool usage marks can be determined through reverse analysis to determine the process of generation. For example, the direction and range of different scratches can determine the position of tool contact and the direction of relative movement; using specialized tools, such as torque wrenches, the corresponding torque can be recorded by reversing the process of loosening the bolt.

[0049] These processes are essentially quality control techniques. By analyzing and collecting the causes and values ​​of abnormalities through quality control, relevant features can be identified from the contact point data and assigned corresponding weights. For example, an abnormal scratch indicates incorrect tool posture during use; a deep scratch indicates excessive force; and an incorrect scratch shape indicates the use of the wrong tool model or type. The corresponding posture, force value, and tool model type are considered relevant features. Based on specific experimental analysis, weights can be assigned to different relevant features. The principle is that some tool marks are caused by complex factors, involving multiple relevant features, some of which are primary and others are secondary. Weights are used to determine the primary and secondary causes and address them. Based on data analysis methods such as machine algorithms and artificial intelligence (AI) models, combined with actual experimental data, a work guidance decision model can be established. This model outputs work guidance data to the intelligent tool unit. This work guidance data is used to correct the values ​​corresponding to the relevant features, such as requiring a change in pressure (e.g., less force), a change in posture (e.g., conforming to the work posture), or the use of a specified tool.

[0050] As mentioned above, the final form of a qualified industrial product must meet certain standards, such as the angle and position between different components. Image recognition can be used to identify scratches, color differences, and differences in background objects to determine whether the current product is qualified. Feedback information is the guidance information output by the intelligent tool unit based on the work instruction data, corresponding to the site. The principle is that specific tools vary greatly, and even individual tool usage habits vary, requiring on-site adjustments to improve efficiency.

[0051] The workshop data processing center is used to: compare the tool usage data before and after the feedback information is output to obtain first comparison data; compare the test results of the tool usage traces before and after the feedback information is output to obtain second comparison data; calculate a first effect score corresponding to the feedback information based on the first comparison data and the second comparison data; share the feedback information corresponding to the first effect score with other production lines; after sharing, calculate the second effect scores corresponding to different production lines to determine the effect of the feedback information corresponding to the first effect score, so as to modify the feedback information or update the operation guidance decision model.

[0052] After providing the operator with guidance, it's necessary to determine whether the operator has followed the instructions. Therefore, a data comparison is performed on the tool usage data before and after the feedback information is output. Based on the comparison results, a first comparison score is output. Theoretically, if the tool usage data before and after the feedback information is output are completely consistent, then a 100% improvement can be expected. However, in practice, this is unlikely, as humans are responsible for the work, and imperfections are normal. Therefore, the tool usage trace test results before and after the feedback information is output are compared. If there is improvement, and the improvement is good, a higher score is assigned; otherwise, a lower score is assigned. Improvements can be identified through data and visual recognition, for example, if the scratch area is reduced, the scratch depth is shallower, or the scratch angle changes by a certain angle; or if torque test results fall within a certain range; or if the angles and relative positions of different structures fall within a certain range. If the improvement is good, the feedback information corresponding to the first effect score is shared with other production lines to improve the overall yield rate of the factory floor. Similarly, if other production lines also show improvements and the corresponding second effect scores meet certain requirements, it means that the current feedback information is effective or has problems, and the feedback information can be modified or the operation guidance decision model can be updated.

[0053] The intelligent tool unit also includes a vibration component and an audio-visual component for outputting the feedback information; the operation-related data includes the operator's identity identification code, psychological judgment information and physical identification information; based on daily training, the exclusive feedback information of a single operator is determined to control the vibration component and the audio-visual component to output the feedback information.

[0054] Vibration or sound and light effects are more effective in practice: vibrations at different positions represent different feedback information. For example, vibration at the thumb position requires reducing the pressure when using the tool, while vibration at the little finger requires changing the posture when using the tool. Different sound effects represent different feedback information, for example, direct language output, requiring changes in the pressure and posture when using the tool, etc.

[0055] Based on daily training, operators can be familiarized with different feedback messages. Based on activities such as testing, customized feedback messages can be provided. For example, if operator A experiences vibration at the thumb position, the operator should reduce tool pressure, while if operator B experiences vibration at the thumb position, the operator should increase tool pressure. These customizations can be implemented based on actual testing, trials, and training.

[0056] The intelligent tool unit further includes an error compensation control component for controlling the tool body when the contact point data exceeds a threshold value so that the tool usage data complies with the operation compliance standard.

