JP2024001571A - Automatic warehouse size calculating apparatus, and automatic warehouse size calculating method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an automatic warehouse size calculating apparatus and an automatic warehouse size calculating method which can rapidly calculate a size required for an automatic warehouse.

SOLUTION: A loading number calculating unit 51 calculates the loading number easily by using probability distribution. A delivery number calculating unit 52, under a predetermined delivery condition, calculates the delivery number of an article 150 delivered from an automatic warehouse per unit time by using the probability distribution. Accordingly, even if the a vertical conveyer machine 22 whose delivery number of deliver per unit time is not constant is used, the delivery number calculating unit 52 can easily calculate the delivery number by using the probability distribution. A storage number calculating unit 53, based on the calculated loading number and the calculated delivery number, calculates transition of the storage number of the article 150 stored in a storage shelf 110. In this case, if the storage number of the article 150 stored in the storage shelf 110 is larger as compared with the arithmetic result of the storage number calculating unit 53, it is easy to grasp how many storage number is required.

SELECTED DRAWING: Figure 4

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to an automatic warehouse scale calculation device and an automatic warehouse scale calculation method.

BACKGROUND ART Conventionally, a technique described in Patent Document 1, for example, is known as a technique for calculating the scale of an automated warehouse. This technology calculates the scale required for an automated warehouse by preparing machine parameters that model the performance of the entire distribution center configuration and determining optimization settings from simulation.

JP2020-520526A

Here, automated warehouses use vertical conveyors to store and take out warehouses, but when a model of an automated warehouse with vertical conveyors is constructed and simulated, the time required for simulation increases as the number of items increases. There's a problem. Therefore, it is required to quickly calculate the scale required for an automated warehouse.

Therefore, an object of the present invention is to provide an automated warehouse scale calculation device and an automated warehouse scale calculation method that can quickly calculate the scale required for an automated warehouse.

An automatic warehouse scale calculation device according to one aspect of the present invention is an automatic warehouse scale calculation device that has storage shelves for storing articles and calculates the scale of an automatic warehouse provided for a vertical conveyance machine, A warehousing number calculation unit that calculates the number of items that are received into the automated warehouse per unit time under warehousing conditions using a probability distribution, and a warehousing number calculation unit that calculates the number of items that are received from the automated warehouse per unit time under predetermined warehousing conditions. an out-of-stock number calculation unit that calculates the out-of-stock number of goods using a probability distribution; and a storage number calculation unit that calculates changes in the number of goods stored in storage shelves based on the calculated in-stock and out-of-stock numbers. , is provided.

In the automatic warehouse scale calculating device, the number of items in stock is calculated by using a probability distribution, under predetermined warehousing conditions, the number of items to be stocked in the automated warehouse per unit time. Therefore, even if a vertical conveyance machine is used in which the number of items received per unit time is not constant, the number calculation unit can easily calculate the number of items received using probability distribution. Further, the outgoing number calculation unit calculates the outgoing number of articles to be outgoing from the automated warehouse per unit time under predetermined outgoing conditions using a probability distribution. Therefore, even if a vertical conveyance machine is used in which the number of items delivered per unit time is not constant, the number calculation unit can easily calculate the number of items delivered using probability distribution. Further, the storage number calculating unit calculates the change in the number of items stored on the storage shelf based on the calculated number of items received and the number of items sent out. In this case, from the calculation result of the storage number calculation unit, when the number of items stored on the storage shelf is large, it is possible to easily grasp how many items are required to be stored. As described above, the automated warehouse scale calculation device can quickly calculate the scale required for an automated warehouse.

The automatic warehouse scale calculation device further includes a statistical information calculation unit that calculates probabilistic statistical information on the number of stored items based on the calculation results of the repeatedly executed storage number calculation unit, outgoing number calculation unit, and storage number calculation unit. You may do so. In this case, the statistical information calculation section can calculate statistical information that can statistically grasp the scale required for the automated warehouse based on the repeated simulation results.

