Informatization management system of smart warehouse

Abstract

The invention discloses an informatization management system of a smart warehouse, relates to the technical field of warehouse management, and solves the technical problems that an abnormal replenishment strategy lacks dynamic adaptation to a cargo demand trend, and warehouse-out path planning does not comprehensively balance cargo storage time and distance cost, resulting in low warehouse-out efficiency. Through multi-dimensional comparison of storage orders and stock, order satisfaction is accurately judged, performance errors caused by detail mismatching are reduced, order judgment accuracy is improved, a cargo demand trend is identified based on historical data, a differential replenishment model of'periodic consumption + safe stock ''trend prediction + buffer coefficient' 'is adopted, and the order replenishment efficiency is improved. The replenishment accuracy is improved, the stockout rate is reduced, meanwhile, the stock overstock cost is reduced, a path is planned preferentially with the longest storage time as the principle, storage points are screened through quantitative weighted scoring of storage time + distance when the stock is insufficient, the first-in first-out rule and the distance cost are considered, and the warehouse-out time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to an information management system for a smart warehouse. Background Art

[0002] With the rapid development of the logistics industry and the explosive growth of e-commerce business, warehouses, as the core nodes of the supply chain, their management efficiency directly affects the operating costs and market response speed of enterprises.

[0003] According to the patent application with publication number CN118822418A, an information-based warehouse management system is disclosed, in which the warehouse information data management platform manages warehouse attribute information and warehouse area information; the organizational structure management platform records basic information within the enterprise and configures customer target needs through customer information; the order management platform collects warehouse data from each link; the goods management platform manages the goods barcode information and goods-specific storage location information of the goods; the business type management platform configures different business processes according to different business types, and manages the splitting and merging of orders; the rule management platform configures batch rules and shelving rules for goods grouping; the incoming warehouse management platform provides delivery appointment registration function, ASN receiving operation function, and receiving status registration function; the outgoing warehouse management platform provides receipt management.

[0004] However, in existing technologies, the matching analysis of orders and inventory relies only on a single dimension, without considering details such as the type, batch, and status of the goods. This can easily lead to inaccurate judgments on order satisfaction. At the same time, abnormal replenishment strategies lack dynamic adaptation to the demand trends of goods, and cannot accurately predict the replenishment quantity and timing based on historical data. The outbound route planning does not comprehensively balance the storage time and distance costs of goods. When inventory is insufficient, there is a lack of a scientific storage point screening mechanism, resulting in low outbound efficiency. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides an information management system for smart warehouses, which solves the problems of abnormal replenishment strategies lacking dynamic adaptation to cargo demand trends, and outbound route planning failing to comprehensively balance cargo storage time and distance costs, resulting in low outbound efficiency.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an information management system for a smart warehouse, comprising:

[0007] The storage order analysis unit is used to analyze the completion status of the storage order based on the storage order and existing goods information transmitted by the storage information collection unit, generate a normal or abnormal goods analysis signal, and transmit the two separately;

[0008] The warehouse abnormality analysis unit is used to process the abnormality analysis signals of goods, clarify the out-of-stock information, and combine historical data to determine whether the demand for the same type of goods is increasing or stable. Based on this, it generates replenishment information and transmits it to the intelligent management output unit;

[0009] The warehouse normal analysis unit is used to process the normal analysis signal of the goods, process the normal signal, check the remaining inventory after the order is completed, and compare it with the warning value. If it is lower than the warning value, the warehouse replenishment information is generated, otherwise a normal monitoring signal is generated;

[0010] The outbound management analysis unit is used to analyze the outbound shipment of the acquired warehousing orders, select pre-selected storage points for storing the same type of goods, and prioritize planning routes starting from the points with the longest storage time. If the total amount of goods on the route meets the order, outbound shipment information is directly generated. If not, the pre-selected indicators are calculated based on the straight-line distance between the storage point and the outbound port and the storage time. The outbound shipment information is generated based on the pre-selected indicators and transmitted to the intelligent management output unit.

