Calibration management method and calibration management system for measuring instruments

Abstract

A calibration management method and a calibration management system for measuring instruments that predict the calibration timing of measuring instruments used in various tests of electrical equipment and enable efficient use of time are provided. [Solution] In an AI-based measuring instrument calibration management system that manages the schedule for loaning a replacement machine from a management company to a user during calibration work, log information indicating the type of measuring instrument, the number of times it has been used within a specified period, and the usage environment (temperature, humidity) is collected by a log collection unit 4 and recorded in a maintenance database 11. A knowledge database 10 containing a maintenance learning model 12 constructed from the maintenance database 11 is referenced, and a calibration timing prediction unit 5 predicts the calibration timing, and a demand prediction unit 6 determines the schedule for the loan timing and loan period of the replacement machine and adjusts the schedule if any inconvenience occurs.

Description

[Technical Field]

[0001] The present invention relates to a calibration management method and a calibration management system for measuring instruments that predict the calibration timing of measuring instruments used by users in various tests of electrical equipment and manage a schedule for lending loaner instruments from a management company to users during the calibration work using AI (Artificial Intelligence), which is information processing by computer. [Background technology]

[0002] Measuring instruments used for various tests on electrical equipment generally include circuit meters (tester) that measure current, voltage, and resistance, clamp meters that measure load current and leakage current, insulation resistance meters (meggers) that measure insulation resistance, and earth resistance meters (earth testers) that measure earth resistance. The timing of maintenance (calibration and repair) of measuring instruments, etc., has generally been determined by public standards, voluntary standards, etc., depending on the time (number of days) that has passed since purchase or the most recent maintenance, such as once a year.

[0003] Patent document 1 describes a method for predicting when a radiation detector will break, managing an inventory of replacement units, and repairing or replacing the detector before it becomes unusable, thereby reducing downtime and costs due to damage to the radiation detector.

[0004] Furthermore, Patent Document 2 describes the use of time-series data on operating conditions, failure history data, and the like to predict equipment failures. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2023-118666 [Patent Document 2] Japanese Patent Application Laid-Open No. 2024-57316 Summary of the Invention [Problem to be solved by the invention]

[0006] In the above-mentioned conventional technology, even if the failure (calibration) timing (schedule) management described in Patent Document 2 and the replacement machine inventory management described in Patent Document 1 are combined, the error in the measurement value may exceed the allowable value earlier than this period depending on the user's method of using the measuring instrument, the usage environment, etc.

[0007] On the other hand, there were also cases where the error remained within the tolerance even after the expected period had passed. To check this error, the measuring instrument in question was removed from its environment, stored in a specialized laboratory, and compared with a standard instrument, which meant that the instrument was unavailable during that time, resulting in downtime.

[0008] The object of the present invention is to solve the problems of the prior art described above, and to provide a method and system for managing the calibration of measuring instruments that can predict the timing of calibration of measuring instruments used in various tests of electrical equipment, etc., predict the demand for replacement instruments, and reduce downtime and be easy to use regardless of the variety of measuring instruments, user usage methods, and usage environments. [Means for solving the problem]

[0009] In order to achieve the above-mentioned object, the present invention provides a method for managing the calibration of measuring instruments using a computer, which predicts the calibration time of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user during calibration work, characterized in that the computer collects log information indicating the type of measuring instrument, the number of times it has been used within a specified period, and the usage environment (temperature, humidity) and records it in a maintenance database, the computer predicts the calibration time by referring to a knowledge database including a maintenance learning model constructed from the maintenance database, the computer determines the schedule for the loaner instrument lending time and loan period based on the predicted calibration time, and the computer adjusts the schedule if any inconvenience occurs with the determined schedule and lends the loaner instrument to the user. Here, the log information collected by the computer may include information about the usage environment, and the information about the usage environment may include information about temperature and humidity. Furthermore, the computer that collects log information and records it in the maintenance database, the computer that predicts the calibration time and determines the schedule for the loaner machine rental time and rental period based on the predicted calibration time, and the computer that adjusts the schedule and rents out the loaner machine to the user if any inconvenience occurs with the determined schedule may be the same computer, or may all be different computers. Alternatively, some of them may be the same computer.

