Intelligent pharmacy system based on informatization management and intelligent control

Abstract

An intelligent pharmacy system based on informatization management and intelligent control can accurately and efficiently manage medicine storage and distribution work of a hospital pharmacy. After the system is used, the management mode of the pharmacy is thoroughly changed. Traditional result guidance is converted into process guidance; data entry is converted into data acquisition, and meanwhile, an original data entry mode is compatible; manual medicine finding is changed into guiding and positioning medicine taking; and meanwhile, the monitoring platform is introduced, so that management is more efficient and faster, the process is fine and controllable, and the result is correct.

Description

Technical Field

[0001] The present invention relates to the technical field of pharmaceutical storage and distribution, and specifically to a smart pharmacy system based on information management and intelligent control. Background Art

[0002] At present, there are approximately more than 20,000 kinds of drugs worldwide. There are about 5,000 kinds of traditional Chinese medicine preparations and about 4,000 kinds of western medicine preparations in China, with a diverse variety. The traditional drug access work mainly relies on pharmacies. Pharmacy management includes three links: drug entry (drug warehousing), drug storage, and drug dispensing (drug picking, warehousing, and distribution).

[0003] However, the following pain points exist in traditional pharmacy management and need to be solved urgently: First, drug entry relies on manual labor. Pharmacists need to classify, store, and record a wide variety of drugs, with cumbersome procedures and heavy workloads. Second, traditional pharmacies adopt a shelf placement form, with outdated related facilities and equipment and low space utilization. In addition, due to the simple function mode of traditional hospital pharmacies, which is just to receive prescriptions and dispense drugs, grass-roots pharmacists have a large prescription adjustment dose and high work intensity, play a limited role in drug guidance, and also prolong the waiting time for patients to pick up drugs. Most critically, manual management may cause errors during drug entry, inventory checking, and drug dispensing. Statistical data released by authoritative institutions show that the error rate of manual pharmacies is about six per thousand.

[0004] With the development and popularization of intelligent and automated technologies, the intelligentization, informatization, and automation of hospital pharmacies have become an important development trend. Summary of the Invention

[0005] In view of the above background art, a smart pharmacy system based on information management and intelligent control is proposed, which can accurately and efficiently manage the drug storage and distribution work in hospital pharmacies. After use, the management mode of the pharmacy has changed from the traditional result orientation to process orientation, from data entry to data collection, while being compatible with the original data entry method, from manual drug searching to guided positioning drug picking, and at the same time introducing a monitoring platform to make management more efficient, fast, with a fine and controllable process and correct results.

[0006] A smart pharmacy system based on information management and intelligent control is composed of a software system, hardware devices, and a pharmacy mode process;

[0007] The software system includes an Intelligent Pharmacy Management System (IPMS), an Intelligent Pharmacy Equipment Control System (IPCS), and a drive control program (PLC program); IPMS issues management tasks to IPCS, and then controls the operation of hardware devices through PLC; the hardware devices are the devices in the pharmacy;

[0008] The pharmacy mode process includes the following steps:

[0009] S1: After the patient sees the doctor, the hospital information system HIS obtains the doctor's prescription information, patient information and fee information;

[0010] S2: The smart pharmacy IPMS receives medication information through integration with the HIS interface, and completes the picking and delivery of drugs through picking route planning based on the minimum time cost;

[0011] S3: The patient reports to the registration machine, and after verification by the pharmacist at the designated window, prints the medication order and completes the medication collection;

[0012] S4: The pharmacy system conducts real-time inventory counting, maintains and controls the inventory of pharmacy drugs, and has the functions of reminding of approaching expiration dates and warning of insufficient drug inventory. The entry, storage and exit of drugs are automatically completed by hardware equipment through barcode management.

[0013] The beneficial effects achieved by the present invention are:

[0014] (1) Real-time and continuous collection of pharmacy data, precise management of the process, fully automated and intelligent operation, storage and analysis of the formed big data, generation of visual reports that are easy to understand, providing strong data support for pharmacy management personnel, and permanent backup of data, promoting the informatization and automation construction of the hospital; (2) Precise positioning management of drug storage locations, comprehensive monitoring of status, and accurate inventory data; (3) Drug warehousing, shelving, distribution, and inventory counting are all fully automated by intelligent devices; (4) Improve the efficiency of dispensing and drug distribution, greatly shorten the waiting queue time of patients, and enhance the patient experience and the service quality of the hospital; (5) Optimize the process, improve the operation efficiency of the pharmacy and the work efficiency of pharmacists, reduce the error rate in each link, improve the accuracy and safety of drug distribution, and fully guarantee the medication safety of patients; (6) Liberate pharmacists from a large number of repetitive and unskilled heavy tasks and focus on providing better medication guidance services; (7) Precise management of drug expiration dates, with intelligent reminder functions for approaching expiration dates, and can automatically pick and distribute according to the principle of first-in, first-out, realizing the prior distribution of near-expiration drugs and automatically locking expired drugs; (8) Real-time control of inventory status, timely issuance of replenishment reminders, and reasonable maintenance and control of pharmacy drug inventory; (9) Through automatic collection of batch information, provide historical record analysis, and the drug storage and distribution processes are traceable; (10) Barcode management promotes the transformation of the pharmacy management mode from relying on traditional experience management to relying on precise digital analysis management, from ex post management to in-process management and real-time management; (11) Adopt high-density storage technology to meet the largest possible drug storage volume with a small floor area, greatly improve the space utilization rate of drug storage, save resources, and make the limited space cleaner; (12) Have sufficient scalability, can be integrated with the interfaces of existing medical systems to achieve seamless connection, and thus be integrated into the overall informatization system of the hospital and operate in coordination with other systems. Description of the Drawings

[0015] Figure 1 It is the system architecture diagram of the intelligent pharmacy system described in the embodiment of the present invention.