[0011] As a further solution of the present invention, it also includes a storage information collection unit and an intelligent management information output unit;

[0012] The warehousing information collection unit is used to obtain warehousing orders and existing goods information, and transmit the two to the warehousing order analysis unit at the same time. The warehousing order includes the type and quantity of the ordered goods, and the existing goods information includes the type and quantity of the goods;

[0013] The intelligent management information output unit is used to display the generated warehouse replenishment information and outbound information to the corresponding management personnel.

[0014] As a further solution of the present invention, the specific manner in which the warehousing order analysis unit generates a normal or abnormal goods analysis signal is as follows:

[0015] The obtained warehousing order is compared with the existing goods information to determine whether the existing goods information meets the warehousing order. If so, a normal goods analysis signal is generated and transmitted to the warehousing normal analysis unit. Otherwise, an abnormal goods analysis signal is generated and transmitted to the warehousing abnormality analysis unit.

[0016] As a further solution of the present invention, the specific manner in which the storage abnormality analysis unit processes the cargo abnormality analysis signal is as follows:

[0017] Obtain the shortage information corresponding to the warehouse order, and the shortage information includes the shortage type and shortage quantity. At the same time, obtain historical data, obtain the goods type corresponding to the warehouse order and record it as the analyzed goods type, judge the change in the order goods quantity of the analyzed goods type based on the historical data, generate an increasing change or stable change, and analyze the two separately.

[0018] As a further solution of the present invention, a specific method for analyzing the increase change or stability is as follows:

[0019] For the stable and unchanged situation, take time T as the cycle, obtain its corresponding cycle consumption, and replenish at 1 / 2 cycle based on the cycle consumption, generate warehouse replenishment information, and transmit it to the intelligent management information output unit at the same time;

[0020] In the case of increasing changes, starting from the initial period of the change and until it returns to stability, the average of the demand increments in adjacent periods is calculated, and the average is added to the basic demand in the stable period to obtain the replenishment quantity. Similarly, replenishment is performed when the period is halfway through, and warehouse replenishment information is generated, which is then transmitted to the intelligent management information output unit.

[0021] As a further solution of the present invention, the specific manner in which the normal storage analysis unit processes the normal goods analysis signal is as follows:

[0022] Based on the warehouse order, the corresponding remaining warehouse goods are obtained and compared with the warning preset value. If the remaining warehouse goods are greater than the warning preset value, a normal monitoring signal is generated. Conversely, if the remaining warehouse goods are less than the warning preset value, a replenishment analysis signal is generated. The replenishment analysis signal is further processed to generate warehouse replenishment information and transmitted to the intelligent management information output unit.

[0023] As a further solution of the present invention, the specific manner in which the delivery management analysis unit performs delivery analysis on the warehousing order is:

[0024] Get all storage points and label them as n, where n = 1, 2, ..., m, where m is the number of storage points. Filter the storage points n according to the type of goods in the order to obtain pre-selected storage points. Extract the quantity and storage time of the pre-selected points, sort them from longest to shortest by storage time, and generate an outbound route starting from the pre-selected point with the longest storage time. Count the total storage quantity of all pre-selected points on the route and compare it with the order demand quantity.

[0025] As a further solution of the present invention, the specific method of comparing the quantity with the order requirement is:

[0026] If the total storage quantity is greater than the order quantity, the generated outbound route is used as the standard to generate outbound information and transmit it to the intelligent management information output unit at the same time;

[0027] If the total storage quantity is less than the order quantity, all pre-selected storage points are obtained and their corresponding two-dimensional coordinates are obtained. Then, the straight-line distance between the pre-selected storage points and the delivery port is calculated respectively. The straight-line distance and storage time are quantified to obtain the corresponding quantitative index. Then, the obtained quantitative index is weighted and summed to obtain the selection index of the pre-selected storage points. The pre-selected storage points are sorted from largest to smallest according to the selection index.

