Intelligent Management Method and System for Tool Borrowing and Returning Based on RFID Technology

Abstract

The present invention relates to the field of tool borrowing and returning management, and particularly to an intelligent management method and system for tool borrowing and returning based on RFID technology. When receiving the label lending request information of RFID, obtain the tool type and user information of the label; judge whether the user meets the lending conditions according to the tool type and user information; when the user meets the lending conditions, mark the lending time; when receiving the label return information, obtain the current status information and historical status information of the tool, and judge whether the return conditions are met according to the current status information and historical status information; when the return conditions are met, obtain the lending time and return time, and determine the return of the tool this time according to the return time, lending time and tool type; based on the result of tool return, analyze whether the tool meets the conditions for continued use; when the tool meets the conditions for continued use, update the label status and the status information of the tool. Ensure that tools meeting safety standards continue to be used.

Description

Technical Field

[0001] This application relates to the technical field of tool borrowing and returning management, and particularly to a smart management method and system for tool borrowing and returning based on RFID technology. Background Art

[0002] The tool borrowing and returning based on RFID technology (Radio Frequency Identification technology) refers to using RFID tags and readers to achieve automated management of tool borrowing and returning. In the system, each tool is attached with an RFID tag, and the unique identification information of the tool is stored in the tag. When the tool is borrowed or returned, the reader can remotely read the information on the tag, thereby automatically recording the status change of the tool.

[0003] In the existing technology for tool borrowing and returning management, the safety of tools is usually judged by regularly checking and manually evaluating the tool status. For example, after a user borrows a tool, they report that there is a problem with the tool. However, this method often relies on the initiative and accuracy of users, which may lead to omission or delay in reporting actual tool problems. For some tools with high safety requirements (such as medical devices, industrial equipment, etc.), relying on users to report the tool status after borrowing has significant potential hazards. Failure to detect and handle tool problems in a timely manner may lead to more serious damage, thereby increasing the maintenance cost and the downtime of the tool. Secondly, the existing technology usually ignores the in-depth analysis of tool usage rate. Tools with high usage rates may not be replenished in a timely manner, while tools with low usage rates may occupy too many resources.

[0004] Therefore, the existing technology has defects and needs to be improved. Summary of the Invention

[0005] In order to solve one or several problems in the existing technology, the main purpose of this application is to provide a smart management method and system for tool borrowing and returning based on RFID technology.

[0006] To achieve the above-mentioned invention purpose, this application proposes a smart management method for tool borrowing and returning based on RFID technology, and the method includes:

[0007] When receiving the RFID tag lending request information, obtain the tool type and user information of the tag;

[0008] Judge whether the user meets the lending conditions according to the tool type and user information;

[0009] When the user meets the lending conditions, mark the lending time;

[0010] When receiving the tag return information, obtain the current status information and historical status information of the tool, and judge whether it meets the return conditions according to the current status information and historical status information;

[0011] When the return conditions are met, obtain the lending time and the return time, and determine the return of the tool this time based on the return time, the lending time, and the tool type;

[0012] Based on the result of the tool return, analyze whether the tool meets the conditions for continued use;

[0013] When the tool meets the conditions for continued use, update the tag status and the status information of the tool.

[0014] The embodiment of the present application also provides an intelligent management system for tool lending and returning based on RFID technology, including:

[0015] A first acquisition module, configured to obtain the tool type and user information of the tag when receiving the RFID tag lending request information;

[0016] A judgment module, configured to judge whether the user meets the lending conditions according to the tool type and user information;

[0017] A marking module, configured to mark the lending time when the user meets the lending conditions;

[0018] A second acquisition module, configured to obtain the current status information and historical status information of the tool when receiving the tag return information, and judge whether the return conditions are met according to the current status information and historical status information;

[0019] A third acquisition module, configured to obtain the lending time and the return time when the return conditions are met, and determine the return of the tool this time based on the return time, the lending time, and the tool type;

[0020] An analysis module, configured to analyze whether the tool meets the conditions for continued use based on the result of the tool return;

[0021] An update module, configured to update the tag status and the status information of the tool when the tool meets the conditions for continued use.

[0022] The present application also provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method described in any one of the above when executing the computer program.

[0023] The present application also provides a computer-readable storage medium, on which a computer program is stored, and the computer program implements the steps of the method described in any one of the above when executed by a processor.

[0024] The intelligent management method and system for tool borrowing and returning based on RFID technology in the embodiments of the present application automatically obtain tool types and user information, ensuring that only eligible users can borrow tools, thereby enhancing the security of borrowing. Secondly, by recording the borrowing and returning times in real time and combining the current and historical status information of the tools, it can accurately determine whether the tools meet the return conditions, thus reducing management risks. Finally, through the analysis of the tool usage status, it ensures that only tools meeting safety standards continue to be used, further enhancing the overall efficiency and security of tool management. This systematic management method effectively reduces manual intervention and improves the transparency and reliability of the tool borrowing and returning process. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic flowchart of the intelligent management method for tool borrowing and returning based on RFID technology according to an embodiment of the present application;

[0026] Figure 2 It is a schematic flowchart of the intelligent management method for tool borrowing and returning based on RFID technology according to an embodiment of the present application;

[0027] Figure 3 It is a schematic block diagram of the structure of the intelligent management system for tool borrowing and returning based on RFID technology according to an embodiment of the present application;

[0028] Figure 4 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present application.