[0016] Figure 2 It is the logic block diagram of single-box drug warehousing described in the embodiment of the present invention.

[0017] Figure 3 It is the logic block diagram of multi-box drug warehousing described in the embodiment of the present invention.

[0018] Figure 4 It is the logic block diagram of medicine bottle warehousing described in the embodiment of the present invention.

[0019] Figure 5 It is the logic block diagram of the warehousing of agreement unpacked drugs described in the embodiment of the present invention.

[0020] Figure 6 This is the drug shelving logic block diagram described in the embodiments of the present invention.

[0021] Figure 7 This is the drug removal and outbound warehouse logic block diagram described in the embodiments of the present invention.

[0022] Figure 8 This is the flowchart of the drug dispensing mode of the intelligent pharmacy system described in the embodiments of the present invention.

[0023] Figure 9 This is the drug collection flowchart described in the embodiments of the present invention.

[0024] Figure 10 This is the three-dimensional view of the front structure of the trolley described in the embodiments of the present invention.

[0025] Figure 11 This is the three-dimensional view of the back structure of the trolley described in the embodiments of the present invention.

[0026] Figure 12 This is the schematic diagram of the XZ-axis frame structure described in the embodiments of the present invention.

[0027] Figure 13 This is the example diagram of the T-axis described in the embodiments of the present invention.

[0028] Figure 14 This is the overall structure diagram of the hardware system described in the embodiments of the present invention.

[0029] In the figure, 1 - telescopic plate, 2 - guide rod, 3 - K axis, 4 - clamping rod, 5 - Y-axis drive, 6 - temporary storage bin door, 7 - trolley temporary storage bin conveyor belt, 8 - trolley, 9 - X-axis overhead rail, 10 - X-axis ground rail, 11 - Z axis, 12 - T axis, 13 - storage shelf, 14 - outer cover sheet metal, 15 - inbound automatic door, 16 - inbound automatic conveyor line, 17 - outbound automatic conveyor line, 18 - inbound operation table, 19 - touch screen, 20 - spiral drug delivery mechanism. Detailed implementation manners

[0030] The technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings of the specification.

[0031] The intelligent pharmacy system consists of software, hardware, and pharmacy mode processes, and its architecture refers to Figure 1, including a planning layer (the HIS / SAP / ERP system of the hospital), a management layer (IPMS), a control layer (IPCS), and a device layer. The software refers to the software part that supports the operation of the entire system, including IPMS, IPCS, and drive control programs (PLC programs). Among them, IPMS is the abbreviation of Intelligent Pharmacy Management System; IPCS is the abbreviation of Intelligent Pharmacy Control System, and can also be called the intelligent pharmacy equipment scheduling system. The hardware refers to all the mechanical and electronic hardware devices of the entire system, including intelligent manipulators, storage shelves 13, inbound automatic doors 15, inbound automatic conveyor lines 16, outbound automatic conveyor lines 17, outer cover sheet metal 14, high-frequency barcode scanners, various sensors, ultrasonic three-dimensional measurement modules, visual monitoring devices, temperature and humidity monitors, etc. The pharmacy mode process refers to a set of management concepts and processes integrated according to the actual situation, management methods, and concepts of the vast majority of hospital pharmacies, that is, the drug dispensing mode process of the intelligent pharmacy (as shown in Figure 8 shown).

[0032] Figure 1 Among them, it also includes a data analysis platform and a device monitoring system. The data analysis platform can collect, store, and analyze various data of IPMS in the management layer. The device monitoring system is mainly communicatively connected to IPCS and PLC programs to monitor the operating status of all devices in the control layer.

[0033] IPMS is a real-time computing software used to provide standardized and intelligent process-oriented management for hospital pharmacies. IPMS can, according to the operating business rules and algorithms, through functions such as inbound management, inventory management, outbound management, task management, query statistics, log management, permission management, configuration management, basic information management, and report management, manage information, resources, behaviors, and the pharmacy operation process more perfectly, thereby improving efficiency. This system can operate independently or be integrated with the interfaces of systems such as the hospital information system HIS, enterprise management software SAP, and enterprise resource planning ERP to achieve seamless connection, thereby providing a more perfect management process for hospital pharmacies. The specific functions of IPMS are as follows:

[0034] (1) Inbound management: inbound information, shelving management; IPMS automatically calculates the best shelving location by sorting according to priority based on the location and remaining space of the same variety or type of drugs already stored, following the principles of first in, first out, avoiding waste of storage space, and the highest picking and distribution efficiency.