[0010] Furthermore, in the above-described method for managing calibration of a measuring instrument, it is preferable that the measuring instrument used by the user is a loaned instrument loaned to the user by the management company.

[0011] Furthermore, in the above-described method for managing calibration of a measuring instrument, it is preferable that the measuring instrument used by the user is a measuring instrument owned by the user.

[0012] Furthermore, in the above-mentioned method for managing calibration of measuring instruments, if there are multiple users and the management company's facilities that can perform simultaneous calibration are insufficient to accommodate the number of users, it is preferable to advance the calibration period for one of the users.

[0013] Furthermore, in the above-described method for managing calibration of a measuring instrument, if calibration cannot be completed within the determined rental period, it is preferable to adjust the schedule so that the rental period is extended and a new measuring instrument is purchased and supplied to the user.

[0014] Furthermore, in the above-described method for managing calibration of measuring instruments, if the demand for replacement machines of the same type held by the management company increases and the computer determines by referring to the inventory database that the demand cannot be met, it is preferable that the computer notify the management company of arrangements to purchase new replacement machines at a time before the increased number of replacement machines start to be used, thereby adjusting the schedule.

[0015] Furthermore, the present invention provides an AI-based measuring instrument calibration management system that predicts the calibration timing of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user while the calibration work is being carried out, and includes: a log collection unit that collects log information indicating the type of measuring instrument, the number of times it has been used within a specified period, and the usage environment (temperature, humidity) and records it in a maintenance database; a knowledge database containing a maintenance learning model constructed from the maintenance database; a calibration timing prediction unit that predicts the calibration timing by referring to the knowledge database; and a demand prediction unit that determines the schedule for the loaner instrument lending timing and loan period based on the predicted calibration timing, and adjusts the schedule if any inconvenience occurs with the determined schedule. Here, the log information collected by the log collection unit may include information about the usage environment, and the information about the usage environment may include information about temperature and humidity.

[0016] Furthermore, in the above-described calibration management system for measuring instruments, it is preferable that the measuring instrument used by the user is a loaned instrument loaned to the user by the management company. [Effects of the Invention]

[0017] According to the present invention, by referring to a knowledge database including a maintenance learning model constructed from a maintenance database, the calibration time for the measuring instrument used by the user is predicted, a schedule for the time and period for lending a replacement instrument is determined, and if any inconvenience occurs with the determined schedule, the schedule is adjusted.This makes it possible to perform schedule management that shortens downtime and enables efficient use of time regardless of the demand for replacement instruments, the variety of measuring instruments, the user's usage method, or the usage environment. [Brief explanation of the drawings]

[0018] [Figure 1] FIG. 1 is a block diagram showing a calibration management system for measuring instruments that uses AI-based machine learning according to one embodiment of the present invention. [Figure 2] FIG. 10 illustrates log information for individual measuring instruments obtained from a user according to one embodiment. [Figure 3] FIG. 1 illustrates an example of a knowledge database 10 according to one embodiment. [Figure 4] 10 is a flowchart illustrating a process from identifying a measuring instrument to lending a replacement instrument according to one embodiment. [Figure 5] A time chart showing the schedule adjustments for loaned and loaner machines in the demand forecasting department, with the horizontal axis representing elapsed days (when the management company's facilities do not have enough facilities for simultaneous calibration to accommodate the number of users). [Figure 6] A time chart showing the schedule adjustments for loaned and replacement machines in the demand forecasting department, with the horizontal axis representing elapsed days (in cases where calibration is not possible due to lifespan, malfunction, etc.). [Figure 7] A time chart showing the schedule adjustments for loaned and replacement machines in the demand forecasting department, with the horizontal axis representing elapsed days (when demand increases). [Figure 8] FIG. 10 is a block diagram showing a calibration management system for measuring instruments that uses AI-based machine learning, which is a modified example of an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0019] There are many types of measuring instruments used for various tests on electrical equipment, as shown below. (1) Relay tester Multi-relay tester Phase characteristic tester Ratio differential tester Voltage 2-phase current 2-phase protective relay tester (2) Pressure tester AC withstand voltage tester Transformer, reactor VCB checker DC withstand voltage test Live line protection tester High voltage voltage detector withstand voltage tester Insulating oil withstand voltage tester (3) Pressure test equipment AC withstand voltage test equipment (4) Power, power quality Power Quality Analyzer Power Meter (5) Other measuring instruments Voltage drop type earth resistance measuring device, Earth resistivity measuring device, Infrared thermography, High voltage insulation resistance tester, Leakage current monitoring logger, Live line megger, DC leakage current logger (6) Calibration standard Multi-product calibrator Decade resistor Digital phase and frequency meter Digital multimeter AC and DC withstand voltage tester calibration equipment

