A task work order process operation and maintenance system

Abstract

The present invention relates to the field of operation and maintenance management, and discloses a task work order process operation and maintenance system, comprising a data acquisition module, which is used to acquire an operation parameter data set of hospital equipment; a data processing module, which is used to pre-process the operation parameter data set and obtain the average value of each monitoring item; an analysis and judgment module, which compares the current operation parameters of hospital equipment with preset operation parameter thresholds and determines whether the hospital equipment is in a stable operation state; a work order generation module, which obtains abnormal operation parameter information and corresponding time points corresponding to the hospital equipment and generates a work order accordingly; a process approval module, which is used to receive and approve work orders; an execution module, which sorts the work orders and pushes them to a mobile terminal worn by an operation and maintenance personnel according to priority, and the operation and maintenance personnel complete the task if the task is successfully executed, and executes a rollback mechanism if the task fails; and a visualization module, which uses an independent window to visualize the data.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance management, and in particular to a task work order process-based operation and maintenance system. Background Art

[0002] Smart healthcare construction has made some progress in my country, but it still faces some challenges and problems. With the advancement of technology and the improvement of policies, hospitals have built their own operation and maintenance systems and have their own set of process-based maintenance methods for their IT businesses.

[0003] At present, many operation and maintenance systems are insufficient in the integration of processing tasks, work orders, equipment alarms and automated operation and maintenance, resulting in the inability to form a complete closed loop of operation and maintenance work. As a result, the entire operation and maintenance management is in a decentralized state, the data of each process is redundant and unnecessary, there is no effective data to support the responsibility audit, and when problems arise, it is impossible to trace them to specific links, which brings certain risks to the operation and maintenance work. Summary of the invention

[0004] The purpose of the present invention is to provide a task and work order process operation and maintenance system to solve the problems that many current operation and maintenance systems are insufficient in the integration of processing tasks, work orders, equipment alarms and automated operation and maintenance, resulting in the inability to form a complete closed loop of operation and maintenance work. As a result, the entire operation and maintenance management is in a decentralized state, the data of each process is redundant and unnecessary, there is no effective data to support the responsibility audit, and when problems arise, it is impossible to trace the specific links, thereby bringing certain risks to the operation and maintenance work.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A task work order process operation and maintenance system, including:

[0007] The data collection module is used to collect the operating parameter data sets of several hospital equipment in the operation and maintenance area;

[0008] The data processing module is used to pre-process the operating parameter data set and obtain the average value of each monitoring item within a monitoring cycle;

[0009] The analysis and judgment module compares the current operating parameters of the hospital equipment with the preset operating parameter thresholds, and judges whether the hospital equipment is in a stable operating state based on the comparison results. If at least one operating parameter of the hospital equipment exceeds the threshold of the monitoring item, the hospital equipment is judged to be in an abnormal operating state; otherwise, the hospital equipment is judged to be in a normal operating state;

[0010] The work order generation module obtains the abnormal operation parameter information and the corresponding time point corresponding to the hospital equipment, obtains the corresponding operation and maintenance level information in the fault operation and maintenance database according to the abnormal operation parameter information, and generates a work order;

[0011] The process approval module is used to receive work orders and approve the operation and maintenance personnel and resources to be called based on the work order content;

[0012] The execution module is used to sort the approved work orders and push them to the mobile terminals worn by the operation and maintenance personnel according to their priorities. If the operation and maintenance personnel successfully execute the task, the task ends; if it fails, the rollback mechanism is executed;

[0013] The visualization module uses an independent window to visualize the data in system operation.

[0014] Through the above technical solution, closed-loop processing of operation and maintenance task work orders is achieved, while reducing the process of human participation and improving the efficiency of operation and maintenance management.

[0015] As a further technical solution, the system further includes: an inspection module for performing random inspections on medical devices in normal operating conditions.