[0035] (2) Inventory Management: Inventory warning, inventory query, in - warehouse inventory count, inventory adjustment; The system supports automatic replenishment. Through the automatic replenishment algorithm, it ensures a reasonable inventory level, improves the utilization rate of warehouse space, and reduces the probability of the occurrence of cargo location honeycombing. The system can logically subdivide and dynamically set cargo locations through depth information without affecting automatic replenishment.

[0036] (3) Out - bound Management: Out - bound information, shelf - taking management, emergency out - bound; The picking instruction contains location information and optimal path planning. According to the layout of cargo locations, it determines the picking order, avoids ineffective shuttling and medicine searching, and improves the picking quantity per unit time.

[0037] (4) Task Management: Issuing, recycling, and re - distributing tasks.

[0038] (5) Query and Statistics: Querying inbound and outbound operations, other operations, inventory, cargo locations, and various reports.

[0039] (6) Log Management: Recording all operation contents of users and all running data of the system.

[0040] (7) Permission Management: Role management, permission allocation, password management.

[0041] (8) Configuration Management: Management of inbound and outbound cargo location allocation strategies.

[0042] (9) Report Management: Inbound and outbound statistical tables, inventory reports.

[0043] (10) Basic Information Management: Management of medicines, cargo locations, personnel, equipment, and information. IPMS can be used to set basic information such as the name, specification, manufacturer, traceability code, product batch number, production date, and expiration date of medicines. It includes a cargo location management function, which encodes all cargo locations and transmits them to the system's database, enabling the system to effectively track the location of medicines and guiding the intelligent manipulator to quickly locate.

[0044] IPCS is a pharmacy equipment control system between IPMS and the underlying drive control program (PLC program). On the one hand, IPCS receives tasks issued by IPMS, distributes tasks to devices such as intelligent manipulators, inbound automatic door 15, inbound automatic conveyor line 16, and outbound automatic conveyor line 17, and issues instructions to the underlying PLC to drive the above - mentioned automation devices to act. On the other hand, IPCS feeds back the task execution status and data of the underlying PLC system to IPMS in real - time, conducts information interaction with IPMS, and all historical records of operations and instructions are traceable. Please refer to Figure 2 、 Figure 3 、 Figure 4 、 Figure 5The present invention provides a logic block diagram for the storage of single-box medicines, a logic block diagram for the storage of multiple-box medicines, a logic block diagram for the storage of medicine bottles, and a logic block diagram for the storage of medicines unpacked by agreement. Figure 2 - 5 Flow in

[0045] The specific functions of IPCS are as follows:

[0046] (1) Provide interface debugging for PLC program;

[0047] (2) Automatically assign tasks issued by IPMS;

[0048] (3) Manage and schedule various underlying devices;

[0049] (4) Real-time monitoring of PLC system status and data;

[0050] (5) Multi-threaded processing and efficient operation.

[0051] The drive control program (PLC program) is used to directly control various automation equipment, sensors, instruments, etc. in the equipment layer. In the smart pharmacy system, the equipment directly controlled by the PLC program includes: intelligent manipulator, automatic storage door 15, automatic storage conveyor line 16, automatic storage conveyor line 17, high-frequency scanner, various sensors, ultrasonic three-dimensional measurement module, visual monitoring equipment, temperature and humidity monitoring instrument, etc. Please refer to Figure 6 , Figure 7 The present invention provides a logic block diagram of putting medicines on shelves and a logic block diagram of taking medicines off shelves and out of warehouse in a PLC program.

[0052] The hardware system includes intelligent manipulators, storage shelves 13, automatic storage doors 15, automatic storage conveyor lines 16, automatic storage conveyor lines 17, outer cover sheet metal 14, high-frequency barcode scanners, various sensors, ultrasonic three-dimensional measurement modules, visual monitoring equipment, temperature and humidity monitoring instruments, etc. The specific functions of each hardware device are as follows:

[0053] (1) Intelligent manipulator: multi-dimensional movement, positioning and access; used to replace manual labor to access medicines on the storage shelf 13, including light and heavy intelligent manipulators, used for accessing different quantities of medicines. It can achieve four-dimensional movement and is equipped with a safety limit system. The operation process will not cause harm to people, equipment and medicines. Figures 10 - 11 The trolley 8 has a telescopic plate 1, a guide rod 2, a K-axis 3, a clamping rod 4, a Y-axis drive 5, a temporary storage door 6, and a trolley temporary storage conveyor belt 7. The trolley temporary storage conveyor belt 7 stores the medicines in the storage space inside the vehicle body and limits the position through the temporary storage door 6. The K-axis 3 drives the clamping rod 4 to open or retract laterally, and the telescopic plate 1 and the guide rod 2 work together to realize the pushing out or storage of the medicine box. For the specific working process of the trolley, please refer to Figures 6 - 7 .

[0054] In addition, the trolley 8 is installed in the XZ-axis frame set in the pharmacy. Refer to Figures 12 - 13 , this frame includes the X-axis overhead rail 9, the X-axis ground rail 10, and the Z-axis 11, as well as the T-axis 12 set on the Z-axis. The trolley 8 can move according to each axis to complete the work of loading or unloading drugs from the storage shelf 13 in its own warehouse.

