JP5925229B2 - Equipment inspection order setting device and program - Google Patents

Description

  The present invention relates to an equipment inspection order setting device and program, and more particularly, to determination of the priority order of equipment that performs maintenance inspection based on a failure history collected from equipment such as a cooling and heating facility.

  Conventionally, there is a remote monitoring service for monitoring a plurality of facilities such as a cooling / heating facility from a monitoring center. In this remote monitoring service, equipment status data indicating the operating status of each equipment such as the temperature and pressure of the equipment in operation is collected from each equipment. When an abnormality in the facility is detected by analyzing the collected facility state data, the maintenance staff performs an inspection on the facility in which the abnormality is detected according to the created inspection schedule.

  In recent years, there is a case where an inspection schedule is created so as to prevent the occurrence of an abnormality in advance by making an inspection target a facility where a failure sign is generated even if no abnormality is detected. In order to prevent the occurrence of anomalies more reliably, an inspection schedule is created to prioritize equipment that is predicted to fail early, in other words, equipment that has a high probability of failure. It is preferable to reduce the occurrence of failures.

JP 2006-266609 A International Publication No. 2009/144780 JP 2005-149137 A Japanese Patent No. 3731125

  However, maintenance personnel can only perform equipment inspections when they arrive at the site where the equipment is installed. When setting the priority order for each facility with reference, the time required for the maintenance staff to move from the branch where they are stationed to the site (site arrival time) was not considered.

  In other words, conventionally, it is assumed that the failure occurrence probability of the equipment A installed at a place where the on-site arrival time is relatively large is lower than the failure occurrence probability of the equipment B installed at a place where the on-site arrival time is relatively small. However, depending on the difference in the arrival time at the site, the probability of failure occurring at the timing when the inspection is performed on each of the facilities A and B may be higher in the facility A. That is, it is considered that the inspection of the facility A should be prioritized in consideration of the on-site arrival time.

  It is an object of the present invention to set a priority for performing maintenance and inspection in consideration of the time to reach the site where each facility is installed, for the facility where a failure sign has occurred.

  The equipment inspection order setting device according to the present invention provides information for identifying a site where each of a plurality of facilities is installed, occurrence status of a failure sign in the facility, and failure history information regarding a failure that has occurred in the facility after the sign, Classifying means for grouping by classifying based on characteristic information indicating the characteristics of the characteristics, and a characteristic for calculating a failure probability that changes with the elapsed time from occurrence of a sign to failure for each group formed by the classification means Another failure probability calculation means, a failure probability storage means for storing the failure probability for each group calculated by the characteristic-specific failure probability calculation means, and a site from the maintenance staff base to the site where each of the facilities where the sign is generated is installed Travel time acquisition means for acquiring travel time, failure probability stored in the failure probability storage means, and movement acquired by the travel time acquisition means Based on the failure probability calculated by the on-site arrival failure probability calculating means, the failure probability calculating means for calculating the failure probability at the time of arrival at the installation site where each of the facilities where the sign has occurred is installed And priority setting means for setting a priority for performing maintenance and inspection on each facility where a sign has occurred.

  Further, the present invention has a travel time result information storage means in which result information relating to the travel time to the site is stored, and the travel time acquisition means stores the travel time included in the result information stored in the travel time result information storage means. The travel time to the site is obtained with reference.

  The travel time acquisition means refers to external environment information related to the external environment that may affect the travel time to the site, included in the performance information accumulated in the travel time performance information storage means, The travel time to the site is obtained by referring to the actual performance information of the site including external environment information similar to the external environment of the travel time acquisition target site at the time when the failure probability calculating means at the time of the site arrival calculates the failure probability Is.

  The travel time acquisition means includes a weighting unit that weights the travel time included in the actual performance information of the travel time acquisition target based on the occurrence probability of the external environment, and refers to the weighted travel time to the site The travel time is calculated.

  In addition, it has a work time acquisition means for acquiring a work time required for inspection of equipment by maintenance personnel, the failure probability calculation means upon arrival at the site is the failure probability stored in the failure probability storage means and the travel time acquisition Based on the travel time acquired by the means and the work time for each facility where the sign obtained by the work time obtaining means is calculated, the failure probability at the time when the inspection of each facility where the sign has occurred ends. is there.

  In addition, there is a work time result information storage means in which result information relating to the work time required for inspection of each facility is stored, and the work time acquisition means is a work time acquisition stored in the work time result information storage means The work time required for the inspection of the equipment is obtained by referring to the work time included in the performance information of the target equipment.

  Further, the classification means uses the sign content as characteristic information and classifies the failure history information for each sign content.

  Further, the classification means uses information indicating the installation status of the equipment as characteristic information, and classifies the failure history information for each installation status.

  The classification means uses information indicating the model of the facility as characteristic information, and classifies the failure history information for each model.

  Further, the classification means uses information indicating the operation status of the facility at the time of occurrence of the sign as characteristic information, and classifies the failure history information for each operation status.

  Further, the classification means uses the weather information at the time of occurrence of the sign as characteristic information and classifies the failure history information for each weather information.