[0029] The realization, functional features and advantages of the purpose of the present application will be further described in conjunction with the embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0031] Refer to Figure 1 , in the embodiments of the present application, an intelligent management method for tool borrowing and returning based on RFID technology is provided, and the method includes:

[0032] S1. When receiving the label borrowing request information of RFID, obtain the tool type and user information of the label;

[0033] S2. Judge whether the user meets the borrowing conditions according to the tool type and user information;

[0034] S3. When the user meets the borrowing conditions, mark the borrowing time;

[0035] S4. When the tag return information is received, obtain the current status information and historical status information of the tool, and determine whether the return condition is met according to the current status information and historical status information;

[0036] S5. When the return condition is met, obtain the lending time and return time, and determine the return of the tool this time according to the return time, lending time and tool type;

[0037] S6. Based on the result of the tool return, analyze whether the tool meets the condition for continued use;

[0038] S7. When the tool meets the condition for continued use, update the tag status and the status information of the tool.

[0039] As described in the above steps S1 - S2, after the system receives the lending request, it reads the RFID tag information contained in the request and extracts the tool type and user information from it. Quickly confirming the tool type borrowed by the user helps with subsequent lending condition judgment. If a user requests to borrow a drill, the system will immediately obtain the RFID tag information of the drill to ensure that subsequent operations are based on the correct tool data. According to the tool type and user information, the system queries the database to determine whether the user meets the conditions for borrowing the tool (such as borrowing permission, number of borrows, etc.). Ensuring that the user borrowing the tool is qualified prevents unauthorized borrowing and reduces the risk of tool loss or damage. If the user's borrowing record shows that their previously borrowed tool was not returned on time, their new lending request will be rejected.

[0040] As described in the above steps S3 - S5, once it is confirmed that the user meets the lending conditions, automatically record the current time as the lending time and update the tool status to "lent out". Providing the lending time information helps with subsequent return management and time tracking. If the lending time of a certain tool is x year x month x day, it is convenient to calculate the overdue return time later. When the return request is received, obtain the current status information (such as damage condition) and historical status information (such as the previous lending record) of the tool. Update the tool status in real time to ensure that the tool is inspected when it is returned, reducing the risk of damage. If the drill malfunctions during the borrowing period, this status will be recorded and corresponding inspections will be carried out when the user returns it. Analyze the current status and historical status to determine whether the tool meets the return conditions (such as being intact and not exceeding the borrowing time, etc.). Ensuring that only qualified tools can be successfully returned thus maintains the standardization of tool management. If the drill is damaged during use, the system will reject the return and require the user to handle the relevant issues first.

[0041] As described in the above steps S6 - S7, when the return condition is met, record the return time and calculate the usage duration using the lending time and return time. Providing the usage duration data helps to evaluate the usage frequency and borrowing patterns of the tools. For example, if a user returns a drill after 3 days of borrowing, usage analysis can be performed based on this data. Evaluate whether the tool is suitable for continued lending according to the status information of the tool (such as normal function, intact appearance, etc.). Identify tools that need maintenance or scrapping in a timely manner to optimize resource utilization. If a tool shows severe wear after multiple borrowings, the system will prompt for repair or removal from the shelves. When the tool meets the conditions for continued use, update the RFID tag status of the tool and its status information in the database. Maintain the accuracy and real - time nature of the tool management system to ensure that the tool information always reflects the current status. For example, once the tool is inspected and confirmed to be available for borrowing again, the system will update its status to "available for borrowing" to facilitate borrowing by other users. Through this series of functions, RFID technology greatly improves the efficiency of tool lending and returning management, reduces manual intervention and errors, and improves the transparency and accuracy of management.

[0042] As described above, the method ensures that only eligible users can borrow tools by automatically obtaining tool types and user information, enhancing the security of borrowing. Secondly, by recording lending and return times in real - time and combining the current and historical status information of the tools, it can accurately determine whether the tool meets the return conditions, thus reducing management risks. Finally, through the analysis of the tool usage status, it ensures that only tools meeting safety standards continue to be used, further enhancing the overall efficiency and security of tool management. This systematic management method effectively reduces manual intervention and improves the transparency and reliability of the tool lending and returning process.

[0043] Refer to Figure 2 , in one embodiment, for analyzing whether the tool meets the conditions for continued use, the method includes:

[0044] S61. Obtain the type of the tool and determine the safety standard data for the continued use of the tool according to the type of the tool;

[0045] S62. Construct a safety analysis model based on the types of all tools and the corresponding safety standard data;

[0046] S63. Obtain the historical status information and current status information, input the type of the tool, historical status information, and current status information into the safety analysis model, predict the safety factor of the tool through the safety analysis model, and output the predicted result;

[0047] S64. When the predicted safety factor is greater than the preset factor threshold, determine the conditions for the continued use of the tool.

