JP2009155043A - Elevator component improvement schedule system and elevator component improvement schedule method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To analyze failure factor of a component forming an elevator. <P>SOLUTION: Shipment information DB 11 stores shipment information containing component identification information for identifying an elevator component and client identification information for identifying shipping destination of the component. Maintenance information DB 12 stores maintenance information containing failure occurrence information representing failure occurrence of the component identified by the component identification information in association with the component identification information contained in the shipment information. Use environment information DB 14 stores use environment information representing the usage state of the component identified by the component identification information in association with the component identification information contained in the shipment information. An analysis section 153 extracts the maintenance information and use environment information associated with the component identification information identifying a target component designated by a user. The analysis section 153 analyzes the failure factor of the target component based on the maintenance information and use environment information. An input/output section 16 outputs a result analyzed by the analysis section 153. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a part improvement planning system and a part improvement planning method for an elevator that are used to improve a method of using parts constituting an elevator.

  For example, an elevator installed and operating in a building or the like is managed by maintenance and inspection of the elevator (hereinafter simply referred to as elevator maintenance) by maintenance personnel (persons in charge) in order to prevent accidents, etc. It is common.

  In maintenance of an elevator, for example, replacement of parts that have reached the end of their service life due to long-term use is performed among the parts constituting the elevator.

  In recent years, for such maintenance of the elevator, for example, customers who ship the elevator (parts constituting the elevator), shipping information indicating the operation time of the elevator, or failure of the parts constituting the elevator, for example. There is known a system in which maintenance information indicating time and the like is stored in a database. This maintenance information includes, for example, a replacement history of parts replaced due to a failure or the like. The replacement time of each part constituting the elevator is set based on, for example, a replacement history included in the maintenance information.

  In such a system, for example, shipping information or maintenance information is input by, for example, a maintenance worker who performs maintenance of the elevator, or is collected from the elevator by remote operation, thereby constructing a database.

  The shipping information or maintenance information stored in the database in this way can be confirmed on the network. Thereby, the persons concerned including a maintenance person can confirm the specification of the elevator which he manages, the exchange situation of the parts which constitute the elevator concerned, etc., for example.

As a technique related to replacement of the parts constituting the elevator as described above, for example, a technique that can perform replacement in accordance with the use state of the parts and can reduce the burden on maintenance personnel is disclosed (for example, , See Patent Document 1). According to this technology, the replacement time of each part is automatically calculated from the customer information, the life prediction table, and the work results for each part of all the elevators under its jurisdiction.
JP-A-6-345348

  In the conventional system as described above, a database is constructed in which shipping information or maintenance information used for elevator maintenance is stored (managed).

  However, in the above-described system, it is possible to confirm the state of each elevator by shipping information or maintenance information stored in a database, but it is not possible to grasp the situation of a plurality of elevators as a whole. That is, when a plurality of elevators installed in various places (a plurality of locations) are assumed, it is impossible to grasp the failure status of each component at each component level constituting these elevators. In addition, it is impossible to grasp the failure status of a specific part in a plurality of elevators installed in a specific area (for example, Kanto, etc.) among the plurality of elevators.

  In addition, the replacement time of the parts constituting the elevator is set based on, for example, the replacement history included in the maintenance information. However, although there are various parts in the parts constituting the elevator, the replacement time is constant. It may be. On the other hand, since the setting of the replacement time often depends on the experience of maintenance personnel, the replacement time may be different even for the same parts depending on the area where the elevator is installed. That is, there is a case where there is no consistency in the replacement time of the parts constituting the elevator.

  In the above system, the maintenance information stored in the database includes the replacement history of parts replaced due to failure, for example, but it is not possible to immediately grasp the cause (cause) of the failure. Can not. Further, for example, when investigating the cause of failure, the response may be delayed because the investigation takes time.

  Further, for example, when the replacement time is set based on the replacement history of the parts, the time required for the parts replacement performed at the replacement time or the cost of the parts is not considered. That is, the total cost required for parts replacement is not taken into consideration.

  In addition, as described above, since there is no consistency in the replacement timing of parts, it is difficult to predict the occurrence of a failure in advance. For this reason, it is conceivable that a failure occurs in the part before the part replacement.

