Intelligent tobacco sorting and scheduling method

Abstract

The invention discloses an intelligent tobacco sorting and scheduling method which comprises the following steps: S1, data acquisition before sorting: before tobacco is sorted, various information needs to be recorded; s2, distribution of sorting tasks: distribution is performed according to order features: tasks are distributed according to scale, variety complexity and customer areas, equipment is adapted, and small orders are merged; and S3, starting sorting, wherein the tobaccos are sequentially placed on sorting equipment according to the order priority sequence, and sorting work on the tobaccos is achieved through the sorting equipment and workers. According to abnormal conditions possibly occurring in the sorting process, a perfect abnormal judgment and processing mechanism is established, whether a problem exists or a global problem exists is intelligently judged, different processing schemes are accurately selected, under the condition that sorting faults occur, feedback can be conducted in the first time, processing work can be carried out, and the sorting efficiency is improved. And the overall sorting efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco transportation and sorting, and in particular to a tobacco intelligent sorting and scheduling method. Background Art

[0002] With the rapid development of the times, people's work pressure is constantly increasing, and tobacco has become a way for people to release stress in their daily lives. In the process of tobacco production and sales, tobacco needs to be sorted through logistics to achieve the effect of classification and facilitate subsequent management and transportation.

[0003] The common method of tobacco sorting mainly relies on the collaborative work of sorting equipment and staff. Sorting equipment is used to quickly sort large quantities of tobacco goods, and staff are used to assist in further improving the efficiency and effectiveness of sorting.

[0004] The existing tobacco sorting, which is assisted by sorting equipment and staff, is often manually distributed based on simple rules or experience. It is difficult to fully consider the differences in the characteristics of tobacco products, the complexity of orders and the actual performance of sorting equipment, which can easily lead to unreasonable task allocation, waste of equipment resources or local congestion, and reduce the overall sorting efficiency. At the same time, once a sorting equipment failure occurs and the staff does not pay attention, it is easy to cause a large amount of tobacco goods to accumulate in a faulty sorting equipment, which not only affects the subsequent sorting of tobacco goods, but also delays the overall work efficiency. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a tobacco intelligent sorting and scheduling method, which solves the problem that in the existing tobacco sorting process, once a sorting equipment failure occurs and the staff does not pay attention, a large amount of tobacco goods will be blocked, affecting the sorting efficiency.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a tobacco intelligent sorting and scheduling method, comprising the following steps:

[0007] S1. Data collection before sorting: Before sorting tobacco, various information needs to be recorded, including: tobacco product information, sorting equipment information, order information and staff information;

[0008] S2. Allocation of sorting tasks: Allocation by order characteristics: Assign tasks according to scale, variety complexity, customer area, adapt equipment, and merge small orders;

[0009] S3. Sorting starts: tobacco is placed on the sorting equipment in order of order priority, and the tobacco is sorted by the sorting equipment and staff;

[0010] S4. Carry out sorting work according to the plan: the staff operates the equipment to sort the products according to the tasks and paths, and uses the transportation equipment to transport the products along the paths, monitors the sorting paths in real time, and is equipped with sensors to collect values ​​from the devices on the sorting paths;

[0011] S5. Abnormality judgment: By comparing the collected values, it is judged whether there is any abnormality in the sorting equipment;

[0012] S6. Sorting completed: After the quality inspection is completed, the staff confirms that the sorting work is completed.

[0013] Preferably, the tobacco product information includes: brand, specification, and packaging.

[0014] Preferably, the sorting equipment information includes equipment model, parameters, location, status, and maintenance records.

[0015] Preferably, the order information includes the order quantity and the order address.

[0016] Preferably, the staff information includes basic and work-related information of the staff.

