Task allocation optimization method and system for industrial robot of production line

Abstract

The invention discloses a task allocation optimization method and system for a production line industrial robot, relates to the technical field of task allocation optimization, and is used for solving the problem that in a multi-processing-end production or logistics system, the speeds of all processing ends are not matched. By acquiring the processing capacity of each processing end and the working state of the to-be-processed area in real time, the system can automatically recognize and adjust the difference between the processing ends, overload or idle of a certain link is avoided, and coordinated operation of all links is ensured. Based on the processing speed of each processing end and the dynamic state of the to-be-processed area, the system can adjust the work distribution among the processing ends in real time to ensure the load balance. By accurately estimating the demand of each to-be-processed area, the system can optimize resource allocation, so that the workload of each processing end is maximized. By acquiring historical data, the system can predict the load conditions of the to-be-processed area and the processing end, estimate whether the cargoes can arrive at the next link on time in advance, and perform adjustment in advance.

Description

Technical Field

[0001] The present invention relates to the technical field of task allocation optimization, and more specifically, to a method and system for optimizing task allocation of industrial robots in a production line. Background Art

[0002] The optimization of task allocation for industrial robots in production lines is one of the key technologies in modern manufacturing, especially in the context of intelligent manufacturing, automated production and Industry 4.0. The optimization of task allocation is directly related to production efficiency, product quality and rational use of resources. Task allocation optimization is not just about allocating tasks to individual robots, but also about how to optimize the allocation scheme based on the capabilities of different robots, the dynamic changes in the production environment and the task requirements.

[0003] The prior art has the following deficiencies:

[0004] In a multi-processing production or logistics system, the speed of each processing end is not matched. Some processing ends may be backlogged while other processing ends are idle, resulting in overall inefficiency and failure to reasonably allocate and balance the processing speed of each processing area, resulting in some parts being processed too fast or too slow. The processing speed of some links suddenly drops, or the arrival time of the next batch of goods is uncertain. Traditional systems do not have good response measures.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for optimizing task allocation of industrial robots in a production line to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for optimizing task allocation of industrial robots in a production line comprises the following steps:

[0009] Step S1, obtaining the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive;

[0010] Step S2, determining the processing speed of the waiting area between each processing end according to the number of items processed per unit time at each processing end, and determining the minimum delivery quantity of each waiting area according to the arrival time of the next batch of goods;

[0011] Step S3, obtaining the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area;

[0012] Step S4, based on the historical remaining number of items in the waiting-to-be-processed area that the current conveyor belt passes through and the current conveyor belt speed, it is estimated whether the processing speed of the subsequent waiting-to-be-processed area is sufficient to match, and the speed is adjusted.

[0013] In a preferred embodiment, step S1 includes the following contents:

[0014] Sensors are installed on each processing end robot to record the start and end time of the task, so as to calculate the number of tasks completed by each robot per unit time, and obtain the processing capacity per unit time of each processing end robot, which is stored in a database.

[0015] Use logistics systems or software to regularly update the number of pieces processed and estimated delivery time, and record the time when the next batch of goods will arrive.

[0016] In a preferred embodiment, step S2 includes the following contents:

[0017] Multiple processing ends are recorded as processing end A, processing end B, processing end C, processing end D..., and there is a waiting area between each processing end, recorded as waiting area 1, waiting area 2, waiting area 3, waiting area 4..., where the left and right sides of processing end A are waiting area 1 and waiting area 2 respectively, and the number of processed items per unit time of processing end A is J1 items, then the number of processed items per unit time of each processing end is: J1, J2, J3, J4...J i ...;

[0018] The processing speed of the waiting area depends on the relationship between the number of processing cases of the previous processing end and the number of processing cases of the current processing end. More processing cases are allocated to the waiting area with a small maximum processing number, where the maximum processing number of the waiting area is the sum of the processing capacity per unit time of the processing ends on the left and right sides of the waiting area, and the maximum processing number per unit time of the waiting area 1 = J1. The processing speed per unit time of each waiting area is determined by the joint allocation of the previous processing end and the next processing end, and the allocation logic of each processing end is determined by the proportional allocation of the maximum processing number of the previous waiting area and the next waiting area;

[0019] In summary, the following formula is used to achieve this: Where: V i The speed of each processing end, J i is the number of processing items per unit time at each processing end, i is the number of each processing end, and it should be noted that when i-1=0, J i-1 = 0 and J i-2 =0, or i-2 =0 when J i-2 = 0, or when i does not exist, J i = 0 and J i+1 =0, or when i+1 does not exist, J i+1 =0;

[0020] The minimum delivery amount is determined based on the arrival time of the next batch of goods and the processing speed of each waiting area. The formula is: Minimum delivery amount of the waiting area = (processing speed of the waiting area × arrival time of the next batch of goods). It should be noted that when the calculated minimum delivery amount of the waiting area is a decimal, it needs to be rounded up, that is, the integer part is added by one.

