Medical instrument full-trace supply chain management method and system

Abstract

The invention discloses a medical instrument full-trace supply chain management method and system, and relates to the technical field of medical instrument supply chain management. The medical device all-tracking supply chain management method comprises the steps of obtaining current order demand data, order delivery destination information, medical device inventory position information and historical order data of each medical device; according to the method, the current order demand and the inventory state of the medical apparatus and instruments are tracked in real time, the historical order data are combined, the potential inventory insufficiency problem is recognized in advance, calculation of the safety inventory value is based on detailed historical analysis, and the safety inventory value of the medical apparatus and instruments is obtained. Comprising order demand and processing cycle, so that inventory management is more accurate and high in predictability, application of real-time data and intelligent calculation of safe inventory significantly improve the response speed and reliability of a supply chain, and it is ensured that medical services are not interrupted due to supply problems.

Description

Technical Field

[0001] The present invention relates to the technical field of medical device supply chain management, and in particular to a medical device full-traceability supply chain management method and system. Background Art

[0002] Supply chain management in the medical device industry faces many challenges, including the difficulty of demand forecasting, the complexity of inventory management, and the opacity of the supply chain. The high uncertainty of demand leads to the coexistence of excess and shortage of inventory, which affects the quality and efficiency of medical services. In addition, the global supply network increases the complexity of management, and any delay in supply point may lead to inefficiency of the entire supply chain.

[0003] Although information technology and logistics management have made significant progress in the past few decades, many existing supply chain management systems still rely on outdated technologies and cannot effectively integrate and analyze real-time data from all links of the supply chain. This technological lag leads to a lack of data support in the decision-making process and difficulty in responding to market changes quickly. In addition, there is a lack of effective risk management tools to predict and mitigate potential supply disruptions.

[0004] The main demands of the medical device supply chain include improving supply chain transparency, enhancing forecast accuracy, optimizing inventory management, reducing costs, and improving the flexibility and responsiveness of the overall supply chain. This requires the use of advanced data analysis tools and algorithms to achieve real-time data integration and intelligent analysis of all links in the supply chain, so as to make more accurate and effective operational decisions.

[0005] Based on the above solutions, it is found that the limitations of existing technologies include at least the following problems. First, traditional supply chain management often relies on periodic inventory audits and manual order processing systems, which can easily lead to slow response to market changes, delayed information updates, and difficulty in adjusting supply chain strategies in real time to cope with sudden demands, which can easily lead to insufficient or excessive supply of medical devices, affecting the quality and efficiency of medical services, and increasing inventory costs and expiration risks. Secondly, in the traditional supply chain management model, there is a serious phenomenon of information islands between various links, and there is a lack of a unified platform to integrate and share data throughout the entire chain. In addition, it is difficult for supply chain participants to obtain comprehensive data support and make optimal inventory and logistics decisions, which can easily lead to waste of resources and a decline in service levels. At the same time, traditional supply chain management fails to effectively use historical data and real-time data analysis to predict and adjust inventory, which can easily lead to a lack of flexibility and predictability in inventory management, which can easily lead to inventory shortages when demand increases, or excessive inventory backlogs when demand decreases, thereby increasing operating costs and risks. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a full-traceability supply chain management method and system for medical devices, which solves the problem that traditional supply chain management often relies on periodic inventory audits and manual order processing systems, which easily leads to slow response to market changes, delayed information updates, and difficulty in adjusting supply chain strategies in real time to cope with sudden demands, which easily leads to insufficient or excessive supply of medical devices, affecting the quality and efficiency of medical services, and increasing inventory costs and expiration risks. Secondly, in the traditional supply chain management model, there is a serious phenomenon of information islands between various links, and there is a lack of a unified platform to integrate and share data across the entire chain. It is also difficult for supply chain participants to obtain comprehensive data support and make optimal inventory and logistics decisions, which easily leads to waste of resources and a decline in service levels. At the same time, traditional supply chain management fails to effectively use historical data and real-time data analysis to predict and adjust inventory, which easily leads to a lack of flexibility and predictability in inventory management, which easily leads to inventory shortages when demand increases, or excessive inventory backlogs when demand decreases, thereby increasing operating costs and risks.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a medical device full traceability supply chain management method, comprising the following steps: obtaining current order demand data, order delivery destination information, medical device inventory location information, and historical order data of each medical device; performing data analysis on the historical order data of each medical device to obtain the safety stock value of each medical device; performing outbound loading processing on the current order demand data, and obtaining the remaining inventory of each medical device in real time; judging in real time whether the remaining inventory of each medical device is lower than the safety stock value, and performing replenishment measures on the medical devices whose remaining inventory is lower than the safety stock value; after the outbound loading of the current order demand data is completed, performing route analysis based on the order delivery destination information and the medical device inventory location information to obtain several transportation and distribution routes; obtaining the historical data of the transport vehicle and the travel distance value of each distribution route, and performing data analysis to obtain the logistics consumption score of each transportation and distribution route; arranging the logistics consumption score of each transportation and distribution route in descending order, recording the transportation and distribution route with the lowest logistics consumption score as the optimal transportation and distribution route, and monitoring the location information of the transport vehicle on the optimal transportation and distribution route in real time.

[0008] Furthermore, the current order demand data specifically refers to the current order demand for each medical device; the historical order data specifically refers to the total number of historical order supply interruptions for medical devices, the total number of historical orders, the historical number of daily uses, the historical order demand for each time, and the historical order processing cycle; the historical data of transport vehicles specifically refers to the historical transport speed value of the transport vehicle at each historical time point for each time it transported goods.