[0017] Preferably, the step S5 includes: S501. Local re-planning: when the device temperature and vibration parameters exceed the normal range, including the device temperature T is greater than the set threshold T max , the vibration amplitude V is greater than the normal upper limit V max , the channel flow is lower than the normal threshold Q for a long time min When the congestion flag B=1, it is determined to be a local abnormality and a local processing solution is used; S502. Global re-planning: It is started when multiple equipment failures or large-scale congestion make local adjustments invalid, and a global processing solution is used.

[0018] Preferably, the local processing scheme is: and re-determine the starting point and target point of the sorted goods, and determine the current position of the product (x start ,y start ) as the new starting point, calculate the coordinates of the nearest normal device or channel to the inaccessible area (x target ,y target ) is the target point, and the distance formula is:

[0019]

[0020] Then recalculate and select the path, calculate the local shortest path with the starting point and the target point as constraints, and set the original path P original , candidate path P candidate , path similarity (n commonis the number of identical or similar nodes, n candidate is the number of candidate path nodes, n original is the number of nodes in the original path), let device i have a current load L i , maximum load Load balancing (n is the number of devices, is the average load), comprehensively weighing S and B to select the optimal path;

[0021] Update the control system with new route information, issue instructions to the transport equipment, and continuously monitor execution.

[0022] Preferably, the global processing scheme is: and construct an objective function, comprehensively considering the order priority P priority (Urgent orders are set to high values, including 3, and ordinary orders are set to 1), urgency U (the smaller the delivery time difference, the higher the urgency), product characteristics F, and the objective function calculation formula is: (m is the number of orders, n is the number of product types, L is the device load balance, D is the total path length, α, β, γ and δ are weight coefficients)

[0023] And optimize the path calculation, use complex network analysis and optimization algorithms (including genetic algorithms), build a topology graph with devices and channels as nodes and edges, and calculate the optimal path combination;

[0024] Reallocate tasks to equipment according to the optimal path, coordinate equipment operation sequence and time,

[0025] Update the control system and operators manually intervene to monitor the execution of the new solution.

[0026] Preferably, the sensor includes a temperature sensor and a vibration sensor.

[0027] An application of an intelligent tobacco sorting and scheduling method, such as the intelligent tobacco sorting and scheduling method as described in claims 1-9, is applied in the tobacco field, especially in the tobacco transportation and sorting field.

[0028] The present invention provides a tobacco intelligent sorting and scheduling method. It has the following beneficial effects:

[0029] 1. Aiming at abnormal situations that may occur during the sorting process, the present invention has established a complete abnormal judgment and processing mechanism. It can intelligently judge whether it is a specific problem or a global problem, and accurately select different processing solutions. In the case of sorting failure, the present invention can provide feedback and carry out processing work in the first time, effectively improving the overall sorting efficiency.

[0030] 2. The present invention provides a distance calculation formula to provide an accurate basis for determining a new sorting path, improve the accuracy and efficiency of path selection, enhance the ability to respond to emergencies, and reduce operating costs.

[0031] 3. The present invention calculates the comprehensive priority value of tobacco goods through a formula, comprehensively and accurately evaluates the importance and urgency of goods, rationally allocates resources, takes into account multiple factors, and improves customer satisfaction and enterprise operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the sorting and scheduling method of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the specification 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.

[0034] Example:

[0035] Please refer to the attached Figure 1 The embodiment of the present invention provides a tobacco intelligent sorting and scheduling method, comprising the following steps:

[0036] S1. Data collection before sorting: Before sorting tobacco, various information needs to be recorded to provide a basis for subsequent work. The information includes: tobacco product information, sorting equipment information, order information and staff information;

[0037] The tobacco product information includes: brand, specification, packaging; the sorting equipment information includes equipment model, parameters, location, status, maintenance records; the order information includes order quantity and order address; the staff information includes basic and work-related information of the staff;

[0038] S2. Allocation of sorting tasks: Allocation by order characteristics: Assign tasks according to scale, variety complexity, customer area, adapt equipment, and merge small orders;