[0021] In a preferred embodiment, step S3 includes the following contents:

[0022] Install sensors in the processing area to track the number of items remaining on the conveyor belt, record the historical records, and average the historical records to calculate the average historical number. The formula is: Where: T is the statistical period, t is the number of remaining pieces transmitted to the waiting area at each moment;

[0023] The contact sensor is usually installed by contacting the conveyor belt or connecting with the drive shaft of the conveyor belt to measure its rotation frequency and calculate the current conveyor belt speed. The calculation formula is: v = k × f, where: k is a constant related to the length of the conveyor belt, the transmission system and the position of the sensor.

[0024] In a preferred embodiment, step S4 includes the following contents:

[0025] Compare the current number of remaining items with the average number of remaining items in history. If it is less than the average number of remaining items in history, speed up; if it is greater than the average number of remaining items in history, slow down.

[0026] First, the difference between the average number of historical remaining pieces and the current number of remaining pieces is calculated as: Difference = Current number of remaining pieces - Average number of historical remaining pieces

[0027] The difference determines whether the conveyor belt speed needs to be accelerated or decelerated. When the difference is negative, it means that the current speed is slow and needs to be accelerated; when the difference is positive, it means that the current speed is too fast and needs to be decelerated.

[0028] The rules for dynamically adjusting the conveyor belt speed are as follows:

[0029] Acceleration rule: When the difference is less than 0, the processing is accelerated. The acceleration range is set according to historical data. The formula is: new conveyor belt speed = current conveyor belt speed × (1 + acceleration coefficient), where: acceleration coefficient = |difference| / average number of historical remaining pieces;

[0030] Deceleration rule: When the difference is greater than 0, the process is decelerated, and the deceleration amplitude is set according to historical data. The expression formula is: new conveyor belt speed = current conveyor belt speed × (1-deceleration coefficient), where: deceleration coefficient = |difference| / average historical number of pieces.

[0031] A task allocation optimization system for industrial robots in production lines, comprising: an information acquisition module 1, a delivery amount calculation module, an information acquisition module 2 and a matching optimization module:

[0032] Information acquisition module 1: obtains the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive;

[0033] Delivery volume calculation module: determines the processing speed of the waiting area between each processing end according to the number of pieces processed per unit time at each processing end, and determines the minimum delivery volume of each waiting area according to the arrival time of the next batch of goods;

[0034] Information acquisition module 2: obtains the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area;

[0035] Matching optimization module: Estimates whether the processing speed of subsequent processing areas is sufficient to match the historical number of remaining items in the processing area that the current conveyor belt passes through and the current conveyor belt speed.

[0036] The technical effects and advantages of the method and system for optimizing task allocation of industrial robots in production lines provided by the present invention are as follows:

[0037] By obtaining the processing capacity of each processing end and the working status of the waiting area in real time, the system can automatically identify and adjust the differences between the processing ends to avoid overload or idleness in a certain link and ensure the coordinated operation of each link. Based on the processing speed of each processing end and the dynamic status of the waiting area, the system can adjust the work distribution between the processing ends in real time to ensure load balance. By accurately estimating the needs of each waiting area, the system can optimize resource allocation to maximize the workload of each processing end without overloading some processing ends and idling others. By obtaining historical data, the system can predict the load conditions of the waiting area and the processing end, estimate in advance whether the goods can arrive at the next link on time, and make adjustments in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention is a flowchart of a method for optimizing task allocation of industrial robots in a production line.

[0039] Figure 2 The present invention is a structural schematic diagram of a system for optimizing task allocation of industrial robots in a production line. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0041] The present invention is collected.

[0042] Example 1

[0043] The present invention Figure 1 As shown, a method for optimizing task allocation of industrial robots for production lines is provided, comprising the following steps:

[0044] Step S1, obtaining the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive;

[0045] Step S2, determining the processing speed of the waiting area between each processing end according to the number of items processed per unit time at each processing end, and determining the minimum delivery quantity of each waiting area according to the arrival time of the next batch of goods;

[0046] Step S3, obtaining the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area;

[0047] Step S4, based on the historical remaining number of items in the waiting-to-be-processed area that the current conveyor belt passes through and the current conveyor belt speed, it is estimated whether the processing speed of the subsequent waiting-to-be-processed area is sufficient to match, and the speed is adjusted.