[0009] Furthermore, the specific steps to obtain the safety stock value of each medical device are as follows: analyze the historical order demand and historical order processing cycle of each medical device respectively to obtain the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, and historical order processing cycle mean standard deviation of each medical device; conduct a comprehensive analysis of the total number of historical order supply interruptions and the total number of historical orders for each medical device to obtain the supply interruption risk index of each medical device; conduct a mean analysis of the historical daily usage times of each medical device to obtain the historical usage frequency of each medical device; conduct a comprehensive analysis of the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, historical order processing cycle mean standard deviation, supply interruption risk index, and historical usage frequency of each medical device to obtain the safety stock value of each medical device.

[0010] Furthermore, the specific formula for calculating the supply interruption risk index, historical usage frequency, and safety stock value of each medical device is as follows: Among them, GyZ i is the supply interruption risk index of the i-th medical device, LgY i is the total number of historical order supply interruptions for the i-th medical device, LdZ i is the total number of historical orders for the i-th medical device, LsP i is the historical frequency of use of the i-th medical device, LsY in is the number of times the i-th medical device has been used on the nth day in history, n=1,2,3,…,n0, n0 is the total number of historical days, AqK i is the safety stock value of the i-th medical device, LdX i is the historical order demand mean of the i-th medical device, θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the mean historical order processing cycle of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i=1,2,3,…,i0, i0 is the number of medical devices.

[0011] Furthermore, the specific steps to obtain the mean historical order demand, standard deviation of historical order demand, mean historical order processing cycle, and standard deviation of the mean of historical order processing cycle for each medical device are as follows: based on the moving exponential average method, the historical order demand for each medical device is analyzed at the mean to obtain the mean historical order demand for each medical device; the historical order demand for each medical device is analyzed in combination with the mean historical order demand to obtain the standard deviation of the historical order demand for each medical device; based on the weighted average method, the historical order processing cycle for each medical device is analyzed at the mean to obtain the mean historical order processing cycle for each medical device; the historical order processing cycle for each medical device is analyzed in combination with the mean historical order processing cycle to obtain the standard deviation of the historical order processing cycle for each medical device.

[0012] Furthermore, the specific formulas for calculating the mean value of historical order demand, the standard deviation of historical order demand, the mean value of historical order processing cycle, and the standard deviation of the mean value of historical order processing cycle for each medical device are as follows: Among them, LdX i is the historical order demand mean of the i-th medical device, LdD ij is the historical order demand for the jth time for the i-th medical device, α ij1 is the weight coefficient of the historical order demand for the jth time for the i-th medical device, LdD i(j+1) is the historical order demand for the i-th medical device in the j+1th order, α ij2 is the weight coefficient of the historical order demand for the i-th medical device, the j+1th time, α ij1 +α ij2 =1,θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the historical order processing cycle average of the i-th medical device, LcL ij is the historical order processing cycle of the jth order of the i-th medical device, W ij is the weighted coefficient of the historical order processing cycle of the jth historical order of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i=1,2,3,…,i0, i0 is the number of medical devices, j=1,2,3,…,j0, i0 is the total number of historical times.

[0013] Furthermore, the specific steps for obtaining a plurality of transport and delivery routes are: reading order delivery destination information and medical device inventory location information, and inputting them into route planning software for route analysis to obtain a plurality of transport and delivery routes.

[0014] Furthermore, the specific steps for calculating the logistics consumption score of each transport and distribution route are as follows: perform mean analysis on the historical transport speed values ​​of the transport vehicles at each historical time point of each transport of goods to obtain the historical mean transport speed of the transport vehicles; analyze the vehicle consumption cost value of each transport and distribution route based on the travel distance value of each transport and distribution route; analyze the transportation time value and labor consumption cost value of each transport and distribution route based on the historical mean transport speed of the transport vehicles and the travel distance value of each transport and distribution route; obtain the historical number of transportations and the number of accidents per day for each transport and distribution route, and conduct a comprehensive analysis to obtain the safety score of each transport and distribution route; conduct a comprehensive analysis of the vehicle consumption cost value, labor consumption cost value, transportation time value, and safety score of each transport and distribution route to obtain the logistics consumption score of each transport and distribution route.

[0015] Furthermore, the specific formula for calculating the historical average transportation speed of transportation vehicles and the safety score and logistics consumption score of each transportation and distribution route is as follows: Among them, LsJ is the historical mean transportation speed of transportation vehicles, Lsd ab is the historical transport speed value of the transport vehicle at the bth time point in the history of the ath transport of goods, a=1,2,3,…,a0, a0 is the number of historical transport times of the transport vehicle, b=1,2,3,…,b0, b0 is the number of historical time points, AqP r is the safety score of the rth transport delivery route, YsC ru is the number of historical transportation times on the uth day of the rth transportation and delivery route, YsC ru is the number of accidents that occurred on the uth day in the history of the rth transportation and distribution route, u=1,2,3,…,u0, u0 is the number of historical days, WpF r is the logistics consumption score of the rth transportation and distribution route, CxH r is the vehicle consumption cost value of the rth transportation and distribution route, RgX r is the labor consumption cost value of the rth transportation and distribution route, ξ1 is the cost consumption coefficient stored in the database, YsJ r is the transportation time value of the rth transportation and distribution route, ξ2 is the transportation time coefficient stored in the database, e is a natural constant, ξ3 is the safety factor stored in the database, ξ1+ξ2+ξ3=1, r=1,2,3,…,r0, r0 is the number of transportation and distribution routes.