[0057] For example, adjusting torque, clamping wrench opening, fixing caliper angle length, etc. Modification is carried out according to the characteristics of specific tools.

[0058] The operator is a disabled person; accordingly, the work limitations of the disabled person are determined through the physical recognition information to decide or modify the feedback information; the psychological judgment information is determined through language recognition and appearance recognition, and the testing method and frequency of the quality inspection station are determined based on the psychological judgment information; the feedback information is synchronized according to the identity identification code.

[0059] In order to improve social responsibility and supplement personnel, the operators can be disabled people, and the physical identification information is the working limitations of disabled people, such as unchanged limb movement, visual limitations, etc., to determine or modify the feedback information, which can be more suitable for disabled people to perform operations.

[0060] Alternatively, body recognition information could include changes in data from specific touchpoints: for example, fatigue from prolonged tool use, with pressure readings consistently decreasing; or hand tremors causing unusual and frequent posture changes. In these cases, the employee could be asked to take a break (this isn't limited to people with disabilities; fatigue can also occur in the general population, but in practice, people with disabilities are more likely to experience excessive fatigue).

[0061] At the same time, in practice, there are occasional cases where work abnormalities are caused by psychological factors. In the best case, the operator is not paying attention while chatting, which leads to work abnormalities; in the worst case, the operator deliberately causes abnormalities, etc.; the more common case is that the worker is distracted, which leads to work abnormalities. Through face recognition and voice recognition, combined with specific language and face models, the current person's psychological judgment information, such as whether he is concentrating, whether he intends to do something bad, etc., can be inferred. If it is believed that the operator's working status will affect the yield of the product, the test method and frequency of the quality inspection station can be determined, such as increasing or reducing the inspection frequency, or checking specific locations (for example, if the operator suddenly lowers his head to work, or accidentally touches the product).

[0062] The work of the operator is assigned according to the exclusive feedback information and the specifications of the object to be processed; the work assignment includes: selection of the intelligent tool unit, allocation of the work station unit and adjustment of the exclusive feedback information.

[0063] In practice, talented individuals, such as skilled workers or role models, often emerge. In these cases, assigning tasks to workers based on their unique feedback and the specifications of the workpieces being processed can improve overall efficiency. For example, someone skilled in screwing could be assigned to the screw station, while someone skilled in fast and effective assembly could be assigned to the assembly station.

[0064] The selection of smart tool units and the adjustment of exclusive feedback information are similar in principle.

[0065] The workshop data processing center includes: a production management software integration module, which is used to integrate the summary data into the production management software; an abnormality prediction module, which is used to set a prediction module based on machine learning and artificial intelligence to obtain abnormality prediction information based on the data output by the production management software; a visualization module, which is used to output visualization data; and a tool testing module, which is used to test and update the intelligent tool unit based on feedback.

[0066] (1) Improve tightening accuracy and consistency: Solve the accuracy and consistency problems caused by human factors in traditional tightening operations, and achieve more precise tightening control through smart wrenches.

[0067] (2) Realize real-time data collection and analysis: solve the problems of real-time and accuracy of data collection, and ensure that tightening data can be collected and analyzed in real time and accurately.

[0068] (3) Intelligent control and automation: Through intelligent control strategies, the tightening process is optimized to ensure qualified and uniform torque distribution and improve assembly quality.

[0069] (4) Predictive maintenance and fault diagnosis: AI can be used to implement predictive maintenance of tools, reducing unexpected tool failures and downtime.

[0070] (5) System experience and ease of operation: Provide customized operation functions, automatically adjust settings according to the needs of different businesses, and provide a customized user experience.

[0071] (6) System compatibility and scalability: Ensure that the smart wrench system is compatible with the existing MES system and other production management systems, and has good scalability to adapt to future technological development and changes.

[0072] Embedded system design and development. Develop an intelligent wrench slave computer system with torque measurement, LCD display, over-torque warning, Bluetooth transmission, and error compensation capabilities. This system is used for tightening operations in intelligent automotive manufacturing to improve production efficiency and product quality.

[0073] The above description is a detailed description of the preferred embodiments of the present invention, but the embodiments are not intended to limit the scope of the patent application of the present invention. Any equivalent changes or modifications completed under the technical spirit suggested by the present invention should fall within the patent scope covered by the present invention.