  The program according to the present invention allows a computer to store information for identifying a site where each of a plurality of facilities is installed, occurrence status of a failure sign in the facility, and failure history information regarding a failure that has occurred in the facility after the sign, Classifying means for grouping by classifying based on characteristic information indicating characteristics, fault for each characteristic that calculates a failure probability that changes with the elapsed time from occurrence of a sign to failure for each group formed by the classifying means Probability calculation means, travel time acquisition means for acquiring the travel time from the base of the maintenance staff to the site where each of the facilities where the sign has occurred is installed, failure probability for each group calculated by the characteristic-specific failure probability calculation means, and The point of arrival at the site where each facility where a sign has occurred is installed based on the travel time acquired by the travel time acquisition means Priority for setting a priority for performing maintenance inspection on each facility where a sign has occurred based on the failure probability calculated by the failure probability calculating means at the time of arrival at the site. It is for functioning as a degree setting means.

  ADVANTAGE OF THE INVENTION According to this invention, the probability that a failure will generate | occur | produce before a maintenance worker arrives at the field can be reduced with respect to the installation which the sign generate | occur | produced.

  In addition, more accurate travel time can be acquired by using past performance information.

  In addition, by referring to the external environment information, it is possible to acquire a more accurate travel time that matches the external environment up to the site.

  In addition, since the travel time is obtained by weighting the travel time based on the past performance information, the travel time corresponding to the external environment that has not occurred in the past can be obtained.

  Moreover, the probability that a failure will occur before the maintenance staff completes the inspection of the facility where the sign has occurred can be reduced.

  In addition, it is possible to generate failure probabilities that take into account the tendency to failure occurrence that varies depending on site characteristics.

  In addition, it is possible to accurately determine the failure probability after the time required for arrival at the site from the occurrence of a sign while suppressing an increase in cost, and as a result, it is possible to increase the reliability of the priority of each facility set as a result. Become.

It is the block block diagram which showed Embodiment 1 of the equipment inspection order setting apparatus which concerns on this invention. FIG. 3 is a diagram illustrating a data configuration example of failure history information indicating a failure history accumulated in a failure history database in the first embodiment. 2 is a hardware configuration diagram of a computer forming the equipment inspection order setting device according to Embodiment 1. FIG. 3 is a flowchart illustrating priority setting processing in the first embodiment. In Embodiment 1, it is the figure which showed the graph of the failure probability of a certain failure group, and a cumulative failure probability. 6 is a diagram illustrating a data configuration example of failure probability information stored in a failure probability accumulation unit according to Embodiment 1. FIG. 6 is a diagram showing data that is referred to or calculated in the process of setting priority in the first embodiment. FIG. It is the figure which showed the example of the other block structure of the equipment inspection order setting apparatus in Embodiment 1. FIG. It is a block block diagram of the equipment inspection rank setting apparatus in Embodiment 2.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

Embodiment 1 FIG.
FIG. 1 is a block configuration diagram showing an embodiment of an equipment inspection order setting device according to the present invention. FIG. 1 shows a cooling facility 2, an operation history receiver 3, a failure history database (DB) 4, and an equipment inspection order setting device 10. As shown in FIG. 1, the facility inspection order setting device 10 is connected to a plurality of refrigeration facilities 2 installed in a plurality of contracted facilities via an operation history receiving unit 3 and a failure history database 4. In the present embodiment, the cooling facility 2 is illustrated as a facility to be inspected, but other facilities that require inspection may be used.

  The equipment inspection order setting device 10, the operation history receiving unit 3, and the failure history database 4 are installed, for example, in a monitoring center. The operation history receiving unit 3 receives equipment state data indicating the equipment state from the cooling / heating equipment (hereinafter, simply referred to as “facility”) 2, equipment state data when a sign or abnormality occurs, and the received equipment state data The fault history information is generated and accumulated in the fault history database 4 by, for example, summing up as necessary. The operation history receiving unit 3 may be realized by a computer having a communication function, and the failure history database 4 may be realized by a database server. As a method of receiving equipment state data and storing it in the failure history database 4, a method of transmitting online via a telephone line and an Internet line by means of communication software installed in a control device (not shown) of the equipment 2, etc. There is.

  FIG. 2 is a diagram illustrating a data configuration example of failure history information indicating a failure history stored in the failure history database 4 according to the present embodiment. The failure history information is configured by associating a failure time interval, installation environment information, and occurrence state information with a sign occurrence date and time indicating a date and time when a sign of failure occurred. The sign occurrence date and time is the date and time when the occurrence of the sign is detected by the operation history receiving unit 3 referring to the equipment state data transmitted from the equipment 2. The failure time interval is a time interval from the occurrence of the sign until the equipment 2 breaks down, and is a value indicating the difference between the date and time of occurrence of the abnormality and the date and time of occurrence of the sign. In this embodiment, the time is shown, but it may be time. Here, “abnormal” refers to a case where one piece of equipment state data deviates from a normal state indicating a value within a normal range. “Failure” means that the equipment 2 is stopped due to the occurrence of abnormality in the equipment status data. Further, the “sign” means a case where the threshold value indicating that the equipment state data is close to an abnormal state even if the equipment state data is within a normal range.

  The installation environment information is information related to the specifications and installation location of the equipment 2, the equipment number that identifies the equipment 2, the building number that identifies the building in which the equipment 2 is installed, the installation destination that indicates the address where the equipment 2 is installed, It includes various information related to the installation start indicating the year of installation, the model name of the facility 2 and the installation direction indicating the direction in which the facility 2 is installed in the building. In the present embodiment, the combination of the building number and the equipment number is used as information for identifying the site where the equipment 2 is installed.