[0028] Taking the order quantity as the standard, the corresponding number of pre-selected storage points are selected in order from large to small according to the selection indicators. At the same time, the corresponding outbound routes are generated, the outbound information is generated, and it is transmitted to the intelligent management information output unit.

[0029] The present invention provides an information management system for smart warehouses. Compared with the existing technology, it has the following advantages:

[0030] The present invention compares warehouse orders and inventory in multiple dimensions to accurately judge order satisfaction, reduce fulfillment errors caused by detail mismatch, improve order judgment accuracy, identify goods demand trends based on historical data, and adopt differentiated replenishment models of "cycle consumption + safety stock" and "trend forecast + buffer coefficient" to improve replenishment accuracy and reduce out-of-stock rate, while reducing inventory backlog costs. It prioritizes planning routes based on the principle of "longest storage time". When inventory is insufficient, storage points are screened through quantitative weighted scoring of "storage time + distance", taking into account the first-in-first-out rule and distance cost, and shortening the delivery time. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0033] Example 1

[0034] See also Figure 1 The present application provides an information management system for a smart warehouse, including: a warehouse information collection unit, a warehouse order analysis unit, a warehouse normal analysis unit, a warehouse abnormality analysis unit, a warehouse delivery management analysis unit and an intelligent management information output unit, and combined with Figure 1 It can be known that the information between the above functional units is transmitted in one direction.

[0035] The warehouse information collection unit is used to obtain the existing goods information of the warehouse, and the existing goods information includes the type and quantity of goods. At the same time, it obtains the warehouse order and transmits the two to the warehouse order analysis unit. The warehouse order specifically includes the type and quantity of ordered goods.

[0036] The storage order analysis unit is used to compare the obtained storage order with the existing goods information to determine whether the existing goods information meets the storage order. If so, a normal goods analysis signal is generated and transmitted to the normal storage analysis unit. Otherwise, if not, a abnormal goods analysis signal is generated and transmitted to the abnormal storage analysis unit.

[0037] The storage anomaly analysis unit is used to analyze the acquired goods anomaly signals, calculate the shortage information corresponding to the storage order, and the shortage information includes the shortage type and shortage quantity. At the same time, historical data is obtained, the goods type corresponding to the storage order is obtained and recorded as the analyzed goods type, and the change in the order goods quantity of the analyzed goods type is judged based on the historical data, and an increase change or stability is generated. Here, stability is represented as the difference in the corresponding order goods quantity being within a preset range, and the specific value of the preset range is set by the operator.

[0038] For the stable and unchanged situation, take time T as the cycle, obtain its corresponding cycle consumption, and replenish at 1 / 2 cycle based on the cycle consumption, generate warehouse replenishment information, and transmit it to the intelligent management information output unit at the same time;

[0039] For example, determine the cycle T (based on historical turnover cycles, such as T = 7 days for daily necessities and T = 2 days for fresh produce). Calculate the cycle consumption by taking the average demand quantity over the past three cycles (e.g., weekly demand of 100, 105, and 95 over the past three weeks, averaging 100). Set the safety stock: To cope with unexpected fluctuations, safety stock = cycle consumption × 1.2 (adjustable coefficient).

[0040] Replenishment point: Replenishment is triggered at 1 / 2 of the cycle T (e.g., day 3.5 if T=7 days);

[0041] Replenishment quantity = cycle consumption + (safety stock - current remaining inventory).

[0042] For the increasing change situation, take time T as the period, and take the time period corresponding to the increasing change as the starting point and the stable and unchanged period as the end point to obtain the corresponding time period, and at the same time obtain the order quantity of adjacent periods, then calculate the numerical difference, record it as the period change value, and calculate the average of all period changes. For example, if there are five groups of time periods, then the period change values of the five groups of adjacent periods are calculated accordingly, and the average is further summed up and recorded as the period change average. At the same time, the calculated average is used as the standard and summed with the basic order quantity to obtain the replenishment quantity. The basic order quantity here specifically refers to the average quantity of order goods corresponding to the stable and unchanged situation, which is used as the standard to be recorded as the basic order quantity. At the same time, take 1 / 2 period as the replenishment point to generate warehouse replenishment information, and then transmit it to the intelligent management information output unit.