The vertical conveyance machine is of an alternating operation type, and at least one of the incoming number calculation section and the outgoing number calculation section calculates the average number of articles per unit time based on the number of floors of the storage shelf using a Poisson distribution as a probability distribution. It's fine. The upper limit on the number of articles per unit time that the alternating-operation vertical conveyance machine can enter or take out is determined by the number of floors of the storage shelves. Furthermore, since Poisson distribution is a probability distribution that tends to have a peak at small numbers, it is a probability distribution suitable for calculating the number of articles to be transported by a vertical conveyor.

An automated warehouse scale calculation method according to one embodiment of the present invention is an automated warehouse scale calculation method for calculating the scale of an automated warehouse that has storage shelves for storing articles and is provided for a vertical conveyance machine, the method comprising: A warehousing number calculation step that calculates the number of items that are received into the automated warehouse per unit time under warehousing conditions using a probability distribution; and a warehousing number calculation step that calculates the number of items that are received from the automated warehouse per unit time under predetermined warehousing conditions. The method includes: a step of calculating the number of goods to be sent out using a probability distribution; and a step of calculating the number of stored goods to calculate the transition of the goods on the storage shelf based on the calculated number of arrivals and the number of goods out.

According to this automatic warehouse scale calculation method, it is possible to obtain the same functions and effects as the above-mentioned automatic warehouse scale calculation device.

According to the present invention, it is possible to provide an automated warehouse scale calculation device and an automated warehouse scale calculation method that can quickly calculate the scale required for an automated warehouse.

1 is a schematic side view showing a distribution warehouse that is a target of calculation by an automatic warehouse scale calculation device according to an embodiment of the present invention. 1 is a schematic configuration diagram showing the configuration of a distribution warehouse. FIG. 2 is a block configuration diagram of a control device. FIG. 1 is a block configuration diagram of an automated warehouse scale calculation device according to the present embodiment. FIG. 2 is a schematic diagram showing an example of the flow of articles entering and leaving an automated warehouse. FIG. 2 is a schematic diagram showing how goods are stored and taken out of the warehouse. (a) is a schematic diagram showing an example of a process of a warehousing number calculating section, and (b) is a schematic diagram showing an example of a process of a warehousing number calculating section. (a) is a graph showing the change in the number of items stored in an automated warehouse, and (b) is a graph showing the probability distribution of the maximum value of the number of items stored in the automated warehouse. This is an example of input information and output information. This is an example of input information and output information. This is an example of input conditions and output conditions. It is a flowchart which shows the flow of the processing content of an automatic warehouse scale calculation device.

Embodiments of the present invention will be described in detail below with reference to the drawings.

FIG. 1 is a schematic side view showing a distribution warehouse 1 equipped with a control device according to an embodiment of the present invention. As shown in FIG. 1, the distribution warehouse 1 is a system in which a plurality of articles 150 are received and stored, and from among the stored articles 150, items that should be taken out can be taken out. The distribution warehouse 1 includes an automated warehouse 100, an outbound elevator 104 (vertical conveyance machine), an incoming elevator 105 (vertical conveyance machine), an outbound lane 121 (transportation lane), and an inbound lane 21 (transportation lane). . The automated warehouse 100 is a warehouse that stores articles 150. The automated warehouse 100 includes a warehouse main body 101, an exit passageway 102, and a warehousing passageway 103. The warehouse main unit 101 has multiple storage shelves 110. The storage shelf 110 extends from one end of the warehouse main body 101 to the other end. In the storage shelf 110, the transfer device 111 performs an operation of transferring articles from the warehousing route to the warehousing route. The warehousing passageway 103 is provided at one end of the warehouse main body 101 and is a mechanism for warehousing articles 150 to the storage shelves 110 at each stage. The retrieval passageway 102 is provided at the other end of the warehouse main body 101 and is a mechanism for retrieving articles 150 from the storage shelves 110 at each stage. The warehousing elevator 105 moves up and down the articles 150 that are warehoused from the warehousing lane 21 and supplies the articles 150 to the warehousing passageway 103 of the stage corresponding to the desired storage shelf 110 . The unloading elevator 104 receives the article 150 to be unloaded from the storage shelf 110 and the unloading passageway 102, and moves it up and down to the unillustrated exit exit. Articles 150 that have been unloaded from the unloading elevator 104 are carried out to the unloading lane 121.

