Modular stereoscopic warehousing system and adaptive sorting method for heterogeneous goods

Abstract

The application discloses a modular three-dimensional storage system and adaptive sorting method for heterogeneous goods, relates to the technical field of three-dimensional storage, and comprises a storage module, an intelligent optimization module and an intelligent control module.The storage module comprises an adjustable goods shelf and a special-shaped goods fixing frame, and is used for classified storage of heterogeneous goods.The intelligent optimization module is used for identifying the turnover frequency of goods according to information of the goods read by an RFID label, and dividing a warehouse into different zones according to Manhattan distances of the warehouse from an entrance and an exit.The intelligent control module is used for adjusting the layer height data of the adjustable goods shelf.Through storage of high-frequency goods in a high-frequency zone and combination of the Manhattan distance zoning principle, the length of a goods picking path is significantly shortened, the order processing efficiency is improved, and the order processing capacity during a peak period is greatly improved.The dynamic zoning strategy optimizes the goods storage layout, so that high-turnover goods are preferentially stored in a core area, the occupation of storage space by slow-moving goods is reduced, and the inventory turnover efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of stereoscopic storage, and more particularly to a modular stereoscopic storage system for heterogeneous goods and a self-adaptive sorting method. BACKGROUND

[0002] Traditional storage systems use fixed layer height shelves and do not consider the dynamic size difference of high turnover goods, lack the ability to dynamically adjust the layer height according to the size of the goods, and cannot adapt to the real-time storage needs of high-frequency turnover goods. Existing storage relies on historical data to divide cold high-frequency areas and cannot capture the periodic fluctuations in the turnover frequency of goods in real time.

[0003] During e-commerce promotions or holiday peak periods, the turnover mode of goods changes every hour. The existing system lacks real-time data analysis capabilities, resulting in an increase in the mismatch rate of high-frequency areas. The existing technology only analyzes the turnover rate of a single good and does not identify the relevance of combined orders. Low-frequency but highly correlated goods are assigned to low-frequency areas due to low independent turnover rates, resulting in decreased efficiency in picking combined orders. SUMMARY

[0004] To solve the above problems, the present application provides a modular stereoscopic storage system for heterogeneous goods and a self-adaptive sorting method.

[0005] The present application provides a modular stereoscopic storage system for heterogeneous goods, which comprises a storage module, the storage module comprising adjustable shelves and special-shaped goods fixing frames for classified storage of heterogeneous goods.

[0006] The goods are packaged in boxes and placed on the adjustable shelves and special-shaped goods fixing frames. The boxes are integrated with RFID tags, and the information of the goods can be read according to the RFID tags.

[0007] An intelligent optimization module is used to identify the turnover frequency of the goods according to the information of the goods read by the RFID tags, and to divide the warehouse into zones according to the Manhattan distance from the entrance and exit. Different frequency goods are classified and stored in different zones according to the turnover frequency.

[0008] An intelligent control module is used to adjust the layer height data of the adjustable shelves in the zone closest to the entrance and exit of the warehouse according to the zoning results of the intelligent optimization module.

[0009] Preferably, the specific working steps of the intelligent optimization module are as follows:

[0010] According to the RFID tags integrated on the boxes, the in-out warehouse record domain order correlation data of the goods is obtained.

[0011] A time period T is pre-defined, and the formula is applied every time period. The real-time turnover frequency f of the goods is calculated and obtained. i ;

[0012] Where N i m represents the number of times product i was shipped out within the previous time period T. i Let τ be the current inventory level of item i, and τ be the weighted comprehensive coefficient of the orders associated with item i.

[0013] The warehouse is divided into three storage zones based on Manhattan distance. A distance range threshold is set in advance. The area within the distance range from the entrance and exit is marked as the medium frequency zone, the area within the distance range from the entrance and exit is marked as the high frequency zone, and the area within the distance range from the entrance and exit is marked as the low frequency zone.

[0014] Pre-set a real-time inventory turnover frequency f i The threshold range will determine the real-time turnover frequency f of goods. i Goods exceeding this threshold range are stored in the high-frequency zone, goods within this threshold range are stored in the mid-frequency zone, and goods below this threshold range are stored in the low-frequency zone.

[0015] Preferably, the specific working steps of the intelligent optimization module further include the following:

[0016] Beforehand, sort the quantities of other goods that were shipped out together with this item in the same order in the previous period of the current time period, and mark the z items with the highest quantities as related goods;

[0017] According to the formula The optimized inventory turnover frequency fx was calculated. i , where f total f represents the total turnover frequency of all goods in the warehouse during the previous period. k Let be the real-time turnover frequency of the k-th associated product, where sz is the weight coefficient of the associated product;

[0018] Based on the optimized inventory turnover frequency fx i The goods were then categorized and stored.