[0016] Through the above technical solution, an inspection module is set up for hospital equipment that is operating normally, and random inspections can be carried out to ensure the smooth operation of hospital equipment and discover potential risks in advance.

[0017] As a further technical solution, the judgment and analysis module further includes a prediction and analysis unit for performing a failure probability prediction and analysis on hospital equipment in a normal operating state, and generating a frequency adjustment signal according to the result of the prediction and analysis;

[0018] The inspection module adjusts the inspection frequency of the corresponding hospital equipment after receiving the frequency adjustment signal.

[0019] Through the above technical solution, it is possible to perform fault probability prediction analysis on hospital equipment in normal operation, and generate a frequency adjustment signal based on the results of the prediction analysis. After receiving the frequency adjustment signal, the inspection module adjusts the inspection frequency of the corresponding hospital equipment, thereby making effective inspection resources more efficiently utilized.

[0020] As a further technical solution, the specific method for adjusting the inspection frequency of the hospital equipment includes:

[0021] Establish a letter set corresponding to n hospital equipments one by one. In the initial state, the number of letters in the letter set is equal and each letter is different.

[0022] Process the frequency adjustment signal into a frequency adjustment coefficient according to the rules, and then obtain the corresponding letter adjustment amount from the preset comparison table according to the frequency adjustment coefficient;

[0023] After controlling the letter set corresponding to the hospital equipment to increase or decrease according to the letter adjustment amount, the new inspection frequency of the current hospital equipment can be obtained.

[0024] Through the above technical solution, a corresponding letter set is established starting from the same number, and the number of letters is increased or decreased accordingly according to the frequency adjustment coefficient during the subsequent inspection process, so that the data can be processed more simply and intuitively, reducing the amount of calculation and adjustment difficulty of the inspection frequency adjustment.

[0025] As a further technical solution, the working process of the prediction and analysis unit includes:

[0026] By formula:

[0027]

[0028] Calculate the failure probability F, i∈[1, m], where m is the total number of monitoring items of hospital equipment. is the weight coefficient of the operating parameter corresponding to the i-th monitoring item, E i is the safety score of the operating parameter corresponding to the i-th monitoring item;

[0029] The failure probability F is compared with the preset threshold F 阈 For comparison,

[0030] If F ≥ F 阈 , then the probability of equipment failure in the current hospital is high, and a signal to increase the inspection frequency is generated

[0031] Otherwise, the current probability of hospital equipment failure is small, and a signal to reduce the inspection frequency is generated.

[0032] Through the above technical solution, the higher the safety score of the current hospital equipment, the lower the final failure probability; if the safety score of each operating parameter of the current hospital equipment is lower, the higher the final failure probability; thus, the inspection frequency of the corresponding hospital equipment can be increased or decreased according to the numerical value of the failure probability, and special attention can be paid to the hospital equipment with a high failure probability in advance.

[0033] As a further technical solution, obtaining the safety score E i The method is:

[0034] Get the curve E of each monitoring item changing over time in a monitoring cycle i (t);

[0035] Divide a monitoring cycle into multiple monitoring periods according to preset time periods;

[0036] By formula: Calculate the safety score E of the operating parameter corresponding to the i-th monitoring item i ;

[0037] Among them, μ ijis the preset proportional coefficient corresponding to each operating parameter in the jth monitoring period, ΔQ ij is the state reference value of each operating parameter in the jth monitoring period, E i’ For the preset safety points, It is the mean value of each operating parameter in the previous monitoring cycle.

[0038] Through the above technical solution, it is possible to judge the stability of the current hospital equipment within each monitoring period, and it can reflect which specific operating parameter has a larger deviation within which monitoring time, and the influencing factors related to the operating parameter all have potential risks.

[0039] As a further technical solution, the method for obtaining the frequency adjustment coefficient is:

[0040] When F ≥ F 阈 When, through the formula: Calculate the frequency adjustment factor R + ;

[0041] Otherwise, by the formula: Calculate the frequency adjustment coefficient R - .