  In addition, for example, the usage period of the parts may be shortened because the environment (usage environment) or the usage method in which the parts constituting the elevator are used is not appropriate. However, even in such a case, since the factor (cause) is unknown, it cannot be fundamentally improved, and there are cases in which it is possible to cope by changing parts.

  An object of the present invention is to provide an elevator parts improvement planning system and a parts improvement planning method for analyzing failure factors of parts constituting an elevator.

  According to one aspect of the present invention, shipping information storage for storing shipping information including part identification information for identifying parts constituting an elevator and customer identification information for identifying a shipping destination to which the parts are shipped. Maintenance information including failure occurrence information indicating that a failure has occurred in the component identified by the component identification information in association with the component identification information included in the shipment information stored in the shipment information storage unit Maintenance information storage means for storing information, and usage environment information indicating the usage status of the parts identified by the parts identification information in association with the parts identification information included in the shipping information stored in the shipping information storage means Use environment information storage means to be stored, and part identification information for identifying the target part specified by the user, and customer identification for identifying the same shipping destination Maintenance information stored in the maintenance information storage means in association with the parts identification information included in the shipping information including the information, and use environment information stored in the use environment information storage means in association with the parts identification information Extraction means for extracting the failure factor of the target part based on the failure occurrence information included in the extracted maintenance information and the acquired use environment information, and an analysis result by the analysis means An elevator parts improvement planning system is provided.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to analyze the failure factor of the components which comprise an elevator.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a block diagram showing a configuration of an elevator parts improvement planning system according to the present embodiment.

  An elevator parts improvement planning system 10 shown in FIG. 1 includes a shipping information database (DB) 11, a maintenance information database (DB) 12, a risk management database (DB) 13, a use environment information database (DB) 14, a computer 15, An output unit 16, an extraction result database (DB) 17, and a reliability analysis database (DB) 18 are included.

  The shipping information database 11 stores shipping information related to the shipping of each part constituting the elevator. The shipment information includes, for example, part identification information for identifying parts constituting the elevator and customer identification information for identifying a customer (shipment destination) to which the parts are shipped.

  The maintenance information database 12 stores maintenance information related to maintenance (maintenance) of each part constituting the elevator. This maintenance information is stored in the maintenance information database 12 in association with, for example, part identification information included in the shipping information stored in the shipping information database 11. The maintenance information includes failure occurrence information indicating that a failure of a component identified by the component identification information associated with the maintenance information has occurred.

  In the risk management database 13, the risk management information indicating the replacement work time required for the work when replacing each part constituting the elevator and the lead time of each part is included in the part identification information for identifying the part. Stored in association. The replacement work time indicated by the risk management information is automatically collected from another database such as a replacement work time management system. The lead time indicated by the risk management information is automatically collected from another database such as a producer management system.

  In the use environment information database 14, the use status (environment used) of the component identified by the component identification information in association with the component identification information included in the shipment information stored in the shipment information database 11 described above. The environment information (usage environment information) is stored. This environmental information includes, for example, the temperature and humidity of the place where each part constituting the elevator is used, the number of times the elevator (each part constituting the elevator) is started, the voltage and current applied to the part, the hardness and stress relating to the part. Data or other data related to the life of the part is included.

  The hardness or stress data regarding the temperature, humidity, and mechanical parts is collected at any time by using, for example, a sensor installed in each elevator. The collected data is sent to the use environment information database 14 via, for example, an elevator control main controller. The number of activations, current, or voltage are also automatically measured and counted by, for example, an elevator control main controller, and sent to the use environment information database 14.

  For data measurement, not only the main controller and sensors, but also products and parts used in the environment are individually provided with a function of collecting data relating to the lifetime. For example, the relay and battery have a structure that can be used in a state in which a function for collecting various data such as temperature, humidity, number of activations, voltage, and current is incorporated.

  Furthermore, in addition to the various sensors described above, for example, a surveillance camera is installed in the elevator. Thereby, for example, the heat distribution and each area of a circuit or a part constituting the elevator can be collected as an image (information) or a video (information). With this collected image or video, for example, it is possible to always monitor and check whether an abnormal situation has occurred.