FIG. 2 is a schematic configuration diagram showing the configuration of the distribution warehouse 1. In the following description, the warehousing elevator 105 and the warehousing elevator 104 may be simply referred to as the "vertical conveyance machine 22." FIG. 2 shows the configuration of the warehouse 1 on the warehousing side. Note that the outgoing side of the distribution warehouse 1 has the same configuration as the incoming side, except that the goods 150 flow through the automated warehouse 100, the vertical conveyance machine 22 (outgoing elevator 104), and the outgoing lane 121, so the description will be made here. omitted. As shown in FIG. 2, the distribution warehouse 1 includes a transport system 2 that transports articles 150, and a control device 10 that controls the transport system 2. The transport system 2 includes a warehousing lane 21, a vertical transport machine 22, and a conveyor 23 of the automated warehouse 100. Among these, the vertical conveyance machine 22 is a device that constitutes the above-mentioned warehousing elevator 105. The warehousing lane 21 is a device that horizontally transports the articles 150 and delivers them to the vertical conveyor 22 . The warehousing lane 21 is provided for a predetermined stage of the vertical conveyance machine 22 . The conveyor 23 is a device that receives articles from the vertical conveyor 22 and conveys them horizontally on each floor of the automated warehouse 100. The conveyor 23 is provided on each floor (here, the fourth floor) of the warehousing passageway 103.

The vertical conveyance machine 22 is a device that includes a horizontal movement means (for example, a conveyor) and a vertical movement means, and moves the article 150 in the vertical direction and the horizontal direction. Each of the articles 150 to be warehoused is associated with a destination floor, which is a conveyance destination. Thereby, the vertical conveyance machine 22 moves each article 150 to the destination floor in the warehousing crossing passageway 103. In addition, in the figure, the number "m" is attached to the article 150 whose destination is "m floor". The same applies to subsequent figures. Furthermore, in the following description, the article 150 whose destination is the m floor may be referred to as "an article destined for the m floor."

The vertical conveyance machine 22 is a vertical conveyance machine that performs vertical conveyance by moving the article 150 in the horizontal direction (lateral direction) while alternately raising and lowering a plurality of adjacent conveyance boxes 22a. The vertical conveyance machine 22 is an alternating operation type lifting device, and has a conveyance shelf 22A on the warehousing lane 21 side and a conveyance shelf 22B on the conveyor 23 side. Each of the transport shelves 22A and 22B has an accommodating area CE with a number of stages equal to "the number of floors of the automated warehouse + the first floor". The transport box 22a has a continuous number of stages (here, four stages) equal to the "number of floors of the automated warehouse". The continuous transport boxes 22a move up and down simultaneously. When the continuous transport boxes 22a move downward, each transport box 22a is arranged in the accommodating areas CE of the first to fourth stages from the bottom. When the continuous transport boxes 22a move upward, each transport box 22a is arranged in the accommodating areas CE of the second to fifth stages from the bottom. In the following description, when simply referring to the number of stages, unless otherwise noted, the number of stages counted from the bottom is meant. Further, the transport box 22a of the transport shelf 22A and the transport box 22a of the transport shelf 22B are alternately moved up and down. That is, when the transport box 22a of the transport shelf 22A moves upward, the transport box 22a of the transport shelf 22B moves downward. Thereby, the article 150 in the transport shelf 22A can be raised one step (see operation M1). Furthermore, when the transport box 22a of the transport shelf 22A moves downward, the transport box 22a of the transport shelf 22B moves upward. Thereby, the article 150 in the transport shelf 22B can be raised one step. Moreover, in the same number of stages, the article 150 can be moved in the horizontal direction between the transportation box 22a of the transportation shelf 22A and the transportation box 22a of the transportation shelf 22B, and the article 150 can be delivered and received from each other. can be performed (see operation M2). Furthermore, the article 150 can be delivered from the transport box 22a of the transport shelf 22B to the conveyor 23 of the desired floor (see operation M3).