[0055] (2) Storage shelf 13: High-density storage of drugs; composed of side plates and bearing plates, with several slots provided on the side plates; during use, one end of the bearing plate is directly inserted into the slot without welding or fastener connection, which is convenient and quick to install. It can store 2000 - 6000 boxes of drugs per linear meter and also supports the storage of medicine bottles.

[0056] (3) Outer cover sheet metal 14: Fixed structure for easy operation; used to fix and protect the internal structure of the equipment. At the same time, considering ergonomic design and potential safety hazards, it ensures that the equipment is easy to operate, comfortable, safe and reliable.

[0057] (4) Inbound automatic door 15: Can automatically open to allow drugs to enter automatically; installed at the entrance of the conveyor belt of the drug shelf, used to receive the tasks issued by the IPMS management system and control the opening or closing and the opening height of the automatic door.

[0058] (5) Inbound automatic conveying line 16: Drug detection, automatic sorting, and conveying into the warehouse; used for high-speed drug warehousing. Under the guidance of the automatic replenishment algorithm, after the three-dimensional detection of the medicine box and the double verification of the barcode are correct, the automatic sorting and warehousing of drugs are realized by using the conveyor belt and the manipulator (trolley).

[0059] (6) Outbound automatic conveying line 17: Medicine verification for outbound, automatic drug dispensing; after being detected and verified by the system software, the drugs are precisely clamped by the manipulator (trolley), and then pass through the conveyor belt and the spiral drug discharging mechanism 20 in sequence, and descend and convey along the spiral surface under the action of gravity.

[0060] (7) High-frequency barcode scanner: Barcode scanning, data collection; used for original data collection, scanning the barcode on the outer package of drugs, identifying and inputting product information to improve management efficiency.

[0061] (8) Various sensors: Information perception, auxiliary control; the sensors convert the measured signals into electrical signals or other required forms of signals according to certain rules and feedback them to the system management software to realize the functions of automatic detection and automatic control.

[0062] (9) Ultrasonic three-dimensional measurement module: Three-dimensional detection, medicine box counting; by sending and receiving ultrasonic waves, using the time difference and the sound propagation speed, three-dimensional detection of the module is carried out, and the number of inbound medicine boxes is automatically calculated.

[0063] (10) Visual monitoring device: Monitor the working process of the device and the human-computer interaction status.

[0064] (11) Temperature and humidity monitor: Monitor and record the temperature and humidity data of drug storage.

[0065] Combined with Figure 14 , the high-frequency barcode scanner can be integrated into the warehousing operation console 18 and operated and controlled through the touch screen 19. In addition, various sensors, ultrasonic three-dimensional measurement modules, visual monitoring devices, and temperature and humidity monitors can be installed inside the warehouse, and the monitoring information can be displayed and the working status can be controlled through the warehousing operation console 18 and the touch screen 19.

[0066] Please refer to Figure 8 , the drug dispensing mode process of the intelligent pharmacy system includes the following steps:

[0067] S1: After the patient sees a doctor, the hospital HIS obtains the prescription information, patient information, and charging information issued by the doctor;

[0068] S2: The intelligent pharmacy IPMS is integrated with the HIS interface and incorporated into the overall hospital information system. It receives the medication information, follows the first-in, first-out principle, and completes the picking and outbound of drugs;

[0069] S3: The patient reports at the reporting machine. After being checked by the pharmacist at the designated window and found to be correct, the medication list is printed and the medication is taken;

[0070] S4: The pharmacy system conducts real-time inventory checks, reasonably maintains and controls the inventory of drugs in the pharmacy, has a reminder for approaching expiration dates and a warning for insufficient drug inventory. The drug warehousing and shelving are automatically completed by intelligent devices through barcode management.

[0071] In traditional pharmacies, decisions are mainly made based on people's subjective experience, while the decisions in intelligent pharmacies rely on intelligent algorithms. During the operation of the intelligent pharmacy system, a large amount of prescription information, drug information, location information, storage information, equipment information, control instruction information, etc. will be generated. The information is large in quantity, diverse in type, and strong in dynamics. The "intelligence" of the intelligent pharmacy system is to intelligently perceive, process, and make decisions on this information in the pharmacy through the application of information recognition technology, intelligent algorithms, and decision optimization technologies, so as to achieve an efficient operation process and timely response to the hospital HIS system. Among them, the core of the "intelligence" of the intelligent pharmacy system is the application of advanced intelligent algorithms. These intelligent algorithms can effectively process a large amount of diverse information, and the intelligent decisions made can avoid errors and inaccuracies caused by human operations, improve the accuracy and timeliness of operations, and achieve intelligent control of each link, enabling the intelligent pharmacy to have learning ability, adaptability, decision-making ability, and organizational ability.

[0072] The most core algorithms are: the storage location optimization and allocation algorithm and the picking path planning algorithm. An excellent storage location allocation algorithm can ensure the orderly and stable storage of drugs in the pharmacy, thereby improving the space utilization rate and safety of the pharmacy. An excellent picking path planning algorithm can effectively avoid the robot arm aimlessly searching in the pharmacy during the process of drug out-of-stock and replenishment, reduce the ineffective time, and improve the working efficiency of the pharmacy.