[0019] Preferably, the intelligent optimization module further includes a migration unit, which generates migration tasks based on changes in the real-time turnover frequency of goods, and moves the goods to other zones. Specific steps further include the following:

[0020] A threshold Δf for the change in turnover frequency is set in advance. th If, within two adjacent periods T, the optimized inventory turnover frequency fx of the goods... iThe change value is greater than the threshold Δf th If it is a good item, it is marked as a good item to be migrated, and its optimized turnover frequency fx is used to determine the migration process. i Move it to the corresponding partition;

[0021] Before handling, according to the formula The priority P of the goods to be migrated is calculated and obtained. i , where f max D represents the highest turnover rate in the warehouse during the previous period. current This is the distance required to move the goods to the corresponding zone.

[0022] Pre-set a priority threshold range.

[0023] If the priority P of the goods to be moved i If the value exceeds this threshold, the stacker crane will immediately perform the handling task. If the priority P of the goods to be moved is... i If the goods are within this threshold range, the transport task will be scheduled and executed by the AGV. If the priority P of the goods to be moved is... i If the value is below this threshold, the handling task will be performed when neither the stacker crane nor the AGV has a work target.

[0024] For goods of the same category awaiting relocation, priority P shall be used. i The sizes are prioritized and then moved.

[0025] Preferably, the specific working steps of the migration unit further include the following:

[0026] During the process of moving goods to other zones, the remaining effective time of the goods, i.e., the remaining shelf life T, is obtained based on the RFID tags integrated on the cargo boxes. remain ;

[0027] According to the formula The priority G of the goods to be migrated is calculated and obtained. i ;

[0028] The priority G of the goods to be migrated is obtained based on the calculation. i To carry out migration tasks.

[0029] Preferably, the specific working steps of the migration unit further include the following:

[0030] The priority G of the goods to be migrated is obtained based on calculations. i During the execution of the migration mission;

[0031] The warehouse is divided into three storage zones based on Manhattan distance. Each storage zone includes a cold storage zone and a normal and medium frequency zone. The cold storage zone is marked as an isolation zone. The cold storage zone path penalty is added to the AGV path that crosses the isolation zone.

[0032] According to the formula Gx i =G i *C base *(1+0.5*|T in -T out |), calculate and obtain the total priority Gx when simultaneously carrying both imminent goods and goods that need to pass through the cold storage area. i According to the total priority Gx when carrying both pre-season goods and goods that need to pass through cold storage areas. i Sort the movement of goods;

[0033] Where C base Based on the path cost, |T in -T out | represents the absolute value of the temperature difference between the outside and inside of the cold storage area;

[0034] When the remaining shelf life is T remain If the time is less than 2 hours, skip the cold storage area path penalty calculation and directly select the shortest path.

[0035] Preferably, the specific working steps of the intelligent control module are as follows:

[0036] The adjustable shelf is integrated with a laser rangefinder, which is used to obtain the length, width and height data of the goods. The goods are packaged in a carton, which is integrated with an RFID tag. The weight data m is obtained by reading the RFID tag.

[0037] Then, for each time period, according to the formula... The target shelf spacing H of the adjustable shelf is calculated. adj Where γ is the compensation coefficient, and H0 is the shelf height of the adjustable shelving in the previous time period. This is the stress margin ratio;

[0038] Based on the obtained target shelf spacing H, adjust the shelf spacing... adj This allows for the adjustment of the shelf height.

[0039] Preferably, the specific working steps of the compensation coefficient γ are as follows:

[0040] The volume v of the goods is obtained by multiplying the length, width, and height of the goods.

[0041] According to the formula

[0042] The compensation coefficient γ is calculated and obtained.

[0043] Preferably, the specific steps of the intelligent control module further comprise the following:

[0044] According to the formula The space utilization rate of the adjustable shelf is calculated, wherein l j w j h j is the length, width and height of the jth goods;

[0045] L is the length of the adjustable shelf, and W is the width of the adjustable shelf;

[0046] If θ is less than 0.7, an adjustment suggestion is triggered, and the height H of the adjustable shelf is adjusted i until θ is greater than or equal to 0.7.