  Occurrence status information is information related to the occurrence status of signs and abnormalities. Predictive contents indicating the contents of the generated signs, temperature and humidity at the time of occurrence of the sign, temperature and set temperature at the time of occurrence of the sign The temperature difference between the start and stop counts indicating the number of times the thermostat of the equipment 2 has been turned on / off from the start of the count until the occurrence of the predictor, and the facility between the start of the count and the occurrence of the predictor Operating time when the time when 2 is in operation is integrated, Thermo ON time when the time when the thermostat of the facility 2 is ON is accumulated from the start of counting until the occurrence of a sign, per operating time The ratio of the number of starts / stops indicating the number of starts / stops, the ratio of the thermo-ON time indicating the thermo-ON time per operation time, and the room in the facility 2 between the start of the count and the occurrence of the sign Degrees is the target temperature reaching time indicating the average time to reach the set temperature, including various types of information about the abnormal content indicating an abnormality occurrence time and generated abnormality contents indicating the date and time when the equipment 2 is stopped by the occurrence of abnormality. FIG. 2 shows a part of the above described occurrence status information.

  FIG. 3 is a hardware configuration diagram of a computer forming the equipment inspection order setting device 10 in the present embodiment. In this embodiment, the computer forming the equipment inspection order setting device 10 can be realized by a hardware configuration of a general-purpose personal computer (PC) that has existed. That is, as shown in FIG. 3, the computer is provided as a CPU 21, ROM 22, RAM 23, HDD controller 25 to which a hard disk drive (HDD) 24 is connected, a mouse 26 and keyboard 27 provided as input means, and a display device. An input / output controller 29 for connecting each display 28 and a network controller 30 provided as a communication means are connected to an internal bus 31.

  Returning to FIG. 1, the equipment inspection order setting device 10 includes an on-site characteristic classification unit 11, a failure probability calculation unit 12 by characteristic, a travel time acquisition unit 13, an on-site failure probability calculation unit 14, a priority setting unit 15, and a failure probability. The storage unit 16 is included. Note that components not used in the description of the present embodiment are omitted from FIG.

  The site characteristic classification unit 11 is provided as a classification unit, and groups the failure history information stored in the failure history database 4 by classifying (clustering) the failure history information based on the property information indicating the site characteristics. This classified failure history information group will be referred to as a “failure group” in the following description. The characteristic-specific failure probability calculation unit 12 is provided as characteristic-specific failure probability calculation means, and calculates, for each group formed by the on-site characteristic classification unit 11, a failure probability that changes with the elapsed time from occurrence of a sign to failure. To do. The travel time acquisition unit 13 is provided as travel time acquisition means, and acquires the travel time from the base of the maintenance staff to the site where each of the facilities 2 where the sign is generated is installed. The on-site arrival failure probability calculation unit 14 is provided as on-site arrival failure probability calculation means, and a sign is generated based on the failure probability stored in the failure probability storage unit 16 and the travel time acquired by the travel time acquisition unit 13. The failure probability at the time of arrival at the site where each of the installed facilities 2 is installed is calculated. The priority setting unit 15 is provided as a priority setting unit, and sets a priority for performing maintenance inspection on each facility 2 in which a sign has occurred based on the failure probability calculated by the on-site failure probability calculation unit 14. To do. The failure probability accumulation unit 16 is provided as failure probability storage means, and stores the failure probability for each failure group calculated by the characteristic-specific failure probability calculation unit 12. In the present embodiment, the cumulative failure probability is stored as will be described later.

  Each component 11-15 in the equipment inspection order setting device 10 is realized by a cooperative operation of a computer that forms the equipment inspection order setting device 10 and a program that operates on the CPU 21 mounted on the computer. Further, the failure probability accumulation unit 16 is realized by the HDD 24 mounted on the equipment inspection order setting device 10. Alternatively, the RAM 23 or an external storage means may be used via a network.

  Further, the program used in this embodiment can be provided not only by communication means but also by storing it in a computer-readable recording medium such as a CD-ROM or DVD-ROM. The program provided from the communication means or the recording medium is installed in the computer, and various processes are realized by the CPU of the computer sequentially executing the program.

  Next, the operation in this embodiment will be described. In the following description, it is assumed that the site and the facility 2 have a one-to-one relationship, and “equipment” and “site” are used almost synonymously. In other words, the sign 2 is written in the facility 2, but for convenience of explanation, the sign may be described as being generated at the site.

  While the equipment 2 is in operation, equipment status data including information necessary for generating failure history information is transmitted from the equipment 2 in which a sign or abnormality has occurred to the operation history receiving unit 3. When the operation history receiving unit 3 detects the occurrence of the sign by analyzing the received equipment state data, the sign occurrence date and time, the installation environment information, the sign content included in the occurrence state information, temperature, humidity, Failure history information is generated by setting a temperature difference, start / stop count, operation time, thermo-ON time, start / stop count ratio, thermo-ON time ratio, and target temperature arrival time. In addition, when the operation history receiving unit 3 detects the occurrence of an abnormality by analyzing the received equipment state data, the abnormality occurs with reference to the installation environment information from the failure history information generated by the occurrence of the sign. The failure history information corresponding to the facility 2 is identified, and the date and time of occurrence of the abnormality and the details of the abnormality are set and registered based on the received equipment state data. Further, the operation history receiving unit 3 calculates a time interval from the occurrence of the sign to the occurrence of the abnormality, and sets and registers the failure time interval.

  As described above, the failure history information is generated by the operation history receiving unit 3 and is stored in the failure history database 4 with the occurrence of the sign and failure.

  Subsequently, the flowchart shown in FIG. 4 shows the priority determination process for setting the priority order for inspecting each facility 2 in which a failure is predicted with reference to the failure history information stored in the failure history database 4. Will be described.