In the present embodiment, the warehousing lane 21 is provided for the storage area CE of the second stage from the bottom, and four conveyors 23 are provided for the storage areas CE of the first to fourth stages from the bottom. In addition, in FIG. 2, locations indicated as "S1" and "S2" in the accommodating area CE are spaces provided for the transport shelves 22A, 22B to move up and down. However, the positional relationship among the accommodating area CE, the warehousing lane 21, and the conveyor 23 is not particularly limited, and may be set as appropriate depending on the configuration of the distribution warehouse 1.

Next, the block configuration of the control device 10 will be explained with reference to FIG. 3. FIG. 3 is a block diagram of the control device 10 according to this embodiment. The control device 10 is a unit that controls the transport system 2. The control device 10 includes an ECU (Electronic Control Unit) that comprehensively manages the distribution warehouse 1. The ECU is an electronic control unit that includes a CPU [Central Processing Unit], a ROM [Read Only Memory], a RAM [Random Access Memory], and a communication circuit such as a CAN [Controller Area Network]. The ECU realizes various functions by, for example, loading a program stored in a ROM into a RAM and executing the program loaded into the RAM by a CPU. The control device 10 includes an operation control section 11, an article information acquisition section 12, and a route calculation section 13. The control device 10 acquires various information from the storage section 3 and transmits a control signal to the transport system 2.

The operation control unit 11 is a unit that controls the transport operation of the distribution warehouse 1 so that each article 150 is transported based on the transport route calculated by the route calculation unit 13. The operation control unit 11 controls the conveyance operation by transmitting a control signal to the conveyance system 2 . The operation control unit 11 operates each drive unit of the warehousing lane 21, the vertical conveyance machine 22, and the conveyor 23 of the conveyance system 2 by transmitting a control signal to each drive unit.

The article information acquisition unit 12 determines when the article 150 moves in the order of the warehousing lane 21, the vertical conveyance machine 22, and the automated warehouse 100, or when the article 150 moves in the order of the automated warehouse 100, the vertical conveyance machine 22, and the outgoing lane 121. , obtains article information indicating the initial movement state and movement completion state of the article 150. The initial movement state is a state in which the article 150 to be transported is present in the warehousing lane 21 . Furthermore, the movement completion state is a state in which all the articles 150 to be transported have been transported from the automated warehouse 100. The article information includes information such as the floor number of the destination of the article 150 existing in the warehousing lane 21 at the time of warehousing, the number of articles 150 for each floor, and the order of warehousing. Further, the article information includes information such as how many articles 150 are to be delivered from which floor from the automated warehouse 100, and information such as the order in which the articles 150 are to be delivered.

The route calculating section 13 is a unit that calculates conveyance route information from article information. The route calculation unit 13 searches the conveyance route of each article 150 in the conveyance system 2 . The route calculation unit 13 calculates what route each article 150 takes within the transport system 2 to reach its destination. The route calculation unit 13 searches for a route for each article 150 using a shortest route search method or the like for a predetermined number of articles 150, using each part of the transport system 2 as a search node.

Next, the automated warehouse scale calculation device 50 according to this embodiment will be explained. FIG. 4 is a block configuration diagram showing an automated warehouse scale calculation device 50 according to an embodiment of the present invention. The automated warehouse scale calculation device 50 is a device that calculates the scale of the automated warehouse 100. The automated warehouse scale calculation device 50 is a device used to estimate the scale of the automated warehouse 100 at the stage of designing the automated warehouse 100 as described above. The scale of the automated warehouse 100 is information indicating how many articles 150 the automated warehouse 100 can store. That is, it is the total number of articles 150 that can be stored on the storage shelves 110 on each floor. The number of stored items is the number of items 150 stored in the automated warehouse 100 minus the number of items 150 removed from the automated warehouse 100. The automated warehouse scale calculation device 50 includes a storage number calculation section 51, an output number calculation section 52, a storage number calculation section 53, and a statistical information calculation section 54.