[0020] The maintenance (calibration, repair) intervals for the above-mentioned measuring instruments have generally been determined by public or voluntary standards, such as once a year, depending on the time (number of days) that has elapsed since purchase or the most recent maintenance. For users who use these measuring instruments on-site, managing measurement error using a large number of different test instruments requires separate equipment, which is difficult. Therefore, users of measuring instruments typically rely on specialized laboratories with the necessary equipment and capabilities to measure and calibrate measurement errors, i.e., management companies, to perform this work on a regular or irregular basis.

[0021] In this embodiment, a management company enters into a measuring instrument rental contract and management contract, or only a management contract, with a user, and uses an AI calibration management system 1 to predict the calibration period (maintenance period) of the measuring instrument currently being used by the user based on maintenance data such as the usage environment, and manages the schedule and loans out loaner instruments during calibration work. Note that a measuring instrument loaned from a management company to a user (borrowed by the user) under a rental contract is referred to as a loaner instrument, and a measuring instrument loaned by the management company to a user during calibration work under a management contract is referred to as a loaner instrument.

[0022] The calibration management system 1 mainly performs the following steps. (1) Calibration prediction: Using AI, we analyze the usage and data of measuring instruments to predict the next calibration date. (2) Schedule management: When the calibration period approaches, manage the loan schedule for the replacement machine. (3) Management of loaner equipment: The management company lends a loaner equipment to the user so that the measuring instrument can continue to be used during the calibration work. To realize the calibration management system 1, an AI-based schedule management system is required, and it is desirable that the calibration management system 1 collects measurement instrument usage data in real time, predicts calibration timing, and automates the procedure for lending a loaner machine when necessary. The introduction of the calibration management system 1 will improve the efficiency of calibration work and user convenience.

[0023] A more specific example of this embodiment will be described below with reference to the drawings. Fig. 1 is a block diagram showing a calibration management system 1 for measuring instruments that uses AI-based machine learning according to one embodiment of the present invention. The calibration management system 1 is connected to user terminals 3 for each of a plurality of users via a network 2. The network 2 is configured from the Internet, an intranet, a wireless LAN (Local Area Network), a WAN (Wide Area Network), or the like.

[0024] The calibration management system 1 may be, for example, a general-purpose computer such as a workstation or personal computer, or may be configured using cloud computing, a cluster or multicomputer consisting of multiple computers, a virtual machine constructed virtually using software, or a quantum computer.

[0025] The information required for the calibration timing prediction unit 5, which predicts the calibration timing of a measuring instrument, is input from a user terminal 3 consisting of a personal computer to a log collection unit 4 via a network 2. FIG. 2 is a diagram showing the log information of an individual measuring instrument obtained from a user, showing at least the type of measuring instrument, the number of times it has been used within a specified period, and the environment in which it is used (temperature, humidity, etc.). In addition, the log information desirably includes the error in the measurement value at the time of the previous calibration, the error in the measurement value at the time of the current calibration, etc., and is recorded in a maintenance database 11.

