Cargo handling method and computer system for carrying out inventory optimization storage through automatic ABC classification calculation

Abstract

The invention discloses a tallying method for carrying out inventory optimization storage through automatic ABC classification calculation, and the method comprises the steps: setting the classification attribute of a storage location, carrying out the initialization classification setting of goods, automatically calculating the classification attribute of the goods according to a set period, checking whether the classification attribute of the goods is matched with the classification attribute of the current storage location or not, and carrying out the transfer of the storage if the classification attribute of the goods is not matched with the classification attribute of the current storage location. And after the target storage location is positioned, generating a warehouse moving task from the initial storage location to the target storage location, and putting a plurality of tallying tasks into one tallying task group. The method has the advantages that data calculation is intelligent, data actually generated in a warehouse is analyzed and calculated and then executed according to a configured rule, manual experience is not relied on any more, and the tallying efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent warehousing, and particularly to a goods tallying method and a computer system for optimizing inventory storage through automatic ABC classification calculation. Background Art

[0002] In actual warehouse location management, warehouse locations are classified according to the convenience of picking and the distance to the outbound temporary storage area. Goods with a high picking frequency are preferentially allocated to locations with high picking convenience. After running for a period of time, the sales rate of goods will change with the season. At this time, it is necessary to move the goods to better locations for the goods with a higher current picking frequency. Currently, the following two methods are provided for the above problems: 1) Manually conduct offline statistics and then organize the goods through the method of moving warehouses; 2) Query the data that needs to be tallied according to specific screening conditions, and then manually select and organize the goods through the method of moving warehouses.

[0003] The above two goods tallying methods mainly rely on the understanding of the storage situation of the managed warehouse and are carried out through manual intervention, which is time-consuming, laborious and inefficient, and this is where the present application needs to be improved. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a goods tallying method for optimizing inventory storage through automatic ABC classification calculation, so as to improve the tallying efficiency and accuracy.

[0005] To solve the above technical problems, the present invention provides a goods tallying method for optimizing inventory storage through automatic ABC classification calculation, including the following steps: Step S10: Set the ABC classification attributes for the warehouse locations; Set the ABC classification attributes for the warehouse locations according to the convenience of picking and the distance to the outbound temporary storage area; Among them, the A-class attribute refers to the warehouse location that is most convenient for picking, the B-class attribute refers to the warehouse location that is generally convenient, and the remaining warehouse locations are C-class; Step S20: Initialize the ABC classification settings for the warehouse goods; Set the initial ABC classification attributes for each warehouse good when it initially enters the warehouse; Among them, the A-class attribute refers to the goods with the most frequent picking and outbound, the B-class attribute refers to the goods with general frequency, and the C-class attribute refers to the goods with rarely picking and outbound; Step S30: Automatically execute according to the set cycle and perform regular calculations; Automatically execute according to the set cycle, and select to automatically execute weekly, monthly or annually; further, in coordination with the automatic execution cycle, specify the day of the week within the cycle to automatically execute; Step S40: Set the ABC classification rules for goods, and recalculate the ABC classification attributes of goods regularly according to the rules. Calculate the data dimensions of goods within the set time period. Select one data dimension, or select multiple data dimensions and configure the weights for comprehensive ranking, and then assign classification attributes proportionally. The set time period refers to the recently set time range, including several days, or several weeks, or several months. The data dimensions include the number of orders, order quantity, picking times, and picking quantity. Assign classification attributes based on the sales ranking of the number of orders, or rank according to the configuration ratio of the sales of the number of orders and the picking quantity, and then assign classification attributes. The proportional assignment of classification attributes is as follows: Proportion of Class A: Set what percentage of the total ranking is Class A. Proportion of Class B: Set what percentage of the total ranking in the middle is Class B. Proportion of Class C: Excluding Class A and Class B is Class C. Step S50: Set the goods sorting location rules, and reposition the new storage locations of the goods to be sorted according to the rules. After the recalculation of the ABC classification of goods is completed, check whether the ABC classification attributes of the goods match the ABC classification attributes of the current storage location. If there is a mismatch, perform a relocation recommendation and generate a sorting and relocation task, including: 1) Filtering rules for goods to be sorted; Based on the mismatch between the ABC classification attributes of the goods and the ABC classification attributes of the storage location, superimpose filtering conditions. The goods that meet this condition are subject to the operation of positioning the new storage location. The filtering conditions can be selected from storage location attributes or goods attributes, specifying the A storage area or goods in the daily necessities category. 2) Filtering rules for the target storage location of relocation; Based on finding the storage location corresponding to the ABC classification of goods, superimpose filtering conditions that limit the range of the target storage location of goods, which can be the storage area, or the roadway, or the floor height. 3) Matching rules for the target storage location of relocation; Enable one or more rules for finding new storage locations, and sort the priorities of multiple rules for searching, including: a) Search for the same product and same batch storage location. Search for the storage location where there is this product and the same batch under the target storage location filtering rules for the goods. If not found, execute the next rule; b) Search for the same product storage location. Search for the storage location where there is this product under the target storage location filtering rules for the goods. If not found, execute the next rule; c) Search for an empty storage location. Search for the storage location under the target storage location filtering rules for the goods. If not found, execute the next rule; d) Search for non-empty storage locations and check if the goods are stored mixed with other goods under the target storage location filtering rules. e) Priority order of target storage locations. When multiple target storage locations are found, set the priority order of the storage locations. Sort them according to the storage area, aisle, floor, row, and column of the storage location to find the most prioritized storage location. Step S60, Generation rule of the tally task group. When the target storage location is located, a relocation task from the starting storage location to the target storage location is generated. At this time, according to the generation rule of the tally task group, multiple tally tasks are grouped into one tally task group and sent to the same execution end. The generation rules include: 1) Upper limit of task quantity, which limits the maximum number of relocation tasks in one task group. 2) Same starting storage location. When enabled, tasks with the same starting storage location are put into the same task group. 3) Same starting storage area. When enabled, tasks with the same starting storage area are put into the same task group. 4) Same target storage location. When enabled, tasks with the same target storage location are put into the same task group. 5) Same target storage area. When enabled, tasks with the same target storage area are put into the same task group. Step S70, Abnormal handling mechanism, which configures the handling method when the result does not meet the expectation due to configuration errors. After each calculation is completed, different data before and after the update of the ABC classification of the goods will be recorded. By the ABC change data of the goods, the update changes each time can be understood in a timely manner. If the result does not meet the expectation, the parameters are adjusted in a timely manner, and manual triggering is performed to recalculate.