  Moreover, it is possible to freely change the arrangement of the various sensors according to the mounting position or temperature distribution of each part constituting the elevator. Moreover, as a method of transmitting data from various sensors, for example, either wired or wireless may be used. For example, when measuring data, processing such as temporarily turning off the power or stopping the elevator is performed depending on the measurement contents.

  Note that, for example, the above-described risk management information and environment information can be set to be transmitted to the risk management database 13 and the usage environment information database 14 after a certain period of time, for example. Further, as described above, risk management information and environment information are associated with each identification information (part identification information) such as a manufacturing number (manufacturing number) of an installed elevator (each part constituting the elevator). Stored (saved) in state.

  The computer 15 executes an analysis tool (program) stored in, for example, a storage medium (not shown). The computer 15 includes an information extraction unit 151, a calculation unit 152, an analysis unit 153, and a management unit 154. These units 151 to 154 are realized by the computer 15 executing the analysis tool described above.

  The information extraction unit 151 extracts data (item data) related to a part (hereinafter referred to as a target part) designated by a user (maintenance staff) via the input / output unit 16, for example. At this time, the information extraction unit 151 executes an extraction process based on the part identification information included in the shipping information stored in the shipping information database 11. This item data includes, for example, customer identification information included in the shipping information stored in the shipping information database 11. Item data extracted from the shipment information database 11 (hereinafter referred to as shipment extraction information of the target part) is stored in the extraction result database 17.

  In addition, the information extraction unit 151 extracts data (item data) related to the target component designated by the user via the input / output unit 16 from the maintenance information database 12. This item data includes, for example, failure occurrence information included in maintenance information stored in the maintenance information database 12. The item data extracted from the maintenance information database 12 (hereinafter referred to as “maintenance extraction information of the target part”) is stored in the extraction result database 17 in the same manner as the above-described shipment extraction information.

  It should be noted that the extraction of the shipment extraction information or the maintenance extraction information can be performed in, for example, a system unit, a device unit, a product type unit, or a part type unit.

  The computing unit 152 calculates the number of target parts shipped to the same customer (shipping destination) based on the target part shipment extraction information stored in the extraction result database 17. If the equipment making up the shipped elevator has the same type of base or parts of the same type, use the number obtained by multiplying the number of units shipped and the number of bases or parts included in the equipment. Thus, the shipment quantity of each component (base) is calculated.

  The computing unit 152 executes a process of storing population information including shipment quantity information indicating the calculated shipment quantity (population number) of the target part in the extraction result database 17. This population information includes, for example, information indicating a customer name and shipping time as a shipping destination.

  Based on the failure occurrence information included in the maintenance extraction information of the target part stored in the extraction result database 17 and the shipment quantity information included in the population information, the analysis unit 153 is a target on which the failure indicated by the failure occurrence information has occurred. Calculate the number of parts (number of failures).

  The analysis unit 153 operates normally on site from the difference between the shipment quantity of the target part indicated by the shipment quantity information included in the population information stored in the extraction result database 17 and the calculated failure quantity of the target part. Calculate the number of target parts that are in operation. For example, when calculating the failure rate, the analysis unit 153 calculates the ratio of the number of failures with respect to the number of shipments of the target part.

  As the analysis unit 153, for example, the time (operation time) during which the target part is operating normally is calculated from the analysis processing date (analysis date) and the operation start date and time, and the calculated time is used as censored data.

  The analysis unit 153 generates reliability analysis information representing the reliability of the target component by executing a reliability analysis process on the target component, for example. For example, the analysis unit 153 generates reliability analysis information based on the shipment quantity of the target part indicated by the shipment quantity information included in the population information stored in the extraction result database 17 and the calculated failure quantity of the target part. To do. The analysis unit 153 performs reliability analysis using functions such as a reliability function R (t), an unreliability function F (t), a failure probability density function f (t), and a cumulative hazard function H (t), for example. Generate information. The analysis unit 153 stores the generated reliability analysis information in the reliability analysis database 18.

  The analysis unit 153 calculates the replacement time of the target part based on the generated reliability analysis information. At this time, the analysis unit 153 calculates the replacement time of the target part using, for example, risk management information stored in the risk management database 13 or environment information stored in the use environment information database 14. The analysis unit 153 stores the calculated replacement time of the target part in the reliability analysis database 18 as reliability analysis information.