[0043] For example, determine the analysis period: from the "starting point of growth" (such as 50 demand in week 1) to the "most recent cycle" (such as 130 demand in week 5);

[0044] Calculate the period change value: the difference in demand between adjacent periods (e.g., week 2-1: 70-50=20; week 3-2: 90-70=20; week 4-3: 110-90=20; week 5-4: 130-110=20);

[0045] Calculate the mean of periodic changes: (20+20+20+20) ÷ 4 = 20;

[0046] Determine the base volume: take the average value of the stable period before the growth (e.g., if the demand is 50 in the three weeks before the growth, the base volume = 50);

[0047] Forecast demand for the next cycle: base volume + (average of periodic changes × number of forecast periods). For example, forecast demand for the sixth week = 50 + (20 × 1) = 70 (the actual demand in the sixth week may reach 150, leaving a buffer).

[0048] Replenishment point: 1 / 2 of the cycle T;

[0049] Replenishment quantity = predicted demand for the next cycle × 1.5 (growth buffer coefficient) - current remaining inventory.

[0050] An intelligent management information output unit is used to perform corresponding replenishment processing based on the acquired warehouse replenishment information.

[0051] Example 2

[0052] As the second embodiment of the present invention, it is implemented on the basis of the first embodiment, and differs from the first embodiment in the following aspects:

[0053] The normal storage analysis unit is used to process the obtained normal analysis signal of goods, obtain the corresponding remaining storage goods based on the storage order, and compare it with the warning preset value. The specific value of the warning preset value is set by the operator. If the remaining storage goods is greater than the warning preset value, a normal monitoring signal is generated. Conversely, if the remaining storage goods is less than the warning preset value, a replenishment analysis signal is generated. The replenishment analysis signal is further processed to generate storage replenishment information and transmit it to the intelligent management information output unit. The method of generating storage replenishment information here is the same as the processing method of the storage abnormality analysis unit.

[0054] Based on the comparison results of the remaining inventory and the classification threshold, differentiated processing signals are generated to avoid "excessive warnings interfering with operations" or "late warnings leading to stockouts":

[0055] If the remaining inventory is greater than or equal to the safety value: a "normal monitoring signal" is generated, no replenishment is required, only the current inventory status is recorded, and the next round of periodic monitoring is entered (the period can be set, such as monitoring once a day). For example, the safety value of a certain mineral water is 200 bottles, and the current remaining inventory is 250 bottles (≥200). The system generates a "normal monitoring signal" and monitors again the next day.

[0056] If the warning value is less than or equal to the remaining inventory and less than the safety value, a "replenishment analysis signal" is generated, and the regular replenishment process is initiated. The reasonable replenishment quantity is calculated based on historical data to ensure that the inventory returns to above the safety value after replenishment. The replenishment quantity = safety value - remaining inventory + (average daily shipment volume in the past week × replenishment cycle)

[0057] (Note: "Replenishment cycle" refers to the number of days from placing an order to the time the goods arrive in the warehouse. For example, the replenishment cycle for local suppliers is 2 days).

[0058] For example, the safety value of a laundry detergent is 100 bottles, the warning value is 60 bottles, and the current remaining stock is 80 bottles (between the warning value and the safety value).

[0059] In the past week, an average of 10 bottles were shipped out per day, and the replenishment cycle is 2 days. The replenishment quantity = 100-80+ (10×2) = 40 bottles.

[0060] Generate a "regular replenishment analysis signal" and the expected inventory after replenishment is 80+40=120 bottles (≥safety value 100).