[0006] The present invention also provides a computer system, including a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program to implement the steps of the tally method for optimizing inventory storage through automatic ABC classification calculation.

[0007] The beneficial effects of the present invention are as follows: 1) Automation of execution: By setting the regular execution rule, it is executed regularly and at a fixed time without manual intervention. 2) Intelligence and objectivity of data calculation. After analyzing and calculating through the data actually occurring in the warehouse and executing according to the configured rules, it no longer depends on manual experience, improving the tally efficiency and accuracy. 3) Linkage between the ABC classification calculation of goods and the tally task. The ABC classification calculation of goods automatically triggers the generation of the tally task, and multiple tasks are completed in one calculation. Brief Description of the Drawings

[0008] The accompanying drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 It is a schematic flow chart of a specific embodiment of the present invention. Detailed implementation manners

[0009] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Taking a supermarket warehouse as an example, the frequency of goods in and out is very high, and there are obvious differences in the popularity of goods during the changing seasons. Taking sports drink goods as an example, a detailed description will be given.

[0010] As Figure 1 shown, the present invention provides a method for optimizing the storage of inventory through automatic ABC classification calculation, including the following steps: Step 1, set the ABC classification attributes for the storage locations; perform an initial ABC classification setting for the warehouse goods. Sports drink goods are in the peak sales season in summer and the slow sales season in winter. The initial storage season is summer, and by default, the classification of sports drink goods at that time is category A, and the storage location is the recommended category A storage location that is most convenient for picking, specifying the aisle and arrangement layer information of the storage location.

[0011] Step 2, execute automatically at the set cycle for regular calculation. Set to perform regular calculation on the first day of each week.

[0012] Step 3, set the ABC classification rules for the goods, and regularly recalculate the ABC classification attributes of the goods according to the rules. Set the "statistical data range" to query the data of the past month, set the "statistical data dimension" to the number of outbound orders, and generate a list of ABC changes for the goods. As the weather turns cold and enters winter, sports drink goods enter the slow sales stage. According to the configured ABC classification rules for the goods, the ABC classification is based on the sales volume ranking of the outbound orders within 1 month. In this embodiment, the top 10% are set as category A, the middle 30% are set as category B, and the last 60% are set as category C. At this time, the sales volume of sports drink goods decreases, resulting in a decrease in the ranking, and it is updated from category A to category B.

[0013] Step 4, set the goods sorting and positioning rules, and reposition the new storage locations of the goods to be sorted according to the rules. After the ABC classification of the goods is recalculated, check whether the ABC classification attributes of the goods match the ABC classification attributes of the current storage location. If there is a mismatch, recommend a relocation of the storage location and generate a task for sorting and relocating the storage location. The linkage between the ABC classification calculation of goods and the tallying task, where the ABC classification calculation of goods automatically triggers the generation of the tallying task. When the sports drink product is updated from category A to category B, the automatic trigger of the tallying task is to move from the category A storage location to the category B storage location, so that the vacated category A storage location can store the remaining goods with category A attributes; Set the range of the storage locations to be tallied as the lower-level storage locations in area B, and the range of the target storage locations as the lower-level storage locations in area B. The positioning rule of the target storage location is of high priority. First, look for the storage locations of the same product, then look for empty storage locations, and finally look for non-empty storage locations. The sorting of the target storage locations gives priority to looking for the first-level storage locations.