Before explaining the automated warehouse scale calculation device 50, an example of the flow of articles 150 entering and leaving the automated warehouse 100 will be explained. As shown in FIG. 5, the automatic warehouse 100 receives articles 150 from companies X, Y, and Z. Then, the automated warehouse 100 rearranges the articles 150 for each customer A, customer B, and customer C, and takes out the rearranged articles 150. The automated warehouse scale calculation device 50 estimates the storage scale required for the automated warehouse 100 in such a situation. As shown in FIG. 6, it is assumed that the item for customer A is "1" article 150, the item for customer B is "2" article 150, and the item for customer C is "3" article 150. At this time, the articles 150 "1", "2", and "3" are stored in the automated warehouse 100 in random order. The automated warehouse 100 leaves the goods 150 sorted in the order of "1", "2", and "3" for each customer.

The stocking number calculation unit 51 calculates the stocking number n of articles 150 stocked from the vertical conveyance machine 22 (warehousing elevator 105) to the automated warehouse 100 per unit time under predetermined stocking conditions using probability distribution. The storage number calculating unit 51 calculates the average number of articles per unit time (the storage number n) based on the number of floors of the storage shelves 110 using a Poisson distribution as a probability distribution. In this embodiment, the storage shelf 110 is on the fourth floor. Therefore, the number n that the vertical conveyor 22 can simultaneously store into the storage shelves 110 is less than four (n<4). The number n of goods received per unit time (one cycle) is 0, 1, 2, or 3. The formula for Poisson distribution is the following formula (1). The Poisson distribution P(k) in equation (1) indicates the probability that k articles 150 are received in a unit time, assuming that an average of λ articles 150 are received per unit time. When "λ=3", the probability that the number of items in stock is 2 or 3 is 22%, the probability that 0 items is 5%, and the probability that 1 item is 15%. The warehousing number calculation unit 51 sets the warehousing number n of a certain cycle according to the probability distribution. Here, since the probability that the number n of goods received is 1 or 2 is highest, the number n of goods received in a certain cycle is often set to 1 or 2, and the next most common is set to 3. , is least likely to be set to 0.

The stocking number calculation unit 51 randomly selects n items from among the stocking target articles 150 based on the stocking number n calculated for each unit time (each cycle). For example, in the example shown in FIG. 7(a), if the number n of items received in a certain cycle is 2, the storage number calculation unit 51 randomly selects items from among the group of items 150 of items ``1'', ``2'', and ``3''. Two articles 150 are selected. The warehousing number calculation unit 51 brings the selected article 150 into a warehousing completed state. The article 150 in the warehousing completed state is pulled out of the group of articles to be warehousing. Here, since the article 150 of "1" and the article 150 of "3" have been selected, the number calculation unit 51 subtracts one article 150 of "1" from the article group, and subtracts one article 150 of "3" from the article group. With one item subtracted, the item 150 for the next cycle is selected. The warehousing number calculating unit 51 repeats the above process until all the articles 150 to be warehousing are in a warehousing completion state.

Note that in the group of articles on the left side of FIG. 7A, the articles 150 are arranged without being restricted by the order of the articles 150 on the warehousing side of FIG. 6. Even if the articles 150 are received in the order shown in FIG. 6, the order is changed by the vertical conveyor 22, so which article 150 among "1", "2", and "3" will be received at random.

The outgoing number calculation unit 52 calculates the outgoing number n of articles 150 to be outgoing from the automated warehouse 100 to the vertical conveyance machine 22 (outgoing elevator 104) per unit time under predetermined outgoing conditions using probability distribution. The number calculation unit 52 calculates the average number of articles per unit time (number n of items delivered) based on the number of floors of the storage shelves 110 using a Poisson distribution as a probability distribution. In this embodiment, the storage shelf 110 is on the fourth floor. Therefore, the number n of items that can be delivered to the storage shelves 110 simultaneously by the vertical conveyance machine 22 is less than four (n<4). The number n of items delivered per unit time (one cycle) is 0, 1, 2, or 3. The formula for Poisson distribution is the same as formula (1) above. The Poisson distribution P(k) in Equation (1) indicates the probability that k items will be delivered per unit time, assuming that an average of λ items 150 are delivered per unit time. When "λ=3", the probability that the number of items to be delivered is 2 or 3 is 22%, the probability that 0 items is 5%, and the probability that 1 item is 15%. The number of deliveries calculation unit 52 sets the number n of deliveries in a certain cycle according to the probability distribution.