[0042] Through the above technical solution, according to the above-mentioned failure probability F and the preset threshold F 阈 According to the comparison situation, it is divided into two situations: increasing the inspection frequency and decreasing the inspection frequency. The inspection frequency is adjusted in real time according to the status of hospital equipment. This can not only maintain efficient inspection of each hospital equipment, but also focus on monitoring hospital equipment with a higher probability of failure, ultimately achieving the effect of optimizing inspection efficiency.

[0043] As a further technical solution, the mobile terminal includes but is not limited to a smart phone, a notebook or a tablet.

[0044] Beneficial effects of the present invention:

[0045] (1) Through the comprehensive cooperation of data collection module, data processing module, analysis and judgment module, work order generation module, process approval module, execution module and visualization module, the closed-loop processing of operation and maintenance task work orders is realized, while reducing the process of human participation and improving the efficiency of operation and maintenance management;

[0046] (2) The prediction and analysis unit can perform a failure probability prediction analysis on hospital equipment in normal operation and generate a frequency adjustment signal based on the prediction and analysis results. After receiving the frequency adjustment signal, the inspection module adjusts the inspection frequency of the corresponding hospital equipment, thereby making effective inspection resources more efficiently utilized;

[0047] (3) Through the set calculation formula, it can be known that the higher the safety score of the current hospital equipment, the lower the final failure probability; the lower the safety score of each operating parameter of the current hospital equipment, the higher the final failure probability; thus, the inspection frequency of the corresponding hospital equipment can be increased or decreased according to the numerical value of the failure probability, and special attention can be paid to the hospital equipment with a high failure probability in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below in conjunction with the accompanying drawings.

[0049] Figure 1 It is a partial flow chart of the present invention;

[0050] Figure 2 It is the system frame of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1-Figure 2 As shown, the present invention is a task work order process operation and maintenance system, comprising:

[0053] The data acquisition module is used to collect the operating parameter data sets of several hospital equipment in the operation and maintenance area; the data can be obtained based on the monitoring equipment deployed in each operation and maintenance area and the various sensors deployed at the key nodes of each hospital equipment. The specific installation method of each type of sensor is carried out by the on-site staff and will not be repeated here;

[0054] The data processing module is used to pre-process the operating parameter data set to obtain the average value of each monitoring item in a monitoring cycle; the process of pre-processing the operating parameter data set is the average value formula in the existing statistical data, which is the existing technology and will not be repeated here;

[0055] The analysis and judgment module compares the current operating parameters of the hospital equipment with the preset operating parameter thresholds, and judges whether the hospital equipment is in a stable operating state based on the comparison results. If at least one operating parameter of the hospital equipment exceeds the threshold of the monitoring item, the hospital equipment is judged to be in an abnormal operating state, otherwise, the hospital equipment is judged to be in a normal operating state; the threshold of the monitoring item is determined based on the information of the hospital equipment itself and the empirical data, which will not be repeated here;

[0056] The work order generation module obtains the abnormal operation parameter information and the corresponding time point corresponding to the hospital equipment, obtains the corresponding operation and maintenance level information in the fault operation and maintenance database according to the abnormal operation parameter information, and generates a work order;

[0057] The process approval module is used to receive work orders and approve the operation and maintenance personnel and resources to be called based on the work order content;

[0058] An execution module is used to sort the approved work orders and push them to the mobile terminal worn by the operation and maintenance personnel according to the priority. If the operation and maintenance personnel successfully execute the task, the task ends. If it fails, a rollback mechanism is executed; the mobile terminal includes but is not limited to a smart phone, a notebook or a tablet;

[0059] The visualization module uses an independent window to visualize the data in system operation; through front-end technologies such as Vue, the data is displayed throughout the entire process, making it easy to query historical records.

[0060] The system also includes: an inspection module, which is used to perform random inspections on medical devices in normal operating states.