  The site characteristic classification unit 11 acquires the failure history information stored in the failure history database 4 (step 110), and classifies (clusters) each site characteristic according to a preset classification condition, thereby one or more failure groups. Is formed (step 120). In the present embodiment, the site characteristics specified as classification conditions include, for example, predictive contents, installation status, model, operation status, or weather information, and each of these site characteristics or a plurality of site characteristics is selected. Classify by combination. The details of the on-site characteristics used for the classification of the failure history information will be described later. Here, the description will be made assuming that the on-site characteristics are classified according to some on-site characteristics.

Subsequently, the characteristic-specific failure probability calculation unit 12 calculates the cumulative failure probability for each failure group (step 130). That is, the characteristic-specific failure probability calculation unit 12 refers to the failure time interval included in the failure history information of the failure group to be processed, and calculates the failure probability at every predetermined time interval from the occurrence of the sign to the occurrence of the failure. FIG. 5 is a graph showing a failure probability and a cumulative failure probability of a certain failure group. In FIG. 5, the horizontal axis represents time, and the vertical axis represents probability. In the present embodiment, as shown in FIG. 5, the cumulative failure probability is defined as the probability P (t) of failure within time t after occurrence of a sign. The cumulative failure probability is obtained by the following equation, where p (x) is the ratio (failure probability) of the number of failure history information at a predetermined time interval x to the number of all failure history information included in a failure group.

  For example, based on the failure history information for four cases where the sites illustrated in FIG. 2 are all different, if the predetermined time interval x is one week (7 days), within one week (1 day to The failure probability p (x) when an abnormality occurs on the 7th) is calculated as p (x) = 1/4 because the failure time interval is only one in 2 days. The failure probability p (2x) when an abnormality occurs within one week and two weeks (8 days to 14 days) after the occurrence of a sign is p (2x ) = 2/4. Similarly, p (3x) = 1/4 is calculated.

  When the failure probability calculation unit 12 by characteristic calculates the failure probability as described above, it calculates the cumulative failure probability by accumulating the calculation results with the elapsed time, and the failure probability information including the accumulated failure probability is determined as the failure. Saved in the probability storage unit 16. FIG. 6 shows a data configuration example of failure probability information stored in the failure probability accumulation unit 16 by this processing.

  As shown in FIG. 6, the failure probability information indicates a cumulative failure probability after x hours have elapsed from the occurrence of a sign in correspondence with each site. The site indicates a place where the facility 2 is installed. In the case of the present embodiment, the site is specified by the building number and the facility number included in the failure history information as described above. The cumulative failure probability after x hours from the occurrence of the sign is the cumulative failure probability calculated in step 130. FIG. 6 shows an example in which the failure probability and the cumulative failure probability are obtained at a time interval x of 1 hour.

  For example, when the failure history information is classified by prefecture according to the site characteristics of the installation destination in step 120, the cumulative failure probability is calculated for each failure group called prefecture. Here, if the site A is located in Hyogo Prefecture, the cumulative failure probability for Hyogo Prefecture is associated with the site A. If the site B is located in Osaka, the site B is associated with the cumulative failure probability for Osaka. Incidentally, when the failure history information is classified by region according to the site characteristics of the installation destination, the cumulative failure probability is calculated for each failure group called the region. In this case, the sites A and B are both in the Kansai region. Will be associated with the cumulative failure probability.

  In addition, if it is known that there is a correlation between the field characteristics and the failure time interval, a coefficient is applied to each failure group in the field characteristics according to the correlation tendency from the standard cumulative failure probability. Thus, the cumulative failure probability may be calculated.

  For example, by performing a correlation analysis, there is a correlation between the field characteristic of failure history information that is the operation time and the failure time interval, and when the operation time is longer, the failure time interval tends to be shorter. If the operation time is long, the cumulative failure probability at time x of the reference cumulative failure probability to increase the degree of urgency is multiplied by 1.2 (> 1.0), or the operation time at site B Is short, the cumulative failure probability is calculated by multiplying by 0.8 (<1.0) to reduce the urgency. At this time, the coefficient may be set flexibly according to the length of the operation time as well as the two types of cases where the operation time is long and short. Further, as the cumulative failure probability serving as a reference, the cumulative failure probability for the total failure history number or the cumulative failure probability for the operation time with the highest occurrence frequency from the operation time for the total failure history number may be used.

  The above process is a process that should be performed before setting the priority for determining the order of inspection at each site. In the present embodiment, since the cumulative failure probability is used in the subsequent processing, the failure probability storage unit 16 stores the cumulative failure probability obtained by accumulating the failure probability, but stores the failure probability. The cumulative failure probability may be calculated by integrating the failure probability when the cumulative failure probability is used.

  Here, an inspection schedule for carrying out an inspection on the facility 2 in which a sign has occurred at a certain time on a certain day is created. For example, an inspection schedule is created at 6 o'clock on a certain day. In this case, the order in which the equipment 2 in which the sign is generated is inspected, that is, the priority order is set for each site. The table summarizing the information referred to before setting the priority order and the result calculated in the process. Is shown in FIG. Hereinafter, processing until priority is set as priority will be described with reference to this table.

  The on-site failure probability calculation unit 14 is configured to install the facility 2 in which a sign has been generated up to the present time, strictly speaking, the facility 2 in which the sign 2 has occurred but has not yet failed. The sign occurrence time is acquired (step 140). For this, the failure history database 4 may be searched and extracted, or the site and the sign occurrence time designated by the maintenance staff may be used. According to FIG. 7, the sites A to E are extracted as the sites where the signs are generated, and the respective sites are arranged in the order of the time when the signs are generated. In FIG. 7, the cumulative failure probability after the elapse of x hours from the occurrence of the sign is extracted from the failure probability information at the corresponding site from those accumulated in the failure probability accumulation unit 16 as is clear from comparison with FIG. Information.