Based on the number of outgoing items n calculated for each unit of time (each cycle), the outgoing number calculation unit 52 selects n customer items 150 to be outgoing from among the items 150 that have been stocked in the automated warehouse 100. . For example, in the example shown in FIG. 7(b), if the number n of deliveries in a certain cycle in which the goods 150 of customer A are to be delivered is 2, the number calculation unit 52 calculates Two "1" articles 150 are selected from the article group of articles 150. The delivery number calculation unit 52 brings the selected article 150 into a delivery completion state. The article 150 that has been placed in the unloaded state is pulled out of the group of articles in the automated warehouse 100. Here, since two "1" articles 150 are selected, the outgoing number calculation unit 52 subtracts two "1" articles 150 from the article group of the automated warehouse 100, and then starts the next cycle. Select the article 150 in . The delivery number calculation unit 52 repeats the above process until all the articles 150 are in the delivery completion state.

The stored number calculation unit 53 calculates the change in the number of stored articles 150 stored on the storage shelf 110 based on the calculated number of items received and the number of items sent out. The number of stored items is the number of items in the automated warehouse 100, and is defined as the difference between the number of items in the warehousing completed state and the number of items in the warehousing completed state. The stored number calculation unit 53 calculates the change in the stored number by simulating the process from the start of warehousing into the automated warehouse 100 to the completion of unloading of all the articles 150. For example, the stored number calculation unit 53 obtains the stored number transition as shown in FIG. 8(a), for example. In the cycle immediately after the start of warehousing, since the number of articles 150 in the automated warehouse 100 is small, it is not possible to take them out much. Therefore, the rate of increase in the number of stored items increases (around cycles 1 to 50). When the number of articles 150 stored in the automated warehouse 100 reaches a predetermined amount, the articles 150 are taken out for each customer. Therefore, the number of stored items increases or decreases (around cycles 50 to 150). When all the articles 150 to be warehoused have been warehoused, they are only taken out from the automated warehouse 100. Therefore, the rate of decrease in the number of stored items increases (around cycles 150 to 210). The storage number calculation unit 53 obtains the maximum value of the storage number in the above transition as the storage number required for the automated warehouse 100.

The statistical information calculation unit 54 calculates probabilistic statistical information on the number of stored items based on the calculation results of the repeatedly executed storage number calculation unit 51, outgoing number calculation unit 52, and storage number calculation unit 53. The storage number calculation section 51, the storage number calculation section 52, and the storage number calculation section 53 obtain the maximum value of the storage number in the simulation by performing one simulation. The storage number calculation section 51, the output number calculation section 52, and the storage number calculation section 53 repeatedly perform such simulation a specified number of times. The statistical information calculation unit 54 calculates probabilistic statistical information by plotting the maximum value of a plurality of stored numbers, as shown in FIG. 8(b). In the example shown in FIG. 8(b), when a certain maximum value is obtained, the statistical information calculation unit 54 increases the frequency of the maximum value by one. As a result, a probability distribution in which the maximum value peaks around 110 is obtained. The statistical information calculation unit 54 outputs the calculated statistical information as the storage scale of the automated warehouse 100. For example, the maximum value that becomes a peak may be adopted as the storage scale, or the maximum value that is equal to or greater than a predetermined frequency may be adopted as the storage scale.

Next, an example of what kind of input information is input and what kind of information is output in the calculation of the automatic warehouse scale calculation device 50 will be explained. For example, as input information to the automated warehouse scale calculation device 50, information specifying the number of articles for each customer as shown in FIG. 9(a) is input. Further, as input information, information specifying a probability distribution used by the number-of-warehousing calculation unit 51 and a probability distribution used by the number-of-output calculation unit 52 as shown in FIG. 9(b) is input. Further, as input information, as shown in FIG. 9(c), information specifying the number of simulations for outputting the storage scale is input.

As the output information outputted by the automatic warehouse scale calculation device 50, storage number transition data for each cycle as shown in FIG. 10(a) is outputted. The table in FIG. 10(a) shows the number of items stored in the automated warehouse in each cycle, and is the graph shown in FIG. 8(a) written out in a table format. As output information, as shown in FIG. 10(b), the data of the maximum number of storages in each simulation is output. Based on the table shown in FIG. 10(b), it is possible to create a probability distribution graph as shown in FIG. 8(b).

