Medical instrument storage management method and device, terminal equipment and storage medium

Abstract

The invention discloses a medical instrument storage management method and device, terminal equipment and a storage medium. The method comprises the following steps: determining the maximum storage quantity of each medical device by obtaining historical warehouse-out data and order data of the medical device; determining a first storage area corresponding to each medical device according to the material attribute and the maximum storage quantity of each medical device; and on the basis of the first storage area, determining a second storage area corresponding to each medical apparatus according to the use attribute and the maximum storage number of each medical apparatus in combination with a genetic algorithm, and determining a first storage position of each medical apparatus in the corresponding second storage area in combination with historical ex-warehouse data of each medical apparatus. Through the method and the device, the utilization rate of the warehouse space and the storage safety of the medical instruments under the dynamic warehouse condition can be improved, and meanwhile, the management efficiency of warehouse management personnel is reduced.

Description

Technical Field

[0001] The present application relates to the field of warehouse management, and in particular to a medical device storage management method, device, terminal equipment and storage medium. Background Art

[0002] With the widespread use of medical devices, the types and quantities of medical devices in warehouses are increasing. Traditional storage management methods for medical devices usually rely on manual operations or simple material classification systems, resulting in inefficient management. Especially in warehouse environments where storage conditions change dynamically on a large scale, it becomes increasingly difficult to rationally plan and quickly access storage locations. Such problems not only increase the cost of medical device management, but also delay the use of medical supplies in emergencies. In addition, due to the wide variety of medical devices and significant differences in their material properties, different medical devices require exclusive storage environments to prevent contamination. And different medical devices have different uses, resulting in different access frequencies for different medical devices.

[0003] When solving the above problems, the existing technology often ignores the future consumption and storage of medical devices. It only re-plans the placement of medical devices in the warehouse based on the current storage situation of the warehouse through mathematical planning methods, and adjusts the placement of medical devices in the warehouse according to the latest planning method. This method not only leads to a large manual load, but also has low warehouse management efficiency when facing dynamically changing storage conditions. At the same time, the existing technology often ignores the impact of the storage environment on medical devices, causing medical devices to be at risk of contamination, thereby reducing the safety of medical device storage.

[0004] Therefore, in actual operations, how to reasonably plan storage locations based on the properties of medical devices and dynamic consumption and storage conditions has become an important challenge to improve warehouse operation efficiency and ensure the storage safety of medical devices. Summary of the invention

[0005] The present application provides a medical device storage management method, apparatus, terminal device and storage medium to solve the technical problem of low warehouse operation efficiency and low medical device storage safety under dynamically changing storage conditions.

[0006] In order to solve the above technical problems, in a first aspect, an embodiment of the present application provides a medical device storage management method, comprising:

[0007] Obtaining historical outbound data of each medical device in the warehouse and order data of each medical device within a first preset time in the future, and determining the maximum storage quantity of each medical device based on the historical outbound data and the order data;

[0008] Clustering the medical devices according to the material properties of each medical device to obtain a plurality of first clusters, and determining a first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each first cluster includes a plurality of the medical devices;

[0009] According to the usage attributes of each of the medical devices, combined with a genetic algorithm, all the medical devices in each of the first clusters are clustered in turn to obtain a corresponding number of second clusters; wherein each of the second clusters includes a number of the medical devices;

[0010] According to the maximum storage quantity of each medical device, the corresponding first storage area is divided, the second storage area corresponding to each second cluster is obtained, and the first storage position of each medical device in the corresponding second storage area is determined in combination with the historical outbound data of each medical device.

[0011] Compared with the prior art, the embodiments of the present application have the following beneficial effects: by collecting the historical outbound data and future order data of medical devices, the fluctuation of the storage quantity of various types of medical devices in the warehouse in the future period of time is accurately evaluated, and effective space constraints are provided for subsequent space planning, thereby ensuring that the storage space is effectively utilized; in addition, by clustering the attributes of medical devices multiple times, hierarchical planning of storage space is realized, which effectively improves the calculation efficiency in the space planning process. Moreover, by clustering medical devices by material attributes, it is ensured that medical devices can be stored in a suitable storage environment, thereby improving the storage safety of medical devices; by further clustering medical devices by use attributes, a basis is provided for the subsequent detailed arrangement of storage locations, effectively improving the work efficiency of warehouse managers.

