JP4940180B2 - Combined diagnosis / maintenance plan support system and support method thereof - Google Patents

Description

  The present invention relates to a combined diagnosis / maintenance plan support system and a support method thereof for making a diagnosis and maintenance plan for factory production facilities, social infrastructure facilities, building incidental facilities, transportation facilities, medical facilities, and the like.

  In recent years, when managing various facilities such as factory production facilities, social infrastructure facilities, building ancillary facilities (for example, elevators, air conditioning facilities, etc.), transportation facilities, medical facilities, etc., the safety and operating rate of the facilities are improved. There is a growing need for diagnosis and maintenance to maintain equipment efficiency.

Conventionally, several maintenance management support systems have been developed or proposed.
As one of the maintenance management support systems, there are change events and damage events related to the initial event that caused the failure for each component of the facility from the field maintenance record of the facility, from the initial event to the inoperability. Is created in a hierarchical manner, and for each event tree, the probability of failure (unreliability) is determined from the operation time or the number of start and stop times, and the failure risk is evaluated from this unreliability and recovery cost In addition, there is a method for determining a planned maintenance time (Non-patent Document 1, Patent Document 1).

  By the way, in order to collect field maintenance records of facilities, it is necessary to diagnose target facilities and components. For this diagnosis, a sensor for detecting and measuring the behavior, tendency and characteristics of the target equipment and components is indispensable.

  Examples of such sensors include sensors that measure various physical variables such as temperature, humidity, vibration, voltage, current, power, illuminance, contact on / off detection, time, and images (still images / moving images). These sensors are indispensable for their accuracy, accuracy, and reliability in order to obtain accurate diagnosis results of equipment. This is because the risk of erroneous diagnosis, failure or oversight of signs is increased due to sensor malfunction, failure, performance degradation, and accuracy degradation.

  Therefore, when realizing a highly reliable diagnosis / maintenance management support system, diagnosis / maintenance management of the sensor itself that becomes the basis of diagnosis becomes important.

Thus, conventionally, diagnostic techniques including sensor diagnosis have been proposed.
One diagnostic technique relates to an automatic door control system. This diagnostic technology is composed of a number of automatic door devices and a management center connected via a communication medium. Each automatic door transmits door operation information to the management center based on self-identification information. This is an automatic door device management system that accumulates operation information for each identification information of each automatic door device and provides the operation information in response to a request from an elevator sales company or a maintenance company (Patent Document 2).

This management system is equipped with an optical sensor that detects passers-by passing through the inside and outside of the door, an encoder that detects the rotational speed of the motor, and a monitoring unit that monitors the current flowing through the motor. The technology relates to the transmission control system of a traffic system. This diagnostic technique transmits diagnostic information of a sensor system related to a transmission mounted on each vehicle and accumulates it in an external database. Based on the diagnostic information accumulated in the database, the operation state of the sensor system of each vehicle is analyzed, and the analysis result is distributed to a vehicle user or a department having access to the database (Patent Document 3).

  The techniques of the above two patent documents both describe a diagnosis method for a feedback control system including a sensor, and the sensor is treated as a part of the facility diagnosis.

  Furthermore, a diagnostic method for an illumination system that simultaneously diagnoses illumination and diagnoses an illuminance sensor (illuminance meter) has been proposed (Patent Document 4).

This diagnosis method is a method of diagnosing an illuminance sensor by simultaneously turning on / off a plurality of illuminations and then diagnosing each illumination using only the illuminance sensor diagnosed as normal. This illuminance sensor is used for diagnosing illumination.
Toshiba Review 2003 Vol. 58, no. 1 pp. 49-51 JP 2003-303014 A Japanese Patent Laid-Open No. 2002-374583 JP 2003-345421 A JP 2006-210114 A

  Therefore, in the techniques of Patent Documents 2 to 4 described above, a plurality of sensors are used and some of the sensors are diagnosed, but this excludes inconvenient sensors for diagnosing the main target equipment. Because. Further, the sensor deteriorates in performance deterioration, accuracy deterioration, lifespan, and the like with the passage of time, but no diagnosis of such lifespan is performed. In addition, the techniques of Patent Documents 2 to 4 are not support techniques for diagnosis / maintenance plans that take into account future replacement times of sensors.

  The present invention has been made in view of the above circumstances, considering the failure risk of both the target equipment and the sensor for diagnosis, and making a diagnosis / maintenance plan efficiently and visually recognizable from a comprehensive viewpoint. An object is to provide a combined diagnosis / maintenance plan support system and a support method thereof.

(1) In order to solve the above-described problem, the present invention provides a target facility, a sensor that is arranged in the target facility and that measures data serving as a basis for diagnosis of the target facility, and the target that is input by maintenance inspection A database for accumulating maintenance history data of the equipment and the sensor and the measurement data of the sensor, and a diagnosis / maintenance plan support apparatus connected to the sensor via a network and supporting a diagnosis / maintenance plan of the target equipment and the sensor And
The diagnosis / maintenance plan support apparatus includes a life model estimation unit that estimates a life model using, as a variable parameter, data related to the life of the target equipment and the sensor among maintenance history data and sensor data stored in the database, A risk diagnosis unit for calculating a failure risk and a predicted failure risk value of each of the target equipment and the sensor based on the life model estimated by the life model estimation unit and the variable parameter data; and the risk diagnosis unit And a composite risk calculation unit for calculating a plurality of composite risks associated with the abnormality and failure of any of the target equipment and the sensor and a composite risk prediction value based on the failure risk and the failure risk prediction value calculated in This is a combined diagnosis and maintenance plan support system.

  In addition, the failure risk of the target equipment calculated by the risk diagnosis unit, the failure risk of the sensor, the first, second and whole calculated by the composite risk calculation unit are newly added to the configuration of (1). If any of the risks exceeds the corresponding threshold, maintenance of the target equipment or sensor with the risk exceeding the threshold will be performed. A configuration in which an alert determination unit that outputs a maintenance request that is necessary may be added.

  Alternatively, in the diagnosis / maintenance plan support apparatus configured as described in (1) above, the failure risk prediction value of the target facility calculated by the risk diagnosis unit, the failure risk prediction value of the sensor, and the combined risk calculation unit The calculated first, second, and overall composite risk prediction values are compared with preset threshold values, and when each risk prediction value exceeds the corresponding threshold value, the target equipment, A configuration may be adopted in which a maintenance plan planning processing unit for determining and displaying a future maintenance plan of the sensor or a maintenance plan in which individual maintenance is integrated is displayed.