[0061] The outbound management analysis unit is used to perform outbound analysis based on the obtained storage order, obtain all storage points and label them as n, and n=1, 2, ..., m, where m represents the number of storage points, and at the same time, screen the storage points n based on the type of order goods corresponding to the storage order to obtain pre-selected storage points, and the pre-selected storage points here indicate that the corresponding storage type is the same as the order goods type, then obtain the storage quantity and storage time corresponding to the pre-selected storage points, and sort them from largest to smallest according to the storage time, and sorting from largest to smallest here means sorting them from longest to shortest according to the storage time, obtain the outbound point and mark it as the outbound destination, take the pre-selected storage point corresponding to the maximum storage time as the starting point, generate the outbound route, and obtain all pre-selected storage points on the outbound route, and at the same time obtain the total storage quantity corresponding to all pre-selected storage points, and then compare it with the order goods quantity corresponding to the storage order;

[0062] If the total storage quantity is greater than the order quantity, the generated outbound route is used as the standard to generate outbound information and transmit it to the intelligent management information output unit at the same time;

[0063] If the total storage quantity is less than the order quantity, all pre-selected storage points are obtained and their corresponding two-dimensional coordinates are obtained. Here, a plane rectangular coordinate system is established with the delivery port as the origin. Then, the straight-line distance between the pre-selected storage points and the delivery port is calculated respectively, and the pre-selected storage points are obtained after being sorted by storage time. At the same time, the straight-line distance and storage time are quantified to obtain the corresponding quantitative index. Then, the obtained quantitative index is weighted and summed to obtain the selection index of the pre-selected storage points, and they are sorted from large to small according to the selection index.

[0064] The linear distance is quantified as shown in the following linear distance score table, and the score decreases by 1 for every 1 meter increase in the table;

[0065] Table 1:

[0066]

[0067] The storage time is quantified as shown in the following storage time scoring table, and the score increases by 1.5 for every additional day in the table;

[0068] Table 2:

[0069]

[0070] According to the obtained straight-line distance index and storage time index, combined with the corresponding formula, the selected index = straight-line distance index × weight one + storage time index × weight two, and the value of weight two is greater than the value of weight one.

[0071] Taking the order quantity as the standard, the corresponding number of pre-selected storage points are selected in order from large to small according to the selection indicators. At the same time, the corresponding outbound routes are generated, the outbound information is generated, and it is transmitted to the intelligent management information output unit.

[0072] An intelligent management information output unit is used to process the warehouse orders according to the obtained warehouse information.

[0073] Example 3

[0074] As the third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0075] Some of the data in the above formulas are calculated based on their numerical values and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0076] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An information management system for a smart warehouse, characterized by: include: The storage order analysis unit is used to analyze the completion status of the storage order based on the storage order and existing goods information transmitted by the storage information collection unit, generate a normal or abnormal goods analysis signal, and transmit the two separately; The warehouse abnormality analysis unit is used to process the abnormality analysis signals of goods, clarify the out-of-stock information, and combine historical data to determine whether the demand for the same type of goods is increasing or stable. Based on this, it generates replenishment information and transmits it to the intelligent management output unit; The warehouse normal analysis unit is used to process the normal analysis signal of the goods, process the normal signal, check the remaining inventory after the order is completed, and compare it with the warning value. If it is lower than the warning value, the warehouse replenishment information is generated, otherwise a normal monitoring signal is generated; The outbound management analysis unit is used to analyze the outbound shipment of the acquired warehousing orders, select pre-selected storage points for storing the same type of goods, and prioritize planning routes starting from the points with the longest storage time. If the total amount of goods on the route meets the order, outbound shipment information is directly generated. If not, the pre-selected indicators are calculated based on the straight-line distance between the storage point and the outbound port and the storage time. The outbound shipment information is generated based on the pre-selected indicators and transmitted to the intelligent management output unit.

2. The information management system for a smart warehouse according to claim 1 is characterized in that: It also includes a storage information collection unit and an intelligent management information output unit; The warehousing information collection unit is used to obtain warehousing orders and existing goods information, and transmit the two to the warehousing order analysis unit at the same time. The warehousing order includes the type and quantity of the ordered goods, and the existing goods information includes the type and quantity of the goods; The intelligent management information output unit is used to display the generated warehouse replenishment information and outbound information to the corresponding management personnel.