[0012] In some embodiments of the first aspect of the present application, determining the maximum storage quantity of each medical device according to the historical delivery data and the order data includes:

[0013] Predicting the consumption rate of each of the medical devices within the first preset time in the future based on all the historical outbound data;

[0014] According to all the order data, predict the warehousing speed of each of the medical devices within the first preset time in the future;

[0015] According to the consumption speed and the warehousing speed, the maximum storage quantity corresponding to the medical device is calculated.

[0016] Compared with the prior art, the above embodiment has the following beneficial effects: by acquiring historical outbound data, the future consumption rate of medical devices is predicted, and based on future order data, the future warehousing rate of medical devices is predicted, thereby dynamically estimating the storage quantity of medical devices in the warehouse at any time point in the future, accurately evaluating the maximum storage space that may be required for medical devices in the future, and effectively improving the space utilization of the warehouse in a dynamic warehouse state.

[0017] In some embodiments of the first aspect of the present application, the determining the first storage position of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device includes:

[0018] According to the consumption speed and the warehousing speed of each medical device, evaluating the unit quantity management load corresponding to each medical device;

[0019] Through a genetic algorithm, the first storage position of each medical device in the second cluster corresponding to the second storage area is optimized to minimize the difference in the total management load between the shelves; wherein the total management load of the shelves is calculated based on the number of medical devices stored on the corresponding shelves and the corresponding unit quantity management load.

[0020] Compared with the prior art, the above embodiment has the following beneficial effects: the second cluster includes a large number of medical devices with the same purpose but with specific differences, such as brand or medical grade. Different medical devices have different usage frequencies. If medical devices of different medical grades but with high usage frequencies are stored on the same shelf, it may cause the same shelf to have frequent consumption and warehousing operations at the same time per unit time, thereby reducing the efficiency of goods retrieval and warehousing in the warehouse. Therefore, by evaluating the frequency of each medical device entering and leaving the warehouse, the frequency of taking out and warehousing of medical devices on each shelf is averaged based on this, thereby improving the efficiency of warehouse management.

[0021] In some embodiments of the first aspect of the present application, the calculating the maximum storage quantity of the corresponding medical device according to the consumption speed and the storage speed includes:

[0022] The calculation formula of the maximum storage quantity is specifically:

[0023]

[0024] Among them, S i is the maximum storage quantity of medical device i; [T1, T2] is the interval of the first preset time in the future; v in,i (t) and v out,i (t) are the storage speed and consumption speed of medical device i in the first preset time in the future; Represents the maximum value of a function in the interval [T1, T2].

[0025] Compared with the prior art, the above embodiment has the following beneficial effects: by fitting the warehousing speed and consumption speed of medical devices in the future time period, the accurate storage quantity of medical devices in the warehouse at each time point is obtained, and the maximum storage quantity is accurately obtained by the method of finding extreme values ​​through integration, thereby improving the accuracy of subsequent area division.

[0026] In some embodiments of the first aspect of the present application, according to the usage attributes of each of the medical devices, in combination with a genetic algorithm, all the medical devices in each of the first clusters are clustered in turn to obtain a number of corresponding second clusters, including:

[0027] Calculate the similarity between the medical devices according to the semantic analysis tool and the usage attributes of the medical devices;

[0028] Determine the idle space of the shelf according to the maximum storage space of each shelf and the maximum storage quantity of each medical device;

[0029] A fitness function is constructed according to the similarity and the idle space of the shelf, and the fitness function is optimized through the genetic algorithm to obtain a plurality of second clusters.