(2) According to the present invention, a sensor is arranged in the target facility, and the target facility and the maintenance history data of the sensor that are input in maintenance inspection by the maintenance staff are detected by the sensor. Is stored in a database to support a diagnosis / maintenance plan for the target equipment and the sensor,
From the database, the data on the life of the target equipment and the sensor is extracted, and a life stage model using these data as variable parameters is estimated.Based on the estimated life model, current and past variable parameter data, A risk diagnosis stage for calculating a failure risk and a future failure risk prediction value of each of the target facility and the sensor, and based on the failure risk and the failure risk prediction value, any abnormality or failure of the target facility or the sensor is detected. This is a combined diagnosis / maintenance plan support method having a combined risk calculation stage for calculating a combined risk.

  Further, in the combined diagnosis / maintenance plan support method in (2), the target equipment failure risk predicted value calculated in the risk diagnosis step, the sensor failure risk predicted value, and the combined risk calculation step are calculated. Comparing the first, second, and overall composite risk prediction values and a preset threshold value, predicting a time exceeding the corresponding threshold value from each risk prediction value, It may be a combined diagnosis / maintenance plan support method having a maintenance plan planning process stage for determining and displaying a future maintenance plan of the sensor or a maintenance plan in which individual maintenance is integrated.

  According to the present invention, the combined diagnosis / maintenance plan support that can plan the diagnosis / maintenance plan efficiently and visually recognizable from a comprehensive viewpoint in consideration of the failure risk of both the target equipment and the sensor for diagnosis. A system and its support method can be provided.

  First, prior to describing an embodiment of a combined diagnosis / maintenance plan support system according to the present invention, a basic configuration of a general maintenance plan support system will be described with reference to FIG.

  In this maintenance plan support system, at least a sensor 2 is connected to a target facility to be diagnosed and a component (hereinafter referred to as a target facility) 1 constituting the facility, and sensor data detected and measured by the sensor 2 is LAN, The data is transmitted to the diagnosis / maintenance plan support apparatus 4 via an intra-company communication network such as a WAN or the Internet (hereinafter collectively referred to as a communication network) 3.

  This diagnosis / maintenance plan support device 4 is installed in a maintenance management center or the like, receives sensor data necessary for diagnosis of the target equipment 1 sent from the sensor 2, divides the area for each target equipment 1, and maintains the maintenance history. Accumulate in database 5.

  Reference numeral 6 denotes a maintenance data input device such as a personal computer. The maintenance staff 7 inputs maintenance history data obtained through visual inspection and other inspections determined by the rules from the maintenance data input device 6 and stores them in a built-in memory (not shown), as well as the communication network 3 and diagnosis / maintenance. It is stored in the maintenance history database 6 via the plan support device 4.

  Reference numeral 8 denotes an input unit such as a keyboard and a mouse for inputting various control instructions and necessary data, and 9 denotes a maintenance plan / alert display unit.

  The diagnosis / maintenance plan support apparatus 4 performs diagnosis on the target facility 1 based on the data that is the basis for diagnosis of the target facility 1 stored in the maintenance history database 5 and maintenance history data, and alerts as necessary. Output from the maintenance plan / alert display unit 9. In addition, the diagnosis / maintenance plan support apparatus 4 creates a maintenance plan for the target facility 1 and displays it on the maintenance plan / alert display unit 9.

  Such a general maintenance plan support system has functions for diagnosis of the target facility 1 and maintenance plan planning, but does not have functions for diagnosis of the sensor 2 and maintenance plan planning.

  On the other hand, although the diagnostic techniques of Patent Documents 2 and 3 having the above-described sensor diagnostic function include the sensor 2 in the target facility 1 from the viewpoint that it is indispensable for realizing the original function of the target facility 1. The point of diagnosing the risk of the sensor 2 itself is not mentioned.

  Patent Document 4 simultaneously turns on and off a plurality of target facilities 1 (lighting), captures the output of each sensor when the target facility 1 is lit, determines that the sensor is faulty when there is no sensor output, and selects only normal sensors. This is used for diagnosis of the target facility 1 (lighting). Therefore, it is not the diagnosis of the sensor that is always incorporated in the facility, but the operation of selecting a sensor that can be used for the diagnosis of the target facility 1 from a plurality of sensors. In addition, there is no mention of a sensor maintenance plan.

(First embodiment)
FIG. 2 is a block diagram showing a first embodiment of the combined diagnosis / maintenance plan support system according to the present invention. In the figure, components identical or equivalent to those in FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted.

  Compared with FIG. 1, this combined diagnosis / maintenance plan support system has a database 10 serving as a storage means for storing data for developing a diagnosis / maintenance plan, and a diagnosis / maintenance plan support installed in a maintenance management center or the like. Unlike the apparatus 4, the other configurations are the same as those shown in FIG. 1 or the conventional general diagnosis / maintenance plan support system.

  Specifically, in the combined diagnosis / maintenance plan support system, a sensor 2 for diagnosis is attached to a target facility 1 such as various facilities and components. In addition, when the target equipment 1 is, for example, plant equipment or the like, there are many examples in which pressure adjusting parts and flow rate adjusting parts (target equipment) for controlling different process amounts are installed. A plurality of sets of facilities 1 and sensors 2 may be installed.

  The sensor 2 detects and measures data that is the basis for diagnosis of the target equipment 1 at all times or at predetermined intervals, and transmits the data as sensor data to the diagnosis / maintenance plan support apparatus 4 via the communication network 3.

  As sensor data, for example, if the target equipment 1 is a motor, it becomes speed data such as the rotational speed of the motor, but other environmental data such as outside air temperature that affects the rotational speed of the motor, for example, It also includes data on usage conditions (load conditions to be diagnosed, intermittent / continuous operation conditions, etc.). Therefore, a plurality of sensors 2,... That individually measure a plurality of different measurement data from one target facility 1 may be arranged.

  For example, a personal computer is used as the maintenance data input device 6 and is always connected to the communication network 3 on the site side, or carried by a maintenance person 7 and connected to the communication network 3 on the site side or communicated as necessary. It may be used without being connected to the network 3.

  The maintenance staff 7 inspects the target equipment 1 and the sensor 2 at the site in accordance with the visual inspection and other inspection items determined by the rules, and the maintenance history data obtained by this inspection is input from the maintenance data input device 6 (not shown). And stored in the database 10 via the communication network 3 and the diagnosis / maintenance plan support apparatus 4. In addition, the maintenance staff 7 may save the maintenance history data in the built-in memory, and then bring the maintenance data input device 6 to the maintenance management center and save it in the database 10 through the diagnosis / maintenance plan support device 4.