[0039] S3. Sorting starts: tobacco is placed on the sorting equipment in order of order priority, and the tobacco is sorted by the sorting equipment and staff;

[0040] S4. Carry out sorting work according to the plan: the staff operates the equipment to sort the products according to the tasks and paths, and uses the transportation equipment to transport the products along the paths to ensure smooth circulation, monitor the sorting paths in real time, and are equipped with sensors to collect values ​​from the devices on the sorting paths, including temperature sensors and vibration sensors;

[0041] S5. Abnormality judgment: By comparing the collected values, it is judged whether there is any abnormality in the sorting equipment;

[0042] S501. Local re-planning: When the device temperature and vibration parameters exceed the normal range, including the device temperature T is greater than the set threshold T max , the vibration amplitude V is greater than the normal upper limit V max , the channel flow is lower than the normal threshold Q for a long time min When the blocking indicator B=1, it is determined to be a local abnormality;

[0043] The starting point and target point of the sorted goods are re-determined, and the current position of the product (x start ,y start ) as the new starting point, calculate the coordinates of the nearest normal device or channel to the inaccessible area (x target ,y target ) is the target point, and the distance formula is:

[0044] Then recalculate and select the path, calculate the local shortest path with the starting point and the target point as constraints, and set the original path P original , candidate path P candidate , path similarity (n common is the number of identical or similar nodes, n candidate is the number of candidate path nodes, n original is the number of nodes in the original path), let device i have a current load L i , maximum load Load balancing (n is the number of devices, is the average load), comprehensively weighing S and B to select the optimal path;

[0045] Update the control system with new route information, issue instructions to the transport equipment, and continuously monitor execution;

[0046] S502. Global re-planning: Started when multiple equipment failures or large-scale congestion make local adjustments ineffective. Collect and analyze the status of all equipment (available equipment, remaining capacity, etc.) i , location) channel status, product and order information, and build a real-time status model;

[0047] And construct the objective function, comprehensively considering the order priority P priority (Urgent orders are set to high values, including 3, and ordinary orders are set to 1), urgency U (the smaller the delivery time difference, the higher the urgency), product characteristics F, and the objective function calculation formula is: (m is the number of orders, n is the number of product types, L is the device load balance, D is the total path length, α, β, γ and δ are weight coefficients)

[0048] And optimize the path calculation, use complex network analysis and optimization algorithms (including genetic algorithms), build a topology graph with devices and channels as nodes and edges, and calculate the optimal path combination;

[0049] Reallocate tasks to equipment according to the optimal path, coordinate equipment operation sequence and time, and ensure smooth product flow;

[0050] Update the control system and operators manually intervene to monitor the execution of the new solution.

[0051] S6. Sorting completed: After the quality inspection is completed, the staff confirms that the sorting work is completed.

[0052] 1. Comparative experiment:

[0053] Construct a simulated tobacco sorting environment, including sorting workshops of the same scale and layout, equipped with the same type and quantity of sorting equipment, transportation equipment and other hardware facilities.

[0054] Prepare the same quantity of tobacco products of various brands, specifications, and packaging as experimental materials, and simulate the generation of order sets with different scales, variety complexity, and customer area distribution. The order quantity is set to 500.

[0055] Arrange an equal number of staff with similar skill levels to participate in the experimental operations.

[0056] 2. Experimental steps:

[0057] Traditional sorting method experiment:

[0058] The traditional manual experience-based task allocation method is used to roughly evenly distribute the tasks to each sorting equipment area based on the order quantity, without considering the characteristics of tobacco products, the complexity of orders, and differences in equipment performance.

[0059] Sorting operations are performed according to fixed, experience-based routes, with no dynamic route adjustment mechanism.

[0060] During the experiment, when abnormal situations such as equipment failure or channel blockage occurred, the staff manually discovered them and made temporary adjustments based on experience, recording the time when the failure or blockage occurred, the start time of processing, the completion time of processing, and the amount of tobacco goods accumulated during the failure.