[0030] Compared with the prior art, the above embodiment has the following beneficial effects: through semantic analysis tools, the similarities between medical devices are accurately evaluated; based on the maximum storage quantity of medical devices, the storage space required for medical devices is accurately evaluated; combined with the maximum storage space of the shelf, the idle space of the shelf is accurately evaluated; by optimizing the similarity and the idle space of the shelf, the rationality of the second clustering division result and the storage space utilization rate are dynamically balanced.

[0031] In some embodiments of the first aspect of the present application, constructing a fitness function according to the similarity and the idle space of the shelf includes:

[0032] The fitness function is specifically:

[0033]

[0034] Among them, ω1 and ω2 are weight coefficients; n k The second cluster G k is the number of types of medical devices; K is the number of the second cluster; sim(i,j) represents the similarity between medical device i and medical device j; V k The second cluster G k The storage space required for all medical devices in the system; V is the maximum storage space of the shelf; mod is the remainder operator.

[0035] Compared with the prior art, the above embodiment has the following beneficial effects: by maximizing the similarity between the medical devices in the second cluster and minimizing the total amount of idle space on each shelf, the second cluster can not only reasonably divide medical devices for different purposes, but also improve the utilization rate of shelf space.

[0036] In some embodiments of the first aspect of the present application, after determining the first storage position of each of the medical devices, it also includes: optimizing the first storage position of each medical device according to the current second storage position of each of the medical devices so that the sum of the adjustment distances of all the medical devices is minimized.

[0037] Compared with the prior art, the above-mentioned embodiments have the following beneficial effects: the present application obtains the first storage location by estimating the in-and-out data of the future time period in advance, so that the warehouse manager can adjust the medical equipment stored in the warehouse to the first storage location in advance. However, since some medical devices have already been stored in the warehouse, there may be a certain difference between the re-planned first storage location and the currently placed second storage location. By optimizing the first storage location again, the sum of the distances between the second storage location and the first storage location is minimized, thereby reducing the workload of the warehouse manager.

[0038] In a second aspect, an embodiment of the present application further provides a medical device storage management device, comprising: a first prediction module, a first clustering module, a second clustering module, and a first storage location determination module;

[0039] The first prediction module is used to obtain the historical outbound data of each medical device in the warehouse and the order data of each medical device within a first preset time in the future, and determine the maximum storage quantity of each medical device based on the historical outbound data and the order data;

[0040] The first clustering module is used to cluster the medical devices according to the material properties of each medical device, obtain a plurality of first clusters, and determine the first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each first cluster includes a plurality of the medical devices;

[0041] The second clustering module is used to cluster all the medical devices in each of the first clusters in turn according to the usage attributes of each of the medical devices in combination with a genetic algorithm to obtain a corresponding number of second clusters; wherein each of the second clusters includes a number of the medical devices;

[0042] The first storage location determination module is used to divide the corresponding first storage area according to the maximum storage quantity of each medical device, obtain the second storage area corresponding to each second cluster, and determine the first storage position of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device.

[0043] In a third aspect, the present application also provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the above-mentioned medical device storage management method when executing the computer program.

[0044] In a fourth aspect, the present application also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned medical device storage management method. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a flow chart of a medical device storage management method provided in some embodiments of the present application;

[0046] Figure 2 This is a structural schematic diagram of a medical device storage management device provided in some embodiments of the present application. DETAILED DESCRIPTION

[0047] When planning warehouse space, the existing technology often ignores the future consumption and storage of medical devices. It only re-plans the placement of medical devices in the warehouse based on the current storage situation of the warehouse through mathematical planning methods, and adjusts the placement of medical devices in the warehouse according to the latest planning methods. This method not only leads to a large manual load, but also has low warehouse management efficiency when facing dynamically changing storage conditions. At the same time, the existing technology often ignores the impact of the storage environment on medical devices, causing medical devices to be at risk of contamination, thereby reducing the safety of medical device storage.

[0048] In order to solve the above technical problems, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] Embodiment 1

[0050] Please refer to Figure 1, a medical device storage management method provided in an embodiment of the present application, including S10 to S40, specifically:

[0051] S10: Obtain historical delivery data of each medical device in the warehouse and order data of each medical device within a first preset time in the future, and determine the maximum storage quantity of each medical device based on the historical delivery data and the order data.