  Further, the analysis unit 153 is used in association with the maintenance extraction information of the target part shipped to the same customer (shipping destination) stored in the extraction result database 17 and the part identification information for identifying the target part, for example. Extract (acquire) environmental information stored in the environmental information database 14 (hereinafter referred to as environmental information of the target part). Here, the target parts shipped to the same customer are specified by customer identification information included in the shipping extraction information of the target parts stored in the extraction result database 17, for example.

  The analysis unit 153 analyzes the failure factor of the target part based on the extracted maintenance extraction information and environmental information of the target part. The analysis unit 153 stores the analysis result in the reliability analysis database 18 as reliability analysis information. The analysis result stored in the reliability analysis database 18 as reliability analysis information is output (displayed) to maintenance personnel or the like via the input / output unit 16, for example.

  In addition, the analysis unit 153 acquires maintenance extraction information of a target part in which no failure has occurred and environment information of the target part from the extraction result database 17 and the use environment information database 14. At this time, the analysis unit 153 performs an acquisition process based on failure occurrence information included in the maintenance extraction information stored in the extraction result database 17. The analysis unit 153 creates (generates) reference data (reference space) serving as a reference that does not cause a failure based on the acquired maintenance extraction information and environmental information.

  The analysis unit 153 compares the created reference data with the maintenance extraction information and environmental information of the target part that is currently operating (no failure has occurred). The analysis unit 153 detects (determines) a defect of the target part from the comparison result. The analysis unit 153 stores the comparison result (or determination result) in the reliability analysis database 18 as reliability analysis information.

  Based on the reliability analysis information (reliability analysis result) stored in the reliability analysis database 18, the management unit 154 collects field data collected at any time (operation of the target component constituting the elevator that is actually operating) If the target part reaches the limit (life), for example, the maintenance staff is notified that it is time to replace the target part. In this case, the management unit 154 notifies the maintenance staff via the input / output unit 16 by displaying on, for example, a monitor of a personal computer (PC).

  The management unit 154 has a function of outputting, for example, reliability analysis information stored in the reliability analysis database 18 via the input / output unit 16.

  Further, the management unit 154 monitors (determines) an abnormality of the target component based on the heat distribution (video or image data indicating the target component) captured by the above-described monitoring camera or the like. When an abnormality is determined, the maintenance staff is notified through the input / output unit 16, for example.

  FIG. 2 shows an example of the data structure of the shipment extraction information of the target part stored in the extraction result database 17. The shipment extraction information shown in FIG. 2 is item data relating to the target parts that constitute the elevator.

  As shown in FIG. 2, the shipment extraction information includes, for example, a note number (temporary number), a building name, an item number, a maintenance work number, a machine number, an abbreviated specification, an FS start date, and the like. In the example illustrated in FIG. 2, customer identification information for identifying a ship-to party (a customer whose building name is) is shown.

  FIG. 3 shows an example of the data structure of the target component maintenance extraction information stored in the extraction result database 17. The maintenance extraction information shown in FIG. 3 is item data relating to the target parts constituting the elevator.

  As shown in FIG. 3, the maintenance extraction information includes, for example, a building name (government-reported building name N), order number (provisional number), maintenance work number (installation number), abbreviated specification, FS (period) start date , Failure occurrence date, years of use (failure years), failure occurrence time, failure number, responsible office CD, failure reception date, etc. are included. In the example shown in FIG. 3, the failure occurrence date, the failure year, the failure occurrence time, the failure number, the failure reception date, etc. are failure occurrence information indicating that the failure of the target component has occurred. In addition, the above-described failure years are expressed in time by, for example, (failure occurrence date−FS start date) × 24.

  Next, the processing procedure of the elevator parts improvement planning system 10 will be described with reference to the flowchart of FIG.

  First, the information extraction unit 151 extracts item data (target part shipment extraction information) of the target part designated by the user via the input / output unit 16 from the shipping information database 11 (step S1). This shipment extraction information includes, for example, customer identification information for identifying a customer (shipment destination) to which the target part has been shipped. The information extraction unit 151 stores the extracted shipment extraction information of the target part in the extraction result database 17.