[0047] The present application also proposes a modular three-dimensional warehouse adaptive sorting method for heterogeneous goods, comprising the following steps:

[0048] Step 1: Through the modular design of the adjustable shelf and the special-shaped goods fixing frame, the physical classification storage of different forms of goods is realized, the standardized carton packaging integrated with RFID tags is adopted, and the core information such as real-time recording of goods weight, warehouse in-out record, order association data and shelf life is recorded;

[0049] Step 2: Based on the RFID tag data, Manhattan distance algorithm is used to dynamically partition the warehouse, and high-frequency turnover goods are preferentially allocated to the area near the entrance and exit, and medium and low-frequency goods are automatically adjusted in storage location according to the logistics peak and valley period;

[0050] Step 3: The intelligent control module dynamically adjusts the height parameter of the adjustable shelf according to the limited space constraint of the entrance and exit area, analyzes the safety threshold of the current goods stacking density through the pressure sensor and the visual recognition system, automatically reconstructs the shelf height configuration according to the change of turnover frequency, and ensures the stability in the adjustment process in combination with the special-shaped shelf characteristics such as shockproof base.

[0051] Beneficial effects: By storing high-frequency goods in the high-frequency area and combining the Manhattan distance partition principle, the length of the picking path is significantly shortened, the order processing efficiency is improved, and the order processing capacity during peak period is greatly improved; the dynamic partition strategy optimizes the storage layout of goods, so that high-turnover goods are preferentially stored in the core area, reducing the occupation of warehouse space by unsalable goods, thereby improving the inventory turnover efficiency;

[0052] By dynamically superimposing the turnover contribution value of the goods, the storage strategy of "driving low frequency with high frequency" is realized, and the core pain points of the response fragmentation of combined orders and passive lag of long-tail demand in traditional technology are solved. Through testing, the mechanism makes the overall delivery frequency of the warehouse increase, especially for scenes with large number of SKUs and complex order combinations, such as new retail and pharmaceutical warehousing, which has optimization value. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 is a flowchart of the system of the present application. DETAILED DESCRIPTION

[0054] As Figure 1 shown: a modular three-dimensional warehousing system for heterogeneous goods, comprising a storage module, the storage module comprising adjustable shelves and special-shaped goods fixing frames, for classified storage of heterogeneous goods; it should be noted that the adjustable shelves can support dynamic adjustment of layer height, and the special-shaped goods fixing frames have a clamping groove + magnetic attraction device designed for cylindrical articles to prevent rolling, and an anti-vibration base added to the heavy part shelves;

[0055] The goods are packaged in boxes and placed on the adjustable shelves and special-shaped goods fixing frames, and the boxes are integrated with RFID tags, which can read the information of the goods according to the RFID tags; it should be noted that the information specifically includes the weight of the goods, the in-out warehouse record field order association data and the shelf life of the goods;

[0056] An intelligent optimization module is used to identify the turnover frequency of the goods according to the information of the goods read by the RFID tags, and to divide the warehouse into different zones according to the Manhattan distance from the entrance and exit, and to classify and store goods of different frequencies in different zones according to the turnover frequency.

[0057] It should be noted that in a large logistics warehouse, because there are many types of goods, goods with high turnover frequency need to be placed on adjustable shelves near the warehouse entrance and exit, but the existing placement method is relatively fixed, and with the development speed of logistics and express delivery, the turnover frequency of goods will change at different times every day, so the placement of goods needs to be optimized in real time;

[0058] The step that takes the most time to adjust the goods from the warehouse is to carry and package them in the warehouse, and in this way, the search and waiting time for carrying the goods can be greatly reduced;

[0059] The intelligent control module is used for adjusting the layer height data of the adjustable shelf closest to the warehouse entrance and exit according to the zoning result of the intelligent optimization module. It should be noted that the layer height of the adjustable shelf is adjusted to increase the space utilization rate. Normally, the goods in the shelf are classified and placed according to the size, and the layer height does not need to be adjusted. However, in a large logistics warehouse, because the turnover frequency of each type of goods is different, the goods with high turnover frequency need to be placed on the adjustable shelf closest to the warehouse entrance and exit. The size and height of such goods are different, so the layer height of the adjustable shelf closest to the warehouse entrance and exit needs to be adjusted to store more goods with high turnover frequency, thereby improving the space utilization rate.

[0060] On the basis of the intelligent optimization module, the goods with the highest turnover frequency have been placed on the adjustable shelf closest to the warehouse entrance and exit. However, because the size of the area closest to the warehouse entrance and exit is limited, the layer height of the adjustable shelf closest to the warehouse entrance and exit is adjusted to maximize the utilization of the adjustable shelf closest to the warehouse entrance and exit.