[0048] As described in the above steps, identify the type of each tool, as the usage requirements and safety standards for different tools vary. For example, there are significant differences in the design and use of power tools and hand tools. By clarifying the tool type, the system can effectively match the corresponding safety standard data. Based on the types of all tools and their corresponding safety standard data, establish a comprehensive safety analysis model. This model can be based on statistical methods or machine learning algorithms and can take into account the characteristics of different tool types. Constructing the model makes the analysis process more systematic and standardized, ensuring that all tools are evaluated under a unified standard and reducing the deviation impact of individual tools. Collect historical and current status information of the tools, including usage frequency, maintenance records, and real-time monitoring data, etc. This information provides comprehensive background data for the model. By integrating historical and current status, the model can more accurately evaluate the safety of tools and identify potential risks. Input the tool type, historical status, and current status information into the constructed safety analysis model, and the model will analyze this data and output the predicted safety factor. The process of predicting the safety factor utilizes the advantages of data analysis and can quickly identify whether the tool meets the criteria for continued use. When the predicted safety factor exceeds the preset threshold, the system determines that the tool meets the conditions for continued use. Otherwise, measures need to be taken. This judgment mechanism ensures that only tools that meet the safety standards are continued to be used, thereby effectively reducing the accident risk and improving the safety management level.

[0049] In one embodiment, after the step of when the tool meets the conditions for continued use and before the step of updating the label status and the status information of the tool, the method further includes:

[0050] Obtain the lending frequency and the current status information of the current tool;

[0051] Input the lending frequency and the current status information of the tool into the tool rotation model, analyze whether the tool meets the rotation conditions through the tool rotation model, and output the analysis result;

[0052] If the analysis result is that the tool meets the rotation conditions, then match the same type of rotation tools to limit the lending times of each tool;

[0053] Update the label status and the status information of the rotation tools according to the matching result.

[0054] As described above, the lending frequency of each tool (such as the number of lending times and the lending duration) and its current status information (such as the usage status and the degree of wear) are collected in real time. For example, if an electric screwdriver has been lent out 10 times in the past month and its current status is "normal", this information will be recorded and analyzed. By accurately capturing the lending frequency and status of the tool, an objective basis can be provided for subsequent analysis, ensuring the transparency of tool usage and the effectiveness of management. The collected lending frequency and status information are input into the tool rotation model, and the model can evaluate whether the tool meets the rotation conditions. For example, if a tool has a high lending frequency and a poor status, it may not meet the rotation conditions. This model can systematically analyze the usage of tools and automatically determine whether rotation is needed, thereby reducing wear caused by high-frequency use and extending the service life of tools. The tool rotation model analyzes the input data to determine whether the tool meets the rotation conditions. This can be based on set thresholds (such as too many lending times or a poor status). For example, if the lending frequency of a tool exceeds 10 times and the status information shows that the wear has reached a certain degree, the model will determine that it needs to be rotated. Through a systematic analysis process, the model can quickly draw conclusions, reducing the subjectivity of human judgment and improving the scientific nature of tool management. The system will search for tools of the same or similar type as the current tool in the tool library as alternatives for matching. For example, if an electric screwdriver needs to be rotated, the system will search for other electric screwdrivers for replacement. This mechanism ensures that when a tool is rotated, other tools of the same type are available, avoiding interruptions in tool usage and improving work efficiency. According to the matching results, an upper limit on the number of lending times will be set for each tool. For example, if the lending frequency of a certain type of tool is too high, the system will limit the number of lending times for each user within a certain period. This measure can effectively manage the usage frequency of tools, prevent damage caused by excessive borrowing, and thus improve the overall management efficiency. Once the rotated tool is determined, the system will update the label status of the tool (such as "in rotation") and its status information (such as "to be repaired"). For example, when a tool is rotated out of use, the label status will change to "awaiting use". Timely updating of the label and status information makes tool management more standardized and orderly, facilitating the tracking of tool usage and maintenance.

[0055] In one embodiment, the method further includes:

[0056] Obtain the usage data of all tools, and count the usage rate of each tool according to the usage data of all tools;

[0057] Extract the tools with low usage rates according to the preset usage rate standard;

[0058] Based on the tools with low usage rates, obtain the current status information and historical status information of the tools;

[0059] Analyze the status change data of the tool based on the current status information and historical status information of the tool;

[0060] Obtain the single - time average usage duration and usage location of the tool;

[0061] Predict the user's usage habits and usage scenarios based on the status change data, average usage duration, and usage location of the tool;

[0062] Analyze the reasons for the low tool usage rate in combination with the user's usage habits and usage scenarios;

[0063] Generate a tool adjustment strategy based on the results of the cause analysis.