[0048] The specific implementation is as follows:

[0049] In step S1, the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive are obtained, including:

[0050] Use sensors to record the processing capacity of each processing end robot and the number of items processed per unit time in real time. Install appropriate sensors (such as position sensors, speed sensors, load sensors, etc.) on each processing end robot to monitor the robot's operating status in real time. By measuring the time required for each robot to complete a task (such as processing, handling, etc.), the processing efficiency of each robot can be calculated. When each robot completes a task, the start and end time of the task can be recorded through the sensor system, thereby calculating the number of tasks completed by each robot per unit time. All data from the sensors will be collected and stored in a database in real time. The data content includes the start time, end time and number of items processed of each operation of the robot. By calculating and analyzing these data, the processing capacity per unit time of each processing end robot can be obtained in real time.

[0051] Use logistics systems or software to regularly update the number of pieces processed and the estimated delivery time, ensure that the software can be seamlessly integrated with conveyor belts, sensors and robotic systems, and record the time when the next batch of goods arrives.

[0052] In step S2, the processing speed of the waiting area between each processing end is determined according to the number of pieces processed per unit time at each processing end, and the minimum delivery quantity of each waiting area is determined according to the time when the next batch of goods arrives. The specific contents include:

[0053] Multiple processing ends are denoted as processing end A, processing end B, processing end C, processing end D..., and there is a waiting area between each processing end, denoted as waiting area 1, waiting area 2, waiting area 3, waiting area 4..., where the left and right sides of processing end A are waiting area 1 and waiting area 2 respectively, and the number of items processed by processing end A per unit time is J1 items, that is, the processing capacity of processing end A is J1 items / unit time, then the number of items processed per unit time of each processing end is: J1, J2, J3, J4...J i ....

[0054] The processing speed of the waiting area depends on the relationship between the number of processing items of the previous processing end and the number of processing items of the current processing end. In order to make the processing speed of each waiting area consistent and avoid too fast or too slow processing speed of a waiting area, which will lead to imbalance of the overall system, more processing items need to be allocated to the waiting area with a small maximum number of processing items. The maximum number of processing items in the waiting area is the sum of the processing capacities of the processing ends on the left and right sides of the waiting area per unit time. The processing speed per unit time of each waiting area is determined by the joint allocation of the previous processing end and the next processing end. The allocation logic of each processing end is determined by the proportional allocation of the maximum number of processing items of the previous waiting area and the next waiting area.

[0055] In summary, this can be achieved using the following formula: Where: V i The speed of each processing end, J i is the number of processing items per unit time at each processing end, i is the number of each processing end, and it should be noted that when i-1=0, J i-1 = 0 and J i-2 =0, or i-2 =0 when J i-2 = 0, or when i does not exist, J i = 0 and J i+1 =0, or when i+1 does not exist, J i+1 =0.

[0056] If it is necessary to achieve basically consistent processing speeds in each processing area, more processing pieces from processing end A need to be allocated to processing area 1, and the allocation is made based on the ratio of the maximum number of processing pieces, taking processing ends A, B, C, D and processing areas 1, 2, 3, 4, 5 as examples.

[0057] Since the processing area 1 is only processed by the processing terminal A, when the processing terminal A only processes the processing area 1, the maximum number of processing cases of the processing area 1 per unit time is J1. The processing area 2 is processed by the processing terminal A and the processing terminal B. When the processing terminals A and B both process the processing area 2, the maximum number of processing cases of the processing area 2 per unit time is J1+J2. Since the processing area 2 is processed by the processing terminal A and the processing terminal B, when the processing terminals A and B both process the processing area 2, the maximum number of processing cases of the processing area 2 per unit time is J1+J2.

[0058] To-be-processed area 1: At this time, i-1 = 0, so J i-1 = 0 and J i-2 =0, then the speed of the treatment area 1 is calculated as: Among them: J1 is the processing capacity of processing end A (the number of items processed per unit time), and J2 is the processing capacity of processing end B. Indicates the load ratio of processing terminal A in the processing area 1.