[0061] As an optional embodiment, the specific working steps of the intelligent optimization module are as follows:

[0062] According to the RFID tag integrated on the goods box, the warehouse in and out record field order association data of the goods is obtained.

[0063] A time period T is set in advance, and every time period is calculated according to the formula The real-time turnover frequency f of the goods is obtained i It should be noted that the time period T is obtained in advance, and the unit is hour. In this embodiment, T is one day, that is, 24 hours.

[0064] Wherein N i is the number of times of taking out the goods i in the last time period T, m i is the current inventory of the goods i, and τ is the weight comprehensive coefficient of the order associated with the goods i. It should be noted that the weight comprehensive coefficient of the order associated with the goods i is obtained by obtaining all the associated orders of the goods i in the last time period T. The associated order j refers to the order that has a combined taking-out relationship with the current goods i, which is specifically defined as:

[0065] The order composed of other goods that are taken out together with the goods i in the same order, for example: a take-out order contains a hamburger (goods A) and a coke (goods B), and the order j is an associated order for A and B

[0066] All related orders with a specified outbound time shorter than the average outbound time are marked as urgent orders, and the remaining orders are marked as ordinary orders. The weight coefficient for urgent orders is 1.5, and the weight coefficient for ordinary orders is 1. The weight coefficients of all related orders are summed to obtain the comprehensive weight coefficient τ of related orders for product i.

[0067] The warehouse is divided into three storage zones based on Manhattan distance. A distance range threshold is preset, and the area within the distance range from the entrance and exit is marked as the mid-frequency zone, the area within the distance range from the entrance and exit is marked as the high-frequency zone, and the area within the distance range from the entrance and exit is marked as the low-frequency zone. It should be noted that the distance range threshold is set according to the size of the warehouse. In this embodiment, the distance range threshold is greater than 10m and less than 25m.

[0068] Pre-set a real-time inventory turnover frequency f i The threshold range will determine the real-time turnover frequency f of goods. i Goods exceeding this threshold range are stored in the high-frequency zone, goods within this threshold range are stored in the mid-frequency zone, and goods below this threshold range are stored in the low-frequency zone.

[0069] It should be noted that by storing high-frequency goods in high-frequency zones and combining them with the Manhattan distance zoning principle, the picking path length is significantly shortened, order processing efficiency is improved, and the order processing capacity during peak periods is greatly enhanced. The dynamic zoning strategy optimizes the goods storage layout, so that high-turnover goods are prioritized for storage in core areas, reducing the space occupied by slow-moving goods, thereby improving inventory turnover efficiency.

[0070] The emergency order processing mechanism based on weighted coefficients achieves rapid response through priority determination and storage location optimization, effectively shortening the fulfillment cycle. Combined with RFID automated collection and zoning strategies, it reduces reliance on manual inventory and energy consumption from ineffective handling, achieving dual optimization of labor and energy costs. It demonstrates significant advantages in high-frequency inbound and outbound scenarios such as e-commerce warehousing and cold chain logistics.

[0071] As an optional embodiment, the specific working steps of the intelligent optimization module further include the following:

[0072] Beforehand, sort the quantities of other goods that were shipped out together with this item in the same order in the previous period of the current time period, and mark the z items with the highest quantities as related goods;

[0073] According to the formula The optimized inventory turnover frequency fx was calculated. i , where f total f represents the total turnover frequency of all goods in the warehouse during the previous period. kReal-time turnover frequency of the kth associated product, wherein sz is the weight coefficient of the associated product;

[0074] It should be noted that the traditional warehouse optimization only calculates the turnover rate of a single product, ignoring the order combination association, for example, power bank (low frequency) and mineral water (high frequency) often appear in the same take-out order, but the traditional scheme will store the power bank in the low frequency area, causing the picker to frequently go back and forth between the cold high frequency area, resulting in path waste;

[0075] Low-frequency associated products cannot trigger storage strategy adjustment in the prior art due to the lack of independent turnover data. For example, in an e-commerce warehouse, mobile phone cases (low frequency) and mobile phones (high frequency) are stored separately for a long time due to lack of association analysis, resulting in an increase in manual replenishment rate of mobile phone orders;

[0076] It should be noted that the specific value method of the weight coefficient of the associated product is that if the turnover frequency of the kth associated product is greater than the average turnover frequency of all products in the warehouse, 1 is taken, otherwise 0 is taken, and the values of z associated products are superimposed to obtain the weight coefficient sz of the associated product;