[0064] As described above, collect the usage records of each tool, including usage frequency, time, location, etc. Providing comprehensive basic usage data helps with subsequent analysis and decision-making. Through data collection, it can be found that a certain tool has a high usage frequency during a specific period, thus determining its peak usage period. Calculate the usage rate of each tool, usually the ratio of the number of uses to the total available times. Quantify the usage efficiency of the tool to facilitate the identification of tools with low usage rates. If the usage rate of a certain tool is 10%, it indicates that it has only been used for 10% of the available time, which prompts attention. According to the preset usage rate standard (such as below a certain threshold), screen out tools with low usage rates. Focus on those tools that are not fully utilized to provide a target for subsequent analysis. For example, the usage rate of tool A is 5%, which is lower than the standard of 10%, so it is selected as the analysis object. Collect the real-time status of the tool (such as working condition, fault situation) and its historical records (such as maintenance, fault records). A comprehensive understanding of the tool's health status helps analyze the reasons for low usage rates. Tool B has had multiple faults recently, and its historical status may indicate that it needs repair, which may lead to low usage rates. Compare the current status with the historical status to identify the change trend of the tool's performance. Reveal the usage problems of the tool and possible improvement points. The failure rate of tool C has increased in the past six months, and it may require more frequent maintenance. Statistically analyze the length of time and location of each use of the tool. Understand the usage efficiency and applicable environment of the tool to facilitate the formulation of usage strategies. If the average usage duration of tool D is 5 minutes and it is mostly used in the meeting room, it indicates that it is suitable for scenarios with short-term and high-frequency usage. Analyze the user's usage patterns based on the usage data, including peak usage periods, common places, etc. Provide data support for the management and adjustment of the tool. If tool E is frequently used from 9 to 11 am on weekdays, it shows that the demand is high during this period. Combine user habits and usage scenarios to find potential factors for low usage rates, such as tool performance, accessibility, etc. Identify the root cause of the problem to provide a direction for subsequent adjustment. If tool F is often neglected due to faults, insufficient maintenance may be the main reason for its low usage rate. Based on the above analysis results, formulate specific improvement measures, such as increasing the maintenance frequency or enhancing the visibility of the tool. Through implementing the strategy, improve the usage rate and efficiency of the tool. If the low usage rate of tool G is due to lack of publicity, the strategy may include increasing training and promotion to improve the awareness of the tool.

[0065] In one embodiment, the method further includes:

[0066] Based on the usage data of all tools, analyze the usage rate of each tool according to the time series to identify the high-frequency time periods of each tool's usage;

[0067] Conduct time correlation point analysis on the high-frequency time periods of each tool's usage, including working hours, rest hours, and seasonal factors;

[0068] Predict the demand for the target tool by the user at the time correlation point based on the analysis results of the usage data and time correlation points of all tools;

[0069] If the predicted result is that the demand for the target tool is greater than the existing inventory of the target tool, then formulate a strategy to increase the number of target tools during high-frequency time periods.

[0070] As described above, perform time series analysis on the collected tool usage data to identify the usage trends and high-frequency time periods of each tool. This helps managers understand when tools are used most frequently, thereby optimizing resource allocation. If a certain tool has the highest usage rate on Monday mornings, the manager can ensure that there are enough tools available at that time. Analyze the impact of working hours, break times, and seasonal factors on tool usage to find the correlation points. Reveal the relationship between user usage habits and time to help adjust strategies to adapt to usage patterns. If it is found that a certain tool is used more frequently in summer than in other seasons, the inventory can be increased in summer. Based on the analysis results of time correlation points, predict the demand for the target tool during a specific time period. Identify demand peaks in advance to ensure sufficient supply. If the predicted demand for a certain time period is greater than the inventory, the manager can prepare for replenishment in advance. When the predicted demand exceeds the inventory, formulate a strategy to increase the number of target tools during high-frequency time periods. Ensure that user needs are met during demand peaks and improve service levels. For example, if the demand for a tool is predicted to increase during the Monday morning rush hour, it may be decided to increase the inventory before that. Through time series analysis, the usage patterns and trends of each tool can be carefully identified, enabling precise management. Enable managers to respond promptly to replenishment of high-usage tools to ensure that work efficiency is not affected by tool shortages. Combining the identification of high-frequency time periods with demand prediction, managers can proactively increase inventory before high-usage periods. Avoid work delays caused by insufficient inventory and improve overall work fluency and response speed. Analyze the usage of low-usage tools, which can help identify their real needs and usage scenarios and avoid resource waste. Managers can consider reducing the inventory of low-usage tools or replacing them with more popular tools to improve resource utilization efficiency. Through data-driven analysis, managers can make more reasonable decisions based on actual usage rather than relying on experience.