  The database 10 includes a facility maintenance history database 10A for storing and accumulating sensor data as a basis for diagnosis of the target facility 1 and maintenance history data for the target facility 1, and a sensor maintenance history database for storing and accumulating maintenance history data regarding the sensor 2. 10B and a maintenance cost database 10C.

  Here, the maintenance history data is not only maintenance inspection information input from the maintenance data input device 6, but also sensor data (for example, state quantity data, usage condition data, external environment) obtained from the sensor 2 required for diagnosis, for example. In addition to (condition data), for example, the operation time of the target equipment 1 and the sensor 2, the number of times of starting and stopping the target equipment 1, etc. are acquired from the sensor data of the sensor 2 and the result of integration is included. The maintenance cost is, for example, a cost related to maintenance work of the target facility 1 and the sensor 2, a cost of damage due to a failure of the target facility 1 and the sensor 2, and the like.

  The diagnosis / maintenance plan support apparatus 4 includes a life model estimation unit 11, a risk diagnosis unit 12, a composite risk calculation unit 13, an alarm determination unit 14, and a maintenance plan planning processing unit 15.

  The life model estimation unit 11 includes, for example, the accumulated operation time, the number of activation / deactivation, and the failure sample among the accumulated operation time, the number of activation / deactivation, the use condition, the external environment condition, the number of failure samples, etc. Using a parameter such as a number as a variable, a life model including coefficients is estimated using a multiple regression analysis (statistical analysis) method, and is stored in the databases 11A and 11B or sent to the risk diagnosis unit 12.

  Based on the life model including the coefficient estimated by the life model estimation unit 11, the risk diagnosis unit 12 predicts the failure risk value and the failure risk prediction value of the present and future target equipment 1 and the sensor 2, that is, the future life. To do.

  The composite risk calculation unit 13 calculates a composite risk value and a composite risk prediction value that cause an abnormality or failure of the target facility 1 or the sensor 2 based on the failure risk value and the failure risk prediction value.

  The alarm determination unit 15 compares each failure risk value and each composite risk value calculated by the risk diagnosis unit 12 and the composite risk calculation unit 13 with each preset threshold value, and determines any failure risk value or When the composite risk value exceeds the threshold value, an alarm is transmitted to the alert display unit 16. The alert display unit 16 sounds based on the transmitted alert, or displays a message indicating which failure risk value or composite risk value has been exceeded.

  The maintenance plan planning processing unit 15 includes the failure risk value of the target facility 1 and the sensor 2 calculated by the risk diagnosis unit 12, the failure risk prediction value, the risk prediction value calculated by the composite risk calculation unit 13, and the maintenance cost database 10C. A maintenance plan for one or both of the target facility 1 and the sensor 2 is drawn up using the cost information. The maintenance plan drafted by the maintenance plan drafting processing unit 15 is transmitted to the maintenance plan display unit 17 and displayed.

  The alert display unit 16 is a personal computer, a mobile terminal, a portable terminal, or the like. As the maintenance plan display unit 17, a computer system, a mobile terminal, a mobile phone or the like having a display function is used. Further, the alert display unit 16 and the maintenance plan display unit 17 may use the same terminal or the like. Reference numeral 18 denotes an input unit such as a keyboard and a mouse for inputting various control instructions and necessary data.

  Next, the operation of the combined diagnosis / maintenance plan support system will be described.

  The at least one type of sensor 2 attached to the target facility 1 has desired data that is a basis for diagnosis of the target facility 1 at all times or at predetermined intervals, for example, state quantity data of the operating state of the target facility 1, external environment Sensor data such as condition data and use condition data is detected and measured, and sensor data such as state quantity data of the sensor 2 when the target facility 1 is stopped is detected and measured, and the diagnosis / maintenance plan support device 4 is used. Are stored in time series in the equipment maintenance history database 10A and the sensor maintenance history database 10B. Similarly, the maintenance history data of the target equipment 1 and the sensor 2 acquired by the maintenance staff 7 at the time of the maintenance inspection is similarly installed in the equipment maintenance history database 10A and the sensor maintenance history database via the maintenance data input device 6 and the diagnosis / maintenance plan support device 4. Save sequentially to 10B.

  As sensor data, for example, if the target equipment 1 is a motor, it becomes state quantity data such as the rotational speed of the motor, but other external environmental condition data such as outside air temperature that affects the rotational speed of the motor, for example. In addition, data on usage conditions (load conditions to be diagnosed, intermittent / continuous operation conditions, etc.) data and the like are also included.

  Here, the life model estimation unit 11 of the diagnosis / maintenance plan support apparatus 4 performs the operation time, the number of times of starting and stopping, the number of failure samples, etc. of the past target equipment 1 and sensor 2 from the equipment maintenance history database 10A and the sensor maintenance history database 10B. Necessary data is extracted, and parameters such as these data are used as variables. For example, model coefficients A, B, C (target equipment) and coefficients As, Bs, Cs (sensors) described later are obtained by a multiple regression analysis (statistical analysis) technique. The life models of the equations (1) and (2) are estimated, stored in the corresponding databases 11A and 11B, and sent to the risk diagnosis unit 12 as necessary.

  The risk diagnosis unit 12 includes, for example, the accumulated operation time and the number of start / stops of the current target equipment 1 and the sensor 2 as parameters of the life model from the databases 11A and 11B, and the life model including the model coefficient estimated by the life model estimation unit 11. Using the equations, the failure risk of the target equipment 1 and the failure risk of the sensor 2 are calculated.

  For example, assuming that the failure risk of a certain target facility 1 can be detected by the vibration frequency of the target facility 1, vibration data obtained from the acceleration sensor 2 is analyzed, and the fundamental frequency of the vibration data deviates from the standard value. The failure risk value of the target facility 1 can be calculated. Further, the failure risk value of the acceleration sensor 2 itself is calculated from the degree to which the vibration data detected by the acceleration sensor 2 deviates from the standard value due to the external environment when the target facility 1 is stopped (for example, noise entering from around the target facility 1). it can. Therefore, it is desirable for the sensor 2 to detect the physical variable that is most susceptible to the degree of failure of the target facility 1 and the sensor 2 as data based on the diagnosis.