[0016] A full-traceability supply chain management system for medical devices, comprising: a data acquisition module, a safety inventory analysis module, an outbound processing module, a route analysis module, a logistics consumption analysis module, and a distribution module; the data acquisition module is used to acquire current order demand data, order distribution destination information, medical device inventory location information, and historical order data for each medical device; the safety inventory analysis module is used to perform data analysis on the historical order data for each medical device to obtain the safety inventory value for each medical device; the outbound processing module is used to perform outbound loading processing on the current order demand data and acquire the remaining inventory of each medical device in real time; the real-time judgment of whether the remaining inventory of each medical device is lower than the safety inventory value , and take replenishment measures for medical devices whose remaining inventory is lower than the safety inventory value; the route analysis module is used to perform route analysis based on the order delivery destination information and the medical device inventory location information after the current order demand data is shipped out and loaded, and obtain several transportation and distribution routes; the logistics consumption analysis module is used to obtain the historical data of the transport vehicle and the travel distance value of each distribution route, and perform data analysis to obtain the logistics consumption score of each transportation and distribution route; the distribution module is used to arrange the logistics consumption score of each transportation and distribution route in descending order, record the transportation and distribution route with the lowest logistics consumption score as the optimal transportation and distribution route, and monitor the location information of the transport vehicle on the optimal transportation and distribution route in real time.

[0017] The present invention has the following beneficial effects:

[0018] (1) This full-traceability supply chain management method for medical devices tracks current order demand and inventory status of medical devices in real time, combines historical order data, and identifies potential inventory shortages in advance. The calculation of safety stock values ​​is based on detailed historical analysis, including order demand and processing cycles, making inventory management more accurate and predictive. The application of real-time data and intelligent calculation of safety stock significantly improve the response speed and reliability of the supply chain, ensuring that medical services are not interrupted due to supply problems, thereby reducing patients' waiting time for treatment and possible health risks.

[0019] (2) This full-traceability supply chain management method for medical devices integrates historical transportation data analysis, including the speed of each transportation and the driving distance of each route, so as to optimize logistics operations and reduce ineffective and redundant transportation behaviors. The selection of transportation routes is not only based on historical efficiency scores, but also combines real-time route analysis to select the best distribution path. This refined route planning reduces transportation costs and time, improves vehicle utilization and fuel efficiency, and arranges logistics consumption scores in descending order and selects the optimal route, further ensuring that costs are minimized during transportation, which directly affects the economic benefits of the overall supply chain.

[0020] (3) This full-traceability supply chain management method for medical devices significantly improves the overall safety and monitoring effect of the supply chain by comprehensively analyzing the safety score and logistics consumption of each transportation and distribution route. By real-time monitoring the location information of the transportation vehicles on the selected optimal route and calculating the safety of each route, this method can prevent and reduce accidents and delays in transportation. This not only ensures the safety of medical devices during transportation, but also ensures the timely arrival of equipment in emergency medical situations, ultimately improving the quality of medical services and patient satisfaction.

[0021] (4) The medical device full traceability supply chain management system provides a highly integrated and automated information flow through its comprehensive modular structure, significantly enhancing the decision-making support capabilities of the supply chain. The real-time information collection and integration function of the data acquisition module ensures real-time update and access to all key data such as inventory location, order requirements and historical transaction records. The immediate availability and accuracy of this data provides a solid data foundation for supply chain management decisions and supports every decision point from inventory management to route planning. In addition, the in-depth data processing and analysis capabilities of the safety inventory analysis module and the logistics consumption analysis module provide detailed insights, allowing managers to not only respond quickly in daily operations, but also conduct long-term strategic planning. This data-driven decision-making process reduces the risk of making decisions based on intuition or incomplete information, making supply chain management more accurate and predictive.

[0022] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The present invention is a flow chart of a method for full traceability supply chain management of medical devices.

[0024] Figure 2 The present invention is a flowchart of the specific steps for obtaining the safety inventory value of each medical device in a medical device full traceability supply chain management method.

[0025] Figure 3 The present invention is a flowchart of the specific steps of obtaining the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, and historical order processing cycle mean standard deviation of each medical device in a medical device full traceability supply chain management method of the present invention.

[0026] Figure 4 This is a block diagram of a medical device full traceability supply chain management system of the present invention. DETAILED DESCRIPTION

[0027] The embodiment of the present application solves the problem that traditional supply chain management often relies on periodic inventory audits and manual order processing systems through a full-traceability supply chain management method and system for medical devices, which can easily lead to slow response to market changes, delayed information updates, and difficulty in adjusting supply chain strategies in real time to cope with sudden demands, which can easily lead to insufficient or excessive supply of medical devices, affecting the quality and efficiency of medical services, and increasing inventory costs and expiration risks. Secondly, in the traditional supply chain management model, there is a serious phenomenon of information islands between various links, and there is a lack of a unified platform to integrate and share data across the entire chain. It is also difficult for supply chain participants to obtain comprehensive data support and make optimal inventory and logistics decisions, which can easily lead to waste of resources and a decline in service levels. At the same time, traditional supply chain management fails to effectively use historical data and real-time data analysis to predict and adjust inventory, which can easily lead to a lack of flexibility and predictability in inventory management, which can easily lead to inventory shortages when demand increases, or excessive inventory backlogs when demand decreases, thereby increasing operating costs and risks.

[0028] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0029] First, it is necessary to collect historical transportation data on current order demand, medical device inventory location, and transportation vehicles, including demand for each medical device, inventory location, number of supply interruptions, order processing cycle, and speed records of transportation vehicles. The collected data is analyzed in detail to calculate the safety stock value of each medical device. Analyze historical order data to determine the mean, standard deviation, and supply interruption risk of demand. Use this information to estimate the inventory level required in different situations to prevent supply shortages. Based on inventory location and destination information, use route planning software to generate several transportation and distribution routes. Further analyze the transportation efficiency of these routes, including transportation time, cost, and safety, so as to select the optimal distribution route. During transportation, monitor the location of the transportation vehicle in real time and make adjustments based on the predicted arrival time and remaining distance information. At the same time, implement replenishment measures for medical devices with remaining inventory below the safety stock value to ensure continuous supply.