  Subsequently, the travel time acquisition unit 13 acquires the travel time from the maintenance staff base to each site (step 150). Maintenance personnel are generally stationed at each base such as a branch, and perform maintenance and inspection of the facility 2 at the site in the area in charge. Accordingly, the location (base) of the maintenance staff serving as the movement source differs depending on the address of the site. A detailed method of obtaining the travel time acquired by the travel time acquisition unit 13 will be described later.

  Subsequently, the on-site arrival failure probability calculation unit 14 calculates the on-site arrival time from the travel time acquired by the travel time acquisition unit 13, the sign occurrence time, and the current time (step 160). The time required for arrival at the site is the time required for the maintenance staff to arrive at the site after a sign is generated at each site. It is not the time required from the present time. According to the numerical example shown in FIG. 7, for example, in the case of Site B, at the current time (6:00), two hours have passed from the time of occurrence of the sign (4:00) to the current time (6:00). Since the travel time to the site B is 1 hour, the time required for arrival at the site is 3 hours (= 2 hours + 1 hour). In the case of Site D, 2 hours have passed from the time of the occurrence of a sign (4:00) to the current time (6:00), and the travel time to Site D is 2 hours. The time required is 4 hours (= 2 hours + 2 hours). In the case of Site A, 1.17 hours have passed from the time of the occurrence of a sign (4:50) to the current time (6:00), and the travel time to Site A is 0.5 hours. The time required for arrival at the site is 1.67 hours (= 1.17 hours + 0.5 hours). The on-site arrival failure probability calculation unit 14 calculates the on-site arrival time for the on-site C and E in the same manner.

  Then, the on-site arrival failure probability calculation unit 14 calculates the failure probability for each site when the maintenance staff arrives on the site based on the calculated required site arrival time (step 170). For example, in the case of the site B, the time required for the site arrival is 3 hours. Further, referring to the cumulative failure probability after elapse of x hours from the occurrence of the sign shown in FIG. 7, the cumulative failure probability at the site B after the elapse of 3 hours from the occurrence of the sign is 0.6. As described above, the time required for arrival at the site is the time required for the maintenance staff to arrive at the site after the occurrence of the sign, so the failure probability when the maintenance staff arrives at the site B can be obtained as 0.6. it can. In the case of the site D, the time required for arrival at the site is 4 hours, and the cumulative failure probability at the site D 4 hours after the occurrence of the sign is 0.8. Accordingly, the failure probability when the maintenance staff arrives at the site D can be obtained as 0.8. For sites C and E, the failure probability is obtained in the same manner as sites B and D.

  In the case of the site A, the time required for the site arrival is 1.67 hours. The cumulative failure probability at 1.67 hours is not calculated even with reference to the cumulative failure probability after elapse of x hours from the occurrence of the sign shown in FIG. Therefore, in such a case, the failure probability at the time when the maintenance staff arrives at the site is obtained as follows.

Of the elapsed time from the occurrence of a sign that sandwiches the time required to arrive at the site, t _{min is the} small elapsed time, t _max is the large elapsed time, p (t _min ) is the cumulative failure probability at t _{min, and} is the cumulative failure probability at t _max . If p (t _max ), the failure probability can be calculated by the following calculation formula.

Failure probability = ((site arrival time−t _min ) / (t _max −t _min )) × (p (t _max ) −p (t _min )) + p (t _min )

In the case of the site A, the time required to arrive at the site is 1.67 hours, and according to the above formula, the failure probability of the site A when the maintenance staff arrives at the site is
((1.67-1) / (2-1)) × (0.7−0.5) + 0.5 = 0.634
Is calculated. In the present embodiment, when the cumulative failure probability corresponding to the time required for arrival at the site (after x hours have elapsed since the occurrence of the sign) has not been obtained, interpolation is performed using the above calculation formula.

  The characteristic-specific failure probability calculation unit 12 calculates a failure probability as shown in FIG. 5 at every predetermined time interval from the occurrence of a sign to the occurrence of a failure, and uses the calculated failure probability to calculate the cumulative failure probability using Equation 1. Asked. If a mathematical expression representing the time change of the cumulative failure probability is obtained, the cumulative failure probability at the time of arrival at the site can be calculated. However, the time change of the cumulative failure probability does not necessarily indicate a simple change as shown in FIG. For this reason, the mathematical expression representing the time change of the cumulative failure probability becomes complicated, and it may be difficult to derive an accurate mathematical expression (regression expression). When it is difficult to show the temporal change of the cumulative failure probability using a mathematical expression, the cumulative failure probability at discrete times may be stored in a table format as shown in FIG. In order to accurately obtain the cumulative failure probability of the time required to arrive at the site with reference to the table, it is necessary to shorten the time interval for calculating the failure probability as much as possible. However, if the time interval is shortened, the amount of data to be stored is increased, the consumption of computing resources is increased, and as a result, the cost of the equipment inspection rank setting device may increase.