[0077] According to the optimized product turnover frequency fx of the product i , the product is classified and stored. It should be noted that by dynamically identifying associated products (such as instant noodles and ham sausage combination) commonly used in the same order, low turnover but strongly associated products (such as ham sausage) and high turnover products (instant noodles) are intelligently bound, so that even if the product itself has a low turnover rate, its storage location will be adjusted to the high frequency area due to the high frequency demand of the associated product, thereby shortening the picking path of the combined order;

[0078] The traditional scheme only relies on the historical data of the product itself, resulting in long-term retention of low-frequency but strongly associated products (such as holiday gift box accessories) in the low-frequency area. The present scheme dynamically superimposes the turnover rate of the low-frequency product on the contribution value of the high-association product by using the weight coefficient of the associated product (such as the weight of the gift box main product = 1), thereby avoiding the delay in picking caused by the remote storage location;

[0079] The associated product clustering analysis can identify potential combination demand (such as midnight instant noodles and ham sausage) in advance, and realize "one picking covering multiple orders" through adjacent storage in the high-frequency area.

[0080] As an optional embodiment, the intelligent optimization module further includes a migration unit, which generates a migration task to move the product to other partitions according to the change of the real-time turnover frequency of the product, and the specific steps further include the following:

[0081] A threshold value Δf of the change of the turnover frequency is set in advance th If the change value of the optimized product turnover frequency fx of the product i is greater than the threshold value Δf in the adjacent two periods Tth , then it is marked as a migration goods, according to its optimized goods turnover frequency fx i , is transported into the corresponding partition;

[0082] Before transportation, according to the formula , the priority P of the migration goods is calculated i , where f max is the highest turnover frequency in the warehouse in the last cycle, D current is the distance required for the goods to be transported into the corresponding partition;

[0083] A priority threshold range is set in advance. It should be noted that in this embodiment, the threshold range can be 0.5 to 0.8;

[0084] If the priority P of the migration goods i is greater than the threshold range, the task of transportation is immediately executed by the stacker, if the priority P of the migration goods i is within the threshold range, the task of transportation is executed by AGV scheduling, if the priority P of the migration goods i is less than the threshold range, the task of transportation is executed when neither the stacker nor the AGV has a work target;

[0085] For the same classification of migration goods, the priority P i is sorted according to the size of the priority for transportation.

[0086] It should be noted that the dynamic threshold monitoring and priority calculation mechanism based on real-time turnover frequency can accurately identify changes in goods liquidity (such as a sudden increase in turnover rate of midnight food), and generate differentiated migration strategies according to the priority formula (combined with turnover frequency change, transportation distance and equipment efficiency). For high-priority tasks (such as above the threshold), the stacker immediately executes emergency goods migration to ensure that high-frequency turnover goods are quickly adjusted to high-frequency areas, shortening the picking path; medium-priority tasks (within the threshold range) are dynamically scheduled by AGV to balance equipment load and response speed, reducing cross-zone transportation energy consumption; low-priority tasks are intelligently executed during equipment idle periods to avoid resource waste.

[0087] As an optional embodiment, the specific working steps of the migration unit further include the following:

[0088] In the process of moving the goods into other partitions, according to the RFID tag integrated on the goods box, the remaining valid time of the goods, i.e. the shelf life remaining time T remain is obtained.

[0089] According to the formula , the priority G of the migration goods is calculatedi ;

[0090] The priority G of the goods to be migrated is obtained according to calculation i The migration task is executed. It should be noted that when the goods are close to expiration, the priority G of the migrated goods is 11 times the priority of ordinary goods, and except for special cases, this nonlinear amplification effect forces the system to prioritize high-risk goods. i

[0091] As an optional embodiment, the specific working steps of the migration unit further include the following:

[0092] The priority G of the goods to be migrated is obtained according to calculation i in the process of executing the migration task;

[0093] The warehouse is divided into three storage areas according to Manhattan distance, each of which contains a refrigerated area and a normal frequency area, and the refrigerated area is marked as an isolation area. The AGV path penalty calculation of the refrigerated area is increased on the basis of the AGV path crossing the isolation area.

[0094] The total priority Gx i is calculated according to the formula Gx i = G base *C in *(1+0.5*|T out -T i |), when carrying both near-expiration goods and goods that need to cross the refrigerated area, and the migration of goods is sorted according to the total priority Gx i when carrying both near-expiration goods and goods that need to cross the refrigerated area.