As the delivery condition used by the delivery number calculation unit 52, for example, as shown in FIG. 11(a), information specifying the interval time of delivery times between customers may be input. For example, when the unloading of item 150 destined for customer A is completed, and then the unloading of article 2 150 intended for customer B, a predetermined number of cycles are waited as the interval time. Further, as the delivery condition, a delivery start cycle may be specified in accordance with the shipping time of the truck. For example, once the loading of one truck is completed, the unloading may wait for a cycle until preparations for loading the next truck are completed.

As the warehousing condition used by the warehousing number calculation unit 51, the order of the articles 150 to be warehousing may be specified. For example, in the example shown in FIG. 7(a), the storage number calculation unit 51 randomly selects and stores customer's articles 150. Alternatively, the stocking number calculation unit 51 may select and stock the customer's articles 150 based on a probability distribution. Alternatively, the storage quantity calculation unit 51 may select and store articles based on customer data as shown in FIG. 11(b). In FIG. 11(b), in cycle 1, two articles 150 of customer A are selected and one article 150 of customer B is selected.

As the delivery condition used by the delivery number calculation unit 52, as shown in FIG. 11(c), the delivery may be made in the order of specified customers. In FIG. 11C, first 40 items 150 of customer A are taken out, then 12 items 150 of customer B are taken out, and then 16 items 150 of customer C are taken out. Alternatively, the delivery condition may be such that the goods are delivered only by the customer who has a specified number of items.

Next, with reference to FIG. 12, the flow of processing contents of the automated warehouse scale calculation device 50 will be explained. First, the stocking number calculating unit 51 executes a stocking number calculation step of calculating the number of stocking items 150 that are stocked into the automated warehouse 100 per unit time under predetermined stocking conditions using a probability distribution (step S10 ). Next, the outgoing number calculation unit 52 executes an outgoing number calculation step of calculating the outgoing number of articles 150 that are outgoing from the automated warehouse 100 per unit time under predetermined outgoing conditions using a probability distribution (step S20). Next, the storage number calculation unit 53 executes a storage number calculation step of calculating the transition of the articles 150 on the storage shelves 110 based on the calculated number of items entered and number of items sent out (step S30). Next, the statistical information calculation unit 54 determines whether the specified number of simulations have been completed (step S40). If it is determined in step S40 that the process has not been completed, the process is repeated again from step S10 for calculating the number of items in stock. If it is determined that the process has been completed in step S40, the statistical information calculation section 54 calculates the probability of the number of stored items based on the calculation results of the repeatedly executed storage number calculation section 51, outgoing number calculation section 52, and storage number calculation section 53. A statistical information calculation step for calculating statistical information is executed to output statistical information (step S50). With the above steps, the process shown in FIG. 12 is completed.

The functions and effects of the automatic warehouse scale calculation device 50 and the automatic warehouse scale calculation method according to this embodiment will be explained.

In the automated warehouse scale calculating device 50, the number-of-arrival calculation unit 51 calculates the number of items 150 that are received into the automated warehouse 100 per unit time under predetermined warehousing conditions using probability distribution. Therefore, even if the vertical conveyance machine 22 is used in which the number of items received per unit time is not constant, the number calculation unit 51 can easily calculate the number of items received using probability distribution. . Further, the outgoing number calculation unit 52 calculates the outgoing number of articles 150 that are outgoing from the automated warehouse per unit time under predetermined outgoing conditions using probability distribution. Therefore, even when using the vertical conveyance machine 22 in which the number of deliveries per unit time is not constant, the number of deliveries calculation section 52 can easily calculate the number of deliveries using probability distribution. . In addition, the stored number calculation unit 53 calculates the change in the number of stored articles 150 stored on the storage shelf 110 based on the calculated number of items received and the number of items sent out. In this case, when the number of articles 150 stored in the storage shelf 110 is large, it is possible to easily grasp from the calculation result of the storage number calculation unit 53 how many items are required to be stored. As described above, the automated warehouse scale calculation device 50 can quickly calculate the scale required for the automated warehouse 100.