[0071] In one embodiment, after the step of if the predicted result is that the demand for the target tool is greater than the existing inventory of the target tool, then formulate a strategy to increase the number of target tools during high-frequency time periods, the method further includes:

[0072] Analyze whether the management terminal adopts the formulated strategy;

[0073] If the management terminal adopts the strategy of increasing the number of target tools during high-frequency time periods, real-time obtain the change data of the usage rate of the target tool during high-frequency time periods;

[0074] Compare the usage rate of the current target tool with that of the historical target tool, and analyze whether there is an increase in the usage rate of the target tool;

[0075] When there is an increase in the usage rate of the target tool, it is determined that the result of predicting the user's demand for the target tool is a credible result.

[0076] As described above, before implementing the strategy, first check whether the management end responds to and executes the proposed strategy of increasing the number of target tools. During high-frequency usage periods, the system will monitor the usage of the target tool in real time and collect relevant data. This data includes the usage frequency of the tool, the usage duration, and the feedback from users, etc. Real-time data collection can help managers respond quickly to usage changes and adjust resource allocation in a timely manner. For example, if the usage rate of a certain tool increases significantly during a specific period, the manager can quickly replenish the inventory to ensure that the work progress will not be affected due to insufficient tools. Compare the usage rate data collected in real time with the historical data to analyze the usage trend and changes. This process helps to identify usage patterns and potential demand fluctuations. Through comparative analysis, managers can understand whether the current change in usage is a short-term phenomenon or a long-term trend. For example, if the usage rate of a tool has been increasing continuously in the recent period, this may indicate a change in user demand, and the manager should consider increasing the inventory in the long term. By comparing the data, it is determined whether the usage rate of the target tool has increased significantly. This determination is based on a preset threshold. For example, the usage rate increases by more than a certain percentage. If the usage rate does increase, it indicates that the user's demand for the tool is also rising. Managers can make more accurate decisions based on this, such as adjusting the procurement plan or increasing the type of this tool. After confirming the increase in the usage rate, it is possible to judge whether the originally predicted tool demand is accurate based on the historical data and the current usage situation. If the current trend is consistent with the prediction, the prediction result is considered credible. This determination mechanism helps managers reduce decision-making risks. For example, if the demand prediction is consistent with the actual usage rate, managers can safely conduct large-scale procurement to avoid problems such as inventory shortages or surpluses.

[0077] In one embodiment, after the step of analyzing whether there is an increase in the usage rate of the target tool, the method further includes:

[0078] If the usage rate of the target tool decreases or remains unchanged, it is determined that the result of predicting the user's demand for the target tool is an unreliable result;

[0079] Based on the unreliable result, re-analyze the time correlation points of the high-frequency time periods when using the target tool;

[0080] According to the usage data of the target tool and the result of the re-analysis of the time correlation points, adjust the parameters for predicting the demand for the target tool.

[0081] As described above, after confirming that the usage rate of the tool has not increased, further analyze the usage situation. If the usage rate decreases or remains unchanged, the system will mark the demand forecast as untrustworthy. For example, if the usage frequency of a certain tool does not increase over a period of time, it may indicate that users' interest in the tool has decreased, or there are alternative tools available. This judgment mechanism ensures that managers can promptly discover potential problems and avoid unnecessary resource investments based on incorrect assumptions. For example, if the forecast result is marked as untrustworthy, managers can reduce the procurement plan for the tool, thereby saving funds. After the demand forecast is marked as untrustworthy, the system will re-examine the high-frequency time periods and analyze the specific time points and patterns of users' tool usage. This may involve factors such as users' active time and reasons for use. By re-analyzing the time correlation points, managers can better understand the changes in users' needs. For example, if it is found that the usage rate of a certain tool decreases during a specific period, it may be due to changes in the work process or the introduction of new tools. This information helps managers make adjustments. The system updates the parameters of the demand forecast model based on the results of the re-analysis data to more accurately reflect users' real needs. This may involve adjusting indicators such as usage rate and periodic demand. The adjusted forecast can better match the actual usage situation and reduce future inventory risks. For example, by updating the parameters, managers can predict the tool demand in the future period of time, thereby reasonably arranging procurement to avoid inventory backlogs or shortages.

[0082] In one embodiment, after the step of updating the label status and the status information of the tool, the method further includes:

[0083] Collect the currently unreturned tools and classify the currently unreturned tools;

[0084] Based on the classification results, obtain the historical borrowing data of each type of tool, where the historical borrowing data includes borrowing duration, return time, and its maintenance history;

[0085] According to the historical borrowing data of each type of tool, predict the return time of each type of tool;

[0086] Construct a statistical model, input the predicted return time and maintenance history of the same type of tool into the statistical model, and analyze and output a maintenance plan through the statistical model. The maintenance plan is used to schedule the maintenance of the same type of tool within the same time period;

[0087] Based on the maintenance plan, formulate a maintenance strategy.