  In addition, the information extraction unit 151 extracts item data (control component maintenance extraction information) of the reference component designated by the user via the input / output unit 16 from the maintenance information database 12 (step S2). This maintenance extraction information includes, for example, failure occurrence information indicating that a failure has occurred in the target part. The information extraction unit 151 stores the extracted maintenance extraction information of the target part in the extraction result database 17.

  Based on the shipment extraction information of the target parts stored in the extraction result database 17, the calculation unit 152 calculates the number of units shipped (paragraph) of the target parts shipped to the same customer (Step S <b> 3). The computing unit 152 stores population information including shipment quantity information indicating the calculated shipment quantity in the extraction result database 17.

  Based on the failure occurrence information included in the maintenance extraction information stored in the extraction result database 17 and the shipment quantity information included in the population information, the analysis unit 153 includes the shipment quantity of the target part indicated by the shipment quantity information. Then, the number of target parts in which the failure indicated by the failure occurrence information has occurred (the number of failures) is calculated (step S4). The analysis unit 153 performs reliability analysis using functions such as a cumulative hazard function H (t), a reliability function R (t), an unreliability function F (t), and a failure probability density function f (t), for example. Information is generated (step S5).

Here, the cumulative hazard function H (t) is

Is defined. In Expression (1), Ni represents the number of target parts shipped calculated by the calculation unit 152. Also, σi indicates whether or not a failure has occurred in each of the target parts. For example, when no failure has occurred in the target part, σi indicates 0. On the other hand, when a failure occurs in the target part, σi indicates 1.

The reliability function R (t) is

Is defined. The unreliability function F (t) is

Is defined.

From the above formula (2) and formula (3),

Is applied to Weibull Hazard paper, and by linear approximation,

as well as

Determine constants η and m based on This constant η is a scale parameter. The constant m is a shape parameter (Weibull coefficient).

  By introducing the Weibull function as described above, it is possible to target a wide range of lifetime data, and the failure pattern of the analyzed data can be known from the value of the shape parameter m, for example. For example, when the value of m is smaller than 1 (m <1), the target part is an initial failure type. Further, when the value of m is 1 (m = 1), it is a random failure type, and when the value of m is greater than 1 (m> 1), it is a wear failure type.

  The failure probability density function f (t) is calculated using, for example, the failure time and the unreliability function F (t). For example, the failure occurrence probability density f (t) is obtained by calculating the maximum value F (nT) Max (n is a positive integer) of F (t) at every failure occurrence time interval T, A value obtained by subtracting the maximum value of the section, that is, f (t) = F (nT) −F ((n−1) T). However, calculation is performed with F (0) = 0.

  The analysis unit 153 calculates a value using the function as described above, and stores reliability analysis information including the calculated value in the reliability analysis database 18.

  Further, for example, it is conceivable that the failure occurrence time may be affected by the use environment of the part, for example, the mounting position of the part, the acquisition time, or the replacement work time. Therefore, the analysis unit 153 acquires the risk management information stored in the risk management database 13 or the environment information stored in the use environment information database 14, and for example, the unreliability function F (t) of the target part or These weights are applied to the values calculated using the cumulative hazard function H (t).

  Hereinafter, the reliability analysis result by the analysis unit 153 will be described with reference to FIGS.

  FIG. 5 shows an example of the data structure of reliability analysis information stored in the reliability analysis database 18. As shown in FIG. 5, the reliability analysis information includes, for example, time, Ln (t), σi, hazard values h (t), H (t), F (t), and LnH (t) for each target part. Etc. are included. Although not shown, the reliability analysis information includes a customer name (customer identification information) for identifying a customer to whom the target part has been shipped, a part identification information for identifying the target part, and a failure occurrence probability density function. f (t) (value calculated using) and the like are also included.

  For example, when the associated σi is 0 (that is, no failure has occurred), the time indicates the normal operation time of the target component. On the other hand, for example, when σi is 1 (that is, a failure has occurred), the failure (occurrence) time of the target component is indicated. Ln (t) is a natural logarithm of time associated with the Ln (t).

  H (t) represents a value (a value of the cumulative hazard function H (t)) calculated using the cumulative hazard function H (t). F (t) represents a value (value of the unreliability function F (t)) calculated using the unreliability function F (t). LnH (t) is the natural logarithm of H (t) described above.