[0061] In this embodiment, the operation of all hospital equipment in the transport area is monitored through the data acquisition module, and the monitored operating parameters are compared with the corresponding operating parameter thresholds. Once an operating parameter of the current hospital equipment exceeds the operating parameter threshold, it is determined that the hospital equipment is in an abnormal operating state, and the operating parameter information and the corresponding time point of the hospital equipment are immediately retrieved. Based on the fault operation and maintenance database set up in the system, the fault and operation and maintenance level corresponding to the abnormal parameters of the hospital equipment can be directly obtained, and then an operation and maintenance work order is generated. The operation and maintenance work order includes the called operation and maintenance personnel and the required operation and maintenance resources, such as maintenance tools; the process approval module determines whether the execution conditions of the operation and maintenance work order are met based on the operation and maintenance personnel information registration form and the operation and maintenance resource registration form. If met, it is approved, and the operation and maintenance work order reaches the execution The operation module allocates operation and maintenance work orders with high operation and maintenance levels to the mobile terminals carried by the operation and maintenance personnel. After receiving the operation and maintenance work orders, the operation and maintenance personnel perform the corresponding operation and maintenance tasks. When the operation and maintenance personnel successfully complete the operation and maintenance task, the task is completed. If the operation and maintenance task is not completed or cannot be completed, the task is returned to the initial state according to the rollback mechanism, and a new operation and maintenance work order is regenerated until the operation and maintenance task is resolved. The data generated by the operation of the above-mentioned operation and maintenance work orders are displayed by the visualization module to facilitate real-time management by the background management personnel, and the inspection module is set for the hospital equipment that operates normally, which can perform random inspections to ensure the smooth operation of the hospital equipment. In summary, the closed-loop processing of the operation and maintenance task work order is realized through the above process, while the process of human participation is reduced and the efficiency of operation and maintenance management is improved.

[0062] The judgment and analysis module also includes a prediction and analysis unit, which is used to perform a failure probability prediction and analysis on hospital equipment in a normal operating state, and generate a frequency adjustment signal according to the result of the prediction and analysis;

[0063] The inspection module adjusts the inspection frequency of the corresponding hospital equipment after receiving the frequency adjustment signal.

[0064] In this embodiment, the prediction and analysis unit can perform failure probability prediction analysis on hospital equipment in normal operation, and generate a frequency adjustment signal based on the results of the prediction and analysis. After receiving the frequency adjustment signal, the inspection module adjusts the inspection frequency of the corresponding hospital equipment, thereby making effective inspection resources more efficiently utilized.

[0065] The working process of the prediction and analysis unit includes:

[0066] By formula:

[0067]

[0068] Calculate the failure probability F, i∈[1, m], where m is the total number of monitoring items of hospital equipment. is the weight coefficient of the operating parameter corresponding to the i-th monitoring item, E i is the safety score of the operating parameter corresponding to the i-th monitoring item;

[0069] The failure probability F is compared with the preset threshold F 阈 For comparison,

[0070] If F ≥ F 阈 , then the probability of equipment failure in the current hospital is high, and a signal to increase the inspection frequency is generated

[0071] Otherwise, the current probability of hospital equipment failure is small, and a signal for reducing the inspection frequency is generated. In this embodiment, a working method of a prediction and analysis unit is provided, through the formula: Calculate the failure probability F, i∈[1, m], where m is the total number of monitoring items of hospital equipment. is the weight coefficient of the operating parameter corresponding to the i-th monitoring item, E i is the safety score of the operating parameter corresponding to the i-th monitoring item; the failure probability F is compared with the preset threshold F 阈 For comparison, if F ≥ F 阈, then the current hospital equipment failure probability is relatively high, and a signal for increasing the inspection frequency is generated; otherwise, the current hospital equipment failure probability is relatively low, and a signal for decreasing the inspection frequency is generated; it can be seen from the above formula that if the safety score of the current hospital equipment is higher, the final failure probability is lower; if the safety score of each operating parameter of the current hospital equipment is lower, the final failure probability is higher; thus, the inspection frequency of the corresponding hospital equipment can be increased or decreased according to the numerical value of the failure probability, and the hospital equipment with a high failure probability can be paid special attention in advance.