Therefore, in the present embodiment, a discrete failure probability is calculated at predetermined time intervals of 1 hour in consideration of an increase in the data amount, and the discrete cumulative failure probability is calculated as the failure probability as illustrated in FIG. Stored in the storage unit 16. However, as described above, the failure probability accumulation unit 16 does not store the cumulative failure probability of the time corresponding to the time required to arrive at the site A of 1.67 hours. Therefore, the failure probability calculation unit 14 at the time of arrival at the site uses the failure probability at the time of arrival at the site A as the failure probability immediately before the time required for arrival at the site (1.67 hours) stored in the failure probability storage unit 16, that is, the occurrence of a sign. Cumulative failure probability (p (t _min ) = 0.5) after elapse of time (t _min = 1) and cumulative failure probability (p _max ) after elapse of time (t _max = 2) It is calculated by interpolation from (t _max ) = 0.7).

  As described above, when the failure probability calculation unit 14 at the time of arrival at the site calculates the failure probability at the time of arrival at each site where the sign is generated, the priority setting unit 15 assigns priority to each site in descending order of failure probability. The rank is set as a priority for each site (step 180). According to the processing result shown in FIG. 7, if the failure probability of the site D is 0.8, which is larger than that of other sites, that is, if the maintenance staff leaves the site at 6 o'clock and arrives at each site, Since the possibility that the equipment 2 installed at the site D will break down is the highest, the maintenance staff will give priority to the site D for inspection.

  The arrival time at each site is not always the same. According to the numerical example shown in FIG. 7, when the maintenance staff leaves the base at 6 o'clock, for example, it arrives at site B at 7 o'clock, site D at 8 o'clock, and site A at 6:30 o'clock. become.

  Even if the failure probability at the current time is lower than at other sites, if the failure probability at the time of arrival and inspection at the site is high as a result of spending time, the time of arrival at that site It is considered that it is preferable to prioritize the inspection at the site where the failure probability is high (at the start of the inspection work). Therefore, in the present embodiment, it is possible to create an inspection schedule with reference to the probability of failure at the time of arrival at the site in consideration of the travel time to each site, not the current time. The possibility that 2 actually breaks down can be reduced.

  Here, the on-site characteristics used for classification of failure history information (formation of failure group) in step 120 will be described.

  As described above, the on-site characteristics used when the on-site characteristic classification unit 11 forms the failure group include, for example, the sign content, the installation status, the model, the operation status, and the weather information. In the present embodiment, basically, data items included in the failure history information illustrated in FIG. 2 are used as characteristic information. Of course, as described below, classification may be performed with reference to data items not shown in FIG. Information that is not shown in FIG. 2 may include failure history information, or may be separately prepared in association with the facility 2.

  The sign content is the sign content included in the occurrence status information. By classifying for each predictor content, the failure probability calculation unit 12 for each characteristic can generate a failure probability in consideration of the tendency until the occurrence of a failure, which changes depending on the predictor content indicating a part or a detection item.

  The installation status is represented by information such as the installation location, the installation direction, and the area, snowfall area, coastal area, distance from the coast, etc. included in the installation environment information. By classifying for each installation situation, the characteristic-specific failure probability calculation unit 12 can generate a failure probability in consideration of a tendency until the occurrence of a failure that changes depending on the installation situation.

  The model is represented by information such as installation start, model name, date of manufacture, and operation start date / time included in the installation environment information. By classifying by model, the failure probability calculation unit 12 by characteristic takes into account the tendency to the occurrence of a failure that changes due to differences in the internal structure, mounted parts, or production date of the equipment 2 depending on the model. Probabilities can be generated.

  The operation status is represented by information such as the number of start / stop times, the operation time, the thermo-ON time, the start / stop frequency ratio, the thermo-ON time ratio, the target temperature arrival time, etc. included in the occurrence status information. By classifying for each driving situation, the failure probability calculating unit 12 for each characteristic can generate a failure probability in consideration of the tendency to the occurrence of a failure that changes depending on the driving situation.

  The weather information is represented by information such as temperature, humidity, temperature difference, and dew point temperature included in the occurrence status information. By classifying for each weather information, the characteristic-specific failure probability calculation unit 12 can generate a failure probability in consideration of the tendency to the occurrence of a failure that changes according to the weather information.

  In the present embodiment, the failure history information is classified into failure groups according to the above-described field characteristics. However, the failure history information may be classified with reference to other types of field characteristics.

  Here, the process for acquiring the travel time in step 150 of the priority setting process described above will be described in detail.

  FIG. 8 is a diagram showing an example of another block configuration of the equipment inspection order setting device according to the present embodiment. FIG. 8 shows a configuration in which a travel record database (DB) 17 in which track record information relating to the time required to move from each base to the site is added to the configuration shown in FIG. It is shown. The movement record database 17 is realized by the HDD 24 mounted on the equipment inspection order setting device 10a. Alternatively, the RAM 23 or an external storage means may be used via a network.

  “Movement time” is the time required to move from a base where maintenance personnel are stationed to the site. As the travel time, maintenance personnel may manually input the travel time, and the travel time acquisition unit 13 may receive and acquire the input value, but the equipment inspection order setting device 10a is as shown in FIG. A travel record database 17 may be provided to store travel time record information. Track record information includes the start date and time of arrival, the date and time of arrival, the maintenance personnel who have moved, the means of transportation (transportation, walking, etc.), and road information (travel routes, whether highways are used, the number of traffic lights on the travel route, etc.) Various information such as weather information (weather, temperature, humidity, etc.) is included. Of course, these pieces of information are examples, and other information may be included.