[0059] To-be-processed area 2: At this time, i-2 = 0, so J i-2 =0, then the speed of the area to be processed 2 is calculated as: Where: J1 is the processing capacity of processing end A, J2 is the processing capacity of processing end B, and J3 is the processing capacity of processing end C. The part represents the load ratio of the processing end A in the processing area 2. Part is a factor that affects the processing speed of the end to be processed B in the processing area 2, taking into account the load distribution between the processing ends A, B and C.

[0060] The calculation of the velocity of the treatment area 3 is: Where: J1 is the processing capacity of processing end A, J2 is the processing capacity of processing end B, J3 is the processing capacity of processing end C, and J4 is the processing capacity of processing end D. The part represents the load ratio of the processing end B in the processing area 3, Part of it is a factor that affects the processing speed of the end C to be processed in the processing area 3.

[0061] To be processed area 4: i+1 does not exist at this time, so J i+1 =0, then the speed of the area to be processed 4 is calculated as: Where: J2 is the processing capacity of processing end B, J3 is the processing capacity of processing end C, J4 is the processing capacity of processing end D, The part represents the load ratio of the processing end C in the processing area 4, Part of it is a factor that affects the processing speed of the end D to be processed in the processing area 4.

[0062] Processing area 5: i does not exist at this time, so J i = 0 and J i+1 =0, then the speed of the area to be processed 5 is calculated as: Where: J3 is the processing capacity of processing end C, J4 is the processing capacity of processing end D, Part of it is a factor that affects the processing speed of the end D to be processed in the processing area 5.

[0063] For the sake of convenience, the above formula is used for assumption: the processing capacity of processing terminal A is: J1 = 25 pieces / unit time, the processing capacity of processing terminal B is: J2 = 15 pieces / unit time, the processing capacity of processing terminal C is: J3 = 20 pieces / unit time, and the processing capacity of processing terminal D is: J4 = 20 pieces / unit time.

[0064] The processing speed of the processing area 1 is calculated according to the given formula: Substituting J1=25 and J2=15 into the formula, we get:

[0065] The processing speed of the processing area 2 is calculated according to the given formula: Substitute the data: J1 = 25, J2 = 15, J3 = 20, then

[0066] The processing speed of the processing area 3 is calculated according to the given formula: Substitute the data: J1 = 25, J2 = 15, J3 = 20, J4 = 20, then

[0067] The processing speed of the processing area 4 is calculated according to the given formula: Substitute the data: J2=15, J3=20, J4=20, then

[0068] The processing speed of the processing area 5 is calculated according to the given formula: Substitute the data: J3=20, J4=20, then

[0069] In summary: the processing speed of the waiting area 1 is 15.385 pieces / unit time, the processing speed of the waiting area 2 is 16.615 pieces / unit time, the processing speed of the waiting area 3 is 17.23 pieces / unit time, the processing speed of the waiting area 4 is 15.999 pieces / unit time, and the processing speed of the waiting area 5 is 13.333 pieces / unit time. According to the example, it can be found that with the interaction of the processing ends, the processing speed of the waiting area varies between different ends, and the formula can be used to balance the processing speed of each waiting area to avoid too fast or too slow processing of a part.

[0070] In order to ensure that there is enough processing space in the waiting area when the next batch of goods arrives, the minimum number of pieces required to be put in is determined according to the arrival time of the next batch of goods and the processing speed of each waiting area. The formula can be expressed as: Minimum amount of waiting area = (processing speed of waiting area × arrival time of the next batch of goods). It should be noted that when the calculated minimum amount of waiting area is a decimal, it needs to be rounded up, that is, the integer part is added by one.

[0071] For example: Assuming that the processing speed of the waiting area is 15.5 pieces of goods per hour, and the time for the next batch of goods to arrive is 2.3 hours, calculate the minimum delivery quantity: the minimum delivery quantity of the waiting area = 15.5 pieces / hour × 2.3 hours = 35.65 pieces

[0072] Since the result is a decimal of 35.65, it needs to be rounded up. Therefore, the minimum amount of goods put into the waiting area is 36 pieces to ensure that there is enough space in the waiting area to handle the incoming goods.

[0073] In step S3, the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area are obtained, including:

[0074] Install sensors in the processing area to track the number of items remaining on the conveyor belt, record the historical records, and average the historical records to calculate the average historical number. The formula can be expressed as: Where: T is the statistical period, and t is the number of remaining pieces transmitted to the waiting area at each moment.

