A self-learning radio assembly system and its assembly method

Abstract

The present invention discloses a self-learning radio assembly system and its assembly method, belonging to the technical field of automatic assembly. Based on the type of work, a number of independent basic units are generated to obtain a set of basic units; wherein, each basic unit is provided with a corresponding execution instruction and configured with a corresponding slave unit, which receives the current task instruction and divides the task instruction into a number of independent subtask instructions based on the type of work; the subtask instructions are matched with the execution instructions, and the basic units adapted to them are retrieved from the set of basic units to obtain a set of occupied units, and the set of basic units is updated to a set of idle units, and the basic units in the set of occupied units are sorted according to the assembly requirements to generate an assembly line for the current task instruction, and the slave units are triggered in sequence to complete the corresponding instructions. The present invention can realize independent training of the basic units and also generate an assembly line based on the assembly task.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic assembly, and particularly relates to a self-learning radio assembly system and an assembly method thereof. Background Art

[0002] With the rapid development of the intelligence in the electronics industry, intelligent production lines for electronic assembly gradually replace manual assembly. When students study relevant professional knowledge, they find that there are very few intelligent production lines for electronic assembly. Taking the teaching radio as an example, students can only practice in enterprises. And during the internship in enterprises, each student cannot complete the assembly of a complete production line or a phased production line according to their own learning situation, but can only operate and learn in the assigned operation units. Most of the time, simple workpieces are selected for simulated assembly during teaching, and the entire production process does not reflect the complete production process. The assembled products are not complete products either, and students cannot feel the actual production process, and the complexity of real equipment cannot be fully reflected. Summary of the Invention

[0003] Object of the Invention: To provide a self-learning radio assembly system and an assembly method thereof, which solve the above problems existing in the prior art.

[0004] Technical Solution: A self-learning radio assembly method includes the following steps: generating a number of independent basic units based on the type of work, to obtain a set of basic units; wherein, each basic unit is provided with a corresponding execution instruction and configured with a corresponding slave unit;

[0005] Receiving a current task instruction, splitting the task instruction into a number of independent sub-task instructions based on the type of work; matching the sub-task instructions with the execution instructions, and calling out the adapted basic units from the set of basic units to obtain an occupied unit set, and updating the set of basic units to an idle unit set;

[0006] Sorting the basic units in the occupied unit set according to the assembly requirements, generating an assembly line for the current task instruction, and sequentially triggering the slave units to complete the corresponding instructions;

[0007] Creating a fuzzy comprehensive evaluation model, when each sub-task instruction is executed, using the fuzzy comprehensive evaluation to evaluate the proficiency of the operator and obtaining an evaluation result, and judging whether to start a learning mode for the corresponding sub-task instruction based on the evaluation result.

[0008] Preferably, it further includes the following steps:

[0009] If the idle unit set is an empty set, then suspend receiving the next task instruction.

[0010] Preferably, it further includes the following steps:

[0011] When the basic unit in the occupied unit set completes the corresponding subtask instruction, the corresponding basic unit is removed from the occupied unit set and updated to the idle unit set;

[0012] Create the next execution criterion, and based on the execution criterion, judge the next task instruction and the idle unit set. If the next execution criterion is met, receive the next task instruction, sort the basic units in the idle unit set according to the next task instruction to generate an assembly pipeline for the next task instruction, and sequentially trigger the slave units to complete the instruction; otherwise, pause receiving the next task instruction until the next execution criterion is met.

[0013] Preferably, the creation process of the execution criterion is as follows:

[0014] Based on the type of work, divide the next task instruction into multiple independent subtask instructions;

[0015] Match the multiple subtask instructions with the execution instructions in the idle unit set. If the multiple subtask instructions are included in the execution instructions in the idle unit set, it is judged that the criterion is met; otherwise, it is not met.

[0016] Preferably, the creation process of the fuzzy comprehensive evaluation model is as follows:

[0017] Define the standard proficiency standard weight value representation range as Wherein, In the formula, α mj represents the standard weight value of the jth action under the mth behavior;

[0018] Obtain the parameter set N of the mth behavior when the operator actually operates j , N j ={n j1 ,…, n jm}, n jm represents the parameter value of the mth action when performing the mth behavior,

[0019] Calculate the average parameter value

[0020] If it indicates that the proficiency in performing the current subtask is qualified; otherwise, it indicates unskilled, and start the learning mode.