  FIG. 6 shows an example of a graph 200 in which the value of the unreliability function F (t) of the target part included in the reliability analysis information stored in the reliability analysis database 18 is shown.

  The graph 200 shown in FIG. 6 shows the value (unreliability F (t)) of the unreliability function F (t) corresponding to the operation time of the target part for each product (elevator model), for example. . A curve 201 indicates, for example, an unreliability F (t) of a target part that constitutes a certain elevator (first elevator). Moreover, the curve 202 shows the unreliability F (t) of the target component which comprises the elevator (2nd elevator) different from a 1st elevator, for example. When the unreliability F (t) shown on the vertical axis of the graph 200 is 1, it indicates a complete failure of the target part.

  From the graph 200 described above, for example, by confirming the transition of the number of failures of the target component for each operating time, the operating time (replacement time) that becomes the lifetime of the target component that statistically constitutes the first or second elevator, etc. Can be calculated.

  FIG. 7 shows an example of a graph 300 in which the value of the failure probability density function f (t) of the target part included in the reliability analysis information stored in the reliability analysis database 18 is shown.

  In the graph 300 shown in FIG. 7, the value of the failure occurrence probability density function f (t) corresponding to the operation time of the target part for each product (elevator model) is provided, for example, as in the graph 200 shown in FIG. It is shown. A line 301 indicates, for example, the value of the failure occurrence probability density function f (t) of the target part constituting the first elevator. A line 302 indicates, for example, the value of the failure occurrence probability density function f (t) of the target part constituting the second elevator.

  In the example shown in FIG. 7, an average failure interval (MTBF: Mean Time Between Failure) that is an average value until the target component fails is 140400 (hours).

  From the graph 300 described above, for example, by confirming the average failure time of the target parts constituting the first or second elevator, it is possible to calculate the replacement time of the target parts.

  FIG. 8 shows an example of a graph 400 in which the value of LnH (t) that is the natural logarithm of the cumulative hazard function H (t) of the target part included in the reliability analysis information stored in the reliability analysis database 18 is shown. .

  A graph 400 illustrated in FIG. 8 shows a plot result of a value of LnH (t) according to, for example, the operation time of the target component (its natural logarithm Ln (t)). The graph 400 shows the linearity of the plot result. Thereby, the above-described shape parameter m can be calculated.

  In the example illustrated in FIG. 8, the value of m is 1.6327 from the linear slope of the plot result of the value of LnH (t) represented in the graph 400. In this case, since m> 1, it can be confirmed that the target part is a wear-out failure type.

  Although omitted in FIG. 8, similarly to the graphs 200 and 300 described above, the graph 400 shows the value of LnH (t) for each product.

  FIG. 9 shows an example of a graph 500 when risk management is performed on the value of the unreliability function F (t) of the target part included in the reliability analysis information stored in the reliability analysis database 18.

  As illustrated in FIG. 9, a graph 500 is obtained by adding a risk curve 501 to the above-described graph 200. This risk curve 501 shows, for example, a product obtained by multiplying the base cost for the target part or the unit price of maintenance personnel, and shows the cost for replacement of the target part corresponding to each operating time.

  As described above, for example, by adding the risk curve 501 to the above-described graph 200, it is possible to calculate a more optimal replacement time for the target part and to optimize the replacement time compared to the graph 200. It becomes possible.

  Returning to FIG. 4 again, the analysis unit 153 calculates the replacement time of the target part based on the reliability analysis result (analysis result) as described above (step S6).

  The analysis unit 153 stores, for example, the temperature, humidity, the number of activations, or the calculated replacement time (replacement optimal time) included in the environment information in the reliability analysis database 18 as reliability analysis information and uses it as limit data. That is, based on this limit data (reliability analysis information), the replacement time of the target part or the like is determined. The shape parameter m described above is also stored in the reliability analysis database 18.

  Further, the analysis unit 153 analyzes a factor (failure factor) affecting the failure of the target component by using, for example, the MT method or analysis software (step S7). At this time, the analysis unit 153 executes failure factor analysis processing based on the maintenance extraction information of the target part stored in the extraction result database 117 and the environment information of the target part stored in the environment information database 14. . Thereby, for example, a factor having a strong influence as a failure factor of the target part is identified. In the failure factor analysis, either the MT method or analysis software may be used.

