Desktop type intelligent manufacturing production line for teaching and scoring system thereof

Abstract

The invention discloses a desktop type intelligent manufacturing production line for teaching and a scoring system thereof. The desktop type intelligent manufacturing production line comprises a production line and a scoring system. The scoring system is composed of a camera monitoring module, an operation process division module, an operation analysis module, a scoring module and a feedback display module. The camera monitoring module collects real-time video data of student operation and transmits the real-time video data to the operation process division module, and the operation process of the production line is divided into a plurality of operation stages. And the operation analysis module compares the student operation with the standard model to generate a deviation quantification result. The scoring module calculates an interval score according to the deviation and generates an overall score, and the feedback display module outputs a scoring result in a visual mode. Through cooperation of multiple modules, monitoring, scoring and feedback of production line operation are realized, and the teaching efficiency and the learning effect are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial teaching, and more specifically, to a desktop intelligent manufacturing production line for teaching and a scoring system thereof. Background Art

[0002] In recent years, with the rapid development of industrial automation technology, intelligent manufacturing assembly lines have been widely used, and the demand for cultivating industrial automation talents has also increased. In order to meet the needs of teaching and training, the teaching intelligent manufacturing assembly line, which shrinks the industrial assembly line and deploys it on the desktop, has gradually become an important tool in vocational schools and corporate training. This teaching assembly line, with its miniaturization, modularization and strong operability, provides students with a low-risk, high-efficiency learning environment, enabling them to intuitively understand the basic principles of production processes and equipment operation.

[0003] However, there are significant differences in design purpose and function between industrial assembly lines and teaching assembly lines. Industrial assembly lines are mainly used for actual production, and their design goal is to achieve efficient, stable and low-cost mass production, while teaching assembly lines focus more on the cultivation and training of students' skills. The core of the teaching assembly line is to help students master the debugging, operation and optimization methods of assembly line equipment by simulating industrial scenarios. Its purpose is not only to complete production tasks, but also to enable students to achieve a deep understanding and flexible mastery of assembly line equipment and processes through repeated operations. Therefore, the teaching assembly line needs to have a high degree of visualization and operation feedback capabilities so that students can clearly understand the effect of each step of the operation and possible errors.

[0004] In the actual teaching process, the teaching pipeline is simple enough and can be debugged by professionals to determine the best standard operation mode. This standard mode can not only serve as a reference for students' operations, but also provide an objective evaluation basis for students' learning outcomes. However, the current teaching pipeline has certain limitations in terms of scoring and feedback mechanisms. For example, existing systems usually lack real-time and accuracy, the quality of students' operations is difficult to quantify, and teachers' guidance on students' operations mainly relies on subjective judgment, resulting in low teaching efficiency. In addition, the existing scoring system usually cannot intuitively display specific problems and improvement suggestions in students' operations, which limits the further improvement of teaching effectiveness. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a desktop intelligent manufacturing production line for teaching and a scoring system thereof, which realizes real-time monitoring, deviation analysis and result feedback of student operations by combining a camera monitoring module, an operation process division module, an operation analysis module, a scoring module and a feedback display module. The system accurately scores the student's operation based on the standard operation mode, and outputs the results in a visual way, providing students with intuitive and clear improvement directions, thereby effectively improving teaching efficiency and student skill levels.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A desktop intelligent manufacturing production line for teaching and a scoring system thereof, comprising a desktop intelligent manufacturing production line and a scoring system configured accordingly, wherein the scoring system comprises a camera monitoring module, an operation process division module, an operation analysis module, a scoring module, and a feedback display module, wherein:

[0008] The camera monitoring module is used to collect real-time video data of the production line operation process operated by students and transmit it to the operation process division module;

[0009] The operation process division module is used to divide the production line operation process corresponding to the video data into multiple intervals, each interval corresponding to an operation stage of the production line;

[0010] The operation analysis module is used to compare the student's operation in each interval with the preset standard operation model to generate a quantitative result of the deviation;

[0011] The scoring module is used to calculate the interval score according to the deviation of each interval, and generate an overall score based on the scores of each interval;

[0012] The feedback display module is used to output the scoring results in a visual manner.