[0075] Install a contact sensor, usually by contacting the conveyor belt or connecting to the drive shaft of the conveyor belt, measure its rotation frequency and calculate the current conveyor belt speed. The calculation formula can be expressed as: v = k × f, where: k is a constant, which is related to the length of the conveyor belt, the transmission system and the position of the sensor, and the current conveyor belt speed is recorded.

[0076] In step S4, it is estimated whether the processing speed of the subsequent processing area is sufficient to match the number of remaining pieces in the processing area that the current conveyor belt passes through and the current conveyor belt speed. The specific contents include:

[0077] Compare the current number of remaining pieces with the average historical number of remaining pieces. If it is less than the average historical number of pieces, accelerate the process and make the next batch of goods arrive earlier. If it is greater than the average historical number of pieces, slow down to prevent accumulation.

[0078] First, the difference between the average number of historical remaining pieces and the current number of remaining pieces can be expressed as: Difference = Current number of remaining pieces - Average number of historical remaining pieces

[0079] The difference can be used to determine whether the conveyor belt speed needs to be accelerated or decelerated. If the difference is negative (that is, the current number of remaining pieces is lower than the average historical value), it means that the current speed is slow and needs to be accelerated; if the difference is positive, it means that the current speed is too fast, which may cause accumulation and needs to be decelerated.

[0080] The rules for dynamically adjusting the conveyor belt speed are as follows:

[0081] Acceleration rule: When the difference is less than 0 (i.e. the current number of remaining pieces is lower than the average level), the processing process is accelerated. The specific acceleration range can be set according to historical data, which can be expressed as: new conveyor belt speed = current conveyor belt speed × (1 + acceleration factor), where: acceleration factor = |difference| / average historical number of remaining pieces.

[0082] Deceleration rule: When the difference is greater than 0 (i.e. the current number of remaining pieces is higher than the average level), the process is decelerated. The deceleration amplitude is set according to historical data, expressed as: new conveyor belt speed = current conveyor belt speed × (1-deceleration coefficient), where: deceleration coefficient = |difference| / average historical number of pieces.

[0083] Assume that the current conveyor belt speed is 10 m / min, the average number of remaining pieces in historical data is 100 pieces, and the current number of remaining pieces is 80 pieces. The difference = 80-100 = -20. The difference is negative, indicating that the current number of remaining pieces is lower than the historical average and needs to be accelerated. The acceleration factor = |-20| / 100 = 0.2, and the new conveyor belt speed = 10×(1+0.2) = 10×1.2 = 12 m / min.

[0084] Example 2

[0085] Figure 2 A task allocation optimization system for industrial robots in production lines is provided, comprising: an information acquisition module 1, a delivery amount calculation module, an information acquisition module 2 and a matching optimization module.

[0086] Information acquisition module 1: obtains the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive;

[0087] Delivery volume calculation module: determines the processing speed of the waiting area between each processing end according to the number of pieces processed per unit time at each processing end, and determines the minimum delivery volume of each waiting area according to the arrival time of the next batch of goods;

[0088] Information acquisition module 2: obtains the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area;

[0089] Matching optimization module: estimates whether the processing speed of subsequent processing areas is sufficient to match the historical number of remaining items in the processing area that the current conveyor belt passes through and the current conveyor belt speed, and adjusts the speed.

[0090] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0091] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0092] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0093] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0094] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0095] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0096] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing task allocation of industrial robots in production lines, characterized in that: Includes steps: Step S1, obtaining the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive; Step S2, determining the processing speed of the waiting area between each processing end according to the number of items processed per unit time at each processing end, and determining the minimum delivery quantity of each waiting area according to the arrival time of the next batch of goods; Step S3, obtaining the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area; Step S4, based on the historical remaining number of items in the waiting-to-be-processed area that the current conveyor belt passes through and the current conveyor belt speed, it is estimated whether the processing speed of the subsequent waiting-to-be-processed area is sufficient to match, and the speed is adjusted.

2. The method for optimizing task allocation of industrial robots for production lines according to claim 1, characterized in that: Install sensors on each processing end robot to record the start and end time of the task, so as to calculate the number of tasks completed by each robot per unit time, and obtain the processing capacity per unit time of each processing end robot, which is stored in a database; Use logistics systems or software to regularly update the number of pieces processed and estimated delivery time, and record the time when the next batch of goods will arrive.