[0021] Preferably, when the slave unit completes the corresponding instruction, it also includes the following work process:

[0022] Obtain the instruction information of each subtask instruction in the assembly pipeline for the current task instruction to generate an original database;

[0023] Obtain the instruction information of each sub - task instruction in the assembly pipeline that actually executes the sub - task instruction;

[0024] Create an alarm model regarding the running time based on the original database and the instruction information of the actual basic unit execution.

[0025] Preferably, the instruction information of each sub - task instruction at least includes: motion state, process parameters, and process running time.

[0026] Preferably, the generation process of the alarm model is as follows: Simultaneously collect the time required for each step of the instruction execution of each basic unit to establish a time database. During the execution of the instruction by the basic unit, compare the usage time of each step with the time in the original database to determine the fault location in the current basic unit.

[0027] Preferably, the information included in the original database at least includes: motion state, process parameters, and process running time.

[0028] Preferably, the theoretical instruction information at least includes: the running state, running time, processing process parameters, and alarm information of the corresponding basic unit.

[0029] A self - learning radio assembly system, including a first unit, which is set to generate a number of independent basic units based on the type of work, obtaining a set of basic units; wherein, each basic unit is provided with a corresponding execution instruction and configured with a corresponding slave unit;

[0030] A second unit, which is set to receive the current task instruction, split the task instruction into a number of independent sub - task instructions based on the type of work; match the sub - task instructions with the execution instructions, retrieve the adapted basic units from the set of basic units to obtain a set of occupied units, and update the set of basic units to an idle unit set; wherein the basic unit at least includes:

[0031] A feeding unit, used for conveying PCB boards;

[0032] An assembly unit, used for grasping electronic components and inserting them into the PCB board in a predetermined order;

[0033] A dispensing unit, used for fixing the electronic components on the PCB board;

[0034] A soldering unit, used for soldering and fixing the electronic components on the PCB board;

[0035] A handling unit, used for handling the PCB board with electronic components installed;

[0036] A corner-cutting unit for detecting the welding points of electronic components on a PCB board; using the slave units in each basic unit to control each unit to complete the installation operation of the components on the PCB board;

[0037] A number of conveying units are arranged on each basic unit; the conveying unit is used to convey the PCB board;

[0038] The assembly line includes at least one set of units among a feeding unit, a dispensing unit, a welding unit, a handling unit, a corner-cutting unit and a number of conveying units;

[0039] When it is necessary to train a single basic unit, each basic unit is independent, and repeated training is carried out for each basic unit.

[0040] Beneficial effects: The present invention relates to a self-learning radio assembly system and its assembly method. During the teaching process, students can fully and proficiently master the training basic units, and repeated training is carried out separately for each basic unit; on the basis of students' proficient mastery of the basic units, according to the assembly requirements, task instructions can be received, and based on the task instructions, they are matched with the basic units. The basic units are divided into an occupied unit set and an idle unit set. The occupied unit set is used to complete the task instructions. After the basic unit in the occupied unit set completes the instruction, the basic unit is removed from the occupied unit set and updated to the idle unit set. At the same time, the next task instruction is received, and the next task instruction is matched with the idle unit set. When the idle unit set meets the next task instruction, an assembly line is generated to execute the task instruction. Description of the Drawings

[0041] Figure 1 It is a schematic structural diagram when the present invention is spliced;

[0042] Figure 2 It is a schematic diagram of the feeding unit of the present invention;

[0043] Figure 3 It is a schematic diagram of the dispensing unit of the present invention;

[0044] Figure 4 It is a schematic diagram of the welding unit of the present invention;

[0045] Figure 5 It is a schematic diagram of the handling unit of the present invention;

[0046] Figure 6 It is a schematic diagram of the corner-cutting unit of the present invention.

[0047] Figures 1 to 6The reference numerals in the figures are: master control unit 1, feeding unit 2, assembly unit 3, dispensing unit 4, welding unit 5, handling unit 6, corner cutting unit 7, conveying unit 8, training bench 21, retaining frame 22, stepper screw motor 23, feeding suction cup 24, assembly table 31, assembly bin 32, first robotic arm 33, dispensing table 41, second robotic arm 42, welding table 51, welding robotic arm 53, placement table 61, handling robotic arm 62, shearing table 71, shearing robotic arm 72, vision inspection component 73. Detailed implementation mode

[0048] In actual applications, the applicant found that: when students learn relevant professional knowledge, they found that there are very few intelligent production lines for electronic assembly, and they can only go to enterprises for internships. Moreover, during the internship in enterprises, each student cannot complete the assembly of a complete production line and can only operate and learn in the assigned operation units. Most production enterprises use simple workpieces for simulated assembly when designing intelligent production lines. The entire production process does not reflect the complete production process, and the assembled products are not complete products, which can only be used for teaching demonstrations and cannot fully reflect the complexity of real equipment. The real electronic assembly production line in the industrial field is relatively expensive, occupies a large area, the system is not open, and the assembled products are relatively fixed and single, which is not suitable for teaching. To address these problems, a self-study method and device for assembling radio sets have been invented, which can effectively solve the above problems.