[0013] In one embodiment, the operation analysis module further corresponds the deviation to an operation parameter or program code input by the student.

[0014] Furthermore, the scoring module also marks the operation parameters or program codes input by the students that are related to the deviations.

[0015] In an optional embodiment, the deviation includes any one or more of the following: time deviation, action deviation and effect deviation.

[0016] In an optional embodiment, the visualization method includes any one or more of the following: video playback, interval scoring chart, light prompt and code highlighting.

[0017] In one embodiment, the desktop intelligent manufacturing production line includes:

[0018] Loading area;

[0019] A first mechanical arm for grabbing materials in the loading area;

[0020] A conveyor belt for transporting materials from the loading area to the assembly area;

[0021] A second robotic arm for assembling materials;

[0022] The third robot arm is used to transport the assembled materials to the finished product area.

[0023] More specifically, the operation process division module divides the entire production line operation process into the following intervals:

[0024] The first section: the process of the first robot arm grabbing and placing the material;

[0025] The second section: the process of conveyor belt transporting materials to the assembly area;

[0026] The third section: The second robotic arm grabs the material and assembles it;

[0027] The fourth area: The third robotic arm transports the assembled products to the finished product area.

[0028] In one embodiment, the camera monitoring module includes multiple cameras, and each camera corresponds to the four interval settings.

[0029] Preferably, the feedback display module transmits the scoring results to both the teacher and the students.

[0030] In an optional embodiment, the feedback display module includes any one or more of the following:

[0031] Real-time lighting feedback: During production line operation, different colors of LED lights are lit according to the scoring results;

[0032] Video playback: Display the operation video of each interval on the teaching terminal, marking the specific location of time deviation, action deviation and effect deviation;

[0033] Rating Report: Generates a detailed table including interval scores and overall scores.

[0034] The advantages of the present invention over the prior art are:

[0035] 1. The present invention introduces an operation analysis module and a scoring module to quantify the time deviation, action deviation and effect deviation of students during the operation process into specific data indicators. Compared with the traditional teaching method that relies on the subjective judgment of teachers, this system can help students quickly identify the problems they have in each operation interval. For example, through interval scoring and overall scoring, students can clearly understand which links they are weak in, so as to improve their operating skills in a targeted manner. This refined teaching model can significantly improve students' understanding and mastery of production line debugging.

[0036] 2. Through real-time monitoring and accurate scoring feedback, teachers can quickly grasp each student's performance and shortcomings. This real-time and intuitive nature not only helps teachers quickly correct students' problems, but also effectively reduces teachers' repetitive explanations in class and improves teaching efficiency. At the same time, the objectivity of the scoring results reduces the subjective bias of teachers' scoring and provides a more fair and transparent basis for teaching evaluation.

[0037] 3. The system scores based on the standard operation model, and uses data-driven methods to scientifically and objectively evaluate students' operations. This evaluation method can avoid the interference of human factors in the scoring results and ensure the fairness and credibility of students' scores. In addition, by introducing a scoring mechanism with segmented intervals, it can not only evaluate students as a whole, but also conduct in-depth analysis of each link, providing students with more targeted improvement suggestions.

[0038] 4. The scoring system design of the present invention is highly modular and can be flexibly adjusted according to different teaching needs and teaching contents. For example, the camera monitoring module can adapt to more complex assembly line scenarios by increasing the number of cameras; the operation analysis module and the scoring module can adapt to different types of teaching tasks by adjusting the standard operation model or introducing new evaluation indicators. At the same time, the feedback display module supports multiple output modes, such as video playback, chart analysis and light prompts, which is convenient for flexible application in different teaching scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system of the present invention;

[0040] Figure 2 It is a schematic diagram of a desktop intelligent manufacturing production line under an embodiment of the present invention system;

[0041] Figure 3 It is a schematic diagram of the classification of system deviations of the present invention;

[0042] Figure 4 It is a classification diagram of the system feedback display model of the present invention;

[0043] Figure 5 It is a schematic diagram of the division of the operation process of the system of the present invention;

[0044] Figure 6 It is a schematic diagram of the deviation corresponding to the annotation of the system of the present invention.