The automatic warehouse scale calculation device 50 performs statistical information calculation that calculates probabilistic statistical information on the number of stored items based on the calculation results of the repeatedly executed storage number calculation unit 51, outgoing number calculation unit 52, and storage number calculation unit 53. It may further include a section 54. In this case, the statistical information calculation unit 54 can calculate statistical information that can statistically grasp the scale required for the automated warehouse 100 based on the results of repeated simulations.

The vertical conveyance machine 22 is of an alternating operation type, and at least one of the incoming number calculation section 51 and the outgoing number calculation section 52 uses a Poisson distribution as a probability distribution of the average number of articles per unit time based on the number of floors of the storage shelves 110. You can use it for calculations. The upper limit of the number of articles per unit time that the alternating-operation vertical conveyance machine 22 can enter or take out is determined by the number of floors of the storage shelves 110. Further, since Poisson distribution is a probability distribution that tends to have a peak at small numbers, it is a probability distribution suitable for calculating the number of articles carried by the vertical conveyor 22.

The automated warehouse scale calculation method according to the present embodiment is an automated warehouse scale calculation method for calculating the scale of an automated warehouse 100 that has a storage shelf 110 for storing articles 150 and is provided for a vertical conveyor 22, and includes: Under predetermined warehousing conditions, the number of goods 150 to be stocked into the automated warehouse 100 per unit time is calculated using a probability distribution. A number calculation step S20 for calculating the number of goods 150 taken out of the warehouse 100 using a probability distribution, and a storage step S20 for calculating the transition of goods on the storage shelves 110 based on the calculated number of arrivals and number of goods out. A numerical calculation step S30 is provided.

According to this automatic warehouse scale calculation method, it is possible to obtain the same operation and effect as the above-mentioned automatic warehouse scale calculation device 50.

The invention is not limited to the embodiments described above.

Although the storage number calculation unit 51 and the storage output number calculation unit 52 used a Poisson distribution as a probability distribution, other probability distributions may be used, and a suitable one may be used depending on the target conveyance machine.

DESCRIPTION OF SYMBOLS 1... Logistics warehouse, 22... Vertical conveyance machine, 50... Automatic warehouse scale calculation device, 51... Input number calculation unit, 52... Output number calculation unit, 53... Storage number calculation unit, 54... Statistical information calculation unit, 100... Automatic Warehouse, 150...Goods.

Claims (4)

An automatic warehouse scale calculation device that has storage shelves for storing articles and calculates the scale of an automatic warehouse provided for a vertical conveyance machine,
a warehousing number calculation unit that calculates the number of items to be stocked in the automated warehouse per unit time under predetermined warehousing conditions using a probability distribution;
an outgoing number calculation unit that calculates the outgoing number of the articles to be outgoing from the automated warehouse per unit time under predetermined outgoing conditions using a probability distribution;
An automatic warehouse scale calculation device, comprising: a storage number calculation unit that calculates a change in the number of items stored in the storage shelf based on the calculated storage number and the output number. Claim further comprising: a statistical information calculation unit that calculates probabilistic statistical information of the stored quantity based on the calculation results repeatedly executed by the storage quantity calculation unit, the outgoing quantity calculation unit, and the stored quantity calculation unit. 1. The automatic warehouse scale calculation device according to 1. The vertical conveyor is of an alternating operation type,
At least one of the stocking number calculation section and the stocking number calculation section,
The automatic warehouse scale calculation device according to claim 1 or 2, wherein the average number of articles per unit time based on the number of floors of the storage shelves is calculated using a Poisson distribution as the probability distribution. An automated warehouse scale calculation method for calculating the scale of an automated warehouse that has storage shelves for storing articles and is provided for a vertical conveyance machine, the method comprising:
a warehousing number calculation step of calculating the number of the goods to be stocked in the automated warehouse per unit time under predetermined warehousing conditions using a probability distribution;
a step of calculating the number of goods to be delivered from the automated warehouse per unit time under predetermined delivery conditions using a probability distribution;
An automatic warehouse scale calculation method, comprising: calculating a storage number calculation step of calculating a transition of the articles on the storage shelf based on the calculated storage number and the storage output number.

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