[0095] Where C base is the basic path cost, and |T in -T out | is the absolute value of the temperature difference between the outside of the refrigerated area and the inside of the refrigerated area. It should be noted that the basic path cost is calculated by the distance and time of goods handling, which can be obtained by equal-weighted calculation of the time cost and energy cost of warehouse AGV or stacker moving unit distance.

[0096] When the shelf life remaining time T remain is less than 2h, skip the refrigerated area path penalty calculation and directly select the shortest path. It should be noted that by introducing the refrigerated area path penalty and the double-factor priority calculation mechanism, the operation efficiency and goods safety in the cold chain storage scene are significantly improved. In the three-level storage area based on Manhattan distance, the refrigerated area is marked as an isolation area and the path penalty coefficient (such as temperature difference absolute value weight) is increased, forcing the AGV to prefer the normal frequency area path and reducing the energy consumption of cold chain equipment.

[0097] ​Meanwhile, the priority of the perishable goods (such as fresh food and medicine) is calculated (total priority = basic path cost + temperature difference x perishable weight) to ensure that the high-priority goods (such as daily-expiring food) are dispatched preferentially and the path is the shortest, so that the invalid exposure time of the goods in the refrigeration area is shortened and the damage rate is reduced.

[0098] For example, after the application of a certain medical warehouse, the number of times that AGV crosses the refrigeration area is reduced, the temperature control stability is improved, and the response speed of the perishable inventory automatically migrating to the fast picking area is improved due to the priority formula driving;

[0099] This breakthrough solves the problem of high energy consumption of equipment and waste of shelf life caused by ignoring the temperature influence in path planning, and is especially suitable for high-value and high-time-efficiency scenarios such as fresh e-commerce and medical cold chain, achieving a breakthrough in both warehouse efficiency and product safety.

[0100] As an optional embodiment, the specific working steps of the intelligent control module are as follows:

[0101] The adjustable shelf is integrated with a laser range finder, which is used to obtain the length, width and height data of the goods. The goods are packaged by a carton, and the carton is integrated with an RFID tag. The RFID tag is read to obtain the weight data m.

[0102] Then, the target layer spacing H of the adjustable shelf is calculated according to the formula adj wherein γ is a compensation coefficient, H0 is the layer height of the adjustable shelf in the last time period, and σ is a stress margin ratio. It should be noted that σ max is the maximum allowable stress of the adjustable shelf material, which is obtained by referring to GB / T28576 (shelf standard), GB12337 (pressure vessel design specification), etc. according to the material type and temperature condition, σ y is the actual stress of the adjustable shelf, which is obtained by installing stress sensors near the beam span and support points of the adjustable shelf. The time period of one time period is a fixed time period, which is 3 minutes in this embodiment.

[0103] It should be noted that the stress margin ratio reflects the proportion of the current stress to the maximum allowable stress, wherein The real-time structural safety state of the adjustable shelf is converted into a quantitative proportion of layer height adjustment to achieve dynamic response. Multiplying the compensation system and the layer height of the adjustable shelf in the last time period, the target layer spacing H of the adjustable shelf can be obtained. adj ;

[0104] According to the target layer spacing H of the adjustable shelf obtained​adj It is to be explained that the layer height adjustment is realized by a screw lifting device driven by a servo motor.

[0105] It is to be further explained that the structural safety margin of the shelf is quantified by comparing the actual stress of the shelf beam span and support point with the allowable stress determined based on the national standard table in real time, so as to dynamically adjust the layer height to prevent overload risk, which can not only avoid mechanical fatigue caused by frequent adjustment, but also automatically reduce the layer height to disperse the load according to the distribution characteristics of the goods, prevent the deformation or collapse of the shelf structure, and compress the invalid space dynamically.

[0106] As an optional embodiment, the specific working steps of the compensation coefficient γ are as follows:

[0107] The volume v of the goods is obtained by multiplying the length, width and height of the goods;

[0108] According to the formula

[0109] The compensation coefficient γ is obtained by calculation. It is to be explained that is the normalized density value of the goods, represents nonlinear amplification, which enhances the sensitivity of the exponential function in the high-density area.

[0110] As an optional embodiment, the specific steps of the intelligent control module further include the following:

[0111] According to the formula The space utilization rate of the adjustable shelf is obtained by calculation, wherein l j w j h j is the length, width and height of the jth goods;

[0112] L is the length of the adjustable shelf, and W is the width of the adjustable shelf;

[0113] If θ is less than 0.7, the adjustment suggestion is triggered, and the layer height H of the adjustable shelf is adjusted i until θ is greater than or equal to 0.7; it is to be explained that the layer height of the adjustable shelf can be adjusted adaptively to improve the space utilization rate of the adjustable shelf.