  In step 150 shown in FIG. 4, the travel time acquisition unit 13 refers to the performance information accumulated in the travel performance database 17 and acquires the travel time to the site. For example, it is also possible to acquire actual information on the same site where the travel time is desired and acquire the representative time as the travel time. As the representative time, for example, an average value of travel times included in the corresponding performance information may be calculated, or a travel time having the highest appearance frequency may be used. In this way, it is possible to acquire a more accurate travel time by referring to the record information related to the travel time.

  Or refer to the external environment information related to the external environment that may affect the travel time to the site included in the result information, narrow down the travel time based on the external environment information, and obtain the representative time of travel time You may make it do. As the external environment information, for example, a day of the week, a movement start time, weather information, road information, and the like are used, and the movement time acquisition unit 13 is the same day, time zone, or weather (rain, snow, etc.) as the maintenance worker moves. The travel time may be acquired with reference to the result information. In this way, by referring to the external environment information, it is possible to acquire a more accurate travel time according to the external environment up to the site.

  Furthermore, the travel time acquisition unit 13 includes a weighting unit (not shown) that weights the travel time included in the actual performance information of the travel time acquisition target based on the occurrence probability of the external environment, and refers to the weighted travel time Then, the travel time to the site may be obtained. For example, as a result of counting and analysis with reference to the result information, it takes 20 minutes in clear weather and 60 minutes in rainy weather to travel to the site where travel time is to be acquired, and the probability of clear weather is 80%. Assume that the probability is 20%. In this case, the travel time acquisition unit 13 weights the travel time based on the past weather probability, as the travel time to the travel time acquisition target site is 20 minutes × 0.8 + 60 minutes × 0.2 = 28 minutes. And get travel time. Further, for example, in addition to the above conditions, it is assumed that the use of a highway is 60% for 30 minutes and the use of a general road is 40% for 90 minutes in the travel route. In this case, the travel time acquisition unit 13 determines that the travel time to the travel time acquisition target site is ((20 minutes × 0.8 + 60 minutes × 0.2) + (30 minutes × 0.6 + 90 minutes × 0.4). ) / 2 = 41 minutes, the travel time is obtained by weighting the travel time based on the probability based on the past weather and the use situation of the expressway. Thus, by weighting the travel time based on the record information, it is possible to deal with an external environment that has not occurred in the past.

Embodiment 2. FIG.
FIG. 9 is a block configuration diagram of the equipment inspection order setting device according to the present embodiment. FIG. 9 shows a configuration in which a work time acquisition unit 18 and a work time database (DB) 19 are added to the configuration shown in FIG. The work time acquisition unit 18 is provided as a work time acquisition unit, and acquires the work time required for the inspection of the equipment 2 by the maintenance staff. The work time database (DB) 19 is provided as work time result information storage means, and the result information on the work time required for the inspection of each facility 2 is accumulated. The performance information related to the work time includes information such as the work start date and time, the work end date and time, information for identifying the maintenance worker who performed the work, and the work content. The work time acquisition unit 18 is realized by a cooperative operation of a computer that forms the equipment inspection order setting device 10b and a program that operates on the CPU 21 mounted on the computer. The work time database 19 is realized by the HDD 24 mounted on the equipment inspection order setting device 10b. Alternatively, the RAM 23 or an external storage means may be used via a network.

  By the way, depending on the type of the facility 2, there is also the facility 2 that can be inspected while operating without stopping. In the case of such equipment 2, there is a possibility that a failure may occur in the equipment 2 even during the inspection because maintenance personnel may arrive at the site and start the inspection. come.

  Therefore, in the first embodiment, the failure probability at the time of arrival at the site is obtained, but in this embodiment, the failure probability at the end of the inspection is obtained and the priority is set. It is a feature. Thereby, it is possible to reduce the probability that the facility 2 will fail before the maintenance staff completes the inspection.

  As the work time, the maintenance person may manually input the work time, and the work time acquisition unit 18 may receive the input value and acquire the work time. The equipment inspection order setting device 10b is shown in FIG. As described above, the work time database 19 may be provided to accumulate the work time result information.

  The hardware configuration of the equipment inspection order setting device 10b in the present embodiment and the contents of the priority setting process may be basically the same as those in the first embodiment. However, since the work time acquisition unit 18 and the work time database 19 are provided, the process for calculating the failure probability in step 170 in FIG. 4 in the priority setting process is slightly different. Therefore, in the present embodiment, a failure probability calculation process different from that in Embodiment 1 will be described, and other description will be omitted.

  In step 170, the failure probability calculation unit 14 at the time of arrival at the site calculates the failure probability at the time when the maintenance staff completes the inspection by considering the work time in addition to the time required for arrival at the site. The failure probability at the time when the maintenance personnel complete the inspection is the result of calculating the failure probability at the time when the maintenance personnel arrive at the site based on the time required for arrival at the site in the same manner as in the first embodiment. What is necessary is just to calculate for every field by adding the working time in each field.

  “Working time” is the time required for inspection work after the maintenance staff arrives at the site, so acquire the actual information of the same site where you want to get the working time, and get the representative time as the working time. May be. As the representative time, for example, an average value of work times included in the corresponding performance information may be calculated, or a work time having the highest appearance frequency may be used. Thus, by referring to the record information, it is possible to acquire a more accurate work time.

  In addition, if the maintenance personnel to be inspected have already been determined, the performance information to be referred to in accordance with various conditions is obtained when acquiring the work time, such as referring to the performance information only for the maintenance personnel's performance information. You may make it narrow down.

  It should be noted that the present invention may be carried out by freely combining the embodiments within the scope of the invention, or may be carried out with appropriate modifications and omissions.