[0045] 1. Loading area, 2. First robotic arm, 3. Conveyor belt, 4. Second robotic arm, 5. Assembly area, 6. Third robotic arm, 7. Finished product area, 8. Materials for assembly. DETAILED DESCRIPTION

[0046] The specific implementation of the present invention will be described below in conjunction with the accompanying drawings.

[0047] like Figure 1 As shown, the present invention is a desktop intelligent manufacturing production line, and a corresponding scoring system, wherein the scoring system includes a camera monitoring module, an operation process division module, an operation analysis module, a scoring module, and a feedback display module, wherein:

[0048] The camera monitoring module is used to collect real-time video data of the production line operation process operated by students and transmit it to the operation process division module;

[0049] The operation process division module is used to divide the production line operation process corresponding to the video data into multiple intervals, each interval corresponding to an operation stage of the production line;

[0050] The operation analysis module is used to compare the students' operations in each interval with the preset standard operation model and generate quantitative results of the deviation;

[0051] The scoring module is used to calculate the interval score according to the deviation of each interval and generate an overall score based on the scores of each interval;

[0052] The feedback display module is used to output the scoring results in a visual way.

[0053] In some embodiments, the operation analysis module further corresponds the deviation to the operation parameters or program codes input by the student. And the scoring module also marks the operation parameters or program codes input by the student related to the deviation. Figure 6 shown.

[0054] In some embodiments, the deviation includes any one or more of the following: time deviation, action deviation, and effect deviation. Figure 3 shown.

[0055] In some embodiments, the visualization method includes any one or more of the following: video playback, interval score chart, light prompt and code highlighting. Figure 4 shown.

[0056] The present invention considers a specific desktop intelligent manufacturing production line as an embodiment, such as Figure 2 As shown, including:

[0057] Loading area 1;

[0058] A first robotic arm 2 for grabbing materials from the loading area 1;

[0059] A conveyor belt 3 for transporting materials from the loading area 1 to the assembly area 5;

[0060] A second robotic arm 4 for assembling materials;

[0061] The third robot arm 6 is used to transport the assembled materials to the finished product area 7.

[0062] The production line includes the following work processes:

[0063] The first robotic arm 2 grabs the material and places it on the conveyor belt 3;

[0064] The conveyor belt 3 transports the materials to the assembly area 5;

[0065] The second robot arm 4 completes the assembly. The specific process may be: the second robot arm 4 places the material on the conveyor belt 3 to the assembly area 5, and grabs the assembly material 8 and assembles it with the material from the conveyor belt 3. The assembly method may be specifically set according to the specific situation, such as direct bonding or clamping, etc.

[0066] The third robot arm 6 transports the assembled product to the finished product area 7, wherein the bottom of the third robot arm 6 can be connected to a screw rod or the like so as to be movable.

[0067] The teaching goal is to guide students to complete the optimal operation of the production line and evaluate their performance through a scoring system.

[0068] Therefore, the scoring system can be set up like this:

[0069] 1) For the camera monitoring module, only one single camera can be set up to monitor the entire process, but for greater accuracy, a high-definition camera can also be installed at each key operation node (such as the first robotic arm 2 grasping position, assembly area 5, and finished product area 7) to monitor the operation of the production line in real time. Its function is to collect video data, such as dynamic images of the robotic arm's grasping, moving, releasing, and assembling operations. In addition, cameras can also be set up according to the partition situation. For example, in the following four partitions, a camera is set up in each partition for separate supervision. Of course, a close-up camera can also be set up separately in each partition to capture more detailed video data.

[0070] 2) The operation process is divided into modules, and the partitioning basis is, for example, Figure 5As shown, the entire production line operation process is divided into the following intervals:

[0071] The first section: the process of the first robot arm 2 grabbing and placing the material.

[0072] Second section: The process of conveyor belt 3 transporting materials to assembly area 5.

[0073] The third section: the process in which the second robot arm 4 grabs the material and assembles it.

[0074] Fourth section: the process in which the third robot arm 6 transports the assembled products to the finished product area 7.