[0026] The knowledge database 10 is configured to store and share information useful for predicting the time for calibration in a certain format, and includes a maintenance learning model 12 in which the prediction of the time for calibration is formulated. The maintenance learning model 12 is constructed from a database of the maintenance database 11, and is a machine learning model that formulates the results of a computer's evaluation and judgment of the maintenance data that is the result stored in the maintenance database 11.

[0027] FIG. 3 is a diagram showing an example of knowledge database 10. In addition to maintenance data, knowledge database 10 stores information such as how many times a measuring instrument is used per month, past deviation amounts, the user's internal rules, the measuring instrument manufacturer's standards, the user's past deviation amount data and deviation amount data for other users of the same measuring instrument, deviation amount data for the same measuring instrument held by the management company, reports from the previous year, and other information that is useful for users and management companies to predict the timing of calibration, know-how including compliance with acceptance standards and processing details, etc., which can be accumulated and shared in a set format.

[0028] 4 is a flowchart showing the process from identifying a measuring instrument to lending a replacement instrument according to this embodiment. First, a measuring instrument to be managed is identified according to a request from a user or a time period determined by a public standard, a voluntary standard, etc. (Step S1). A log showing the usage status of the identified measuring instrument is collected from the user terminal 3 (step S2).

[0029] The user terminal 3 is, for example, an information processing device such as a personal computer or tablet terminal, but may also be configured as a smartphone, mobile phone, PDA, etc. Furthermore, the log is input by the user via a graphical user interface (GUI) based on screen information displayed via the user interface on the user terminal 3. Preferably, the log is collected by providing a communication interface in the measuring instrument, and automatically transmitting the log to the calibration management system 1 via the network 2 on a regular or irregular basis.

[0030] Next, the knowledge database 10 is a computer program having a maintenance learning model 12, which is a machine learning algorithm for prediction and classification. The proofreading time prediction unit 5 refers to the already constructed knowledge database 10 (step S3), that is, predicts the proofreading time based on the formula by the machine learning algorithm (step S4). Furthermore, the calibration timing prediction unit 5 inputs an inquiry to the maintenance learning model 12 as needed, and obtains the evaluation and judgment results (step S5).

[0031] The calibration timing prediction is performed using one of the following methods: (1) linear regression, which is used to predict continuous values ​​and models data using a straight line; (2) logistic regression, which calculates the probability that a data point belongs to a particular class; (3) decision trees, which use data features to ask a series of questions in order and use branching conditions to make a final decision; (4) random forests, which are ensemble learning algorithms that combine multiple decision trees to make predictions; (5) neural network algorithms that are divided into an input layer that receives data, a hidden layer that processes and transforms the data, and an output layer that outputs the final prediction; and (6) Bayesian estimation, which uses observed data to update the parameters of a probabilistic model based on Bayes' theorem.

[0032] The calibration timing prediction unit 5 outputs the time when calibration will be required, that is, the predicted time when the measurement error of the measuring instrument will become larger than the reference value determined by public standards, voluntary standards, etc., as the calibration time to the demand prediction unit 6. In addition, the calibration timing prediction unit 5 refers to the maintenance database 11 to obtain the work period required to calibrate the measuring instrument and outputs this to the demand prediction unit 6 (step S6).

[0033] The demand forecasting unit 6 determines the calibration time (the time when a replacement machine will be lent) and the calibration work period as a schedule (step S7).

[0034] However, since the determined schedule may cause inconvenience in the following cases, the demand forecasting unit 6 checks whether or not the determined schedule will cause inconvenience, and if an inconvenience occurs, adjusts the schedule. (1) When the same type of measuring instrument (rental equipment) is rented to multiple users and the management company does not have enough facilities to calibrate simultaneously to accommodate the number of users, or when there are not enough loaned or replacement equipment. (2) If proofreading cannot be completed within the determined proofreading schedule. (3) When there is an increase in demand for the same type of measuring equipment (rented equipment and replacement equipment) owned by the management company.