[0052] Furthermore, in some embodiments of the present application, determining the maximum storage quantity of each medical device according to the historical outbound data and the order data includes:

[0053] Predicting the consumption rate of each of the medical devices within the first preset time in the future based on all the historical outbound data;

[0054] According to all the order data, predict the warehousing speed of each of the medical devices within the first preset time in the future;

[0055] According to the consumption speed and the warehousing speed, the maximum storage quantity corresponding to the medical device is calculated.

[0056] By obtaining historical outbound data, the consumption rate of medical devices in the future is predicted, and based on future order data, the incoming stock rate of medical devices in the future is predicted, so as to dynamically estimate the storage quantity of medical devices in the warehouse at any point in the future, accurately evaluate the maximum storage space that may be required for medical devices in the future, and effectively improve the space utilization of the warehouse in a dynamic warehouse state.

[0057] Preferably, in some embodiments of the present application, the consumption rate of each medical device can be predicted by the following preferred implementations:

[0058] S11: Determine the first preset time in the future; here, a quarter may be preferentially selected as the first preset time in the future;

[0059] S12: Obtain the historical outbound data of each medical device in several historical years, and sort the historical outbound data in chronological order; if the first preset time selected in S11 is the third quarter, then obtain the historical outbound data of all third quarters of the previous three years;

[0060] S13: According to the SARIMA model, combined with the historical delivery data obtained in S12, the parameters of the non-seasonal part and the seasonal part of the SARIMA model corresponding to each medical device are fitted in turn to obtain the consumption rate of each medical device.

[0061] Preferably, in some embodiments of the present application, the warehousing speed can be fitted directly according to the order data through a linear fitting method; or the real order data can be directly called, and according to the time unit in the order data, the continuous time variables involved in the consumption speed obtained by fitting S11 to S13 are replaced with discrete time variables with the above time units as intervals.

[0062] Preferably, in some embodiments of the present application, the calculating the maximum storage quantity of the corresponding medical device according to the consumption speed and the storage speed includes:

[0063] The calculation formula of the maximum storage quantity is specifically:

[0064]

[0065] Among them, S i is the maximum storage quantity of medical device i; [T1, T2] is the interval of the first preset time in the future; v in,i (t) and v out,i (t) are the storage speed and consumption speed of medical device i in the first preset time in the future; Represents the maximum value of a function in the interval [T1, T2].

[0066] Specifically, when the time variable t in the above formula is a continuous variable, directly replace the function v in,i (t)-v out,i (t) is integrated to obtain the function of the change in the storage quantity of medical devices in the warehouse, and to obtain the maximum value of the function of the change in the storage quantity within the first preset time in the future. When the time variable t in the above formula is a discrete variable, the number of medical devices stored in the warehouse in each discrete time period is obtained according to the order data. If the order is in days, the discrete time period is one day; further, by integrating v in,i (t), calculate the consumption of medical devices in the discrete time period; combine the inventory quantity and consumption of medical devices in each discrete time period to calculate the storage quantity of medical devices at the end of each discrete time period; obtain the maximum storage quantity from all discrete time periods.

[0067] S20: Clustering the medical devices according to the material properties of each of the medical devices to obtain a plurality of first clusters, and determining a first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each of the first clusters includes a plurality of the medical devices.

[0068] Preferably, in some embodiments of the present application,

[0069] S30: Clustering all medical devices in each of the first clusters in turn according to the usage attributes of each of the medical devices in combination with a genetic algorithm to obtain a corresponding number of second clusters; wherein each of the second clusters includes a number of the medical devices.