[0075] The division method is to use camera data combined with timestamps to perform behavior recognition and mark the start and end points of each interval.

[0076] 3) Run the analysis module, which can include the following three deviations, such as Figure 3 As shown:

[0077] Time deviation: Compare the time set in the standard operation model with the actual time of the student's operation. For example, the standard time for the first robot 2 to grab the material is 5 seconds, and the student actually took 7 seconds, and the time deviation is +2 seconds.

[0078] Motion deviation: Analyze the robot’s grasping accuracy (such as the distance from the target position) or trajectory optimization (such as whether there are unnecessary turns in the path).

[0079] Effect deviation: whether the assembly meets standard specifications (such as whether the parts are aligned and whether the buckles are fully inserted).

[0080] 4) Scoring module, the interval scoring is as follows:

[0081] First interval scoring: time deviation, grasping accuracy, and accuracy of material placement.

[0082] Second interval scoring: stability of the transport mechanism (such as whether the material is offset or dropped).

[0083] Scoring in the third interval: material alignment, robot arm movement path and total time during assembly.

[0084] Scoring for the fourth interval: Accuracy of unloading position and efficiency of movement.

[0085] Overall score: The scores of each interval are weighted and summarized into a comprehensive score.

[0086] 5) Feedback display module, which can use visual output, such as Figure 4 As shown, for example:

[0087] Real-time light feedback: During the operation of the robot arm, different colors of LED lights are lit according to the scoring results (green: correct; yellow: small deviation; red: large deviation).

[0088] Video playback: Display the operation video of each interval on the teaching terminal, marking the specific locations of time deviation, action deviation and effect deviation.

[0089] Scoring report: Generates a detailed table including interval scores, overall scores, and improvement suggestions (such as "In the third interval, the grasping angle deviation is 5°, it is recommended to adjust the path planning").

[0090] For example, during specific operations, students write programs through the control terminal to command the robotic arms and transport mechanisms to complete the operations. If the grasping action of the first robotic arm 2 deviates from the standard position by 3 cm, the system records the deviation and marks it in the score sheet. If the buckle is not fully inserted due to inaccurate movements during the assembly process of the second robotic arm 4, the system points out the specific problem through video playback and recommends adjusting the grasping position and strength. If the material is offset during the operation of the transport mechanism, the system proposes suggestions for improving the path planning by analyzing the trajectory.

[0091] The above-mentioned scoring system is technically feasible.

[0092] From the perspective of hardware implementation, the construction of this system is completely based on existing mature technologies. The camera monitoring module can choose high-definition industrial cameras, such as the Basler ace series or the FLIR Blackfly series. These cameras have high frame rates (usually greater than 60fps) and high resolutions (reaching 1920×1080 or higher), which are sufficient to accurately capture the real-time dynamics of the production line operation. Equipped with standard GigE or USB3.0 interfaces, these cameras can be seamlessly connected to the control terminal. To ensure that light conditions do not affect data collection, the system can also be equipped with an LED ring light to provide uniform fill light, and a mechanical pan / tilt can be used to adjust the shooting angle to cover all key areas of the production line. For the control terminal, embedded devices (such as Raspberry Pi 4 or NVIDIA Jetson Nano) can be used for preliminary data processing, while complex calculations are completed by the central server. The server can choose a high-performance workstation, such as a device equipped with an Intel i7 processor or NVIDIA RTX GPU, to ensure that the system can run efficiently.

[0093] In terms of algorithm implementation, the core of the scoring system is to combine computer vision technology and production line operation logic to achieve real-time monitoring, zoning and scoring calculation. The real-time video data collected by the camera first uses the target detection algorithm (such as YOLOv8) to identify the position and status of the robot arm, materials and other key objects, and then uses the optical flow method or multi-target tracking algorithm (such as DeepSORT) to track the trajectory of the object. The system automatically segments the production line operation process by analyzing the timestamp, dividing it into multiple operation intervals, each of which corresponds to a key operation link of the production line, such as "robot grabs materials", "materials are transported to assembly area 5", etc. The operation analysis module then compares the student's operation parameters in each interval with the preset standard operation model to calculate the time deviation, action deviation and effect deviation. The time deviation can accurately calculate the start and end frames through the video frame rate to obtain the difference between the actual operation time and the standard time; the action deviation analyzes the path deviation of the robot arm through the inverse kinematics algorithm; and the effect deviation can use template matching technology (such as ORB or SIFT algorithm) to determine whether the product is assembled correctly.