[0088] As described above, the borrowing status of all tools is monitored in real time, and a list of unreturned tools is collected. Ensure that managers can promptly understand which tools have not been returned, providing a basis for subsequent classification and data analysis. Classify the unreturned tools according to criteria such as tool type, usage, borrowing frequency, etc. Classification makes subsequent data analysis more accurate. Different types of tools have different characteristics in use and maintenance. Through classification, corresponding management strategies can be formulated more effectively. The system extracts historical borrowing information related to each classified tool, including borrowing duration, return time, and its maintenance history. Historical data provides an important basis for analyzing tool usage patterns and maintenance requirements, enabling the identification of peak usage periods and potential problems of tools, and helping to optimize resource allocation. Based on historical borrowing data, statistical and machine learning methods are used to predict the return time of tools. By predicting the return time, managers can make preparations in advance, allocate resources, and avoid work delays caused by unreturned tools. The predicted return time and maintenance history of the same type of tools are input into a statistical model to analyze the maintenance requirements and dynamic changes of tools. The statistical model can identify the maintenance rules among different types of tools, thereby providing a scientific basis for formulating a reasonable maintenance plan. After analysis by the statistical model, a maintenance schedule for the same type of tools is generated. Scheduling the maintenance of the same type of tools within the same time period can centrally process similar tools, improve efficiency, reduce maintenance costs, and reduce equipment idle time. According to the maintenance plan and tool usage, specific maintenance strategies are formulated, including maintenance frequency, required materials, and personnel arrangements. Through reasonable maintenance strategies, the service life of tools can be extended, the failure rate can be reduced, ensuring that tools are always in the best working condition, while reducing maintenance costs.

[0089] In a specific embodiment, assume that a construction company has three tools: electric drills, saws, and wrenches. They need to be maintained regularly to ensure normal use.

[0090] The maintenance requirements are as follows: Electric drill: maintain once every 3 months; Saw: maintain once every 6 months; Wrench: maintain once every 2 months

[0091] Maintenance cost

[0092] Electric drill: 200 yuan per piece

[0093] Saw: 150 yuan per piece

[0094] Wrench: 100 yuan per piece

[0095] Maintenance plan

[0096] Assume that the company decides to conduct maintenance at the end of the 1st month:

[0097] Electric drills (10): 2000 yuan (10 × 200); Saws (5): 750 yuan (5 × 150); Wrenches (12): 1200 yuan (12 × 100)

[0098] Total maintenance cost: 2000 yuan + 750 yuan + 1200 yuan = 3950 yuan

[0099] If all tools are maintained on the same day, efficiency can be improved:

[0100] The maintenance time is reduced from 3 days to 2 days.

[0101] Assume that sharing parts and improving efficiency reduce costs by 10%:

[0102] New maintenance cost

[0103] New total cost: 3950 yuan × 90% = 3555 yuan

[0104] As a result, the maintenance time is reduced from 3 days to 2 days; the maintenance cost is reduced from 3950 yuan to 3555 yuan.

[0105] From the above analysis, by arranging tools of the same type for maintenance within the same time period, the construction company not only reduces the maintenance time and cost, but also improves the utilization efficiency of resources. This method effectively integrates the maintenance process, saves expenses for the company, and ensures the optimal state of the tools.

[0106] In an embodiment, after the step of formulating the maintenance strategy, the method further includes;

[0107] When receiving the return information of the tool, analyze whether the predicted return time is within the preset accurate range according to the return time of the tool;

[0108] If the predicted return time is within the preset accurate range, then maintain the existing maintenance strategy;

[0109] If the predicted return time is not within the preset accurate range, then adjust the maintenance time in the maintenance plan and re - formulate the maintenance strategy based on the adjustment result.

[0110] As described above, after the system receives the tool return information, it records the actual return time of the tool and compares it with the previously predicted return time. Ensure that the maintenance plan can be adjusted according to the actual situation, thereby optimizing resource utilization. The actual tool return time may vary due to various factors (such as project delays, weather, etc.), so timely updating of information can avoid unreasonable maintenance plans caused by inaccurate predictions. The system compares the predicted return time with a preset accurate range to determine whether it is within an acceptable range. Provide a basis for the maintenance strategy to ensure that the maintenance arrangement can adapt to the actual usage of the tool in a timely manner. The maintenance strategy needs to flexibly respond to the actual usage of the tool to avoid unnecessary maintenance delays or over-maintenance, which can improve the overall work efficiency. If the predicted return time is within the preset accurate range, the system keeps the current maintenance plan unchanged and continues to perform maintenance according to the established schedule. Avoid unnecessary adjustments, saving management time and resources. The strategy can reduce the chaos caused by frequent adjustments and ensure that the team can focus on other important tasks. If the predicted return time is not within the preset accurate range, the system will re-evaluate the maintenance time based on the actual return situation and make adjustments. Optimize the maintenance time to ensure that the tool is available in the best condition, while preventing tool idleness or damage caused by improper maintenance time. The availability of the tool directly affects the progress and quality of the project, so timely adjustment of the maintenance plan can ensure the smooth progress of the project and reduce waste of manpower and material resources. Based on the adjusted maintenance time, the system will re-evaluate the maintenance strategy to adapt to the new return information and maintenance requirements. Form a dynamic maintenance system that can continuously optimize the maintenance strategy according to the actual situation. The maintenance strategy needs to flexibly adapt to changes. Only through dynamic adjustment can the efficient utilization of the tool and the smooth progress of the project be ensured.