[0061] Experiment of the sorting method of the present invention:

[0062] First, proceed to step S1 to comprehensively collect tobacco product information, sorting equipment information, order information and staff information, and enter them into the system.

[0063] Execute step S2. The system automatically assigns tasks based on order characteristics (such as order size, product complexity, and customer region) and equipment adaptability, and merges small orders for optimal processing.

[0064] Enter step S3 to start sorting, place the tobacco on the sorting equipment in order of order priority, and the staff and equipment work together.

[0065] In step S4, the transport equipment transports the products according to the planned route. At the same time, temperature sensors, vibration sensors, etc. collect equipment values ​​in real time and transmit them to the system. The system dynamically monitors the sorting route.

[0066] If an exception occurs, in step S5:

[0067] For local anomalies (such as a single device temperature exceeding the threshold, set as the device temperature reaching 80°C, which is greater than the normal threshold of 70°C, the vibration amplitude exceeding the normal upper limit by 20%, the channel flow rate being lower than the normal threshold by 50% and the blockage flag being triggered):

[0068] The system quickly determines the new starting point and target point. Assuming that the original path has 20 nodes and the candidate path has 18 nodes, of which 12 are the same or similar nodes, the path similarity is calculated.

[0069] In terms of equipment, suppose there are 5 equipments, and the current loads are [0.6, 0.4, 0.8, 0.3, 0.5] (full load is 1), and the average load is Calculate load balance According to S and B, the optimal path is selected and the control system is updated. Instructions are issued to the transport equipment, and the entire local abnormality processing time is recorded as 5 minutes, and the tobacco cargo accumulation volume is 10 pieces.

[0070] For global anomalies (simulating simultaneous failure of three key devices or large-scale channel blockage):

[0071] The system collects and analyzes all information, builds a real-time status model, and constructs an objective function by comprehensively considering order priority (assuming 100 urgent orders and 400 ordinary orders), urgency (the average delivery time difference for urgent orders is 2 hours, and for ordinary orders is 10 hours), and product characteristics. It sets a=0.3, β=0.2, γ=0.2, and δ=0.3, calculates the objective function value Z, and uses a genetic algorithm to construct a topological graph with equipment and channels as nodes and edges. It calculates the optimal path combination and task allocation plan, and the operator manually intervenes according to the system prompts (such as starting backup equipment, etc.). The global exception processing time is recorded as 15 minutes, and the tobacco cargo accumulation volume is 30 pieces.

[0072] Finally, complete step S6 and confirm that the sorting is complete after quality inspection.

[0073] 3. Comparison and analysis of experimental data:

[0074] Sorting efficiency comparison:

[0075] The traditional sorting method takes 10 hours to complete the 500-order sorting task, while the sorting method of the present invention takes 8 hours, and the efficiency is improved by (10-8) / 10×100%=20%

[0076] Comparison of exception handling effects:

[0077] In terms of local exception handling, the average processing time of the traditional method is 15 minutes, and the cargo accumulation volume is 30 pieces, while the processing time of the method of the present invention is 5 minutes, and the cargo accumulation volume is 10 pieces.

[0078] In terms of global exception handling, the traditional method may cause sorting to be stalled for more than 30 minutes due to the lack of an effective response mechanism, and the goods are piled up in a chaotic manner that is difficult to count. The processing time of the method of the present invention is 15 minutes, the amount of goods piled up is relatively small, and the sorting order can be restored quickly.

[0079] Comparison of equipment resource utilization:

[0080] The load balance of the equipment in the traditional sorting method is poor, some equipment runs overloaded for a long time, and some equipment has a high idle rate. The load imbalance index (such as the standard deviation of the equipment load) is calculated to be 0.25. The load imbalance index of the method of the present invention is 0.15 through intelligent task allocation and path planning, and the utilization of equipment resources is more reasonable.