  In the failure factor analysis process, the analysis unit 153 creates reference data that serves as a reference for no failure based on, for example, shipment extraction information, maintenance extraction information, and environmental information of a target part that is operating normally (operating). To do. This reference data is a reference space in the MT method described above. The analysis unit 153 determines (detects) a defect in the target part by comparing the created reference data with the shipment extraction information, maintenance extraction information, and environment information of the target part. The analysis unit 153 stores the determination result in the reliability analysis database 18 as reliability analysis information.

  Here, FIG. 10 shows an example of the result analyzed using, for example, the MT method. FIG. 10 shows the reference data created by the analysis unit 153 and, for example, target parts (shipment extraction information, maintenance extraction information, and environment information).

  In the example shown in FIG. 10, target parts A to D are shown as target parts. These target parts A to D are, for example, the same parts constituting different products (elevators), and are currently operating parts.

  The center of FIG. 10 shows the reference data (reference space) created by the analysis unit 153. That is, in FIG. 10, each defect of the target component A to the target component D is determined based on the distance between the position of the target component A to the target component D and the center (reference data).

  Specifically, in FIG. 10, for example, the position of the target component A is far from the reference data, that is, the target component A (the shipment extraction information, the maintenance extraction information, and the environment information) is a reference that does not cause a failure. Therefore, it can be determined that a defect has occurred in the target part A. On the other hand, since the position of the information of the target component C is close to the reference data, it can be determined that no malfunction has occurred in the target component C (it is operating normally).

  Thereby, for example, the failure factor can be recognized (analyzed) by recognizing an environment (usage environment) in which the target part in which the defect occurs is used.

  FIG. 11 shows an example of a result analyzed using, for example, analysis software. FIG. 11 shows a graph 601 and a graph 602, for example. The graph 601 shows, for example, the distribution of the operating time (years) of the target part for each elevator model that the target part constitutes. In addition, the graph 602 shows the distribution of the operation time of the target part for each shipping year of the target part.

  Thereby, for example, the failure factor can be recognized (analyzed) by recognizing an environment or the like in which a target part having a short operating period is used.

  Moreover, FIG. 12 is a figure which shows the influence which it has on the operation time (number of years) of the object components for every factor based on the analysis result shown in FIG. 11 mentioned above, for example. In addition, this FIG. 12 is displayed with respect to a maintenance worker etc., for example.

  In FIG. 12, for example, when the operation time of the target part for each product is 2000 hours, the value of each factor affecting the operation time of the target part, and the operation time and satisfaction corresponding to the value are shown. Has been. Here, factors affecting the operation time of the target part include the period until the inspection date, the average number of activations (month), the cumulative number of activations, the travel distance (monthly average), and the stop floor.

  In the example shown in FIG. 12, for example, the period until the inspection date is “1947”, the average number of activations (month) is “38627”, the cumulative number of activations is “2064358”, and the travel distance (monthly average) is “277.3311”. When the stop floor is “2.503704”, it indicates that the operation time of the target part is 2000 hours set. At these values, the satisfaction is 1.00. The operating time of the target part can be changed. For example, when the operating time of the target part is set to 3000 hours, the value of each factor corresponding to the operating time is indicated.

  Also, as shown in FIG. 12, the degree of change in satisfaction (and operating time) when the value is changed for each factor is different. For example, the average number of activations (month) and distance traveled (monthly average), for example, when the average number of activations (monthly) is decreased, the degree of satisfaction decreases greatly, but the distance traveled (monthly average) The degree of decrease in satisfaction when the value of) is decreased is moderate.

  That is, it can be said that the factor that the change of the satisfaction level (and the operation time) when the value of the factor is changed has a great influence on the operation time of the target part. On the contrary, it can be said that the factor that the change in the satisfaction level (and the operation time) when the factor value is changed has a small influence on the operation time of the target part.

  As a result, it is possible to identify factors that have a strong influence as failure factors, and it is possible to extract an optimum usage method including environmental improvement for each factor (item). The extracted usage method is stored in the reliability analysis database 18 as reliability analysis information, for example.