[0070] Furthermore, in some embodiments of the present application, according to the usage attributes of each of the medical devices, in combination with a genetic algorithm, all the medical devices in each of the first clusters are clustered in turn to obtain a number of corresponding second clusters, including:

[0071] Calculate the similarity between the medical devices according to the semantic analysis tool and the usage attributes of the medical devices;

[0072] Determine the idle space of the shelf according to the maximum storage space of each shelf and the maximum storage quantity of each medical device;

[0073] A fitness function is constructed according to the similarity and the idle space of the shelf, and the fitness function is optimized through the genetic algorithm to obtain a plurality of second clusters.

[0074] Through semantic analysis tools, the similarities between medical devices are accurately evaluated. The storage space required for medical devices is accurately evaluated based on the maximum storage quantity of medical devices. Combined with the maximum storage space of the shelf, the idle space on the shelf is accurately evaluated. By optimizing similarities and idle space on the shelf, the rationality of the second clustering results and the utilization of storage space are dynamically balanced.

[0075] Preferably, in some embodiments of the present application, the text embedding vector of each medical device usage attribute can be obtained by any semantic analysis method, and the cosine similarity between any two corresponding text embedding vectors of medical devices can be calculated as a measure of similarity.

[0076] Preferably, in some embodiments of the present application, the chromosome of the genetic algorithm can be constructed by the following preferred implementations:

[0077] chromosome=[random[h k ],random[h k ],…,random[h k ]]

[0078] Among them, chromosome is a randomly generated chromosome; random[h k ] is a chromosome gene, and its physical meaning represents which cluster the medical device corresponding to the gene belongs to. The value is in the interval [1,h k ] are randomly generated between kis a parameter set artificially, representing the number of the second cluster. Assuming random[h k ]=1, it means that the current corresponding medical device belongs to the first second cluster; a chromosome contains l k Gene random[h k ],l k is the first cluster L k The number of types of medical devices in the industry. Through a chromosome, we can determine the number of types of medical devices in the industry. k The second cluster corresponding to various medical devices.

[0079] Preferably, in some embodiments of the present application, each medical device has a corresponding minimum occupied storage space. By multiplying the maximum storage quantity by the minimum occupied storage space, the required maximum storage space corresponding to any medical device can be obtained. After the division scheme of the second cluster is obtained, medical devices with different uses will not be placed on the same shelf. Therefore, after the medical devices with the same purpose are placed, there will be a part of idle space left on the last shelf. The total storage space occupied by all medical devices in each second cluster can be calculated based on the maximum storage space of various medical devices, which serves as the basis for the subsequent calculation of the idle space of the shelf. The total storage space occupied by each specific second cluster can be obtained by the following calculation formula:

[0080]

[0081] Among them, S i is the maximum storage quantity of medical device i; V k,i The second cluster G k The minimum storage space occupied by each medical device i; V k The second cluster G k The storage space required for all medical devices.

[0082] Preferably, in some embodiments of the present application, constructing a fitness function according to the similarity and the idle space of the shelf includes:

[0083] The fitness function is specifically:

[0084]

[0085] Among them, ω1 and ω2 are weight coefficients; n k The second cluster G k is the number of types of medical devices; K is the number of the second cluster; sim(i,j) represents the similarity between medical device i and medical device j; V k The second cluster G kThe storage space required for all medical devices in the system; V is the maximum storage space of the shelf; mod is the remainder operator.

[0086] Through the above preferred embodiment, there is no need to decode the chromosome, and the fitness function is directly optimized through the existing genetic algorithm combined with the above chromosome generation method to obtain the optimal feasible solution.

[0087] S40: Divide the first storage area corresponding to each medical device according to the maximum storage quantity of each medical device, obtain the second storage area corresponding to each second cluster, and determine the first storage position of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device.

[0088] Preferably, in some embodiments of the present application, after determining the first storage area corresponding to each first cluster, the storage area of ​​the second cluster G is determined according to the above preferred embodiment. k Storage space required for all medical devices in V k , so as to determine the number of shelves required, and the size of each second storage area can be known accordingly. The specific corresponding position of each second storage area can be combined with the use of the medical devices corresponding to each second cluster to evaluate its priority. This application does not limit the optimization of the specific corresponding position of each second storage area, but it is necessary to ensure the continuity of each second storage area.