[0072] Get the security score i The method is:

[0073] Get the curve E of each monitoring item changing over time in a monitoring cycle i (t);

[0074] Divide a monitoring cycle into multiple monitoring periods according to preset time periods;

[0075] By formula: Calculate the safety score E of the operating parameter corresponding to the i-th monitoring item i ;

[0076] Among them, μ ij is the preset proportional coefficient corresponding to each operating parameter in the jth monitoring period, ΔQ ij is the state reference value of each operating parameter in the jth monitoring period, E i’ For the preset safety points, is the mean value of each operating parameter in the previous monitoring period, t a ,t b are the left and right endpoints of the jth monitoring period.

[0077] In this embodiment, a method for obtaining a safety score is provided. Specifically, the formula is: Calculate the safety score E of the operating parameter corresponding to the i-th monitoring item i ; where μ ij is the preset proportional coefficient corresponding to each operating parameter in the jth monitoring period, ΔQ ij is the state reference value of each operating parameter in the jth monitoring period, E i’ For the preset safety points, is the mean value of each operating parameter in the previous monitoring period, t a ,t b are the left and right endpoints of the jth monitoring period; obviously, when the preset safety score remains unchanged, the greater the deviation between the real-time operating parameter and its corresponding mean, the lower the safety score of the operating parameter, which can also reflect the overall operating stability of the hospital equipment.

[0078] The specific method for adjusting the inspection frequency of the hospital equipment includes:

[0079] Establish a letter set corresponding to n hospital equipments one by one. In the initial state, the number of letters in the letter set is equal and each letter is different.

[0080] Process the frequency adjustment signal into a frequency adjustment coefficient according to the rules, and then obtain the corresponding letter adjustment amount from the preset comparison table according to the frequency adjustment coefficient;

[0081] After controlling the letter set corresponding to the hospital equipment to increase or decrease according to the letter adjustment amount, the new inspection frequency of the current hospital equipment can be obtained.

[0082] In the present embodiment, a method for adjusting the inspection frequency is provided; specifically, a letter set corresponding to n hospital equipment is established, and in an initial state, the number of letters in the letter set is equal, and each letter is different; the frequency adjustment signal is then processed into a frequency adjustment coefficient according to a rule, and then the corresponding letter adjustment amount is obtained from a preset comparison table according to the frequency adjustment coefficient; then the letter set corresponding to the hospital equipment is controlled to increase or decrease according to the letter adjustment amount, so as to obtain a new inspection frequency of the current hospital equipment; through the above process, the corresponding letter set is established starting from the same number, and in the subsequent inspection process, the number of letters is correspondingly increased or decreased according to the frequency adjustment coefficient, so that the data can be processed more simply and intuitively, reducing the amount of calculation and adjustment difficulty of the inspection frequency adjustment.

[0083] The method for obtaining the frequency adjustment coefficient is:

[0084] When F ≥ F 阈 When, through the formula: Calculate the frequency adjustment factor R + ;;

[0085] Otherwise, by the formula: Calculate the frequency adjustment coefficient R - .

[0086] In this embodiment, a method for obtaining a frequency adjustment coefficient is provided, according to the aforementioned fault probability F and the preset threshold F 阈 The comparison situation is divided into two cases: increasing the inspection frequency and decreasing the inspection frequency. Specifically, when F ≥ F 阈 When, through the formula: Calculate the frequency adjustment factor R + ; Otherwise, by the formula: Calculate the frequency adjustment coefficient R -Through the above process, the inspection frequency can be adjusted in real time according to the status of hospital equipment, which can not only maintain efficient inspection of each hospital equipment, but also focus on monitoring hospital equipment with a higher probability of failure, ultimately achieving the effect of optimizing inspection efficiency.