3. The information management system for a smart warehouse according to claim 1 is characterized in that: The specific method for the warehousing order analysis unit to generate a normal or abnormal goods analysis signal is: The obtained warehousing order is compared with the existing goods information to determine whether the existing goods information meets the warehousing order. If so, a normal goods analysis signal is generated and transmitted to the warehousing normal analysis unit. Otherwise, an abnormal goods analysis signal is generated and transmitted to the warehousing abnormality analysis unit.

4. The information management system for a smart warehouse according to claim 1 is characterized in that: The specific method of processing the cargo abnormality analysis signal by the storage abnormality analysis unit is as follows: Obtain the shortage information corresponding to the warehouse order, and the shortage information includes the shortage type and shortage quantity. At the same time, obtain historical data, obtain the goods type corresponding to the warehouse order and record it as the analyzed goods type, judge the change in the order goods quantity of the analyzed goods type based on the historical data, generate an increasing change or stable change, and analyze the two separately.

5. The information management system for a smart warehouse according to claim 4 is characterized in that: The specific methods for analyzing increasing changes or stable changes are: For the stable and unchanged situation, take time T as the cycle, obtain its corresponding cycle consumption, and replenish at 1 / 2 cycle based on the cycle consumption, generate warehouse replenishment information, and transmit it to the intelligent management information output unit at the same time; In the case of increasing changes, starting from the initial period of the change and until it returns to stability, the average of the demand increments in adjacent periods is calculated, and the average is added to the basic demand in the stable period to obtain the replenishment quantity. Similarly, replenishment is performed when the period is halfway through, and warehouse replenishment information is generated, which is then transmitted to the intelligent management information output unit.

6. The information management system for a smart warehouse according to claim 1 is characterized in that: The specific method of processing the normal analysis signal of goods by the storage normal analysis unit is as follows: Based on the storage order, the corresponding remaining storage goods are obtained and compared with the warning preset value. If the remaining storage goods are greater than the warning preset value, a normal monitoring signal is generated. Conversely, if the remaining storage goods are less than the warning preset value, a replenishment analysis signal is generated. The replenishment analysis signal is further processed to generate storage replenishment information and transmitted to the intelligent management information output unit.

7. The information management system for a smart warehouse according to claim 1 is characterized in that: The specific method of the outbound management analysis unit performing outbound analysis on the warehousing order is as follows: Get all storage points and label them as n, where n = 1, 2, ..., m, where m is the number of storage points. Filter the storage points n according to the type of goods in the order to obtain pre-selected storage points. Extract the quantity and storage time of the pre-selected points, sort them from longest to shortest by storage time, and generate an outbound route starting from the pre-selected point with the longest storage time. Count the total storage quantity of all pre-selected points on the route and compare it with the order demand quantity.

8. The information management system for a smart warehouse according to claim 7 is characterized in that: The specific method of comparing with the order quantity is as follows: If the total storage quantity is greater than the order quantity, the generated outbound route is used as the standard to generate outbound information and transmit it to the intelligent management information output unit at the same time; If the total storage quantity is less than the order quantity, all pre-selected storage points are obtained and their corresponding two-dimensional coordinates are obtained. Then, the straight-line distance between the pre-selected storage points and the delivery port is calculated respectively. The straight-line distance and storage time are quantified to obtain the corresponding quantitative index. Then, the obtained quantitative index is weighted and summed to obtain the selection index of the pre-selected storage points. The pre-selected storage points are sorted from largest to smallest according to the selection index. Taking the order quantity as the standard, the corresponding number of pre-selected storage points are selected in order from large to small according to the selection indicators. At the same time, the corresponding outbound routes are generated, the outbound information is generated, and it is transmitted to the intelligent management information output unit.

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