  2 cooling facility, 3 operation history receiving unit, 4 failure history database (DB), 10, 10a, 10b equipment inspection rank setting device, 11 site characteristic classification unit, 12 characteristic failure probability calculation unit, 13 travel time acquisition unit, 14 Site arrival failure probability calculation unit, 15 priority setting unit, 16 failure probability storage unit, 17 movement record database (DB), 18 work time acquisition unit, 19 work time database (DB), 21 CPU, 22 ROM, 23 RAM , 24 hard disk drive (HDD), 25 HDD controller, 26 mouse, 27 keyboard, 28 display, 29 I / O controller, 30 network controller, 31 internal bus.

Claims (13)

Classify information identifying the site where each of the multiple facilities is installed, the occurrence status of a failure sign in the facility, and failure history information related to the failure that occurred in the facility after the sign based on the characteristic information indicating the characteristics of the site Classification means to group by,
For each group formed by the classification means, characteristic-specific failure probability calculation means for calculating a failure probability that changes with the elapsed time from occurrence of a sign to failure,
Failure probability storage means for storing failure probability for each group calculated by the characteristic-specific failure probability calculation means;
Travel time acquisition means for acquiring the travel time from the maintenance staff base to the site where each of the equipment where the sign has occurred is installed,
At the time of arrival at the site, the failure probability is calculated at the time of arrival at the site where each of the facilities where the sign has occurred is installed based on the failure probability stored in the failure probability storage unit and the travel time acquired by the travel time acquisition unit Failure probability calculating means;
Priority setting means for setting a priority for performing maintenance and inspection on each facility where a sign has occurred based on the failure probability calculated by the failure probability calculating means upon arrival at the site;
A facility inspection order setting device characterized by comprising: There is a travel time record information storage means in which record information related to the travel time to the site is stored,
2. The facility inspection according to claim 1, wherein the travel time acquisition unit obtains a travel time to the site with reference to a travel time included in the record information accumulated in the travel time record information storage unit. Rank setting device.   The travel time acquisition means refers to the external environment information related to the external environment that may affect the travel time to the scene, which is included in the record information accumulated in the travel time record information storage means. Determining the travel time to the site by referring to the actual results information of the site including external environment information similar to the external environment of the target site for the travel time acquisition at the time when the failure probability calculation means at the time of arrival calculates the failure probability The equipment inspection order setting device according to claim 2, wherein   The travel time acquisition means includes a weighting unit that weights the travel time included in the actual performance information of the travel time acquisition target based on the occurrence probability of the external environment, and refers to the weighted travel time to travel to the site The equipment inspection rank setting device according to claim 3, wherein time is obtained. It has work time acquisition means to acquire the work time required for inspection of equipment by maintenance personnel,
The on-site arrival failure probability calculation means is configured to generate a failure probability stored in the failure probability storage means, a travel time acquired by the travel time acquisition means, and a sign obtained by the work time acquisition means. The equipment inspection rank setting apparatus according to claim 1, wherein a failure probability at the time when inspection of each equipment where a sign has occurred is calculated based on a work time for the equipment. There is a work time result information storage means in which the result information on the work time required for inspection of each facility is accumulated,
The work time acquisition means obtains the work time required for the inspection of the equipment with reference to the work time included in the performance information of the equipment for which the work time is acquired, stored in the work time result information storage means. The equipment inspection order setting device according to claim 5.   2. The equipment inspection rank setting apparatus according to claim 1, wherein the classification means classifies the sign content as characteristic information and classifies the failure history information for each sign content.   2. The equipment inspection order setting device according to claim 1, wherein the classification means uses information indicating the installation status of equipment as characteristic information and classifies the failure history information for each installation status.   2. The equipment inspection order setting device according to claim 1, wherein the classification means uses information indicating the equipment model as characteristic information and classifies the failure history information for each model.   2. The equipment inspection order setting device according to claim 1, wherein the classification means classifies information indicating the operation state of the facility at the time of occurrence of the sign as characteristic information and classifies the failure history information for each operation state.   The equipment inspection rank setting device according to claim 1, wherein the classification means classifies the weather information at the time of occurrence of the sign as characteristic information and classifies the failure history information for each weather information. In the case where discrete failure probabilities are stored in the failure probability storage means,
The failure probability calculation means at the time of arrival at the site stores a failure probability at a time corresponding to the time required for arrival at the site from when a sign is generated at the site until the maintenance staff arrives at the site. 2. The failure probability at the time of arrival at the site when not present is calculated by interpolating from the failure probability immediately before and after the time required for arrival at the site stored in the failure probability storage means. Equipment inspection rank setting device. Computer
Classify information identifying the site where each of the multiple facilities is installed, the occurrence status of a failure sign in the facility, and failure history information related to the failure that occurred in the facility after the sign based on the characteristic information indicating the characteristics of the site Classification means to group by,
For each group formed by the classification means, a failure probability calculation means for each characteristic that calculates a failure probability that changes with an elapsed time from occurrence of a sign to failure,
Travel time acquisition means for acquiring the travel time from the maintenance staff base to the site where each of the equipment where the sign has occurred is installed,
Based on the failure probability for each group calculated by the failure probability calculation means by characteristic and the travel time acquired by the travel time acquisition means, the failure probability at the time of arrival at the site where each of the facilities where the sign has occurred is installed. On-site failure probability calculation means for calculating,
Priority setting means for setting a priority for performing maintenance and inspection on each facility where a sign has occurred based on the failure probability calculated by the failure probability calculating means upon arrival at the site,
Program to function as.

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