[0030] See also Figure 1The embodiment of the present invention provides a technical solution: a medical device full traceability supply chain management method, comprising the following steps: obtaining current order demand data, order delivery destination information, medical device inventory location information, and historical order data of each medical device; performing data analysis on the historical order data of each medical device to obtain the safety stock value of each medical device; performing outbound loading processing on the current order demand data, and obtaining the remaining inventory of each medical device in real time; determining in real time whether the remaining inventory of each medical device is lower than the safety stock value, and executing replenishment measures for the medical devices whose remaining inventory is lower than the safety stock value (specifically, sending replenishment instructions to relevant staff) , and send the number of medical devices to be replenished at the same time); after the current order demand data is shipped out and loaded, perform route analysis based on the order delivery destination information and the medical device inventory location information to obtain several transportation and distribution routes; obtain the historical data of the transportation vehicle and the driving distance value of each distribution route, and perform data analysis to obtain the logistics consumption score of each transportation and distribution route; arrange the logistics consumption score of each transportation and distribution route in descending order, record the transportation and distribution route with the lowest logistics consumption score as the optimal transportation and distribution route, and monitor the location information of the transportation vehicle on the optimal transportation and distribution route in real time, and send the remaining distance and predicted arrival time information to relevant staff.

[0031] The current order demand data specifically refers to the current order demand for each medical device; the historical order data specifically refers to the total number of historical order supply interruptions for medical devices, the total number of historical orders, the historical number of daily uses, the historical order demand for each time, and the historical order processing cycle; the historical data of transport vehicles specifically refers to the historical transport speed value of the transport vehicle at each historical time point for each time it transported goods.

[0032] Among them, the current order demand data is directly obtained through the order management system (OMS), the historical daily usage times of medical devices, the historical order demand volume each time, and the historical order processing cycle are obtained from the historical sales records of medical devices, the total number of historical order supply interruptions and the total number of historical orders of medical devices are obtained through the supply chain management software, and the historical transportation speed value of the transport vehicle at each time point in the history of each transportation of goods is obtained through the on-board GPS tracking system.

[0033] Specifically, Figure 2As shown in the figure, the specific steps to obtain the safety stock value of each medical device are as follows: analyze the historical order demand and historical order processing cycle (the entire cycle time from placing an order to receiving an order) of each medical device to obtain the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, and historical order processing cycle mean standard deviation of each medical device; analyze the total number of historical order supply interruptions (the number of orders that were not completed on time due to various reasons within a certain period of time, such as supplier problems, logistics delays, natural disasters, etc.), the total number of historical orders (the number of orders received within the same time period), and the historical order demand and historical order processing cycle standard deviation of each medical device. A comprehensive analysis is performed on the total number of orders received to obtain the supply interruption risk index for each medical device; a mean analysis is performed on the historical daily usage times of each medical device (in this implementation plan, it refers to selecting a medical institution for several historical days and then counting the number of times each medical device is used in each historical day) to obtain the historical usage frequency of each medical device; a comprehensive analysis is performed on the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, historical order processing cycle mean standard deviation, supply interruption risk index, and historical usage frequency of each medical device to obtain the safety stock value of each medical device.

[0034] The specific formula for calculating the supply interruption risk index, historical usage frequency, and safety stock value for each medical device is as follows: Among them, GyZ i is the supply interruption risk index of the i-th medical device, LgY i is the total number of historical order supply interruptions for the i-th medical device, LdZ i is the total number of historical orders for the i-th medical device, LsP i is the historical frequency of use of the i-th medical device, LsY in is the number of times the i-th medical device has been used on the nth day in history, n=1,2,3,…,n0, n0 is the total number of historical days, AqK i is the safety stock value of the i-th medical device, LdX i is the historical order demand mean of the i-th medical device, θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the mean historical order processing cycle of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i = 1, 2, 3, …, i0, i0 is the number of medical devices, and when calculating the safety stock value of each medical device, all calculation parameters are standardized before calculation.

[0035] In this implementation scheme, through in-depth analysis of the historical order demand, processing cycle and supply interruption of each medical device, the safety stock value obtained is more accurate and meets the actual needs. This accurate safety stock calculation can help medical institutions or supply chain managers effectively prevent over-inventory and under-inventory problems, thereby reducing inventory costs and avoiding potential supply shortages. Especially in the case of urgent need for medical devices, through comprehensive analysis of historical data on supply interruptions and current order processing cycles, potential supply chain risks can be identified and predicted. This risk assessment makes the supply chain more flexible and able to respond to emergencies such as natural disasters, supplier failures or logistics delays. With the improvement of risk management capabilities, medical institutions can better ensure the continuity and safety of patient treatment and convert historical usage frequency into Incorporating safety stock calculations allows inventory levels to better reflect actual usage and changes in market demand, which not only helps medical institutions optimize resource allocation and reduce resource waste, but also improves operational efficiency while ensuring the quality of medical services. In addition, standardized analytical processing provides a unified method to evaluate and compare the performance and requirements of different medical devices, which helps to formulate more scientific and reasonable procurement and replenishment strategies. This method continuously collects and analyzes data to not only provide support for current inventory and supply chain decisions, but also accumulates valuable data assets to provide a basis for future strategy adjustments and improvements. This data-based continuous improvement mechanism can gradually improve the response speed of the entire supply chain and its ability to adapt to market changes, further strengthening the position of medical service providers in competition.