  The risk diagnosis unit 12 receives from the life model estimation unit 11 or is obtained by the life model estimation unit 11 and stored in the databases 11A and 11B, and the coefficients A, B, and C of the past target equipment 1 and past sensors. The failure risk of each of the future target equipment 1 and the sensor 2 is predicted from the coefficients As, Bs, and Cs of the life model of 2.

For example, the failure risk of a certain target facility 1 is that the total operation time integrated value of the target facility 1 is calculated from the facility maintenance history database 10A, where Top is the total operation time integrated value of the target facility and Tst is the number of times the target facility is started and stopped Read the value Top and the number of repetitions Tst of starting and stopping the target equipment.
Pobject = A × Top + B × Tst + C (1)
The failure risk Pobject of the current target equipment is calculated based on the operational model of the life model.

Similarly, for the failure risk of the sensor 2, the total operation time integrated value Tops of the sensor 2 accumulated in the sensor maintenance history database 10B and the number of repetitions Tsts of start and stop of the target equipment 1 are read.
Psensor = As × Tops + Bs × Tsts + Cs (2)
The failure risk Psensor of the current sensor 2 is calculated based on the operational model of the life model.

  Furthermore, the risk diagnosis unit 12 calculates a failure risk prediction value of the future target equipment 1 and the sensor 2. That is, the risk diagnosis unit 12 estimates the operating status of the target equipment 1 from the total operation time accumulated value Top of the past target equipment accumulated in the equipment maintenance history database 10A, the number Tst of repetitions of start and stop of the past target equipment, and the like. For example, the estimated parameters Top and Tst after one year are predicted, and the failure risk prediction value Pobject (1) after one year of the target facility 1 is calculated according to the equation (1).

  The risk diagnosis unit 12 estimates the operation status of the sensor 2 from the past total accumulated operation time value Tops of the sensor 2 accumulated in the sensor maintenance history database 10B, the start / stop count Tsts of the target facility 1, and the like. Estimated parameters Tops and Tsts after the year are predicted, and a failure risk prediction value Psensor (1) after one year of the sensor 2 is calculated according to the equation (2).

  The risk value Pobject, risk predicted value Pobject (1) of the target facility 1 calculated by the risk diagnosis unit 12, the risk value Psensor of the sensor 2, and the risk predicted value Psensor (1) are the combined risk calculation unit 13 and the maintenance plan planning processing unit. 15 is sent.

The composite risk calculation unit 13 calculates risk values Pα, Pβ, and Ptotal of (a) to (c) described below using the risk values and risk prediction values described above.
(A). Compound risk value Pα: Risk value that erroneously determines that the target facility 1 has failed even though the target facility 1 has not failed
(B). Compound risk value Pβ: Risk value that erroneously determines that the target facility 1 has failed despite the failure
(C). Overall composite risk value Ptotal: a risk value in which at least one of the target facility 1 and the sensor 2 is out of order.

Specifically, when the failure risk value Pobject and failure risk prediction value Pobject (1) of the target facility 1 are set, and the failure risk value Psensor and failure risk prediction value Psensor (1) of the sensor 2 are set,
Compound risk value Pα = Psensor × (1-Pobject) (3)
Composite risk value Pβ = Psensor × Pobject (4)
Total composite risk value Ptotal = 1- (1-Psensor) × (1-1-Pobject) (5)
Is calculated by the following equation.

  The composite risk value Pα indicates that the sensor 2 is abnormal (damaged or malfunctioned), the risk value when the target equipment 1 is not abnormal, and the composite risk value Pβ indicates that the sensor 2 is abnormal (damaged or malfunctioned) and the target equipment 1 is abnormal. When it becomes, it is a risk value which cannot detect the abnormality of the target facility 1, and the overall composite risk value Ptotal is a risk value at which one of the sensor 2 and the target facility 1 becomes abnormal.

  As for the risk predicted value, Pobject (1) and value Psensor (1) are used, and the composite risk predicted value Pα (1) after one year in the future using the same calculation formula as Expressions (3) to (5). , Composite risk prediction value Pβ (1), overall composite risk prediction value Ptotal (1) can be calculated.

  The failure risk values Pobject, Psensor calculated by the risk diagnosis unit 12 and the composite risk calculation unit 13 and the composite risk values Pα, Pβ, Ptotal of the target equipment 1 and the sensor 2 are sent to the alert determination unit 14.

  The threshold value for each failure risk value and each composite risk value Pα, Pβ, Ptotal is set in advance in the alert determination unit 14 from the input unit 18 and corresponds to each failure risk value, each composite risk value Pα, Pβ, Ptotal. For example, it is determined whether or not the failure risk value Pobject has exceeded the threshold value.

  Here, when the failure risk value Pobject exceeds the threshold value, the alert display unit 16 is notified of warning information and maintenance request information indicating that the failure risk value Pobject has exceeded the threshold value.

  Based on the warning information and maintenance request information output from the alert display unit 16, the maintenance staff 7 visits the site and performs maintenance inspection on the target equipment 1 and the sensor 2 that are the targets of the maintenance request information.

  On the other hand, in the maintenance planning processing unit 15, each failure risk value, each failure risk predicted value, composite risk predicted value Pα (1), Pβ (1), Ptotal (1), or target equipment is previously input from the input unit 9. 1 and a threshold value based on a combination of the sensor 2 is set, and each failure risk value calculated by the risk diagnosis unit 12, each failure risk prediction value, and a composite risk prediction value Pα (1 ), Pβ (1), Ptotal (1), and any failure risk value, failure risk prediction value or composite risk prediction value Pα (1), Pβ (1), Ptotal (1) correspond to each other. When the threshold value is exceeded, a maintenance plan is automatically drafted, or an integrated maintenance plan including the individual target equipment 1, sensor 2, etc. is edited and drafted and displayed on the maintenance plan display unit 17.

  For example, the failure risk prediction value Pobject (1) (life model) of the target facility 1 obtained according to the life model of the equation (1) and the failure risk prediction value Psensor (2) of the sensor 2 obtained according to the operation equation of the equation (2). 1) From the (life model), when the total composite risk value Ptotal (1) calculated by the formula (3) is predicted to exceed the threshold of 10% as 6 months, the target is within 6 months. A maintenance plan for carrying out maintenance inspection (including replacement) of the equipment 1 and the sensor 2 is drawn up.