[0073] The following is a brief description of these two decision-making intelligent algorithms.

[0074] 1. Storage location optimization and allocation algorithm - the preferential evolution algorithm, which is applied to the inbound management part of the above-mentioned IPMS:

[0075] Regarding the problem of storage location allocation optimization, some experts and scholars have proposed using genetic algorithms or ant colony algorithms to solve it. However, both of these algorithms have some drawbacks. For example, the genetic algorithm depends on the changes of parameters such as the crossover rate and mutation rate and cannot well solve the problem of large-scale computational volume; while the programming of the ant colony algorithm is complex and its operability is relatively low. In order to find the optimal solution for storage location allocation, the preferential evolution algorithm is used to solve the problem of storage location optimization and allocation in the intelligent pharmacy.

[0076] The preferential evolution algorithm is a random search algorithm evolved from the principle of species evolution in nature.

[0077] According to the "r-k selection theory", in the evolution of organisms, classified by population dynamic types, there are two types of adaptations: one is r (r represents rate, meaning speed) selection, whose population density is very unstable, usually with high birth rates, short lifespans, small individuals, lacking a mechanism to protect offspring, high offspring mortality, and strong dispersal ability, adapting to variable habitats. The other is k (the initials of a German word , meaning capacity limitation) selection, whose population density is relatively stable, often around the k value. Such organisms usually have low birth rates, long lifespans, large individuals, mostly have relatively perfect mechanisms to protect offspring, low offspring mortality, and mostly do not have strong dispersal ability, and they adapt to stable habitats.

[0078] The Optimal Evolution Algorithm simulates the "r-k selection" process in nature (here, r-selection refers to selecting individuals with fast growth, fast reproduction, and fast extinction in an unstable and unpredictable environment; k-selection refers to selecting individuals with slow growth, slow reproduction, and slow extinction in a stable and predictable environment). It guides the evolution of the population through the excellent individuals in the population, superimposes the offspring individuals generated by the excellent individuals around the parent individuals in the way of dynamically changing the standard deviation according to the normal distribution, and then obtains the optimal individual through the competition among individuals. In this way, the selected individuals have stronger competitiveness. r-selection corresponds to the global exploration method of the Optimal Evolution Algorithm, and k-selection corresponds to the local exploration method of the Optimal Evolution Algorithm. The Optimal Evolution Algorithm has a simple structure, with the characteristics of few parameters, fast speed, and good robustness. It takes into account both global search and local search and has great potential for engineering applications. Compared with the Ant Colony Algorithm, the Optimal Evolution Algorithm is simple and easy to implement. Compared with the Genetic Algorithm, the Optimal Evolution Algorithm takes into account the diversity of the population and the selection intensity, has a larger search space and better performance, does not require genetic operation operators, can simply and effectively converge to the optimal solution of the problem, and is a powerful intelligent optimization tool.

[0079] The establishment of the goods location optimization allocation model is as follows:

[0080] Suppose there are a rows of shelves in the pharmacy, and each row of shelves has b columns and c layers. The row closest to the pharmacy entrance is denoted as the 1st row, the column closest to the pharmacy entrance is denoted as the 1st column, and the bottom layer of the shelf is denoted as the 1st layer. Then the goods location coordinates of the x-th row, y-th column, and z-th layer are denoted as: (x, y, z), where x = {1, 2,..., a}, y = {1, 2,..., b}, and z = {1, 2,..., c}.

[0081] Explanation of relevant parameters in the model:

[0082] a: The number of rows of shelves in the pharmacy; b: The number of columns of shelves in the pharmacy; c: The number of layers of shelves in the pharmacy; L0: The length of the goods location cell, assuming that the length, width, and height of the goods location cell are the same; m i : The mass of the i-th type of drug; P i : The turnover rate of the i-th type of drug; x: The row number of a certain goods location, x = {1, 2,..., a}; y: The column number of a certain goods location, y = {1, 2,..., b}; z: The layer number of a certain goods location, z = {1, 2,..., c}; v x : The moving speed of the manipulator in the x direction; v y : The moving speed of the manipulator in the y direction; v z : The moving speed of the manipulator in the z direction; N: The total number of drug types.

[0083] Taking the three items of storing the same type of drugs in adjacent positions, improving the drug out-of-stock efficiency, and improving the stability of the shelves as the storage location allocation and optimization objectives for inbound goods, a multi-objective goods location optimization mathematical model is established.

[0084] (1) Medicines of the same type are stored in adjacent positions:

[0085] To improve operational efficiency and management efficiency, the same medicine or medicines of the same category can be stored in adjacent storage locations.

[0086] Suppose there are already n storage locations in the pharmacy storing type-i medicines, and the coordinate vectors representing the storage locations of these type-i medicines in three-dimensional space are (x i , y i , z i ). Then the coordinate vector group of these n storage locations is:

[0087]

[0088] Let the coordinate vector of the center of the storage location of type-i medicines be R i (i = 1, 2,..., N) be:

[0089]

[0090] After calculating the center coordinates of a certain type of medicine already stored in the pharmacy, medicines of the same category should be placed at the position closest to these center coordinates.