[0035] The demand forecasting unit 6 adjusts the schedule for the loaned machine and the replacement machine (step S8) and notifies the user of the schedule (step S9). Thereafter, the management company lends out the replacement machine via the lending unit 7 based on the schedule (step S10). The lending unit 7 records the lending based on the schedule as a history. Then, the management company performs calibration work on the target measuring instruments collected from the users by mail or by bringing them in (step S11). When the calibration is complete, the calibrated measuring instrument is returned to the user (step S11), and a loaner instrument is returned from the user (step S13).

[0036] Figure 5 is a time chart with the horizontal axis representing elapsed days, showing the schedule adjustment of loaned and replacement machines in the demand forecasting unit 6. In this case, the above-mentioned inconvenience (1) occurs when the facilities of the management company that can perform simultaneous calibration are insufficient for the number of users (when there is only one facility that can perform simultaneous calibration, there are two users, and two measuring devices cannot be calibrated at the same time). Alternatively, this occurs when there are not enough loaned measuring devices.

[0037] Assume that users Y1 and Y2 have signed a measuring instrument rental contract and management contract. User Y1 uses measuring instrument K1 as a rental device from the management company, and user Y2 uses measuring instrument K2 as a rental device in the field.

[0038] The calibration time for measuring instrument K1 is predicted to be point a, the calibration period required for the calibration work is scheduled to start from point a and end at point b, and a loaner instrument D1 is loaned to user Y1 in place of measuring instrument K1. Measuring instrument K1 is scheduled to be calibrated from point a to point b during the calibration period. The calibration time for measuring instrument K2 is predicted to be point f, and the calibration period required for the calibration work is from point f to point g.

[0039] In this case, calibration work overlaps between point f and point b, so if the management company's facility cannot calibrate two measuring devices at the same time, the calibration work cannot be performed. Also, if the management company only has three measuring devices of the same type, K1, K2, and D1, it cannot supply loaner device D1 to user Y2 between point f and point b.

[0040] Therefore, the demand forecasting unit 6 adjusts the schedule and, for one of the users, for example, advances the calibration time (start of calibration) of measuring instrument K1 from point a to point c, and determines the calibration time and period so that the calibration work of measuring instrument K1 is completed by the predicted calibration time of measuring instrument K2, point f.

[0041] If the calibration work for measuring instrument K1 is completed by the calibration time point f, a loaner instrument D1 can be supplied to user Y2. The schedule adjustment in Figure 5 also applies when both users Y1 and Y2 own their own equipment and have only concluded a management contract without concluding a rental contract. The above was explained for the case of users Y1 and Y2, but the same applies when there are more users than users.

[0042] Figure 6 shows the response to the above-mentioned inconvenience (2) when the measuring instrument used by a user cannot be calibrated due to its lifespan, malfunction, etc. User Y1 has a measuring instrument loan contract and management contract with a management company. User Y1 borrows measuring instrument K1 from the management company and uses it in the field. The calibration time for measuring instrument K1 is predicted to be point a, and the calibration period required for the calibration work is scheduled to start at point a and end at point b.

[0043] If it is determined at point h during the calibration period of measuring instrument K1 that calibration is not possible due to a malfunction or the end of its life, the demand forecasting unit 6 adjusts the schedule and extends the loan period of loaner instrument D1 from point b to point j. The demand forecasting unit 6 also references the inventory database 20, and if there is an inventory of a measuring instrument identical to the measuring instrument K1 used by user Y1, it selects measuring instrument N1 from the inventory; if not, it adjusts the schedule so that a new measuring instrument N1 is purchased and supplied to user Y1. This makes it possible to eliminate downtime caused by delays in procuring measuring instruments, etc.

[0044] Figure 7 is a time chart with the horizontal axis representing the elapsed days, showing the schedule adjustment in the demand forecasting unit 6 when demand increases compared to the same type of measuring instruments (rented machines and replacement machines) owned by the management company in response to the above-mentioned inconvenience (3).