  In addition, the maintenance planning processing unit 15 calculates the failure risk prediction values Pobject (1) and Psensor (1) of the target equipment 1 and the sensor 2, that is, based on the life model, from the maintenance cost database 10C. The predicted damage cost value due to failure and the predicted maintenance cost value required for maintenance of the target equipment 1 or sensor 2 are extracted, and the maintenance time at which the sum of the predicted damage cost value and the predicted maintenance cost value is minimized is calculated. The maintenance plan that defines the maintenance time is displayed on the maintenance plan display unit 17.

Next, an example of a maintenance plan considering the maintenance cost due to equipment failure will be described with reference to FIG.
For example, as shown in FIG. 4, the horizontal axis represents a time axis indicating maintenance time, the vertical axis represents a cost axis indicating each cost, and curves A and B are created. Here, the curve A is the equipment failure risk cost obtained by multiplying the failure risk prediction value (1) Pobject of the target equipment 1 by the failure cost of the target equipment 1. The curve A may be, for example, a facility stop cost obtained by multiplying the risk prediction value Ptotal when any of the target facility 1 or the sensor 2 fails by the cost of the impact of the facility stop due to the failure, or It may be an equipment failure response failure list cost obtained by multiplying the risk prediction value Pβ (1) overlooking the failure by the total damage cost due to the equipment failure accident spread when the initial failure cannot be taken due to failure oversight.

  Curve B shows the maintenance cost necessary for maintenance and inspection of the target equipment 1 (maintenance labor costs, transportation costs for the maintenance staff to move to the site, loss due to equipment shut down for equipment inspection, etc. Cost). In addition, the maintenance cost rushes to the site from the maintenance cost obtained by multiplying the maintenance cost by the risk prediction value Pα (1), which is the result of misdiagnosing normality as a failure. It is possible to include useless costs that would otherwise prove to be lost.

  Therefore, the maintenance planning processing unit 15 creates a curve of the total (total) cost A + B obtained by adding the equipment failure risk cost of the curve A and the maintenance cost of the curve B, and the curve of the total cost A + B is the minimum. The time taken on the horizontal axis from that point is determined as the optimum maintenance plan (maintenance time) and displayed on the maintenance plan display unit 17.

Furthermore, an example of a maintenance plan based on equipment failure / maintenance inspection of a single target equipment 1 and sensor 2 will be described with reference to FIG.
This maintenance plan planning example is a planning example assuming that one sensor 2 is attached to one target facility 1. Conventionally, only the maintenance plan of the target equipment 1 shown in the drawing (A) is displayed and maintenance is performed. In the present invention, the above-described formulas (1) and (2) of the target equipment 1 and the sensor 2 are used. From the failure risk by the life model such as the equation and the predicted value thereof, the composite risk values Pα, Pβ, Ptotal and the risk predicted values Pα (1), Pβ (1), Ptotal (1) of the equations (3) to (5) Is calculated, and a maintenance plan is drawn up and displayed on the maintenance plan display unit 17.

  That is, the system of the present invention is any one of the failure risk value of the target facility 1 and the sensor 2 according to the expressions (1) and (2) and the composite risk values Pα, Pβ, and Ptotal of the expressions (3) to (5). When one of the thresholds exceeds an individually set threshold value, an alert is output from the alert display unit 16 and maintenance inspection is executed.

  In the system of the present invention, the failure risk of the target facility 1 in the illustration (b) becomes a combined risk in which the failure risk of the sensor 2 is raised as shown in the drawing (b), so that the threshold value is exceeded at the time T1. The maintenance of the sensor 2 is executed, and as a result, the combined risk is reduced. Conventionally, only the risk of failure of the target facility 1 is present, so the maintenance of the sensor 2 is not performed at the time T1, and usually a failure of the sensor 2 having a shorter lifetime than the target facility 1 is encountered, and the system is down. Or wrong sensor output is used as effective sensor data.

Subsequently, since the combined risk reaches the threshold again at the time of the regular inspection T2, the maintenance of the target facility 1 is executed. This equipment maintenance reduces the combined risk.
In addition, the failure risk prediction value and the risk prediction values Pα (1), Pβ (1), and Ptotal (1) are similarly predicted by setting threshold values individually and in combination to predict when the threshold value will be exceeded. Yes, you can make a maintenance plan in the meantime.

  In this way, a maintenance plan for the target facility 1 and the sensor 2 that keeps the overall composite risk within the allowable threshold can be made automatically, and the overall risk can be kept to a minimum.

  Therefore, according to the embodiment as described above, the diagnosis of the target equipment 1 taking into account the risk of failure of the sensor 2 makes it possible to make a diagnosis with higher accuracy and reliability than before, and at a minimum risk or maintenance cost. Maintenance can be performed. As a result, failure of the target facility 1 and the sensor 2 can be prevented in advance, and damage due to failure can be minimized.

  Further, since the maintenance plan can be calculated not only for the target facility 1 but also for the sensor 2, the maintenance of the sensor 2 can be performed appropriately, and the entire facility including the sensor 2 has high reliability. A diagnosis / maintenance plan support system can be realized.

(Second Embodiment)
FIG. 5 is a block diagram for explaining a second embodiment of the combined diagnosis / maintenance plan support system according to the present invention. In the figure, the same or equivalent components as those in FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted.

  In this embodiment, the difference is that a plurality of target facilities 1a, 1b,... And a plurality of sensors 2a, 2b,. , 2b,... Are provided with a plurality of signal lines.

  And, as a plurality of target facilities 1a, 1b,... And sensors 2a, 2b,. The composite risk values Pα, Pβ, Ptotal, composite risk prediction values Pα (1), Pβ (1), Ptotal (1) are calculated for the failure risk values and failure risk prediction values of the sensors 2a, 2b,. In addition to the function to perform, it has the function of calculating the largest worst risk value (maximum risk value) Phole among the total risk values for each of the facility / sensor combinations 1a-2a, 1b-2b,.

  Furthermore, the alarm determination unit 15 is configured to calculate the total risk by each failure risk value of each target equipment and sensor obtained by the risk diagnosis unit 12 and the composite risk calculation unit 13 and each risk value or a threshold value or combination set individually. In addition to the function of comparing and determining the value and the total threshold value, a function is provided for setting the priority order for comparison determination in descending order of the total risk value and executing the comparison determination at the time of the comparison determination. .

  In FIG. 5, each failure risk value, each failure risk predicted value, each risk value, and the signal line of each risk predicted value are simplified and shown as a single line, but the target facilities 1 a, 1 b,. A signal line is provided for each failure risk value, each failure risk prediction value, each risk value, and each risk prediction value corresponding to 2b,.