[0036] Specifically, Figure 3 As shown, the specific steps for obtaining the mean historical order demand, standard deviation of historical order demand, mean historical order processing cycle, and standard deviation of the mean of historical order processing cycle for each medical device are as follows: based on the moving exponential average method, the historical order demand of each medical device is analyzed at the mean value to obtain the mean historical order demand of each medical device; the historical order demand of each medical device is analyzed in combination with the mean historical order demand to obtain the standard deviation of the historical order demand of each medical device; based on the weighted average method, the historical order processing cycle of each medical device is analyzed at the mean value to obtain the mean historical order processing cycle of each medical device; the historical order processing cycle of each medical device is analyzed in combination with the mean historical order processing cycle to obtain the standard deviation of the historical order processing cycle of each medical device.

[0037] The specific formulas for calculating the mean historical order demand, standard deviation of historical order demand, mean historical order processing cycle, and standard deviation of the mean historical order processing cycle for each medical device are as follows: Among them, LdX iis the historical order demand mean of the i-th medical device, LdD ij is the historical order demand for the jth time for the i-th medical device, α ij1 is the weight coefficient of the historical order demand for the jth time for the i-th medical device, LdD i(j+1) is the historical order demand for the i-th medical device in the j+1th order, α ij2 is the weight coefficient of the historical order demand for the i-th medical device, the j+1th time, α ij1 +α ij2 =1,θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the historical order processing cycle average of the i-th medical device, LcL ij is the historical order processing cycle of the jth order of the i-th medical device, W ij is the weighted coefficient of the historical order processing cycle of the jth historical order of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i=1,2,3,…,i0, i0 is the number of medical devices, j=1,2,3,…,j0, i0 is the total number of historical times (i.e., the historical order demand obtained and the total number of historical order processing cycles).

[0038] It needs to be explained that α ij1 , α ij2 The specific calculation process is: sum up and analyze the historical order demands of the i-th medical device for the jth and j+1 times to obtain the historical order demand and value of the i-th medical device for the jth time in history, and then perform ratio analysis on the historical order demands of the i-th medical device for the jth and j+1 times respectively with the historical order demand and value, and the ratio result is the corresponding weight coefficient.

[0039] W ij The specific calculation process is as follows: for the i-th medical device, the historical order processing cycles of each history are summed up and analyzed to obtain the historical order processing cycle and value of the i-th medical device, and then the j-th historical order processing cycle of the i-th medical device is ratio analyzed with the historical order processing cycle and value, and the ratio result is the corresponding weighting coefficient.

[0040] In this implementation scheme, by applying the moving exponential average method and the weighted average method, this method can more accurately reflect the actual changing trends of order demand and processing cycle. This method takes into account the time series characteristics in historical data and can smooth random fluctuations, thereby providing more stable and reliable data analysis results, which is particularly important for determining accurate safety stock levels because it directly affects inventory holding costs and service levels. By accurately calculating the mean and standard deviation of order demand, as well as relevant statistical data on the order processing cycle, supply chain managers can better predict future inventory demand and thus optimize inventory levels, which not only helps reduce the waste of funds caused by excess or insufficient inventory, but also ensures the timeliness of the supply of medical devices and improves medical By analyzing historical data on supply disruptions and calculating supply disruption risk indicators, managers can identify potential supply chain vulnerabilities. This information is critical for developing risk mitigation strategies and emergency plans, and helps to respond quickly to supply disruptions or other uncertainties to ensure the continuity and safety of medical device supply. Integrating these statistical methods into the medical device supply chain management system can provide managers with a powerful decision support tool. The system can automatically provide key operating indicators and update them in a timely manner to reflect the latest operating status. This real-time data-driven decision-making tool can greatly improve management efficiency, reduce human errors, and improve the transparency and controllability of the entire supply chain.

[0041] Specifically, the specific steps to obtain several transportation and delivery routes are: reading the order delivery destination information and the medical device inventory location information, and inputting them into the route planning software for route analysis to obtain several transportation and delivery routes. The specific process is: based on a pre-selected map or route planning software that supports multi-point delivery route planning, such as Google Maps, Here Maps, MapQuest, etc., all delivery addresses are then input into the selected route planning tool. This is usually done through interface operations, such as pasting an address list or entering them one by one. In the route planning tool, the command to generate routes is executed. This command will automatically calculate multiple routes connecting these points based on the input address points. The tool will display the routes connecting all input points. To view the route data generated by the tool, you can usually view the route details directly on the vehicle screen or download them through specific functions.

[0042] In this embodiment, the use of maps or route planning software such as Google Maps, Here Maps, MapQuest, etc. to automatically plan routes can significantly improve delivery efficiency. Automated route planning reduces the time and effort required for manual planning, and also reduces inefficient delivery caused by human errors. Automated route planning helps identify the most cost-effective transportation path. Fast and reliable delivery services increase the trust of medical service providers in the supply chain and help establish stable customer relationships, which is particularly important in the medical field because it is directly related to the treatment and health of patients. Modern route planning tools are usually equipped with real-time tracking functions, allowing managers to monitor any changes in the transportation process and make adjustments based on actual conditions. The acquisition and application of such real-time data can respond to emergencies in a timely manner, such as traffic accidents or extreme weather conditions, to ensure the smooth progress of delivery activities. Effective route planning also supports the sustainable development goals of enterprises. By reducing unnecessary mileage and time, carbon emissions and environmental impacts are reduced, while improving the environmental friendliness of overall operations.