[0111] The intelligent management method for tool borrowing and returning based on RFID technology in this application ensures that only eligible users can borrow tools by automatically obtaining tool types and user information, enhancing the security of borrowing. Secondly, by real-time recording the borrowing and returning times and combining the current and historical status information of the tool, it can accurately determine whether the tool meets the return conditions, thereby reducing management risks. Finally, through the analysis of the tool usage status, it ensures that only tools meeting safety standards continue to be used, further enhancing the efficiency and security of overall tool management. This systematic management method effectively reduces manual intervention and improves the transparency and reliability of the tool borrowing and returning process.

[0112] Refer to Figure 3 , an intelligent management system for tool borrowing and returning based on RFID technology is further provided in an embodiment of this application, including:

[0113] The first acquisition module 1 is used to obtain the tool type and user information of the tag when receiving the tag lending request information of RFID;

[0114] A judgment module 2, configured to judge whether a user meets the lending condition according to the tool type and user information;

[0115] A marking module 3, configured to mark the lending time when the user meets the lending condition;

[0116] A second acquisition module 4, configured to, when receiving the tag return information, acquire the current status information and historical status information of the tool, and judge whether the return condition is met according to the current status information and historical status information;

[0117] A third acquisition module 5, configured to, when the return condition is met, acquire the lending time and return time, and determine the return of the tool this time according to the return time, lending time and tool type;

[0118] An analysis module 6, configured to analyze whether the tool meets the condition for continued use based on the result of tool return;

[0119] An update module 7, configured to update the tag status and tool status information when the tool meets the condition for continued use.

[0120] As described above, it can be understood that each component of the tool borrowing and returning intelligent management system based on RFID technology proposed in this application can implement the functions of any one of the above-mentioned tool borrowing and returning intelligent management methods based on RFID technology, and the specific structure will not be elaborated.

[0121] Refer to Figure 4 , an embodiment of the present application further provides a computer device, which may be a server, and its internal structure may be as Figure 4 shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store data such as monitoring data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a tool borrowing and returning intelligent management method based on RFID technology.

[0122] The above-mentioned processor executes the above-mentioned intelligent management method for tool borrowing and returning based on RFID technology, including: when receiving the RFID tag lending request information, obtaining the tool type and user information of the tag; judging whether the user meets the lending conditions according to the tool type and user information; when the user meets the lending conditions, marking the lending time; when receiving the tag return information, obtaining the current status information and historical status information of the tool, and judging whether the return conditions are met according to the current status information and historical status information; when the return conditions are met, obtaining the lending time and return time, and determining the return of the tool this time according to the return time, lending time and tool type; based on the result of tool return, analyzing whether the tool meets the conditions for continued use; when the tool meets the conditions for continued use, updating the tag status and the status information of the tool.

[0123] The above-mentioned intelligent management method for tool borrowing and returning based on RFID technology automatically obtains the tool type and user information, ensuring that only eligible users can borrow tools, thus enhancing the security of borrowing. Secondly, by recording the lending and return times in real time and combining the current and historical status information of the tool, it can accurately judge whether the tool meets the return conditions, thereby reducing the management risk. Finally, by analyzing the usage status of the tool, it ensures that only tools meeting safety standards can continue to be used, further enhancing the efficiency and security of overall tool management. This systematic management method effectively reduces manual intervention and improves the transparency and reliability of the tool borrowing and returning process.

[0124] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements an intelligent management method for tool borrowing and returning based on RFID technology, including the steps: when receiving the RFID tag lending request information, obtaining the tool type and user information of the tag; judging whether the user meets the lending conditions according to the tool type and user information; when the user meets the lending conditions, marking the lending time; when receiving the tag return information, obtaining the current status information and historical status information of the tool, and judging whether the return conditions are met according to the current status information and historical status information; when the return conditions are met, obtaining the lending time and return time, and determining the return of the tool this time according to the return time, lending time and tool type; based on the result of tool return, analyzing whether the tool meets the conditions for continued use; when the tool meets the conditions for continued use, updating the tag status and the status information of the tool.

[0125] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0126] It should be noted that in this document, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, apparatus, article or method comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article or method. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, apparatus, article or method comprising the element.

[0127] The above are only the preferred embodiments of this application, and do not limit the patent scope of this application accordingly. Any equivalent structural or equivalent process transformation made by using the specification and drawings of this application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of this application.