  In this embodiment, for example, the sensors 2a, 2b, 2c,... Associated with the target facilities 2a, 2b, 2c,. The sensors attached to 2b, 2c,... Are old and new towns.

  Therefore, for example, when the sensor 2a of the target facility 1a having the largest maximum risk value is the oldest, for example, by replacing it with a relatively new sensor 2b, for example, so-called reuse, each composite risk value Pα, Pβ, Ptotal Can be reduced.

  Next, the operation of the combined diagnosis / maintenance plan support system as described above will be described, particularly the diagnosis / maintenance plan planning system.

  The life model estimation unit 11 takes out the operation time, the number of start / stops, the number of failure samples, and other necessary data of each past target equipment 1a, 1b,... And past past sensors 2a, 2b,. (Statistical analysis) technique is used to estimate the life models of the equations (1) and (2) including model coefficients A, B, and C (target equipment) and coefficients As, Bs, and Cs (sensors), and corresponding databases 11A and 11B. And is sent to the risk diagnosis unit 12 as needed or.

  The risk diagnosis unit 12 includes the individual target facilities 1a, 1b,... And the sensor 2a, 2b,. .. And a total failure risk prediction value Pobject (1) a, b,... Combined with 2b,.

  The composite risk calculation unit 13 calculates a composite risk value and a composite risk prediction value, respectively, and extracts the maximum risk value Phole and the maximum risk prediction value Phole (1) from these composite risk value and composite risk prediction value, The overall risk value and the overall risk prediction value of the equipment group are sent to the alert determination unit 14 for the risk value, and to the maintenance plan processing unit 15 for the composite risk prediction value.

  The alert determination unit 14 compares each risk value with a corresponding threshold value, and outputs an individual alert or an overall alert to the alert display unit 16 when any risk value exceeds the threshold value. In addition, the alert determination part 14 sets a priority order in the order of the most dangerous equipment when the threshold value is exceeded in advance, and among the plurality of target equipments 1a, 1b, ... and the plurality of sensors 2a, 2b, ... When each risk value exceeds the threshold value, an alert is sent to the alert display unit 16 according to the priority order.

  As described above, the maintenance planning processing unit 15 sends the target facilities 1a, 1b,... And the target facilities 1a, 1b,. The failure total risk prediction value Pobject (1) a, b,... Combined with the corresponding sensors 2a, 2b,... Is received, and each composite risk prediction value Pα (1), Pβ (1 ), Ptotal (1) and the maximum risk prediction value Phole (1), compare them with the threshold values already set, find out the maintenance time when each risk value will exceed the threshold value in the future, and For the composite maximum risk prediction value Phole (1), a maintenance time that will exceed the threshold value in the future is found, and the maintenance plan display unit 17 includes, for example, the target facility 1a including the sensor 2a and the center as shown in FIG. The total risk value of the target facility 1b including the sensor 2b is displayed. At this time, although not shown in the drawing, for example, various characteristics relating to accuracy and performance including the sensor installation date for the target equipment are extracted from the sensor maintenance history database 10B and displayed, and the risk of each target equipment 1a, 1b,. A maintenance plan for optimal sensor installation will be made.

  For example, an optimum sensor is selected from a plurality of sensors including a sensor having a short life and high failure detection accuracy and a sensor having a long life and low failure detection accuracy, and depending on the risk value of each target facility 1a, 1b,. And attach. This means that, for the time being, the target equipment with a very low risk of failure can be used by attaching a sensor with low accuracy, not installing a sensor, or using a sensor installed in another target equipment. In addition, a plurality of sensors may be combined and installed in one target facility.

  In addition, the maintenance plan planning processing unit 15 formulates a maintenance plan from the risk prediction value. At this time, as a work plan based on the maintenance plan, the maintenance work of the target facility 1, the sensor operation check work, the sensor check At least one of maintenance work including adjustment work, sensor replacement work, replacement work of parts including the sensor, and sensor rearrangement work among the plurality of target facilities 1a, 1b,.

  Therefore, the maintenance planning processing unit 15 relates to the maintenance cost required for each work, as shown in FIG. 3, from the maintenance cost database 10C, a predicted damage cost due to the failure of the target equipment after the maintenance work, and the target It is also possible to select from conditions that minimize the total cost of equipment and sensor maintenance costs, and output the result as a maintenance plan.

  Further, in the maintenance plan planning processing unit 15 of this system, when a plurality of sensors 2a, 2b,... Are installed for a plurality of target facilities 1a, 1b,. Advantages of the replacement will be described from the display example of the maintenance plan shown in FIG.

  That is, each target equipment 1a, 1b, ..., each sensor 2a, 2b, ... is based on the failure risk prediction value by life models, such as said (1) Formula and (2) Formula calculated in the risk diagnosis part 12. FIG. The composite risk calculation unit 13 calculates the risk values and risk prediction values of the equations (3) to (5). As a result, a composite risk such as equipment 1a / sensor 2a, equipment 1b / sensor 2b as shown in FIG. 6 is created in the maintenance plan drafting processing section 15 and displayed on the maintenance plan display section 17 as a maintenance plan.

  At this time, although the periodic inspection time is T2, since the risk prediction value of the target facility 1b is more dominant than the sensor 2b, the combined risk including the target facility 1b and the sensor 2b at the time T1 before the periodic inspection time T2. Since the predicted value exceeds the threshold value, the time point T1 is set as the maintenance time of the target facility 1b, and the maintenance is executed. As a result, the target facility 1b is reduced by the failure risk prediction value of the facility 1b, and the failure risk of the target facility 1b is reduced.

  Therefore, if the process proceeds as it is, it is predicted that when the composite risk prediction value including the target equipment 1a and the sensor 2a reaches the time point T3 ′, maintenance is required to exceed the threshold value. .

  In the maintenance plan planning processing unit 15 according to the present invention, the combined risk calculation unit 13 determines that the periodic inspection time is the total risk value Pa total of the target facility 1a and the sensor 2a at T2, the total risk value Pb total of the target facility 1b and the sensor 2b, … Is displayed.

  In view of this, the maintenance planning processing unit 15 according to the present invention takes out the predicted cost of damage due to the failure of the target equipment and the maintenance cost of the target equipment and sensor from the maintenance cost database 10C as shown in FIG. When it is determined that the cost is minimized when the sensors 1a and 1b are replaced with each other by the calculation calculation, the sensor 2a of the target facility 1a is arranged in the target facility 1b with the periodic inspection time T2, and the sensor 2b of the target facility 1b is It decides to arrange in the target equipment 1a, and displays it with a dotted line as shown in the figure, or displays a message.