[0089] Further, in some embodiments of the present application, combining the historical outbound data of each medical device to determine the first storage position of each medical device in the corresponding second storage area includes:

[0090] According to the consumption speed and the warehousing speed of each medical device, evaluating the unit quantity management load corresponding to each medical device;

[0091] Through a genetic algorithm, the first storage position of each medical device in the second cluster corresponding to the second storage area is optimized to minimize the difference in the total management load between the shelves; wherein the total management load of the shelves is calculated based on the number of medical devices stored on the corresponding shelves and the corresponding unit quantity management load.

[0092] The second cluster includes a large number of medical devices with the same purpose but with specific differences, such as brand or medical grade. Different medical devices have different usage frequencies. If medical devices of different medical grades but with high usage frequencies are stored on the same shelf, it may cause the same shelf to have frequent consumption and warehousing operations at the same time per unit time, thereby reducing the efficiency of goods retrieval and warehousing in the warehouse. Therefore, by evaluating the frequency of each medical device entering and leaving the warehouse, the frequency of taking out and warehousing of medical devices on each shelf is averaged to improve warehouse management efficiency.

[0093] Preferably, in some embodiments of the present application, the unit quantity management load corresponding to each medical device can directly take the sum of the consumption speed and the storage speed as the unit quantity management load of the corresponding medical device; or calculate the average daily storage and retrieval amount of the corresponding medical device in the first preset time in the future through the consumption speed and the storage speed, as the unit quantity management load of the corresponding medical device; or sort the medical devices according to the sum of the consumption speed and the storage speed, assign corresponding weights according to the order of priority, and use the weights as the unit quantity management load of the medical device. The above method is only an example, and the present application does not limit how to evaluate the unit quantity management load of the corresponding medical device according to the consumption speed and the storage speed.

[0094] Preferably, in some embodiments of the present application, when optimizing the first storage location by a genetic algorithm, a corresponding number may be set for each storage location, and a chromosome may be generated according to the following example:

[0095] chromosome=[random[G k ],random[G k ],…,random[G k ]]

[0096] Assuming that each row of each shelf is a storage location, the length of each chromosome (also the number of genes) is the total number of storage locations in the corresponding second region, and random[G k ] represents the second cluster G k A medical device is randomly selected from the k ] is the i-th gene in the chromosome, which means that the i-th number corresponds to the storage location where random[G k ]A medical device randomly selected. At the same time, when optimizing the difference in the total management load between shelves through genetic algorithms, constraints need to be set so that the storage space allocated to each medical device can meet the requirements of its maximum storage quantity.

[0097] Furthermore, in some embodiments of the present application, after determining the first storage position of each of the medical devices, it also includes: optimizing the first storage position of each medical device according to the current second storage position of each of the medical devices so that the sum of the adjustment distances of all the medical devices is minimized.

[0098] The present application obtains the first storage location by estimating the in-and-out data of the future time period in advance, so that the warehouse manager can adjust the medical equipment stored in the warehouse to the first storage location in advance. However, since some medical devices have already been stored in the warehouse, there may be a certain difference between the re-planned first storage location and the currently placed second storage location. By optimizing the first storage location again, the sum of the distances between the second storage location and the first storage location is minimized, thereby reducing the workload of the warehouse manager.

[0099] Preferably, in some embodiments of the present application, when adjusting the second storage location, it is necessary to ensure that the second storage location cannot be adjusted from the second area to which it currently belongs to to other second areas.

[0100] In summary, it can be seen that the medical device storage management method provided by the embodiment of the present application has the following beneficial effects: by collecting the historical outbound data and future order data of medical devices, the fluctuation of the storage quantity of various types of medical devices in the warehouse in the future period of time is accurately evaluated, and effective space constraints are provided for subsequent space planning, thereby ensuring that the storage space is effectively utilized; in addition, by clustering the attributes of medical devices multiple times, hierarchical planning of storage space is realized, and the calculation efficiency in the space planning process is effectively improved. Moreover, by clustering medical devices by material attributes, it is ensured that medical devices can be stored in a suitable storage environment, thereby improving the storage safety of medical devices; by further clustering medical devices by use attributes, a basis is provided for the subsequent arrangement of detailed storage locations, effectively improving the work efficiency of warehouse managers.