[0091] The model obtained therefrom is as follows:

[0092]

[0093] (2) Improve the efficiency of medicine out-of-stock:

[0094] To shorten the travel distance of the manipulator, medicines with a high turnover rate are placed close to the medicine outlet, and medicines with a low turnover rate are placed slightly farther away from the medicine outlet.

[0095] The model obtained therefrom is as follows:

[0096]

[0097] (3) Improve the stability of the shelf:

[0098] To ensure uniform force on the shelf and stable structure, medicines with a larger mass should be stored in the lower storage locations of the shelf, that is, to minimize the center of gravity of the shelf. This is an important principle for ensuring safety.

[0099] The model obtained therefrom is as follows:

[0100]

[0101] In summary, the storage location optimization allocation model is considered from three aspects, which is a multi-objective optimization problem. Since there are relationships of mutual connection, competition, and conflict of interests among various objectives, it is necessary to use the weight coefficient method to transform the multi-objective optimization problem into a single-objective optimization problem.

[0102] Based on the weight coefficients ω1, ω2, and ω3, the obtained model is as follows:

[0103]

[0104] Among them, f1(x, y, z), f2(x, y, z), and f3(x, y, z) are as shown in Formula ③, Formula ④, and Formula ⑤.

[0105] It can be seen from Formula ③, Formula ④, and Formula ⑤ that the smaller the value of the objective function f(x, y, z), the better the storage location allocation plan and the higher the operation efficiency of the pharmacy. In the elitist evolutionary algorithm, the larger the fitness function value, the better the evolved offspring. Therefore, the fitness function only needs to take the reciprocal of the objective function. The smaller the objective function value, the larger the corresponding fitness value. To prevent data overflow, 1 is added to the objective function value. Therefore, the objective function of the storage location allocation optimization model is transformed into the corresponding fitness function as follows:

[0106]

[0107] 2. The picking path planning algorithm - the minimum time cost strategy is mainly applied to the picking and outbound process in step S2 of the above-mentioned drug dispensing mode process:

[0108] The minimum time cost strategy: The individual time cost t is defined as the time consumed to pick a certain drug from a prescription form; the collective time cost T is defined as the sum of the waiting time required for other drugs and the individual time cost when picking a certain drug from a prescription form.

[0109] For example: There are n drugs to be picked from a prescription form. The time required to pick the first drug is t1. During the process of t1, the remaining (n - 1) drugs have to wait for the time t1. Then the total waiting time required to pick this drug is t1+(n - 1)t1 = nt1. Among them, t1 is the individual time cost, and T = nt1 is the collective time cost. It can be seen that when evaluating the efficiency of a system, it is more scientific and comprehensive to use the collective time cost than the individual time cost.

[0110] Therefore, the picking path planning strategy is to pursue the minimum collective time cost.

[0111] Assume that the initial position of the manipulator is at the medicine outlet. Then, for each type of medicine taken from the prescription list, the manipulator needs to return to its original position once. In this way, the time it takes for the manipulator to start from the medicine outlet, pick up the medicine, and return to the medicine outlet again is the time consumed for taking a certain type of medicine.

[0112] Suppose there are n types of medicines in a prescription list, and the time required to take each type of medicine is t i (i = 1, 2, 3, …, n). Also, assume that the time required to take the first type of medicine is t1. Then the total time consumed for taking the first type of medicine is: t1+(n - 1)t1 = nt1. Assume that the time required to take the second type of medicine is t2. Then the total time consumed for taking the second type of medicine is: t2+(n - 2)t2 = (n - 1)t2.

[0113] And so on. Assume that the time required to take the i-th type of medicine is t i ,then the total time consumed for taking the i-th type of medicine is t i +(n - i)t i =(n - i + 1)t i ; Assume that the time required to take the n-th type of medicine is t n ,then the total time consumed for taking the n-th type of medicine is t n +(n - n)t n =t n . In this way, the total time used to take the n types of medicines on this prescription list, that is, the collective time cost, is:

[0114] T = nt1+(n - 1)t2+…+(n - i + 1)t i +…+t n Formula ⑧

[0115] In the above formula, the coefficient (n - i + 1) before t i is only related to the order of taking medicines and has nothing to do with what kind of medicine is taken this time. Therefore, as long as the order of taking medicines is changed, a new collective time cost T can be obtained. According to the principle of permutation and combination, the subscripts 1, 2, 3, …, i, …, n of the individual time cost t i have a total of n! permutations, that is, there are n! orders of taking medicines, and thus there are n! collective time costs T. The goal is to find the smallest one among these n! Ts.

[0116] In the above example, if the time used to take the n types of medicines on this prescription list is expressed as the sum of the individual time costs, it is: T' = t1 + t2+…+t i +…+t n . It can be seen that this T' is independent of the order of taking medicines. That is to say, no matter in what order the medicines are taken, the total time consumed is the same. This is obviously not as scientific and accurate as using the collective time cost.

[0117] The time t taken to pick a certain drug i is independent of the time taken to pick the other n - 1 drugs, and is only related to the position of this drug and the distance between the manipulator. That is, the individual time costs of picking each drug are independent of each other. Thus, as long as the minimum value of each individual time cost t i is found respectively, the minimum value of the collective time cost T is also found.