  As a result, the sensor 2b having a low failure risk and a high reliability is arranged in the target facility 1a whose facility failure risk is increasing, while the target facility 1b having a small facility failure risk immediately after the facility maintenance has a slightly higher failure risk. The sensor 2b having low reliability is arranged to minimize the overall failure risk.

  That is, the maintenance of the target equipment 1a can be postponed from the time T3 ′ to the time T3 only by exchanging the sensors 2a and 2b, and the equipment maintenance is executed for the first time at the time T3. At this time, maintenance of the sensor 2a of the target facility 1b should be performed at the same time. Thereafter, a maintenance plan such as executing equipment maintenance of the target equipment 1b at time T4 can be made.

  As described above, based on the respective failure risk prediction values (life model) of the plurality of target facilities 1a, 1b,... And the plurality of sensors 2a, 2b,. By optimizing the operation of the target equipment and the state of the risk of the sensor, the sensor can be reused as appropriate to avoid overlapping the sensor with high risk of failure with the target equipment with high risk of failure. And the overall risk can be kept to a minimum.

  Therefore, according to the above embodiment, in addition to the effects obtained in the first embodiment, each target facility 1a, Since the optimal sensors 2a, 2b,... Can be arranged for 1b,..., It is possible to avoid problems such as a decrease in diagnostic reliability in some target facilities and an increase in cost due to excessive investment of sensors. The sensor can be operated.

(Third embodiment)
FIG. 7 is a block diagram for explaining a third embodiment of the combined diagnosis / maintenance plan support system according to the present invention. 2 has almost the same configuration as FIG. 2 or FIG. 5, the same or equivalent components are denoted by the same reference numerals, and detailed description thereof is omitted.

  In this embodiment, the difference is that the sensors 2a, 2b,... Arranged on the respective target facilities 1a, 1b,... Have wireless sensors 22a, 22b,. On the other hand, an access point 24 for individually receiving sensor data transmitted from the wireless sensors 22a, 22b,... Via the wireless communication network 23 is provided on the diagnosis / maintenance plan support apparatus 4 side.

  The life model estimation unit 11A of the diagnosis / maintenance plan support apparatus 4 uses the wireless sensors 22a, 22b,... With built-in batteries 21a, 21b,. A life model including a model coefficient is estimated from the consumption characteristics of the batteries 21a, 21b, ... of the sensors 22a, 22b, ..., and provided to the risk diagnosis unit 12.

  Specifically, the life model estimation unit 11A is configured based on the total operation time value Top of the batteries 21a, 21b,... And the total communication count Tst of the wireless sensors 22a, 22b,. For the probability that the remaining charge amount becomes 0, the following life model calculation formula including the total operation time integrated value Top and the coefficients A and B of the total communication count Tst is estimated.

Pbuttery = A × Top + B × Tst + C (6)
The life model calculation formula is sent to the risk diagnosis unit 12. A correction term such as an external temperature condition can be added to this arithmetic expression.

  Since the risk diagnosis unit 12, the composite risk calculation unit 13, the alert determination unit 14, the maintenance plan planning processing unit 15 and the like are as described above, they are omitted here.

  That is, in this embodiment, as in the first and second embodiments, the failure risk, failure risk prediction value and risk value, and risk prediction value calculated by the risk diagnosis unit 12 and the composite risk calculation unit 13 are used. Based on the target equipment 1a, 1b,... And the wireless sensors 22a, 22b,.

  In particular, in the maintenance plan planning processing unit 15, in the work plan under the maintenance plan, replacement work for the batteries 21a, 21b,... Of the wireless sensors 22a, 22b,. This includes the work of reusing the batteries 21a, 21b,... Between the wireless sensors 22a, 22b,.

  Therefore, according to this embodiment, by using the wireless sensors 22a, 22b,... As temporary sensors, the same effects as those of the first and second embodiments described above can be obtained, and the second embodiment. The sensor replacement operation described in (1) can be performed extremely easily and in a short time, and the maintenance operation including the sensor can be performed efficiently. In addition, the reliability of the wireless sensors 22a, 22b,... And the optimal maintenance plan can be established without being affected by the depletion of the remaining charge amount of the batteries 21a, 21b,. The reliability of the sensors 22a, 22b,... Can be maintained.

  In addition, the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the invention.

  In addition, the above embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, when an invention is extracted by omitting some constituent elements from all the constituent elements shown in the embodiment, when the extracted invention is carried out, the omitted part is appropriately determined by a well-known common technique. It is to be supplemented.

The figure which shows the basic composition of a general diagnostic and maintenance plan support system. 1 is a configuration diagram showing an embodiment of a combined diagnosis / maintenance plan support system according to the present invention. Explanatory drawing which determines the maintenance plan of the optimal maintenance time from the maintenance cost and the risk cost by the failure of an installation. The display figure which shows the example of a maintenance plan drafting in a single object installation. The block diagram which shows other embodiment of the composite diagnosis and the maintenance plan assistance system which concerns on this invention. The display figure which shows the example of a plan of the maintenance plan in a some target facility. The block diagram which shows other embodiment of the composite diagnosis and the maintenance plan assistance system which concerns on this invention.

Explanation of symbols

  1 (1a, 1b,...) ... target equipment, 2 (2a, 2b,...) ... sensor, 3 ... communication network, 4 ... diagnosis / maintenance plan support device, 6 ... database, 7 ... maintenance data input device, 8 ... Maintenance personnel, 9 ... input unit, 10 ... database, 10A ... equipment maintenance history database, 10B ... sensor maintenance history database, 10C ... maintenance cost database, 11 ... life model estimation unit, 12 ... risk diagnosis unit, 13 ... complex risk calculation , 14 ... Alarm determination unit, 15 ... Maintenance plan planning processing unit, 16 ... Alert display unit, 17 ... Maintenance plan display unit, 21a, 21b, ... ... Battery, 22a, 22b, ... Wireless sensor, 23 ... Wireless communication Network, 24 ... access point.