[0043] Specifically, the specific steps for calculating the logistics consumption score of each transport and distribution route are as follows: perform mean analysis on the historical transport speed values ​​of the transport vehicles at each historical time point of each transport of goods to obtain the historical mean transport speed of the transport vehicles; based on the travel distance value of each transport and distribution route, analyze the vehicle consumption cost value of each transport and distribution route (vehicle consumption cost per kilometer * number of kilometers traveled); based on the historical mean transport speed of the transport vehicles and the travel distance value of each transport and distribution route, analyze the transportation time value (in minutes) and labor consumption cost value (specifically, the labor required per minute) of each transport and distribution route. Cost value * transportation time value); obtain the historical daily transportation times (obtained through the transportation management system TMS) and accident times of each transportation and distribution route (refers to the number of all accidents or problems that occurred during the inspection period during the transportation process, including traffic accidents, cargo damage, delays exceeding specific time standards, etc., and obtained through the accident reporting system), and conduct a comprehensive analysis to obtain the safety score of each transportation and distribution route; conduct a comprehensive analysis of the vehicle consumption cost value, labor consumption cost value, transportation time value, and safety score of each transportation and distribution route to obtain the logistics consumption score of each transportation and distribution route.

[0044] The specific formula for calculating the historical average transportation speed of transportation vehicles and the safety score and logistics consumption score of each transportation and distribution route is as follows: Among them, LsJ is the historical mean transportation speed of transportation vehicles, Lsd abis the historical transport speed value of the transport vehicle at the bth time point in the history of the ath transport of goods, a=1,2,3,…,a0, a0 is the number of historical transport times of the transport vehicle, b=1,2,3,…,b0, b0 is the number of historical time points, AqP r is the safety score of the rth transport delivery route, YsC ru is the number of historical transportation times on the uth day of the rth transportation and delivery route, YsC ru is the number of accidents that occurred on the uth day in the history of the rth transport and distribution route, u=1,2,3,…,u0, u0 is the number of historical days (i.e. the number of days of historical usage), WpF r is the logistics consumption score of the rth transportation and distribution route, CxH r is the vehicle consumption cost value of the rth transportation and distribution route, RgX r is the labor consumption cost value of the rth transportation and distribution route, ξ1 is the cost consumption coefficient stored in the database, YsJ r is the transportation time value of the rth transportation and distribution route, ξ2 is the transportation time coefficient stored in the database, e is a natural constant, ξ3 is the safety factor stored in the database, ξ1+ξ2+ξ3=1, r=1,2,3,…,r0, r0 is the number of transportation and distribution routes, and when calculating the logistics consumption score of each transportation and distribution route, all calculation parameters are standardized before calculation.

[0045] It needs to be explained that ξ1, ξ2, and ξ3 are specifically determined through statistical analysis, expert opinions, or empirical judgment, and a set of embodiment data of ξ1, ξ2, and ξ3 are specifically: ξ1 is 0.3, ξ2 is 0.3, and ξ3 is 0.4.

[0046] In this implementation scheme, the vehicle consumption cost is calculated by analyzing the historical transportation speed and combining it with the actual mileage. This method can more accurately estimate the transportation cost of each route. When calculating the transportation time and labor cost, the cost per minute is multiplied by the actual transportation time. This provides management with a clear view of the cost structure, making cost control more refined, which helps to identify routes with lower cost-effectiveness and make adjustments to reduce the total cost. The safety score of each route is evaluated by comprehensively analyzing the number of transportations and the occurrence of accidents, so that the safety risks in the transportation process can be quantified and managed. This method not only improves the awareness of potential dangers, but also helps to take preventive measures, such as improving route selection, strengthening driver training and improving vehicle maintenance. By reducing the occurrence of accidents, it can avoid traffic accidents or cargo accidents. The additional costs and delays caused by damage, the calculated logistics consumption score provides a comprehensive indicator for each delivery route, including multiple dimensions such as cost, time, and safety. Through this score, supply chain managers can more reasonably choose the optimal route, which not only reduces transportation costs and time, but also improves the overall efficiency of the distribution process and customer satisfaction. Real-time monitoring of distribution progress and optimizing routes based on these data can ensure that medical devices are delivered in time, especially in emergency medical situations. By standardizing all calculation parameters and combining statistical analysis and expert opinions for weight allocation, the scientificity and practicality of the scoring model are ensured. This data-driven decision support tool can help managers make more reasonable decisions based on actual data and improve the responsiveness of the entire supply chain and its ability to adapt to market changes.

[0047] See also Figure 4The embodiment of the present invention provides a technical solution: a medical device full traceability supply chain management system, including: a data acquisition module, a safety inventory analysis module, an outbound processing module, a route analysis module, a logistics consumption analysis module, and a distribution module; the data acquisition module is used to obtain current order demand data, order distribution destination information, medical device inventory location information, and historical order data of each medical device; the safety inventory analysis module is used to perform data analysis on the historical order data of each medical device to obtain the safety inventory value of each medical device; the outbound processing module is used to perform outbound loading processing on the current order demand data, and obtain the remaining inventory of each medical device in real time; it is judged in real time whether the remaining inventory of each medical device is lower than the safety inventory value, and executes the medical device whose remaining inventory is lower than the safety inventory value Replenishment measures (specifically sending replenishment instructions to relevant staff and sending the number of medical devices to be replenished at the same time); route analysis module, which is used to perform route analysis based on the order delivery destination information and medical device inventory location information after the current order demand data is shipped out and loaded, and obtain several transportation and distribution routes; logistics consumption analysis module, which is used to obtain the historical data of transportation vehicles and the driving distance value of each distribution route, and perform data analysis to obtain the logistics consumption score of each transportation and distribution route; distribution module, which is used to arrange the logistics consumption score of each transportation and distribution route in descending order, record the transportation and distribution route with the lowest logistics consumption score as the optimal transportation and distribution route, and monitor the location information of the transportation vehicle on the optimal transportation and distribution route in real time, and send the remaining distance and predicted arrival time information to relevant staff.