[0101] Embodiment 2

[0102] refer to Figure 2 , a medical device storage management device provided in an embodiment of the present application, includes: a first prediction module 11, a first clustering module 12, a second clustering module 13 and a first storage location determination module 14.

[0103] Further, in some embodiments of the present application, the first prediction module 11 is used to obtain the historical outbound data of each medical device in the warehouse, and the order data of each medical device within the first preset time in the future, and determine the maximum storage quantity of each medical device based on the historical outbound data and the order data; the first clustering module 12 is used to cluster the medical devices according to the material properties of each medical device, obtain a plurality of first clusters, and determine the first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each first cluster includes a plurality of medical devices; the second clustering module 13 is used to cluster all the medical devices in each first cluster in turn according to the use attributes of each medical device, combined with a genetic algorithm, to obtain a plurality of corresponding second clusters; wherein each second cluster includes a plurality of medical devices; the first storage position determination module 14 is used to divide the corresponding first storage area according to the maximum storage quantity of each medical device, obtain the second storage area corresponding to each second cluster, and determine the first storage position of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device.

[0104] It can be understood that the above-mentioned device item embodiments correspond to the method item embodiments of the present invention. A medical device storage management device provided by the embodiments of the present invention can implement any method item embodiment of the present invention, that is, the medical device storage management method provided in Embodiment 1.

[0105] In summary, it can be seen that the medical device storage management device provided by the embodiment of the present application has the following beneficial effects: by collecting the historical outbound data and future order data of medical devices, the fluctuation of the storage quantity of various types of medical devices in the warehouse in the future period of time is accurately evaluated, and effective space constraints are provided for subsequent space planning, thereby ensuring that the storage space is effectively utilized; in addition, by clustering the attributes of medical devices multiple times, hierarchical planning of storage space is realized, and the calculation efficiency in the space planning process is effectively improved. Moreover, by clustering medical devices by material attributes, it is ensured that medical devices can be stored in a suitable storage environment, thereby improving the storage safety of medical devices; by further clustering medical devices by use attributes, a basis is provided for the subsequent arrangement of detailed storage locations, effectively improving the work efficiency of warehouse managers.

[0106] Embodiment 3

[0107] Based on the above-mentioned embodiment of the medical device storage management method, another embodiment of the present application provides a medical device storage management terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the medical device storage management method of any embodiment of the present application is implemented.

[0108] Exemplarily, in this embodiment, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the medical device storage management device.

[0109] The medical device storage management device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The medical device storage management terminal device may include, but is not limited to, a processor and a memory.

[0110] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the medical device storage management device, and uses various interfaces and lines to connect the various parts of the entire medical device storage management device. The memory may be used to store the computer program and / or module, and the processor implements various functions of the medical device storage management device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0111] Embodiment 4

[0112] Based on the above-mentioned embodiments of the medical device storage management method, another embodiment of the present application provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the medical device storage management method of any embodiment of the present application.

[0113] In this embodiment, the storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0114] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A medical device storage management method, characterized in that: include: Obtaining historical outbound data of each medical device in the warehouse and order data of each medical device within a first preset time in the future, and determining the maximum storage quantity of each medical device based on the historical outbound data and the order data; Clustering the medical devices according to the material properties of each medical device to obtain a plurality of first clusters, and determining a first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each first cluster includes a plurality of the medical devices; According to the usage attributes of each of the medical devices, combined with a genetic algorithm, all the medical devices in each of the first clusters are clustered in turn to obtain a corresponding number of second clusters; wherein each of the second clusters includes a number of the medical devices; According to the maximum storage quantity of each medical device, the corresponding first storage area is divided, the second storage area corresponding to each second cluster is obtained, and the first storage position of each medical device in the corresponding second storage area is determined in combination with the historical outbound data of each medical device.