[0114] The present application also proposes a modular three-dimensional warehouse adaptive sorting method for heterogeneous goods, comprising the following steps:

[0115] Step 1: Through the modular adjustable shelves and special-shaped goods fixing racks, physical classification storage of different forms of goods is realized, and the standardized case packaging integrated with RFID tags is adopted to record the core information such as the weight of goods, warehouse in-out records, order association data and shelf life in real time;

[0116] Step 2: Based on the RFID tag data, Manhattan distance algorithm is used to dynamically partition the warehouse, and high-frequency turnover goods are preferentially allocated to the area near the entrance and exit, and medium and low-frequency goods are automatically adjusted in the storage location according to the logistics peak and valley period;

[0117] Step 3: The intelligent control module dynamically adjusts the layer height parameters of the adjustable shelves according to the limited space constraint of the entrance and exit area, analyzes the safety threshold of the current goods stacking density through the pressure sensor and visual recognition system, automatically reconstructs the shelf layer height configuration according to the turnover frequency change, and ensures the stability in the adjustment process combined with the special-shaped shelf characteristics such as shockproof base.

[0118] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiments only, and any technical solution falling within the idea of the present application shall fall within the protection scope of the present application. It should be noted that for ordinary technicians in the technical field, some improvements and decorations without departing from the principles of the present application shall also be considered as the protection scope of the present template.

Claims

1. A modular, three-dimensional warehousing system for heterogeneous items, characterized in that, Including a storage module, the storage module includes an adjustable shelf and a special-shaped goods fixing frame, and heterogeneous goods are classified and stored; The goods are packaged by a box, placed on the adjustable shelf and the special-shaped goods fixing frame, and the box is integrated with an RFID tag, and the information of the goods can be read according to the RFID tag; An intelligent optimization module is used to identify the turnover frequency of the goods according to the information of the goods read by the RFID tag, and the warehouse is divided into zones according to the Manhattan distance from the entrance and exit, and goods of different frequencies are classified and stored in different zones according to the turnover frequency; An intelligent control module is used to adjust the layer height data of the adjustable shelf in the zone closest to the entrance and exit of the warehouse according to the zoning result of the intelligent optimization module; The specific working steps of the intelligent optimization module are as follows: According to the RFID tag integrated on the box, the warehouse entry and exit record field order association data of the goods is obtained; A time period T is set in advance, and the real-time turnover frequency of the goods is calculated every time period according to the formula . ; wherein is the number of times the goods i is delivered out of the warehouse in the last time period T, is the current inventory of goods i, is the goods the weight comprehensive coefficient of the associated order; The warehouse is divided into three storage zones according to the Manhattan distance, and a distance range threshold is set in advance, the area within the distance range from the entrance and exit is marked as a medium frequency zone, the area within the distance range from the entrance and exit is less than the distance range is marked as a high frequency zone, and the area within the distance range from the entrance and exit is greater than the distance range is marked as a low frequency zone; Pre-set a real-time inventory turnover frequency The threshold range will determine the real-time turnover frequency of goods. Goods exceeding this threshold range are stored in the high-frequency zone, goods within this threshold range are stored in the mid-frequency zone, and goods below this threshold range are stored in the low-frequency zone. The specific working steps of the intelligent control module are as follows: The adjustable shelf is integrated with a laser range finder, the laser range finder is used for obtaining length, width and height data of goods, the goods are packaged by a carton, an RFID tag is integrated on the carton, the RFID tag is read, and weight data obtained is acquired ; Then the target layer spacing of the adjustable shelf is calculated according to the formula in each time period , wherein is a compensation coefficient, is the layer height of the adjustable shelf in the last time period, is a stress margin ratio; The height of the adjustable shelving is adjusted in accordance with the target inter-shelf spacing obtained for adjusting the shelving.

2. The modular, three-dimensional warehouse system for heterogeneous items of claim 1, wherein, The specific working steps of the intelligent optimization module further include the following: Sort the number of other goods in the same order that are out of the warehouse together with the goods in the previous period of the current time period, mark the top z goods in the sorting quantity as associated goods; According to the formula , the optimized turnover frequency of goods is calculated , wherein represents the total turnover frequency of all goods in the warehouse in the last period, is the real-time turnover frequency of the kth associated goods, wherein is the weight coefficient of the associated goods; According to the optimized turnover frequency of the goods The goods are classified and stored.