[0048] In summary, this application has at least the following effects:

[0049] By real-time tracking of current order demand and inventory status of medical devices, combined with historical order data, potential inventory shortages can be identified in advance. The calculation of safety stock values ​​is based on detailed historical analysis, including order demand and processing cycles, making inventory management more accurate and predictive. The application of real-time data and intelligent calculation of safety stock significantly improves the response speed and reliability of the supply chain, ensuring that medical services are not interrupted due to supply problems, thereby reducing patients' waiting time for treatment and possible health risks.

[0050] By integrating historical transportation data analysis, including the speed of each transportation and the travel distance of each route, it is possible to optimize logistics operations and reduce ineffective and redundant transportation behaviors. The selection of transportation routes is not only based on historical efficiency scores, but also combined with real-time route analysis to select the best distribution path. This refined route planning reduces transportation costs and time, improves vehicle utilization and fuel efficiency, arranges logistics consumption scores in descending order and selects the optimal route, further ensuring that costs are minimized during transportation, which directly affects the economic benefits of the overall supply chain.

[0051] By comprehensively analyzing the safety score and logistics consumption of each transportation and distribution route, the overall safety and monitoring effect of the supply chain are significantly improved. By real-time monitoring of the location information of the transport vehicles on the selected optimal route and calculating the safety of each route, this method can prevent and reduce accidents and delays in transportation. This not only ensures the safety of medical devices during transportation, but also ensures the timely arrival of equipment in emergency medical situations, ultimately improving the quality of medical services and patient satisfaction.

[0052] Through its comprehensive modular structure, it provides a highly integrated and automated information flow, significantly enhancing the decision-making support capabilities of the supply chain. The real-time information collection and integration functions of the data acquisition module ensure real-time updating and access to all key data such as inventory location, order requirements and historical transaction records. The immediate availability and accuracy of this data provide a solid data foundation for supply chain management decisions and support every decision point from inventory management to route planning. In addition, the in-depth data processing and analysis capabilities of the safety inventory analysis module and the logistics consumption analysis module provide detailed insights, allowing managers to not only respond quickly in daily operations, but also conduct long-term strategic planning. This data-driven decision-making process reduces the risk of making decisions based on intuition or incomplete information, making supply chain management more accurate and predictive.

[0053] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0054] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for full traceability supply chain management of medical devices, characterized in that: The following steps are involved: Obtain current order demand data, order delivery destination information, medical device inventory location information, and historical order data for each medical device; Analyze the historical order data of each medical device to obtain the safety stock value of each medical device; Carry out outbound loading processing for current order demand data, and obtain the remaining inventory of each medical device in real time; Determine in real time whether the remaining inventory of each medical device is lower than the safety stock value, and implement replenishment measures for medical devices whose remaining inventory is lower than the safety stock value; After the current order demand data is shipped out and loaded, a route analysis is performed based on the order delivery destination information and the medical device inventory location information to obtain several transportation and delivery routes; Obtain historical data of transport vehicles and the travel distance of each delivery route, and perform data analysis to obtain the logistics consumption score of each transport and delivery route; The logistics consumption score of each transport and distribution route is arranged in descending order, the transport and distribution route with the lowest logistics consumption score is recorded as the optimal transport and distribution route, and the location information of the transport vehicle on the optimal transport and distribution route is monitored in real time.

2. The medical device full traceability supply chain management method according to claim 1, characterized in that: The current order demand data specifically refers to the current order demand for each medical device; the historical order data specifically refers to the total number of historical order supply interruptions for medical devices, the total number of historical orders, the historical number of daily uses, the historical order demand for each time, and the historical order processing cycle; the historical data of transport vehicles specifically refers to the historical transport speed value of the transport vehicle at each historical time point for each time it transported goods.

3. The medical device full traceability supply chain management method according to claim 2 is characterized in that: The specific steps to obtain the safety stock value of each medical device are as follows: The historical order demand and historical order processing cycle of each medical device are analyzed respectively to obtain the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, and historical order processing cycle mean standard deviation of each medical device; Comprehensively analyze the total number of historical order supply interruptions and the total number of historical orders for each medical device to obtain the supply interruption risk index for each medical device; Perform mean analysis on the historical daily usage times of each medical device to obtain the historical usage frequency of each medical device; A comprehensive analysis was conducted on the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, historical order processing cycle mean standard deviation, supply interruption risk indicator, and historical usage frequency of each medical device to obtain the safety stock value of each medical device.

4. The medical device full traceability supply chain management method according to claim 3 is characterized in that: The specific formula for calculating the supply interruption risk index, historical usage frequency, and safety stock value for each medical device is as follows: Among them, GyZ i is the supply interruption risk index of the i-th medical device, LgY i is the total number of historical order supply interruptions for the i-th medical device, LdZ i is the total number of historical orders for the i-th medical device, LsP i is the historical frequency of use of the i-th medical device, LsY in is the number of times the i-th medical device has been used on the nth day in history, n=1,2,3,…,n0, n0 is the total number of historical days, AqK i is the safety stock value of the i-th medical device, LdX i is the historical order demand mean of the i-th medical device, θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the mean historical order processing cycle of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i=1,2,3,…,i0, i0 is the number of medical devices.