[0049] As Figures 1 to 6 shown, a self-study method for assembling radio sets includes the following steps:

[0050] Generate a number of independent basic units based on the type of work to obtain a basic unit set; among them, each basic unit is provided with a corresponding execution instruction and is configured with a corresponding slave unit.

[0051] Receive the current task instruction, split the task instruction into multiple independent subtask instructions based on the type of work; match the subtask instructions with the execution instructions, and call out the adapted basic units from the basic unit set to obtain an occupied unit set, and update the basic unit set to an idle unit set.

[0052] Sort the basic units in the occupied unit set according to the assembly requirements to generate an assembly pipeline for the current task instruction, and trigger the slave units in sequence to complete the corresponding instructions. At the same time, create a fuzzy comprehensive evaluation model. During the process of the pipeline executing the task instruction, use the fuzzy comprehensive evaluation to evaluate the proficiency of the operator and obtain an evaluation result. Based on the evaluation result, judge whether it is necessary to start the learning mode for the corresponding subtask instruction, that is, based on the completion time of the current basic unit as the evaluation result. If the completion time of the current basic unit is longer than the preset completion time, that is, the fuzzy comprehensive evaluation of the current basic unit does not meet the requirements, start the learning mode, and perform repeated practice on the current basic unit until the result of the fuzzy comprehensive evaluation of this basic unit reaches the predetermined value, and then execute the unexecuted part of the task instruction until the current task instruction is completed.

[0053] In a further embodiment, the creation process of the fuzzy comprehensive evaluation model is as follows:

[0054] Define the standard proficiency standard weight value representation range as Among them, In the formula, α mj represents the standard weight value of the jth action under the mth behavior;

[0055] Obtain the parameter set N of the operator's actual operation for the mth behavior j , N j ={n j1 , …, n jm}, n jm represents the parameter value of the mth action when performing the mth behavior,

[0056] Calculate the average parameter value

[0057] If Then it means that the proficiency in performing the current subtask is qualified; otherwise, it means unskilled, start the learning mode, that is, perform repeated practice on the current basic unit until the proficiency of the current basic unit reaches the average operation time range, and then continue to complete the unfinished task.

[0058] When the idle unit set is an empty set, then pause receiving the next task instruction.

[0059] The basic unit at least includes a feeding unit 2, an assembling unit 3, a dispensing unit 4, a soldering unit 5, a handling unit 6, a trimming unit 7, and a plurality of conveying units 8; the conveying units 8 are respectively installed on each basic unit; the conveying units 8 are used to convey the PCB boards after the operations of each basic unit are completed, wherein the feeding unit 2 is used to supply the initial PCB board raw materials, the assembling unit 3 is used to grab electronic components and insert them into the PCB board in a predetermined order, the dispensing unit 4 is used to fix the electronic components on the PCB board, the soldering unit 5 solders and fixes the electronic components on the PCB board, the handling unit 6 realizes the handling of the PCB boards with electronic components installed, and the trimming unit 7 detects the soldering points of the electronic components on the PCB board and trims the pins of the electronic components; the slave units in each basic unit are used to control each unit to complete the installation operation of the components on the PCB board.