[0087] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A task work order process operation and maintenance system, characterized in that: include: The data collection module is used to collect the operating parameter data sets of several hospital equipment in the operation and maintenance area; The data processing module is used to pre-process the operating parameter data set and obtain the average value of each monitoring item within a monitoring cycle; The analysis and judgment module compares the current operating parameters of the hospital equipment with the preset operating parameter thresholds, and judges whether the hospital equipment is in a stable operating state based on the comparison results. If at least one operating parameter of the hospital equipment exceeds the threshold of the monitoring item, the hospital equipment is judged to be in an abnormal operating state; otherwise, the hospital equipment is judged to be in a normal operating state; The work order generation module obtains the abnormal operation parameter information and the corresponding time point corresponding to the hospital equipment, obtains the corresponding operation and maintenance level information in the fault operation and maintenance database according to the abnormal operation parameter information, and generates a work order; The process approval module is used to receive work orders and approve the operation and maintenance personnel and resources to be called based on the work order content; The execution module is used to sort the approved work orders and push them to the mobile terminals worn by the operation and maintenance personnel according to their priorities. If the operation and maintenance personnel successfully execute the task, the task ends; if it fails, the rollback mechanism is executed; Visualization module, using an independent window to visualize the data in system operation; The system further comprises: an inspection module for performing random inspections on medical devices in normal operating states; The analysis and judgment module also includes a prediction analysis unit, which is used to perform a failure probability prediction analysis on hospital equipment in a normal operating state, and generate a frequency adjustment signal according to the result of the prediction analysis; The inspection module adjusts the inspection frequency of the corresponding hospital equipment after receiving the frequency adjustment signal; The specific method for adjusting the inspection frequency of the hospital equipment includes: Establish a letter set corresponding to n hospital equipments one by one. In the initial state, the number of letters in the letter set is equal and each letter is different. Process the frequency adjustment signal into a frequency adjustment coefficient according to the rules, and then obtain the corresponding letter adjustment amount from the preset comparison table according to the frequency adjustment coefficient; After controlling the letter set corresponding to the hospital equipment to increase or decrease according to the letter adjustment amount, the new inspection frequency of the current hospital equipment can be obtained; The working process of the prediction analysis unit includes: By formula: Calculate the failure probability F, i∈[1, m], where m is the total number of monitoring items of hospital equipment. is the weight coefficient of the operating parameter corresponding to the i-th monitoring item, E i is the safety score of the operating parameter corresponding to the i-th monitoring item; The failure probability F is compared with the preset threshold F 阈 For comparison, If F ≥ F 阈 , then the probability of equipment failure in the current hospital is high, and a signal to increase the inspection frequency is generated Otherwise, the probability of equipment failure in the current hospital is low, and a signal to reduce the inspection frequency is generated; Get the security score i The method is: Get the curve E of each monitoring item changing over time in a monitoring cycle i (t); Divide a monitoring cycle into multiple monitoring periods according to preset time periods; By formula: Calculate the safety score E of the operating parameter corresponding to the i-th monitoring item i ; Among them, μ ij is the preset proportional coefficient corresponding to each operating parameter in the jth monitoring period, ΔQ ij is the state reference value of each operating parameter in the jth monitoring period, E i ' is the preset security score, is the mean value of each operating parameter in the previous monitoring cycle; The method for obtaining the frequency adjustment coefficient is: When F ≥ F 阈 When, through the formula: Calculate the frequency adjustment factor R + ; Otherwise, by the formula: Calculate the frequency adjustment coefficient R - .

2. The task work order process operation and maintenance system according to claim 1 is characterized in that: The mobile terminal includes but is not limited to a smart phone, a notebook or a tablet.

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