5. The medical device full traceability supply chain management method according to claim 3, characterized in that: The specific steps to obtain the historical order demand mean, historical order demand standard deviation, historical order processing cycle mean, and historical order processing cycle mean standard deviation of each medical device are as follows: Based on the moving exponential average method, the historical order demand of each medical device is analyzed at each time to obtain the historical order demand mean of each medical device; The historical order demand of each medical device is analyzed in combination with the mean of historical order demand to obtain the standard deviation of historical order demand of each medical device; Based on the weighted average method, the historical order processing cycle of each medical device is analyzed for the mean value, and the mean value of the historical order processing cycle of each medical device is obtained; The historical order processing cycle of each medical device is analyzed separately with the mean of the historical order processing cycle to obtain the standard deviation of the historical order processing cycle of each medical device.

6. The medical device full traceability supply chain management method according to claim 5, characterized in that: The specific formulas for calculating the mean historical order demand, standard deviation of historical order demand, mean historical order processing cycle, and standard deviation of the mean historical order processing cycle for each medical device are as follows: Among them, LdX i is the historical order demand mean of the i-th medical device, LdD ij is the historical order demand for the jth time for the i-th medical device, α ij1 is the weight coefficient of the historical order demand for the jth time for the i-th medical device, LdD i(j+1) is the historical order demand for the i-th medical device in the j+1th order, α ij2 is the weight coefficient of the historical order demand for the i-th medical device, the j+1th time, α ij1 +α ij2 =1,θ i is the standard deviation of historical order demand for the i-th medical device, LgZ i is the historical order processing cycle average of the i-th medical device, LcL ij is the historical order processing cycle of the jth order of the i-th medical device, W ij is the weighted coefficient of the historical order processing cycle of the jth historical order of the i-th medical device, ω i is the mean standard deviation of the historical order processing cycle of the i-th medical device, i=1,2,3,…,i0, i0 is the number of medical devices, j=1,2,3,…,j0, i0 is the total number of historical times.

7. The medical device full traceability supply chain management method according to claim 1, characterized in that: The specific steps for obtaining several transport and delivery routes are: reading order delivery destination information and medical device inventory location information, and inputting them into route planning software for route analysis to obtain several transport and delivery routes.

8. The medical device full traceability supply chain management method according to claim 2, characterized in that: The specific steps for calculating the logistics consumption score of each transportation and delivery route are as follows: Perform mean analysis on the historical transport speed values ​​of the transport vehicle at each historical time point of each transport of goods, and obtain the mean historical transport speed of the transport vehicle; Based on the travel distance value of each transport and distribution route, analyze the vehicle consumption cost value of each transport and distribution route; Based on the historical average transport speed of transport vehicles and the travel distance of each transport and distribution route, the transport time value and labor consumption cost value of each transport and distribution route are analyzed; Obtain the historical daily transportation times and accident times of each transportation and distribution route, and conduct a comprehensive analysis to obtain the safety score of each transportation and distribution route; A comprehensive analysis is conducted on the vehicle consumption cost value, labor consumption cost value, transportation time value, and safety score of each transportation and distribution route to obtain the logistics consumption score of each transportation and distribution route.

9. The medical device full traceability supply chain management method according to claim 8, characterized in that: The specific formula for calculating the historical average transportation speed of transportation vehicles and the safety score and logistics consumption score of each transportation and distribution route is as follows: Among them, LsJ is the historical mean transportation speed of transportation vehicles, Lsd ab is the historical transport speed value of the transport vehicle at the bth time point in the history of the ath transport of goods, a=1,2,3,…,a0, a0 is the number of historical transport times of the transport vehicle, b=1,2,3,…,b0, b0 is the number of historical time points, AqP r is the safety score of the rth transport delivery route, YsC ru is the number of historical transportation times on the uth day of the rth transportation and delivery route, YsC ru is the number of accidents that occurred on the uth day in the history of the rth transportation and distribution route, u=1,2,3,…,u0, u0 is the number of historical days, WpF r is the logistics consumption score of the rth transportation and distribution route, CxH r is the vehicle consumption cost value of the rth transportation and distribution route, RgX r is the labor consumption cost value of the rth transportation and distribution route, ξ1 is the cost consumption coefficient stored in the database, YsJ r is the transportation time value of the rth transportation and distribution route, ξ2 is the transportation time coefficient stored in the database, e is a natural constant, ξ3 is the safety factor stored in the database, ξ1+ξ2+ξ3=1, r=1,2,3,…,r0, r0 is the number of transportation and distribution routes.

10. A medical device full traceability supply chain management system, applying the medical device full traceability supply chain management method according to any one of claims 1 to 8, characterized in that: include: Data acquisition module, safety inventory analysis module, outbound processing module, route analysis module, logistics consumption analysis module, and distribution module; The data acquisition module is used to obtain current order demand data, order delivery destination information, medical device inventory location information, and historical order data for each medical device; The safety stock analysis module is used to analyze the historical order data of each medical device to obtain the safety stock value of each medical device; The outbound processing module is used to process the outbound loading of the current order demand data and obtain the remaining inventory of each medical device in real time; The method comprises determining in real time whether the remaining inventory of each medical device is lower than the safety inventory value, and executing replenishment measures for the medical devices whose remaining inventory is lower than the safety inventory value; The route analysis module is used to perform route analysis based on order delivery destination information and medical device inventory location information after the current order demand data is shipped out of the warehouse and loaded onto the vehicle, and obtain several transportation and delivery routes; The logistics consumption analysis module is used to obtain the historical data of the transport vehicles and the travel distance value of each delivery route, and perform data analysis to obtain the logistics consumption score of each transport and delivery route; The distribution module is used to arrange the logistics consumption score of each transportation and distribution route in descending order, record the transportation and distribution route with the lowest logistics consumption score as the optimal transportation and distribution route, and monitor the position information of the transportation vehicle on the optimal transportation and distribution route in real time.

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