[0060] When the basic units required for matching multiple subtask instructions needed to complete the current task instruction include a feeding unit 2, an assembling unit 3, and a dispensing unit 4, the feeding unit 2, the assembling unit 3, and the dispensing unit 4 form an occupied unit set, while the welding unit 5, the handling unit 6, the corner cutting unit 7, and several conveying units 8 form an idle unit set. Sort the basic units in the occupied unit set according to the assembly requirements to generate an assembly line for the current task instruction, and sequentially trigger the slave units to complete the corresponding instructions; at the same time, create a fuzzy comprehensive evaluation model. When each subtask instruction is executed, use the fuzzy comprehensive evaluation to evaluate the proficiency of the operator and obtain an evaluation result. Based on the evaluation result, determine whether to start the learning mode for the corresponding subtask instruction. When the subtask instruction matches the execution instruction, retrieve the appropriate basic unit from the basic unit set to obtain the occupied unit set. When the basic units in the occupied unit set complete the corresponding subtask instructions, the corresponding basic units are removed from the occupied unit set and updated to the idle unit set; that is, the order of the current assembly line is the feeding unit 2, the assembling unit 3, and the dispensing unit 4. When the feeding unit 2 completes feeding, the feeding unit 2 is removed from the occupied unit set and updated to the idle unit set, and an execution standard between the next task instruction and the execution instruction in the idle unit set is created. When the idle unit set meets the execution standard, it receives the next task instruction, sorts the basic units according to the task instruction to generate an assembly line, and sequentially triggers the slave units to complete the instructions; when the basic units in the idle unit set do not meet the execution standard, it pauses receiving the next task instruction until the basic units in the idle unit set meet the execution standard to receive the next task instruction. And when the idle unit set is an empty set, it means that there are no idle basic units in the idle unit set. When the idle unit set is an empty set, it pauses receiving the next task instruction. When the feeding unit 2 feeds, at the same time, the fuzzy comprehensive evaluation model evaluates the feeding unit 2. According to the time required for each feeding action of the feeding unit 2, use a timing sensor to time the time required for each action, and at the same time compare it with the average time required for the corresponding action of the fuzzy comprehensive evaluation. If the time consumed by the first feeding action of the feeding unit exceeds the average time required for the corresponding action of the fuzzy comprehensive evaluation, start the learning mode, pause the assembly line of the current task instruction, and repeatedly train the feeding unit until the time required for each operation of the feeding unit reaches within the average parameter range of the fuzzy comprehensive evaluation, then pause the learning mode, continue to complete the assembly line of the current task instruction, and repeatedly use the fuzzy comprehensive evaluation model to evaluate each operation until the current task instruction is completed.

[0061] In a further embodiment, the creation process of the execution standard is as follows:

[0062] Split the task instruction into multiple independent subtask instructions based on the type of work.

[0063] Match the multiple subtask instructions with the execution instructions in the idle unit set. If the multiple subtask instructions are included in the execution instruction set of the idle unit set, it is determined to meet the standard; otherwise, it does not meet the standard.

[0064] In a further embodiment, the slave unit at least includes the following work processes:

[0065] Obtain the instruction information of each subtask instruction in the assembly line of the current task instruction to generate an original database; the information included in the original database at least includes: motion state, process parameters, and process running time; obtain the instruction information of each subtask instruction in the assembly line that actually executes the subtask instruction; the instruction information of each subtask instruction at least includes: motion state, process parameters, and process running time; create an alarm model for the running time based on the original database and the actual basic unit execution instruction information; the generation process of the alarm model is: collect the time required for each step of the execution instruction of each basic unit to establish a time database, and during the execution of the instruction by the basic unit, compare the usage time of each step with the time in the original database to determine the fault location in the current basic unit.

[0066] A self-learning radio assembly system includes at least one master control unit and several basic units, and each basic unit includes a slave unit; the slave unit adopts a small PLC control system, and the model of the small PLC is AS330T-A, and the master control unit 1 adopts a large PLC control system, and the model of the large PLC is AHCPU530-EN; use the master control unit 1 to communicate with each slave unit to realize data intercommunication between each slave unit.

[0067] When comprehensive training is required, split the task instruction into multiple subtask instructions based on the type of work, match the subtask instructions with the specified instructions, divide several basic units into an occupied unit set and an idle unit set, and complete the task instruction by using the occupied unit set according to the assembly requirements of the type of work. After the basic unit in the occupied unit set completes the instruction, the basic unit is removed from the occupied unit set and updated to the idle unit set. At the same time, receive the next task instruction and match the next task instruction with the idle unit set. When the idle unit set meets the next task instruction, generate an assembly line to execute the task instruction; when the student has not yet mastered the operation of each basic unit proficiently and needs to train a single basic unit, each basic unit is independent, and each basic unit is repeatedly trained until the student proficiently masters the operation of each basic unit.