2. A medical device storage management method as claimed in claim 1, characterized in that: Determining the maximum storage quantity of each medical device according to the historical outbound data and the order data includes: Predicting the consumption rate of each of the medical devices within the first preset time in the future based on all the historical outbound data; According to all the order data, predict the warehousing speed of each of the medical devices within the first preset time in the future; According to the consumption speed and the warehousing speed, the maximum storage quantity corresponding to the medical device is calculated.

3. A medical device storage management method as claimed in claim 2, characterized in that: The determining of the first storage location of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device includes: According to the consumption speed and the warehousing speed of each medical device, evaluating the unit quantity management load corresponding to each medical device; Through a genetic algorithm, the first storage position of each medical device in the second cluster corresponding to the second storage area is optimized to minimize the difference in the total management load between the shelves; wherein the total management load of the shelves is calculated based on the number of medical devices stored on the corresponding shelves and the corresponding unit quantity management load.

4. A medical device storage management method as claimed in claim 2, characterized in that: The calculating the maximum storage quantity of the corresponding medical device according to the consumption speed and the storage speed includes: The calculation formula of the maximum storage quantity is specifically: Among them, S i is the maximum storage quantity of medical device i; [T1, T2] is the interval of the first preset time in the future; v in,i (t) and v out,i (t) are the storage speed and consumption speed of medical device i in the first preset time in the future; Represents the maximum value of a function in the interval [T1, T2].

5. A medical device storage management method as claimed in claim 1, characterized in that: According to the usage attributes of each of the medical devices, combined with a genetic algorithm, all the medical devices in each of the first clusters are clustered in turn to obtain a number of corresponding second clusters, including: Calculate the similarity between the medical devices according to the semantic analysis tool and the usage attributes of the medical devices; Determine the idle space of the shelf according to the maximum storage space of each shelf and the maximum storage quantity of each medical device; A fitness function is constructed according to the similarity and the idle space of the shelf, and the fitness function is optimized through the genetic algorithm to obtain a plurality of second clusters.

6. A medical device storage management method as claimed in claim 5, characterized in that: The constructing of a fitness function according to the similarity and the idle space of the shelf includes: The fitness function is specifically: Among them, ω1 and ω2 are weight coefficients; n k The second cluster G k is the number of types of medical devices; K is the number of the second cluster; sim(i,j) represents the similarity between medical device i and medical device j; V k The second cluster G k The storage space required for all medical devices in the system; V is the maximum storage space of the shelf; mod is the remainder operator.

7. A medical device storage management method as claimed in claim 1, characterized in that: After the first storage position of each medical device is determined, the method further includes: optimizing the first storage position of each medical device according to the current second storage position of each medical device so as to minimize the sum of the adjustment distances of all the medical devices.

8. A medical device storage management device, characterized in that: include: A first prediction module, a first clustering module, a second clustering module, and a first storage location determination module; The first prediction module is used to obtain the historical outbound data of each medical device in the warehouse and the order data of each medical device within a first preset time in the future, and determine the maximum storage quantity of each medical device based on the historical outbound data and the order data; The first clustering module is used to cluster the medical devices according to the material properties of each medical device, obtain a plurality of first clusters, and determine the first storage area corresponding to each first cluster according to the maximum storage quantity of each medical device; wherein each first cluster includes a plurality of the medical devices; The second clustering module is used to cluster all the medical devices in each of the first clusters in turn according to the usage attributes of each of the medical devices in combination with a genetic algorithm to obtain a corresponding number of second clusters; wherein each of the second clusters includes a number of the medical devices; The first storage location determination module is used to divide the corresponding first storage area according to the maximum storage quantity of each medical device, obtain the second storage area corresponding to each second cluster, and determine the first storage position of each medical device in the corresponding second storage area in combination with the historical outbound data of each medical device.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a medical device storage management method as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute a medical device storage management method as described in any one of claims 1 to 7.

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