[0045] The management company owns four measuring instruments of the same type, K1, K2, D1, and D2, and this is recorded in the inventory database 20. Users Y1 and Y2 have signed measuring instrument rental and management contracts, and user Y1 uses measuring instrument K1 as a loaned instrument from the management company, and similarly user Y2 uses measuring instrument K2 as a loaned instrument in the field.

[0046] In the case of Figure 5, the management company only owns three measuring instruments of the same type: K1, K2, and D1, so the schedule was adjusted to bring forward the start of the calibration period for measuring instrument K1. In Figure 7, the management company owns four measuring instruments: K1, K2, D1, and D2, and the facility is allowed to calibrate more than two measuring instruments. Therefore, if there are only users Y1 and Y2, there is no need to adjust the schedule.

[0047] However, if the demand of new user Y3 increases, the four machines already owned will not be able to meet the demand. When the demand forecasting unit 6 acquires information that the demand for rental machines and replacement machines has increased, it refers to the inventory database 20 and determines whether or not to meet the demand.

[0048] If the demand forecasting unit 6 determines that it cannot meet the demand, it enters the field use of user Y3 into the schedule, issues a command to purchase a new measuring device N1 and a replacement device D3 at time point n before the start time m of the use of measuring device N1, and notifies the management company. This command is sent by alert, email, etc. to the management company. This also minimizes downtime due to delays in procuring loaned and replacement devices.

[0049] If the user does not enter into a rental contract but only into a management contract, the demand forecasting unit 6 contacts the user to prepare for the purchase, informing them that a new measuring instrument needs to be purchased. The management company notifies users who have entered into a management contract and are using the services of the calibration management system 1 that a replacement instrument will be loaned free of charge. In addition, the calibration management system 1 predicts the calibration period (calibration time) for the measuring instrument used by the user and notifies the user in advance by email or the like via the network 2 and user terminal 3.

[0050] When the user is notified of the loan period and work period for the measuring instrument, the user receives a loaner and sends the measuring instrument they were using to the management company by courier, drop-off, etc. The management company will loan a loaner instrument to the user if necessary. Once the calibration work for the measuring instrument used by the user is completed, the management company returns it to the user and receives the loaner instrument that was loaned to the user.

[0051] Since the calibration management system 1 uses AI to predict calibration times by referencing the knowledge database 10, the calibration frequency may change even for the same measuring instrument. Even in this case, the demand forecasting unit 6 can adjust the schedule for loaned machines and replacement machines as described above.

[0052] When the loaned machine is returned to the user, the calibration management system 1 records the calibration period, when the error in the measurement value becomes large, in the knowledge database 10 and provides this information to the user as a report. When a communication interface is provided on the loaned machine and the loaner machine, a monitoring device that monitors temperature and humidity is attached to measure the usage environment used by the user. The monitoring device also acquires log information indicating the frequency of use. The monitoring device then automatically transmits the acquired information to the calibration management system 1 via the network 2 on a regular or irregular basis.

[0053] The above embodiment is merely an example, and the present invention may be modified as appropriate without departing from the spirit of the present invention. Furthermore, the processing described as being performed by one calibration management system 1 may be shared and executed by multiple devices. Alternatively, the processing described as being performed by different devices may be executed by a single device.

[0054] In the computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed. The present invention can also be realized by supplying a computer program that implements the functions described in the above embodiments to a computer, and having one or more processors in the computer read and execute the program.

[0055] In the above embodiment, the AI-based measuring instrument calibration management system 1 has been described as being owned by the management company, but part of it may be configured as a server provided by another provider, as shown in Figure 8. For example, it is desirable for the management company to use a cloud computing service that allows on-demand use of computing resources such as physical servers, virtual servers, data storage, networking functions, application development tools, software, and AI-equipped analysis tools to perform processing by the calibration timing prediction unit 5 or demand prediction unit 6 based on reference to the knowledge database 10.