Claims (13)

A target facility, a sensor that is arranged in the target facility and measures data that is a basis for diagnosis of the target facility, the target facility and maintenance history data of the sensor, and measurement data of the sensor that are input by maintenance inspection A database to be stored, and a diagnosis / maintenance plan support device connected to the sensor via a network and supporting a diagnosis / maintenance plan for the target equipment and the sensor;
This diagnostic / maintenance plan support device
Of the maintenance history data and sensor data stored in the database, a life model estimation unit that estimates a life model using data related to the life of the target equipment and sensor as a variable parameter, and a life estimated by the life model estimation unit Based on the model and the variable parameter data, a risk diagnosis unit that calculates a failure risk and a predicted failure risk value of each of the target equipment and the sensor, and a failure risk and a failure risk calculated by the risk diagnosis unit A composite diagnosis / maintenance comprising a plurality of composite risks associated with an abnormality or failure of any of the target equipment and the sensor based on a predicted value, and a composite risk calculation unit for calculating the composite risk predicted value Planning support system. In the combined diagnosis and maintenance plan support system according to claim 1,
The variable parameter data used in the lifetime model estimation unit is the cumulative operating time of the target equipment and the sensor, the number of start / stop times, usage conditions, external environmental conditions, the number of fault samples, etc., at least the cumulative operating time, A combined diagnosis / maintenance plan support system characterized by the number of start / stop times. In the combined diagnosis and planning support system according to claim 1,
The composite risk calculation unit is configured to determine a first composite risk and its risk prediction that the sensor diagnoses as abnormal even though the target facility is normal based on a failure risk and a failure risk prediction value of the target facility and the sensor. A combined diagnosis / maintenance plan support system, which calculates a value, a second combined risk for diagnosing normality due to an abnormality of the sensor even though the target equipment is abnormal, and a risk prediction value thereof. In the combined diagnosis and maintenance plan support system according to claim 3,
The composite risk calculation unit calculates the overall composite risk and the overall composite risk prediction value that at least one of the target equipment and the sensor is in failure based on the failure risk and the failure risk prediction value of the target equipment and the sensor. A combined diagnosis and maintenance plan support planning system characterized by calculating. In the combined diagnosis and maintenance plan support system according to any one of claims 1 to 4,
The diagnosis / maintenance plan support device includes:
A failure risk of the target equipment calculated by the risk diagnosis unit, a failure risk of the sensor, the first, second and overall composite risks calculated by the composite risk calculation unit and preset threshold values; When one of the risks exceeds a corresponding threshold, an alert determination that outputs a maintenance request that the maintenance of the target equipment or sensor having the risk exceeding the threshold is required A combined diagnosis / maintenance plan support system characterized by further adding a department. In the combined diagnosis and maintenance plan support system according to any one of claims 1 to 5,
The diagnosis / maintenance plan support device includes:
The target equipment failure risk prediction value calculated by the risk diagnosis unit, the sensor failure risk prediction value, the first, second and overall composite risk prediction values calculated by the composite risk calculation unit are preset. To determine when each risk prediction value exceeds the corresponding threshold value, and determine a future maintenance plan for the target equipment, the sensor, or a maintenance plan that integrates individual maintenance. A combined diagnosis / maintenance plan support system characterized by further adding a maintenance plan planning processing unit to be displayed. In the combined diagnosis and maintenance plan support system according to claim 6,
A cost information storage unit is provided for storing maintenance work costs due to maintenance work of the target equipment and the sensor and damage costs due to failure of the target equipment and sensors,
The maintenance planning processing unit is based on the target facility calculated by the risk diagnosis unit, the risk prediction value of the sensor, and the damage cost due to the failure stored in the cost information storage unit, the failure of the sensor Determine and display a maintenance plan with the maintenance time as the sum of the estimated damage cost value and the maintenance work cost stored in the cost information storage unit required for maintenance of the target equipment and the sensor. Combined diagnosis / maintenance plan support system characterized by being displayed in the department. In the combined diagnosis and maintenance plan support system according to any one of claims 1 to 7,
When a facility group consisting of multiple target facilities and sensors corresponding to these facilities is installed,
The combined risk calculation unit calculates the largest combined risk as the overall risk of the facility group among the combined risks calculated by the combination of each target facility and the corresponding sensor. -Maintenance plan support system. In the combined diagnosis and maintenance plan support system according to any one of claims 1 to 8,
When a facility group consisting of multiple target facilities and sensors corresponding to these facilities is installed,
The maintenance planning processing unit, based on the combined risk state of each target facility obtained from the combined risk calculation unit at the time of maintenance and the combined risk state of the sensor corresponding to each target facility, the sensor of each target facility A combined diagnosis / maintenance plan support system characterized in that replacement is determined and displayed, and the overall risk of the equipment group after maintenance is reduced. In the combined diagnosis and maintenance plan support system according to claim 9,
The means for replacing the sensors considers characteristics related to the performance of each target facility and the failure risk of each sensor, arranges a sensor suitable for each target facility, and reduces the overall risk of the facility group after maintenance inspection. A combined diagnosis / maintenance plan support system. In the combined diagnosis / maintenance plan support system according to claim 1 to 10,
When a wireless sensor is used as the sensor,
The combined diagnosis / maintenance plan support system, wherein the lifetime model estimation unit estimates a lifetime model of a wireless sensor from a consumption characteristic of a battery built in the wireless sensor. A sensor is arranged in the target equipment, and the data of the target equipment detected by the sensor and the maintenance history data of the target equipment and the sensor input in maintenance inspection of the maintenance staff are stored in a database, In a method for supporting a diagnosis / maintenance plan for the target equipment and the sensor,
From the database, the data on the life of the target equipment and the sensor is extracted, and a life stage model using these data as variable parameters is estimated.Based on the estimated life model, current and past variable parameter data, A risk diagnosis stage for calculating a failure risk and a future failure risk prediction value of each of the target facility and the sensor, and based on the failure risk and the failure risk prediction value, any abnormality or failure of the target facility or the sensor is detected. A composite diagnosis / maintenance plan support method comprising: a composite risk calculation stage for calculating a composite risk involved. In the combined diagnosis and maintenance plan support method according to claim 12,
Predicted failure risk prediction value of the target facility calculated in the risk diagnosis step, failure risk prediction value of the sensor, first, second and overall combined risk prediction values calculated in the combined risk calculation step Compared with the measured threshold value, predicting when the corresponding threshold value is exceeded from each risk prediction value, and determining the maintenance plan that integrates the future maintenance plan or individual maintenance of the target equipment, the sensor And a maintenance plan planning process stage for displaying the combined diagnosis / maintenance plan support method.

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