[0094] The scoring module calculates the interval score based on the above deviations and generates an overall score through a weighted formula. The calculation weight of each interval score can be flexibly set according to the teaching objectives, such as 30% for time deviation, 40% for action deviation, and 30% for effect deviation. The scoring results are presented in a variety of visual forms, including interval score bar charts, real-time video playback, and color-prompted RGB LED lights to help students quickly understand their operating performance. In addition, the operation analysis module can further associate the deviation information with the specific operating parameters or program codes entered by the students to locate the source of the problem. The scoring module can simultaneously annotate these operating parameters to facilitate diagnosis and improvement by teachers and students.

[0095] It can be seen that the scoring system of the present invention can effectively combine modules such as camera monitoring, operation analysis, and scoring feedback, and can perform multi-dimensional analysis and scoring on the entire process of student operations. It can also help students quickly discover and improve problems through visual feedback, thereby improving teaching efficiency and learning outcomes.

[0096] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A desktop intelligent manufacturing production line for teaching and its scoring system, characterized in that: It includes a desktop intelligent manufacturing production line and a corresponding scoring system, wherein the scoring system includes a camera monitoring module, an operation process division module, an operation analysis module, a scoring module, and a feedback display module, wherein: The camera monitoring module is used to collect real-time video data of the production line operation process operated by students and transmit it to the operation process division module; The operation process division module is used to divide the production line operation process corresponding to the video data into multiple intervals, each interval corresponding to an operation stage of the production line; The operation analysis module is used to compare the student's operation in each interval with the preset standard operation model to generate a quantitative result of the deviation; The scoring module is used to calculate the interval score according to the deviation of each interval, and generate an overall score based on the scores of each interval; The feedback display module is used to output the scoring results in a visual manner.

2. According to claim 1, the teaching desktop intelligent manufacturing production line and its scoring system are characterized in that: The operation analysis module further corresponds the deviation to the operation parameters or program codes input by the student.

3. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 2, characterized in that: The scoring module also marks the operation parameters or program codes input by the students that are related to the deviations.

4. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 1, characterized in that: The deviation includes any one or more of the following: time deviation, action deviation and effect deviation.

5. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 1, characterized in that: The visualization method includes any one or more of the following: video playback, interval scoring chart, light prompt and code highlighting.

6. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to any one of claims 1 to 5, characterized in that: The desktop intelligent manufacturing production line includes: Loading area (1); A first mechanical arm (2) for grabbing materials from the loading area (1); A conveyor belt (3) for transporting materials from the loading area (1) to the assembly area (5); A second robotic arm (4) for assembling materials; A third robotic arm (6) is used to transport the assembled materials to a finished product area (7).

7. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 6, characterized in that: The operation process division module divides the entire production line operation process into the following intervals: First section: the process of the first robot arm (2) grabbing and placing the material; Second section: the process of the conveyor belt (3) transporting materials to the assembly area (5); The third section: the process in which the second robot arm (4) grabs the material and assembles it; Fourth section: The process in which the third robot arm (6) transports the assembled products to the finished product area (7).

8. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 7, characterized in that: The camera monitoring module includes a plurality of cameras, and each camera is respectively set corresponding to the four intervals.

9. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 6, characterized in that: The feedback display module transmits the scoring results to the teacher and the students at the same time.

10. The desktop intelligent manufacturing production line for teaching and the scoring system thereof according to claim 6, characterized in that: The feedback display module includes any one or more of the following: Real-time lighting feedback: During production line operation, different colors of LED lights are lit according to the scoring results; Video playback: Display the operation video of each interval on the teaching terminal, marking the specific location of time deviation, action deviation and effect deviation; Rating Report: Generates a detailed table including interval scores and overall scores.

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