[0014] Step 5: The rule for generating the tallying task group is that at most 10 tasks in the same starting storage area are divided into one group.

[0015] The present invention provides a tallying method for optimizing the storage of inventory through automatic ABC classification calculation. At 0:00 on the first day of each week, the ABC classification of goods is automatically recalculated, and the calculation result is used to check whether the ABC classification of the goods matches the ABC classification of the current storage location. If they do not match, a tallying task is automatically generated. The update situation of each item of goods can be understood in a timely manner through the goods ABC change list. If an abnormal result is found, manual triggering of recalculation is performed for parameter adjustment.

[0016] The present invention also provides a computer system, including a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program to implement the steps of the tallying method for optimizing the storage of inventory through automatic ABC classification calculation.

[0017] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for optimizing inventory storage by automatic ABC classification calculation, comprising the following steps: Step S10, set ABC classification attributes for the storage location; Step S20, initializing ABC classification settings for warehouse goods; Step S30, automatically calculate according to the set period; Step S40: Set the ABC classification rules for goods, and recalculate the ABC classification attributes of goods regularly according to the rules; Calculate the data dimensions of the goods within the set time period, select one data dimension, or select multiple data dimensions and configure the weights for comprehensive ranking, and assign ABC classification attributes in proportion; Step S50: Set the goods tallying positioning rules, and relocate the new storage location of the goods to be tallied according to the rules; If the ABC classification attributes of the goods do not match the ABC classification attributes of the current warehouse location, a transfer task is generated; Step S60: After the target storage location is located, a transfer task from the starting storage location to the target storage location is generated, and multiple tallying tasks are grouped into one tallying task group.

2. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: It also includes an exception handling mechanism. If a configuration error causes the result to not meet the expectations, recalculation can be manually triggered.

3. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: In step S10, the storage locations are set with ABC classification attributes according to the convenience of picking and the distance to the temporary storage area for outbound delivery; wherein the A-class attribute refers to the storage location that is most convenient for picking, the B-class attribute refers to the storage location that is generally convenient, and the remaining storage locations are of the C-class.

4. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: In step S20, the A-type attribute refers to the goods that are most frequently picked and shipped out of the warehouse, the B-type attribute refers to the goods that are generally frequently picked and shipped out of the warehouse, and the C-type attribute refers to the goods that are rarely picked and shipped out of the warehouse.

5. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: In step S30, according to the automatic execution cycle, select weekly, monthly or yearly automatic execution.

6. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 5 is characterized by: In conjunction with the automatic execution cycle, specify the days within the cycle for automatic execution.

7. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: The data dimensions in step S40 include the number of orders, order quantity, number of picking times, and number of pickings.

8. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1 is characterized by: The step S50 comprises: 1) Filtering rules for goods to be sorted; On the basis of the mismatch between the ABC classification of goods and the ABC classification of storage locations, the filtering conditions are superimposed, and the goods that meet this condition are operated to locate the new storage location. The filtering conditions are selected as storage location attributes or product attributes; 2) Filtering rules for the target location of the transfer; On the basis of searching for the corresponding storage locations of the goods in the ABC classification, add filtering conditions to limit the target storage location range of the goods; 3) Target location matching rules for transfer; Enable one or more rules for finding new storage locations and prioritize the multiple rules, including: a) Search for the same product and the same batch of warehouse locations. Search for warehouse locations with the same product and the same batch under the target warehouse location filtering rule. If no warehouse locations are found, execute the next rule. b) Search for the same product's stock location, and find the stock location with the same product under the target stock location filtering rule. If no stock location is found, execute the next rule; c) Search for empty storage locations and find the products under the target storage location filtering rules. If no products are found, execute the next rule; d) Find non-empty storage locations and find the goods that are mixed with other goods under the target storage location filtering rules; e) Target storage location priority: when multiple target storage locations are found, set the priority of the storage locations, sort them according to the storage area, aisle, layer, row, and column, and find the highest priority storage location.

9. The method for optimizing inventory storage by automatic ABC classification calculation according to claim 1, characterized in that: The generation rules in step S60 include: 1) The upper limit of the number of tasks, which limits the maximum number of warehouse transfer tasks in a task group; 2) The same starting location, when enabled, the tasks of the same starting location are put into the same task group; 3) The same starting storage area, when activated, the tasks in the same starting storage area are put into the same task group; 4) When the same target location is enabled, tasks at the same target location are placed in the same task group; 5) For the same target warehouse area, when enabled, tasks in the same target warehouse area are placed in the same task group.

10. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor executes the computer program to implement the steps of any one of the tally methods of claims 1-9.

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