[0068] Due to different types of PCB boards, the thicknesses of each PCB board are different. However, since the volume of the PCB board itself is relatively small, even for different types of PCB boards, the thickness difference is not significant. During the process of feeding the PCB board, due to its own characteristics, it is prone to inaccurate stepper control and unable to accurately feed the material. In a further embodiment, the feeding unit 2 includes a training bench 21, a retaining frame 22, a stepper screw motor 23, and a feeding suction cup 24. The training bench 21 is built with industrial-grade aluminum profiles, with veneer panels inlaid on the sides and back, and a door in the front. The door panel is made of transparent material, and the internal electrical circuits are visible, facilitating the observation of the internal situation of the training bench 21. The retaining frame 22 is installed on the training bench 21, and the retaining frame 22 is used to position the PCB board. The stepper screw motor 23 is installed on the training bench 21, and the stepper screw motor 23 is used to convey the PCB board. The feeding suction cup 24 is installed on the training bench 21, and the feeding suction cup 24 is located above the retaining frame 22. The feeding suction cup 24 is used to convey the PCB board in the retaining frame 22. The movement of the PCB board is precisely controlled by the screw motor, and at the same time, the moving distance of the screw motor is adjusted according to the PCB boards of different thicknesses to move the PCB boards of different thicknesses.

[0069] In a further embodiment, since each basic unit can be individually and repeatedly trained for each basic unit when the student has not yet mastered the operations of each basic unit, or based on the assembly task, the basic units required to complete the current task instructions can be selected from the execution instruction database, and the selected basic units are spliced with the master control unit 1 to complete the assembly task. However, since each basic unit is relatively bulky, when splicing or independently training, the basic unit needs to be moved. In a further embodiment, moving casters are provided at the lower end of each basic unit. When the basic unit needs to be moved, the moving casters are adjusted, and the corresponding basic unit can be quickly moved, improving the splicing or moving rate of each basic unit.

[0070] In a further embodiment, the assembly unit 3 includes an assembly table 31, an assembly bin 32 provided on the assembly table 31, and a first robotic arm 33 provided on the assembly table 31. The assembly bin 32 is used to store PCB boards. The first robotic arm 33 is an industrial four-axis SCARA robot with an arm span of 400 mm, a load of 3 Kg, and a repeat positioning accuracy of ±0.01 mm. The first robotic arm 33 is used to pick up electronic components and insert the electronic components into the PCB boards.

[0071] In a further embodiment, the dispensing unit 4 includes a dispensing table 41 and a second robotic arm 42 disposed on the dispensing table 41; the second robotic arm 42 is used for dispensing on the electronic components inserted on the PCB board, and the slave unit is used to control the glue output amount, time interval and glue output pressure of the second robotic arm 42, wherein the range of the glue output amount is: 0.01 ml - 1 ml, the time interval is between 0.1 s and 9.9 s, and the glue output pressure is between 0.05 mp and 0.99 mp.

[0072] In a further embodiment, the soldering unit 5 includes a soldering table 51 and a soldering robotic arm 53 disposed on the soldering table 51; wherein the soldering robotic arm 53 is an industrial 6-axis serial robot with an arm span of 710 mm, a load of 7 Kg, and a repeat positioning accuracy of ±0.02 mm; the soldering robotic arm 53 is used for soldering and fixing the electronic components on the PCB board; the soldering robotic arm 53 is controlled by the slave unit, and the electronic components are soldered on the PCB board by scheduling parameters such as temperature, time, and movement trajectory.

[0073] In a further embodiment, the handling unit 6 includes a placement table 61 and a handling robotic arm 62 disposed on the placement table 61; the handling robotic arm 62 is used for flipping the PCB board; the handling robotic arm 62 is controlled by the slave unit in the handling unit 6.

[0074] In a further embodiment, the corner cutting unit 7 includes a cutting table 71, a scissor robotic arm 72 disposed on the cutting table 71, and a vision detection component 73 disposed on the cutting table 71; the slave unit is used to control the prime vision detection component 73 to detect the soldering points of the electronic components on the PCB board, and the vision detection component 73 is used to detect whether the soldering of the electronic components on the PCB board is correct and whether there is any phenomenon of missed soldering. After the detection is completed, the scissor robotic arm 72 is used to cut the redundant length of the pins on the PCB board according to a preset path.

[0075] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all belong to the protection scope of the present invention.