Claims

1. Manufacturing factory operation parameter synchronization system, characterized by: include: The workstation unit is used to provide a workbench and output current work record data; Smart tool units, used to collect operator touchpoint data; An operator parameter collection unit is used to collect operator operation-related data; A data acquisition unit, configured to acquire, summarize and output the contact point data, the current operation record data and operation-related data; The workshop data processing center is used to obtain and process summary data and output operation guidance data to achieve synchronization of operation parameters.

2. The manufacturing plant operation parameter synchronization system according to claim 1, characterized in that: The intelligent tool unit includes a tool body, a pressure sensor group, a fingerprint recognition component, a displacement sensor and a posture sensor; Correspondingly, the contact point data includes pressure data, displacement data and posture data; The pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor are combined with the tool body based on an embedded design; The work station unit is provided with a receiving space matching the smart tool unit, for placing the smart tool unit and realizing maintenance and communication connection; The work station unit is provided with a modification tool box for storing embedded components, which is used to provide different models of the pressure sensor group, the fingerprint recognition component, the displacement sensor and the posture sensor.

3. The manufacturing plant operation parameter synchronization system according to claim 2, characterized in that: Designating the workstation units to form a production line, and determining the operation compliance standards of different workstation units according to the objects to be processed corresponding to the current production line; Correspondingly, the workshop data processing center is used to obtain the contact point data and parse it to obtain the operator's tool usage data, and determine the operation compliance judgment data based on the tool usage data and the corresponding current operation record data; If the operation compliance judgment data is non-compliant, verification, tracing and corrective measures are performed; If the operation compliance judgment data is compliant, the corresponding data is saved normally.

4. The manufacturing plant operation parameter synchronization system according to claim 3, characterized in that: The production line includes a quality inspection station for testing and recording tool usage traces; According to the test results of the tool usage traces, correlation features are determined from the contact point data, and corresponding correlation weights are assigned to establish an operation guidance decision model; The workshop data processing center obtains the test records output by the quality inspection station and outputs the operation guidance data to the intelligent tool unit based on the operation guidance decision model. The intelligent tool unit outputs feedback information to guide the operator to use the tool body. Testing the tool usage traces includes appearance recording and parameter reverse testing verification, wherein the appearance recording includes obtaining the appearance of the work target and determining scratches, color differences, and background control differences based on image recognition; The parameter reverse test verification includes using relevant tools to perform reverse operations and recording tool usage parameters.

5. The manufacturing plant operation parameter synchronization system according to claim 4, characterized in that: The workshop data processing center is used to: Comparing the tool usage data before and after the feedback information is output to obtain first comparison data; Comparing the test results of the tool usage trace before and after the feedback information is output to obtain second comparison data; Calculating a first effect score corresponding to the feedback information based on the first comparison data and the second comparison data; Sharing the feedback information corresponding to the first effect score with other production lines; After sharing, second effect scores corresponding to different production lines are calculated to modify the feedback information or update the operation guidance decision model.

6. The manufacturing plant operation parameter synchronization system according to claim 5, characterized in that: The intelligent tool unit further includes a vibration component and an acousto-optic component for outputting the feedback information; The operation-related data includes the operator's identification code, psychological identification information, and physical identification information; Based on daily training, exclusive feedback information for a single operator is determined to control the vibration component and the sound and light component to output the feedback information.

7. The manufacturing plant operation parameter synchronization system according to claim 6, characterized in that: The intelligent tool unit further includes an error compensation control component for controlling the tool body when the contact point data exceeds a threshold value so that the tool usage data complies with the operation compliance standard.

8. The manufacturing plant operation parameter synchronization system according to claim 7, characterized in that: The operator is a person with a disability; Correspondingly, determining the work limitations of the disabled person through the body recognition information to determine or modify the feedback information; Determine the psychological discrimination information through language recognition and appearance recognition, and determine the testing method and frequency of the quality inspection station based on the psychological discrimination information; The feedback information is synchronized according to the identity identification code.

9. The manufacturing plant operation parameter synchronization system according to claim 7 or 8, characterized in that: Assigning work to operators based on the exclusive feedback information and the specifications of the object to be processed; The work allocation includes: selection of the intelligent tool unit, allocation of the work station unit and adjustment of the exclusive feedback information.

10. The manufacturing plant operation parameter synchronization system according to claim 9, characterized in that: The workshop data processing center includes: A production management software integration module, used to integrate the summary data into the production management software; An abnormality prediction module is used to set a prediction module based on machine learning and artificial intelligence to obtain abnormality prediction information based on the data output by the production management software; Visualization module, used to output visual data; The tool testing module is used to test and update the intelligent tool unit based on feedback.

Images