[0118] In formula ⑧, let the coefficient (n - i + 1) of t i be j, t i is a fixed value, independent of the drug - picking order, and j is also a fixed value, but j is related to the drug - picking order and takes any value from 0 to n as the drug - picking order changes.

[0119] From the above and formula ⑧, it can be seen that the total time taken to pick the first drug is nt1, where n is a fixed value. To make nt1 minimum, only t1 needs to be minimum, that is, as long as the time taken to pick the first drug is the shortest among the times taken to pick the n drugs.

[0120] Similarly, the total time taken to pick the second drug is (n - 1)t2, where n - 1 is a fixed value. To make (n - 1)t2 minimum, only t2 needs to be minimum, that is, as long as the time taken to pick the second drug is the shortest among the remaining n - 1 drugs.

[0121] By analogy, it can be obtained that for the n! collective time costs T, the minimum one is:

[0122] T = nt1+(n - 1)t2+…+(n - i + 1)t i +…+t n

[0123] (where t1 < t2 <…< t i <…< t n )

[0124] So far, the goal is achieved.

[0125] Algorithm implementation: The picking path planning strategy described above can be implemented using the bubble - sort algorithm.

[0126] The drug - picking process is as Figure 9 shown. The specific algorithm process:

[0127] (1) Select the drug outlet as the initial point.

[0128] (2) Detect all nodes to be visited (i.e., the coordinate values mapped by each drug), calculate and save the distances from each node to the initial point, and sort them (using the bubble - sort method).

[0129] (3) Access the node with the shortest distance and return to the starting point.

[0130] (4) Access the node with the shortest distance among the remaining nodes and return to the starting point.

[0131] (5) Repeat step (4) until all nodes have been accessed.

[0132] Implementation of the minimum time - cost drug - taking strategy:

[0133]

[0134]

[0135]

[0136] The minimum time - cost drug - taking strategy and its algorithm optimize the drug - taking process in the intelligent pharmacy, further improving the efficiency and better playing the functions and roles of the intelligent pharmacy.

[0137] The intelligent pharmacy system can accurately and efficiently manage the storage and distribution of drugs in the hospital pharmacy. After its use, the management mode of the pharmacy has undergone a complete transformation. It has changed from the traditional "result - oriented" to "process - oriented"; from "data entry" to "data collection", while also being compatible with the original "data entry" method; from "manual drug - searching" to "guided - location drug - taking"; and at the same time, a "monitoring platform" has been introduced to make the management more efficient, fast, with a fine - controllable process and correct results.

[0138] The above - mentioned is only the preferred embodiment of the present invention. The protection scope of the present invention is not limited to the above - mentioned embodiment. Any equivalent modification or change made by those of ordinary skill in the art according to the disclosure of the present invention shall be included in the protection scope recorded in the claims.

Claims

1. A smart pharmacy system based on information management and intelligent control, characterized in that: It consists of a software system, hardware devices, and a pharmacy mode process; The software system includes an Intelligent Pharmacy Management System (IPMS), an Intelligent Pharmacy Equipment Control System (IPCS), and a drive control program; IPMS issues management tasks to IPCS, and then controls the operation of hardware devices through the drive control program; the hardware devices are the devices in the pharmacy; The pharmacy mode process includes the following steps: S1: After the patient sees a doctor, the Hospital Information System (HIS) obtains the prescription information, patient information, and charging information issued by the doctor; S2: The smart pharmacy IPMS receives the medication information through integration with the HIS interface, and completes the picking and outbound of drugs through the picking path planning based on the minimum time cost; S3: The patient reports at the reporting machine, and after being reviewed by the pharmacist at the designated window and found correct, a medication list is printed to complete the drug collection; S4: The pharmacy system conducts real-time inventory checks to maintain and control the inventory of drugs in the pharmacy, with functions of reminding of approaching expiration dates and warning of insufficient drug inventory. The inbound, storage, and outbound of drugs are automatically completed by hardware devices through barcode management.

2. The intelligent pharmacy system based on information management and intelligent control according to claim 1, characterized in that: IPMS manages drug information, resources, behaviors, and the pharmacy operation process through functions such as inbound management, inventory management, outbound management, task management, query statistics, log management, permission management, configuration management, basic information management, and report management.

3. A smart pharmacy system based on information management and intelligent control according to claim 1, characterized in that: IPCS is between IPMS and the underlying PLC, receives the tasks issued by IPMS, distributes the tasks to the devices in the pharmacy, and sends the instructions to the underlying PLC to drive the above devices to act; IPCS feeds back the task execution status and data of the underlying PLC to IPMS in real time, conducts information interaction with IPMS, and saves the historical records of all operations and instructions for traceability.

4. A smart pharmacy system based on information management and intelligent control according to claim 1, characterized in that: The hardware system includes a manipulator, storage shelves, outer cover sheet metal, inbound automatic door, inbound automatic conveyor line, outbound automatic conveyor line, high-frequency barcode scanner, sensors, ultrasonic three-dimensional measurement module, visual monitoring equipment, and temperature and humidity monitor.