Claims

1. A tool borrowing and returning intelligent management method based on RFID technology, characterized in that: The method comprises: When receiving the tag lending request information of the RFID, obtaining the tool type and user information of the tag; Determining whether the user meets the lending conditions according to the tool type and user information; When the user meets the lending conditions, the lending time is marked; When the tag return information is received, the current status information and historical status information of the tool are obtained, and whether the return condition is met according to the current status information and historical status information; When the return conditions are met, the loan time and return time are obtained, and the return of the tool is determined based on the return time, loan time and tool type; Based on the result of the tool return, analyzing whether the tool meets the conditions for continued use; When the tool meets the condition for continued use, updating the tag status and the status information of the tool; After the step of updating the tag status and the status information of the tool, the method further includes: collecting the tools that are not currently returned and classifying the tools that are not currently returned; based on the classification result, obtaining the historical borrowing data of each type of tool, the historical borrowing data including the borrowing duration, the return time and the maintenance history thereof; predicting the return time of each type of tool according to the historical borrowing data of each type of tool; constructing a statistical model, inputting the predicted return time and the maintenance history of the same type of tool into the statistical model, analyzing and outputting a maintenance plan through the statistical model, the maintenance plan being used to arrange the maintenance of the same type of tools within the same time period; formulating a maintenance strategy based on the maintenance plan; centrally processing similar tools, and formulating specific maintenance strategies according to the maintenance plan and the usage of the tools, including the maintenance frequency, the required materials, the personnel arrangement and the shared parts.

2. The intelligent management method for tool borrowing and returning based on RFID technology according to claim 1 is characterized in that: The method of analyzing whether the tool meets the conditions for continued use comprises: Acquiring the type of the tool, and determining safety standard data for continued use of the tool according to the type of the tool; Build a safety analysis model based on the types of all tools and the corresponding safety standard data; Acquire historical status information and current status information, input the type of the tool, the historical status information and the current status information into a safety analysis model, predict the safety factor of the tool through the safety analysis model, and output the prediction result; When the predicted safety factor is greater than a preset factor threshold, it is determined that the tool meets the conditions for continued use.

3. The intelligent management method for tool borrowing and returning based on RFID technology according to claim 2 is characterized in that: After the step of when the tool meets the condition for continued use and before the step of updating the tag status and the status information of the tool, the method further includes: Get the lending frequency and current status information of the current instrument; Inputting the lending frequency and current status information of the tool into a tool rotation model, analyzing whether the tool meets the rotation conditions through the tool rotation model, and outputting the analysis result; If the analysis result shows that the instrument meets the rotation conditions, then the same type of rotation instruments are matched to limit the number of times each instrument is lent; Based on the matching results, the label status and status information of the rotation tool are updated.

4. The intelligent management method for tool borrowing and returning based on RFID technology according to claim 1 is characterized in that: The method further comprises: Obtain usage data of all tools, and calculate the usage rate of each tool based on the usage data of all tools; Extract tools with low usage rate according to preset usage rate standards; Based on the tools with low usage rate, current status information and historical status information of the tools are obtained; Analyze the state change data of the tool according to the current state information and historical state information of the tool; Obtaining the average single usage duration and usage location of the tool; Predict user usage habits and scenarios based on tool status change data, average usage time, and usage location; Analyze the reasons for low tool usage rate based on the user's usage habits and usage scenarios; Based on the results of the causal analysis, a tool adjustment strategy is generated.

5. The intelligent management method for tool borrowing and returning based on RFID technology according to claim 4 is characterized in that: The method further comprises: Based on the usage data of all tools, analyze the usage rate of each tool in time series and identify the high-frequency time periods for each tool; Conduct time-correlation analysis on the high-frequency time periods of each tool, including working hours, rest time, and seasonal factors; Based on the usage data of all tools and the analysis results of the time-related points, predict the user's demand for the target tool at the time-related points; If the forecast result shows that the demand for the target tool is greater than the existing inventory of the target tool, a strategy is formulated to increase the quantity of the target tool in the high-frequency time period.

6. The intelligent management method for tool borrowing and returning based on RFID technology according to claim 5 is characterized in that: After the step of formulating a strategy to increase the quantity of target tools in the high-frequency time period if the predicted result is that the demand for the target tool is greater than the inventory of the existing target tool, the method further includes: Analyzing whether the management end adopts the formulated strategy; If the management end adopts the strategy of increasing the number of target tools in the high-frequency time period, the usage rate change data of the target tools in the high-frequency time period is obtained in real time; Compare the current usage of the target tool with the historical usage of the target tool and analyze whether the usage of the target tool has increased; When the usage rate of the target tool increases, the result of predicting the user's demand for the target tool is determined to be a credible result.

7. A tool borrowing and returning intelligent management system based on RFID technology, used in the method described in any one of claims 1 to 6, characterized in that: include: A first acquisition module, configured to acquire the tool type and user information of the tag when receiving tag lending request information from the RFID; A judgment module, used to judge whether the user meets the lending conditions according to the tool type and user information; A marking module, used for marking the lending time when the user meets the lending conditions; A second acquisition module is used to acquire the current status information and historical status information of the tool when the tag return information is received, and determine whether the return condition is met according to the current status information and historical status information; The third acquisition module is used to acquire the loan time and return time when the return condition is met, and determine the return of the tool according to the return time, loan time and tool type; An analysis module, used for analyzing whether the tool meets the conditions for continued use based on the result of the tool return; The updating module is used to update the label status and the status information of the tool when the tool meets the condition for continued use.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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