Claims

1. A self - learning radio assembly method, characterized in that, it includes the following steps: Generate a number of independent basic units based on the type of work, and obtain a set of basic units; among them, each basic unit is set with a corresponding execution instruction and configured with a corresponding slave unit; Receive the current task instruction, divide the task instruction into multiple independent sub - task instructions based on the type of work; match the sub - task instructions with the execution instructions, retrieve the appropriate basic units from the set of basic units to obtain an occupied unit set, and update the set of basic units to an idle unit set; Sort the basic units in the occupied unit set according to the assembly requirements, generate an assembly pipeline for the current task instruction, and sequentially trigger the slave units to complete the corresponding instructions; Create a fuzzy comprehensive evaluation model. When each sub - task instruction is executed, use the fuzzy comprehensive evaluation model to evaluate the proficiency of the operator and obtain an evaluation result. Based on the evaluation result, determine whether to start the learning mode for the corresponding sub - task instruction; The creation process of the fuzzy comprehensive evaluation model is as follows: Define the standard proficiency standard weight value, and the representation range is , where 1j mj , 1j mj ; In the formula, mj represents the standard weight value of the j-th action under the m-th behavior; Obtain the parameter set N j of the operator's actual operation regarding the m-th behavior, N j = {n j1 , n jm}, n jm represents the parameter value of the j-th action when performing the m-th behavior, calculate the average parameter value . If , it means that the proficiency in performing the current subtask is qualified; otherwise, it means unskilled, and start the learning mode; When the basic units in the occupied unit set complete the corresponding sub - task instructions, the corresponding basic units are removed from the occupied unit set and updated to the idle unit set; Create the next execution standard, based on the execution standard, judge the matching degree between the basic units required by the next task instruction and the basic units in the idle unit set. If the next execution standard is met, receive the next task instruction, sort the basic units in the idle unit set according to the next task instruction to generate an assembly pipeline for the next task instruction, and sequentially trigger the slave units to complete the instructions; otherwise, pause receiving the next task instruction until the next execution standard is met; The creation process of the execution standard is as follows: Divide the next task instruction into multiple independent sub - task instructions based on the type of work; match the multiple sub - task instructions with the execution instructions in the idle unit set. If the multiple sub - task instructions are included in the execution instructions in the idle unit set, it is judged to meet the standard; otherwise, it does not meet the standard.

2. A self - learning radio assembly method according to claim 1, characterized in that, it further includes the following steps: If the idle unit set is an empty set, pause receiving the next task instruction.

3. A self - learning radio assembly method according to claim 1, characterized in that, The slave unit at least includes the following work processes: Obtain the instruction information of each sub - task instruction in the assembly pipeline for the current task instruction, and generate an original database; Obtain the instruction information of each sub - task instruction in the assembly pipeline for the actually executed sub - task instruction; The instruction information of each sub - task instruction at least includes: motion state, process parameters, and process running time; Create an alarm model for the running time based on the original database and the actual basic unit execution instruction information.

4. A self - learning radio assembly method according to claim 3, characterized in that, The generation process of the alarm model is as follows: collect the time required for each step of each basic unit to execute an instruction simultaneously to establish a time database. During the process of the basic unit executing the instruction, compare the usage time of each step with the time in the original database to determine the fault location in the current basic unit.

5. A self-learning radio assembly method according to claim 3, characterized in that the instruction information of each sub-task instruction at least includes: the operating state, operating time, processing process parameters, and alarm information of the corresponding basic unit.

6. A self-learning radio assembly system, characterized in that this system uses a self-learning radio assembly method described in claim 1, including: The first unit is configured to generate a number of independent basic units based on the type of work to obtain a set of basic units; among them, each basic unit is provided with a corresponding execution instruction and is configured with a corresponding slave unit; The second unit is configured to receive the current task instruction, divide the task instruction into a number of independent sub-task instructions based on the type of work; match the sub-task instructions with the execution instructions, and retrieve the appropriate basic units from the set of basic units to obtain a set of occupied units, and update the set of basic units to an idle unit set; The basic unit at least includes: A feeding unit for conveying the PCB board; An assembly unit for grasping electronic components and inserting them into the PCB board in a predetermined order; A dispensing unit for fixing the electronic components on the PCB board; A soldering unit for soldering and fixing the electronic components on the PCB board; A handling unit for handling the PCB board with electronic components installed; A trimming unit for detecting the soldering points of the electronic components on the PCB board; use the slave unit in each basic unit to control each unit to complete the installation operation of the components on the PCB board; A number of conveying units are arranged on each basic unit; the conveying unit is used to convey the PCB board; The assembly line includes at least one group of units among the feeding unit, dispensing unit, soldering unit, handling unit, trimming unit, and a number of conveying units.

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