5. A smart pharmacy system based on information management and intelligent control according to claim 1, characterized in that: In the inbound management of drugs, IPMS adopts the optimal location allocation based on the optimal evolution algorithm, specifically: There are a rows of shelves in the pharmacy, and each row of shelves has b columns and c layers; the row closest to the pharmacy entrance is recorded as the 1st row, the column closest to the pharmacy entrance is recorded as the 1st column, and the bottom layer of the shelf is recorded as the 1st layer. Then the location coordinates of the xth row, yth column, and zth layer are recorded as (x, y, z), where x = {1, 2,..., a}, y = {1, 2,..., b}, and z = {1, 2,..., c}; Taking storing the same type of drugs in adjacent positions, improving the drug outbound efficiency, and improving the shelf stability as the goals of inbound location allocation and optimization, a multi-objective location optimization mathematical model is established, and then the weight coefficient method is used to transform the multi-objective optimization problem into a single-objective optimization problem. Based on the weight coefficients ω1, ω2, and ω3, the obtained model is as follows: Among them, f1(x, y, z), f2(x, y, z), and f3(x, y, z) are the target optimization models for storing the same type of drugs in adjacent positions, improving the drug outbound efficiency, and improving the shelf stability respectively; The smaller the value of the objective function f(x, y, z), the better the goods location allocation plan and the higher the operation efficiency of the pharmacy. In the elitist evolutionary algorithm, the fitness function takes the reciprocal of the objective function and adds 1 to the value of the objective function. The objective function of the goods location allocation optimization model is transformed into the corresponding fitness function as follows:

6. The intelligent pharmacy system based on information management and intelligent control according to claim 5, characterized in that: The goal of storing the same type of drugs in adjacent positions is to store the same drug or drugs of the same category in adjacent storage locations. Suppose there are already n storage locations in the pharmacy storing drugs of type i, and the coordinate vectors representing the storage locations of these i types of drugs in three-dimensional space are (x i , y i , z i ). Then the coordinate vector group of these n storage locations is as follows: Let the coordinate vector of the center of the storage location of Class-i drugs be R i as follows, where i = 1, 2, …, N and N is the total number of drug types: After calculating the central coordinates of a certain type of medicine already stored in the pharmacy, the same type of medicine is placed at the position closest to the central coordinates. The resulting model is as follows:

7. A smart pharmacy system based on information management and intelligent control according to claim 5, characterized in that: The goal of improving the efficiency of medicine out-of-stock is defined as placing the medicines with high turnover rates near the medicine outlet and the medicines with low turnover rates slightly farther away from the medicine outlet. The resulting model is as follows: Among them, v x is the moving speed of the manipulator in the x direction, v y is the moving speed of the manipulator in the y direction, v z is the moving speed of the manipulator in the z direction, L0 is the length of the storage cell, P i is the turnover rate of the i-th type of drug.

8. The intelligent pharmacy system based on information management and intelligent control according to claim 5, characterized in that: The goal of improving the stability of the shelf is defined as storing the medicines with large masses in the lower-level storage locations of the shelf to minimize the center of gravity of the shelf. The resulting model is as follows: where m i is the mass of the i-th drug.

9. The intelligent pharmacy system based on information management and intelligent control according to claim 1, characterized in that: The picking path planning based on the minimum time cost in step S2 of the pharmacy mode process is specifically as follows: Set the initial position of the manipulator at the medicine outlet. Then, for each medicine taken from the prescription form, the manipulator needs to return to its original position. The time taken for the manipulator to leave the medicine outlet to pick up the medicine and then return to the medicine outlet is defined as the time consumed for picking a certain medicine. For the n kinds of drugs in the prescription form, let the time required to obtain the i-th drug be t i , i = 1, 2, 3, …, n, then the total time consumed to obtain the i-th drug is t i +(n - i)t i =(n - i + 1)t i ; let the time required to obtain the n-th drug be t n , then the total time consumed to obtain the n-th drug is t n +(n - n)t n =t n ; the total time used to obtain the n kinds of drugs on this prescription form, that is, the collective time cost T is: T = nt1+(n - 1)t2+…+(n - i + 1)t i +…+t n Formula ⑧ Based on permutations and combinations, there are n! ways of taking medicine, resulting in n! collective time costs T. The goal is to obtain the minimum collective time cost T, and thus the goal is decomposed into finding the minimum value of each individual time cost t i ; For the n! collective time costs T, the smallest one is: T = nt1+(n - 1)t2+…+(n - i + 1)ti+…+t i +…+t n ,where t1 < t2 < … < ti<…< t i <…< t n The individual time cost t i is sorted according to the size, and the smallest individual time cost is prioritized to obtain the smallest collective time cost T.

10. A smart pharmacy system based on information management and intelligent control according to claim 9, characterized in that: The picking path planning is implemented using the bubble sort algorithm. The specific process is as follows: (1) Select the medicine outlet as the initial point; (2) Set the coordinate values mapped by each medicine as nodes, detect all nodes to be visited, calculate and save the distances from each node to the initial point, and use the bubble sort method for sorting; (3) Visit the node with the shortest distance and return to the initial point; (4) Visit the node with the shortest distance among the remaining nodes and return to the initial point; (5) Repeat step (4) until all nodes have been visited.

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