[0056] Fig. 8 is a block diagram showing a modified example in which part of the AI-based measuring instrument calibration management system 1 is configured as a different server. Although a detailed explanation will be omitted, the embodiment shown in Fig. 1 is configured as an AI prediction server 50 using a cloud computing service, where processing by the calibration time prediction unit 5 based on reference to the knowledge database 10 is performed, and other processing is performed by the management company terminal 40, which is configured as a personal computer.

[0057] Log information of the measuring instruments used by the user is input from the user terminal 3 via the network 2 to the log collection unit 4 of the management company terminal 40. The management company terminal 40 transmits the collected log information to the AI ​​prediction server 50. The AI ​​prediction server 50 predicts the calibration time in the calibration time prediction unit 5 by referring to the knowledge database 10 including the maintenance database 11 and the maintenance learning model 12.

[0058] The results are reflected in the maintenance learning model 12. The predicted calibration time is sent to the demand forecasting unit 6 of the management agent terminal 40. The demand forecasting unit 6 determines the loan timing and loan period of the replacement machine as a schedule, and adjusts the schedule if necessary by referring to the inventory database 20. The management agent terminal 40 then notifies the user of the schedule, and the management agent lends out a replacement machine via the lending unit 7 based on the schedule. The lending unit 7 records the lending based on the schedule as history. [Explanation of symbols]

[0059] 1. Calibration management system 2. Network 3...User terminal 4...Log collection section 5...Calibration time prediction section 6...Demand Forecasting Department 7. Lending Department 10. Knowledge database 11...Maintenance database 12...Conservative Learning Model 20...Inventory database 40...Administrator terminal 50…AI prediction server

Claims

1. A method for managing calibration of a measuring instrument using a computer, which predicts the calibration timing of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user during the calibration work, The computer collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a computer predicting the calibration time by referring to a knowledge database including a maintenance learning model constructed from the maintenance database; a computer determines the schedule for the loaner machine rental time and rental period based on the predicted calibration time; A method for managing the calibration of measuring instruments, characterized in that if the number of measuring instruments that the management company needs to calibrate at the calibration time exceeds a predetermined number as the number of measuring instruments that the management company can calibrate simultaneously, or if the number of loaner machines that should be loaned to the user exceeds the number of loaner machines that the management company has in stock at the calibration time, a computer adjusts the schedule to bring forward the determined calibration time.

2. A method for managing calibration of a measuring instrument using a computer, which predicts the calibration timing of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user during the calibration work, The computer collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a computer predicting the calibration time by referring to a knowledge database including a maintenance learning model constructed from the maintenance database; a computer determines the schedule for the loaner machine rental time and rental period based on the predicted calibration time; A measuring instrument calibration management method characterized in that, if it is found that calibration of the measuring instrument is impossible during the rental period based on the schedule, a computer adjusts the schedule so that the rental period is extended based on the period until the management company supplies a new measuring instrument to the user.

3. A method for managing calibration of a measuring instrument using a computer, which predicts the calibration timing of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user during the calibration work, The computer collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a computer predicting the calibration time by referring to a knowledge database including a maintenance learning model constructed from the maintenance database; a computer determines the schedule for the loaner machine rental time and rental period based on the predicted calibration time; A method for managing the calibration of measuring instruments, characterized in that, when the number of replacement machines to be loaned to the user exceeds the number of replacement machines held by the management company at the time of calibration, a computer notifies the management company of procurement arrangements for new replacement machines prior to the time of calibration, and adjusts the schedule to include the new replacement machines.

4. A method for managing calibration of a measuring instrument using a computer, which predicts the calibration timing of a measuring instrument used by a user and manages a schedule for lending a loaner instrument from a management company to the user during the calibration work, The computer collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a computer predicting the calibration time by referring to a knowledge database including a maintenance learning model constructed from the maintenance database; a computer determines the schedule for the loaner machine rental time and rental period based on the predicted calibration time; A method for managing calibration of a measuring instrument, characterized in that if it is determined that calibration of the measuring instrument is impossible during the rental period based on the schedule, the computer extends the rental period for a predetermined period and notifies the user that a new purchase of the measuring instrument is necessary.