3. The modular, three-dimensional warehouse system for heterogeneous items of claim 2, wherein, The intelligent optimization module further includes a migration unit, which generates a migration task according to the change of the real-time turnover frequency of the goods, and moves the goods to other zones, and the specific steps further include the following: a threshold value of a turnover frequency change is set in advance If the change value of the optimized turnover frequency of the goods in the two adjacent periods T is greater than the threshold value , the goods are marked as goods to be migrated, and are transported to the corresponding subzone according to the optimized turnover frequency of the goods . Before the transportation, the priority of the goods to be migrated is calculated according to the formula wherein is the highest turnover frequency in the warehouse in the last cycle, is the distance required for the goods to be transported to the corresponding sub-area.​ A priority threshold range is set in advance; If the priority of the goods to be moved If the value exceeds this threshold, the stacker crane will immediately perform the handling task, depending on the priority of the goods to be moved. If the goods are within this threshold range, the transport task will be scheduled and executed by the AGV. If the priority of the goods to be moved is... If the value is below this threshold, the handling task will be performed when neither the stacker crane nor the AGV has a work target. For the same classification of goods to be migrated, the priority is sorted according to the size of the priority of the goods to be transported.

4. The modular, three-dimensional warehouse system for heterogeneous items of claim 3, wherein, The specific working steps of the migration unit further include the following: In the process of moving the goods into other sub-zones, the remaining valid time of the goods, i.e. the shelf life remaining time, is obtained according to the RFID tag integrated on the box ; According to the formula , the priority of the goods to be migrated is calculated ; obtaining a priority of the goods to be migrated according to the calculation performing the migration task.

5. The modular, three-dimensional warehouse system for heterogeneous items of claim 4, wherein, The specific working steps of the migration unit further include the following: In accordance with the calculation, the priority of the goods to be migrated is obtained In the process of performing the migration task; The warehouse is divided into three storage zones according to the Manhattan distance, wherein each storage zone contains a refrigeration zone and a common medium frequency zone, and the refrigeration zone is marked as an isolation zone, and the refrigeration zone path penalty calculation is added on the basis of the AGV path through the isolation zone; The total priority of carrying both the near-expiring cargo and the cargo that needs to cross the refrigerated zone is calculated according to the formula The total priority of carrying both the near-expiring cargo and the cargo that needs to cross the refrigerated zone is calculated according to the formula The migration of the cargo is sorted according to the total priority of carrying both the near-expiring cargo and the cargo that needs to cross the refrigerated zone​ wherein is the base path cost, is the absolute value of the temperature difference outside the refrigerated zone and inside the refrigerated zone; When the shelf life remaining time Less than 2h, skip the cold storage area path penalty calculation, directly select the shortest path.

6. The modular, three-dimensional warehouse system for heterogeneous items of claim 1, wherein, The compensation coefficient The specific working steps are as follows: The volume of the cargo is obtained by multiplying the length of the cargo by the width of the cargo by the height of the cargo ; According to the formula ; The compensation coefficient is calculated .

7. The modular, three-dimensional warehouse system for heterogeneous items of claim 6, wherein, The specific steps of the intelligent control module further include the following: The space utilization of the adjustable shelf is calculated according to the formula , wherein is the length, width and height of the th product. to adjust the length of the shelf, to adjust the width of the shelf; If less than 0.7, a regulation suggestion is triggered to adjust the height of the shelves of the adjustable shelf , until greater than or equal to 0.

7.

8. A modular cube storage adaptive sorting method for heterogeneous goods, applicable to the modular cube storage system for heterogeneous goods according to any one of claims 1 to 7, characterized in that, The steps are as follows: Step 1: The physical classification and storage of goods of different shapes are realized by using the modular design of the adjustable shelf and the special-shaped goods fixing frame, and the standardized box packaging integrated with the RFID tag is used to record the core information of the goods in real time, such as weight, warehouse entry and exit record, order association data and shelf life; Step 2: Based on the RFID tag data, the Manhattan distance algorithm is used to dynamically zone the warehouse, and high-frequency turnover goods are preferentially allocated to the area near the entrance and exit, and medium and low-frequency goods are automatically adjusted in the storage area according to the logistics peak and valley period; Step 3: The intelligent control module dynamically adjusts the height parameter of the adjustable shelf according to the limited space constraint of the entrance and exit area, analyzes the safety threshold of the current goods stacking density through the pressure sensor and the visual recognition system, and automatically reconstructs the shelf height configuration according to the change of the turnover frequency, combined with the shockproof base to ensure the stability during the adjustment process.

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