3. The method for optimizing task allocation of industrial robots for production lines according to claim 2 is characterized in that: Multiple processing ends are recorded as processing end A, processing end B, processing end C, processing end D..., and there is a waiting area between each processing end, recorded as waiting area 1, waiting area 2, waiting area 3, waiting area 4..., where the left and right sides of processing end A are waiting area 1 and waiting area 2 respectively, and the number of processed items per unit time of processing end A is J1 items, then the number of processed items per unit time of each processing end is: J1, J2, J3, J4...J i ...; The processing speed of the waiting area depends on the relationship between the number of processing cases of the previous processing end and the number of processing cases of the current processing end. More processing cases are allocated to the waiting area with a small maximum processing number, where the maximum processing number of the waiting area is the sum of the processing capacity per unit time of the processing ends on the left and right sides of the waiting area, and the maximum processing number per unit time of the waiting area 1 = J1. The processing speed per unit time of each waiting area is determined by the joint allocation of the previous processing end and the next processing end, and the allocation logic of each processing end is determined by the proportional allocation of the maximum processing number of the previous waiting area and the next waiting area; In summary, the following formula is used to achieve: Where: V i The speed of each processing end, J i is the number of processing items per unit time at each processing end, i is the number of each processing end, and it should be noted that when i-1=0, J i-1 = 0 and J i-2 =0, or i-2 =0 when J i-2 = 0, or when i does not exist, J i = 0 and J i+1 =0, or when i+1 does not exist, J i+1 =0; The minimum delivery amount is determined based on the arrival time of the next batch of goods and the processing speed of each waiting area. The formula is: Minimum delivery amount of the waiting area = (processing speed of the waiting area × arrival time of the next batch of goods). It should be noted that when the calculated minimum delivery amount of the waiting area is a decimal, it needs to be rounded up, that is, the integer part is added by one.

4. The method for optimizing task allocation of industrial robots for production lines according to claim 3 is characterized in that: Install sensors in the processing area to track the number of items remaining on the conveyor belt, record the historical records, and average the historical records to calculate the average historical number. The formula is: Where: T is the statistical period, t is the number of remaining pieces transmitted to the waiting area at each moment; The contact sensor is usually installed by contacting the conveyor belt or connecting with the drive shaft of the conveyor belt to measure its rotation frequency and calculate the current conveyor belt speed. The calculation formula is: v = k × f, where: k is a constant related to the length of the conveyor belt, the transmission system and the position of the sensor.

5. The method for optimizing task allocation of industrial robots for production lines according to claim 4 is characterized in that: Compare the current number of remaining items with the average number of remaining items in history. If it is less than the average number of remaining items in history, speed up; if it is greater than the average number of remaining items in history, slow down. First, the difference between the average number of historical remaining pieces and the current number of remaining pieces is calculated as: Difference = Current number of remaining pieces - Average number of historical remaining pieces The difference determines whether the conveyor belt speed needs to be accelerated or decelerated. If the difference is negative, it means that the current speed is slow and needs to be accelerated; if the difference is positive, it means that the current speed is too fast and needs to be decelerated. The rules for dynamically adjusting the conveyor belt speed are as follows: Acceleration rule: When the difference is less than 0, the processing is accelerated. The acceleration range is set according to historical data. The formula is: new conveyor belt speed = current conveyor belt speed × (1 + acceleration coefficient), where: acceleration coefficient = |difference| / average number of historical remaining pieces; Deceleration rule: When the difference is greater than 0, the process is decelerated, and the deceleration amplitude is set according to historical data. The expression formula is: new conveyor belt speed = current conveyor belt speed × (1-deceleration coefficient), where: deceleration coefficient = |difference| / average historical number of pieces.

6. A system for optimizing task allocation of industrial robots in production lines, used to implement a method for optimizing task allocation of industrial robots in production lines as claimed in any one of claims 1 to 5, characterized in that: include: Information acquisition module 1, delivery amount calculation module, information acquisition module 2 and matching optimization module; Information acquisition module 1: obtains the number of items processed per unit time by each processing end robot and the time when the next batch of goods will arrive; Delivery volume calculation module: determines the processing speed of the waiting area between each processing end according to the number of pieces processed per unit time at each processing end, and determines the minimum delivery volume of each waiting area according to the arrival time of the next batch of goods; Information acquisition module 2: obtains the average historical number of remaining pieces and the current conveyor belt speed when conveyed to each waiting area; Matching optimization module: Estimates whether the processing speed of subsequent processing areas is sufficient to match the historical number of remaining items in the processing area that the current conveyor belt passes through and the current conveyor belt speed.

Images