[0081] Through the above comparative experiments, it can be intuitively seen that the tobacco intelligent sorting and scheduling method of the present invention has significant advantages over the traditional sorting method in terms of sorting efficiency, exception handling capability and equipment resource utilization.

[0082] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tobacco intelligent sorting and scheduling method, characterized in that: The following steps are involved: S1. Data collection before sorting: Before sorting tobacco, various information needs to be recorded, including: tobacco product information, sorting equipment information, order information and staff information; S2. Allocation of sorting tasks: Allocation by order characteristics: Assign tasks according to scale, variety complexity, customer area, adapt equipment, and merge small orders; S3. Sorting starts: tobacco is placed on the sorting equipment in order of order priority, and the tobacco is sorted by the sorting equipment and staff; S4. Carry out sorting work according to the plan: the staff operates the equipment to sort the products according to the tasks and paths, and uses the transportation equipment to transport the products along the paths, monitors the sorting paths in real time, and is equipped with sensors to collect values ​​from the devices on the sorting paths; S5. Abnormality judgment: By comparing the collected values, it is judged whether there is any abnormality in the sorting equipment; S6. Sorting completed: After the quality inspection is completed, the staff confirms that the sorting work is completed.

2. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The tobacco product information includes: brand, specification, and packaging.

3. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The sorting equipment information includes equipment model, parameters, location, status, and maintenance records.

4. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The order information includes the order quantity and order address.

5. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The staff information includes basic and work-related information of the staff.

6. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The step S5 includes: S501. Local re-planning: When the device temperature and vibration parameters exceed the normal range, including the device temperature T is greater than the set threshold T max , the vibration amplitude V is greater than the normal upper limit V max , the channel flow is lower than the normal threshold Q for a long time min When the congestion flag B=1, it is determined to be a local abnormality and a local processing solution is used; S502. Global re-planning: It is started when multiple equipment failures or large-scale congestion make local adjustments invalid, and a global processing solution is used.

7. A tobacco intelligent sorting and scheduling method according to claim 6, characterized in that: The local processing scheme is: re-determine the starting point and target point of the sorted goods, and determine the current position of the product (x start ,y start ) as the new starting point, calculate the coordinates of the nearest normal device or channel to the inaccessible area (x target ,y target ) is the target point, and the distance formula is: Then recalculate and select the path, calculate the local shortest path with the starting point and the target point as constraints, and set the original path P original , candidate path P candidate , path similarity (n common is the number of identical or similar nodes, n candidate is the number of candidate path nodes, n original is the number of nodes in the original path), let device i have a current load L i , maximum load L maxi , load balancing (n is the number of devices, is the average load), comprehensively weighing S and B to select the optimal path; Update the control system with new route information, issue instructions to the transport equipment, and continuously monitor execution.

8. A tobacco intelligent sorting and scheduling method according to claim 6, characterized in that: The global processing scheme is: and construct an objective function, comprehensively considering the order priority P priority (Urgent orders are set to high values, including 3, and ordinary orders are set to 1), urgency U (the smaller the delivery time difference, the higher the urgency), product characteristics F, and the objective function calculation formula is: (m is the number of orders, n is the number of product types, L is the device load balance, D is the total path length, α, β, γ and δ are weight coefficients) And optimize the path calculation, use complex network analysis and optimization algorithms (including genetic algorithms), build a topology graph with devices and channels as nodes and edges, and calculate the optimal path combination; Reallocate tasks to equipment according to the optimal path, coordinate equipment operation sequence and time, Update the control system and operators manually intervene to monitor the execution of the new solution.

9. A tobacco intelligent sorting and scheduling method according to claim 1, characterized in that: The sensors include a temperature sensor and a vibration sensor.

10. An application of a tobacco intelligent sorting and scheduling method, characterized in that: The tobacco intelligent sorting and scheduling method as described in claims 1-9 is applied in the tobacco field, especially in the tobacco transportation and sorting field.

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