5. 5. The calibration management method for a measuring instrument according to claim 1, wherein the measuring instrument used by the user is a loaned instrument loaned to the user by the management company.

6. 5. The method for managing calibration of a measuring instrument according to claim 1, wherein the measuring instrument used by the user is the measuring instrument owned by the user.

7. A calibration management system for measuring instruments that predicts the calibration time of a measuring instrument used by a user and manages a schedule for lending a loaner instrument to the user from a management company during calibration work, a log collection unit that collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a knowledge database including a maintenance learning model constructed from the maintenance database; a calibration time prediction unit that predicts the calibration time by referring to a knowledge database; a demand prediction unit that determines the schedule of the loaner machine rental time and rental period based on the predicted calibration time, and adjusts the schedule if any inconvenience occurs with the determined schedule; Equipped with A measuring instrument calibration management system in which the demand forecasting unit adjusts the schedule to bring forward the determined calibration period if the number of measuring instruments that the management company needs to calibrate at the calibration period exceeds a predetermined number as the number of measuring instruments that the management company can calibrate simultaneously, or if the number of replacement machines that should be loaned to the user exceeds the number of replacement machines that the management company has in its possession at the calibration period.

8. A calibration management system for measuring instruments that predicts the calibration time of a measuring instrument used by a user and manages a schedule for lending a loaner instrument to the user from a management company during calibration work, a log collection unit that collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a knowledge database including a maintenance learning model constructed from the maintenance database; a calibration time prediction unit that predicts the calibration time by referring to a knowledge database; a demand prediction unit that determines the schedule of the loaner machine rental time and rental period based on the predicted calibration time, and adjusts the schedule if any inconvenience occurs with the determined schedule; Equipped with If it is determined that the measuring instrument cannot be calibrated during the rental period based on the schedule, the demand forecasting unit adjusts the schedule so as to extend the rental period based on the period until the management company supplies a new measuring instrument to the user.

9. A calibration management system for measuring instruments that predicts the calibration time of a measuring instrument used by a user and manages a schedule for lending a loaner instrument to the user from a management company during calibration work, a log collection unit that collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a knowledge database including a maintenance learning model constructed from the maintenance database; a calibration time prediction unit that predicts the calibration time by referring to a knowledge database; a demand prediction unit that determines the schedule of the loaner machine rental time and rental period based on the predicted calibration time, and adjusts the schedule if any inconvenience occurs with the determined schedule; Equipped with A measuring instrument calibration management system in which, if the number of replacement machines to be loaned to the user exceeds the number of replacement machines held by the management company at the time of calibration, the demand forecasting unit notifies the management company of procurement arrangements for new replacement machines prior to the time of calibration, and adjusts the schedule to include the new replacement machines.

10. A calibration management system for measuring instruments that predicts the calibration time of a measuring instrument used by a user and manages a schedule for lending a loaner instrument to the user from a management company during calibration work, a log collection unit that collects log information indicating the type of the measuring instrument and the number of times it has been used within a predetermined period of time and records the information in a maintenance database; a knowledge database including a maintenance learning model constructed from the maintenance database; a calibration time prediction unit that predicts the calibration time by referring to a knowledge database; a demand prediction unit that determines the schedule of the loaner machine rental time and rental period based on the predicted calibration time, and adjusts the schedule if any inconvenience occurs with the determined schedule; Equipped with A measuring instrument calibration management system in which, if it is determined that the measuring instrument cannot be calibrated during the rental period based on the schedule, the demand forecasting unit extends the rental period for a predetermined period and notifies the user that a new measuring instrument needs to be purchased.

11. 11. The calibration management system for measuring instruments according to claim 7, wherein the measuring instrument used by the user is a loaned instrument loaned to the user by the management company.

Images