  Returning to FIG. 4 again, the management unit 154 configures, for example, an elevator that is collected from time to time based on the reliability analysis information (reliability analysis result) stored in the reliability analysis database 18 as described above. Compare with data (field data) indicating the operating status of the target component. Thus, for example, when the target part reaches the end of its life (limit), the management unit 154 notifies that it is time to replace the target part (need maintenance) (step S6). In this case, the time for replacement of the target part is displayed on a display device such as a monitor via the input / output unit 16 to notify the maintenance staff or the like.

  FIG. 13 shows an example of a display screen 700 displayed when notifying that it is time to replace the target part.

  On the display screen 700 shown in FIG. 13, for example, a nation-wide map is displayed so that customers who can ship the target parts (the elevator in which the target parts are used) are generally understood. For example, when it is time to replace the target part, the shipping destination of the target part is displayed on the display screen 700 in red or the like. At this time, although not shown, the number of target parts that need to be replaced or how much the target parts have a replacement risk is displayed.

  In addition, the maintenance staff or the like can confirm the details of the elevator in which the target part is used by designating the shipping destination (mark) displayed in red or the like. At this time, the maintenance staff can check the reliability analysis results as shown in FIGS. 6 to 9 as appropriate, for example. It is also possible to change. Similarly, the maintenance staff can manually set limit values such as operating time.

  For example, the configuration may be such that the shape parameter m can be confirmed and design feedback can be performed depending on the situation.

  Next, with reference to FIG. 14, the process of the management unit 154 when, for example, video information of a target part is collected by the above-described sensor or monitoring camera will be described.

  The video information collected by the sensor or the monitoring camera indicates, for example, the heat distribution of a circuit or a part (target part) constituting the elevator. This video information includes, for example, a sensor output image collected by a sensor or a surveillance camera output image collected by a surveillance camera.

  The video information indicating the heat distribution of the target component is collected by a sensor or a monitoring camera (hereinafter simply referred to as a monitoring camera or the like), for example, every predetermined period (periodically).

  As shown in FIG. 14, the video information 800 collected by the monitoring camera or the like includes video information 801 in an initial state and video information 802 in a time lapse state. The video information 801 in the initial state indicates, for example, the heat distribution of the target component 901 and the target component 902 immediately after replacement (initial state). On the other hand, the video information 802 in the time lapse state indicates, for example, the heat distribution of the target component 901 and the target component 902 after a predetermined period has elapsed since the replacement (time lapse state).

  The management unit 154 includes a data comparison unit 154a and a determination unit 154b. The data comparison unit 154a compares the video information 801 in the initial state and the video information 802 in the elapsed time state. The determination unit 154b determines abnormality of the target component 901 and the target component 902 based on the comparison result by the data comparison unit 154a, that is, the change in the heat distribution in the target component. As a result, the management unit 154 can always monitor and confirm whether an abnormality (abnormal situation) has occurred in the target component based on the video information collected by the monitoring camera or the like.

  As described above, in this embodiment, by using the MT method or analysis software, the target component maintenance extraction information stored in the extraction result database 117 and the environment of the target component stored in the environment information database 14 are used. Based on the information, a failure factor analysis process for the target part is executed. In other words, for example, by identifying (extracting) factors that have a strong influence as a failure factor of the target part in the target part that constitutes the elevator, it is possible to extract an optimal usage method including environmental improvement of the target part. It becomes. As a result, the target parts constituting the elevator can be used in an optimum environment, so that, for example, the life (limit) of the target parts can be prolonged. Therefore, it is possible to reduce the cost due to replacement of the target part.

  Further, in the present embodiment, it is determined whether or not an abnormality has occurred in the target component by comparing video information indicating the heat distribution of the target component collected periodically. Thereby, in this embodiment, it becomes possible to always monitor and confirm whether an abnormality has occurred in the target part.

  In the present embodiment, for example, functions such as a reliability function R (t), an unreliability function F (t), a failure probability density function f (t), and a cumulative hazard function H (t) are used. By generating the reliability analysis information, an accurate replacement time can be obtained from the reliability analysis results as shown in FIGS. Therefore, in the present embodiment, it is possible to clarify the replacement time depending on the lifetime of the parts constituting the elevator, and to prevent a situation in which, for example, the target part is replaced in an unreasonably short period.

  Further, in the present embodiment, for example, by performing risk management, it becomes possible to grasp the replacement time with higher accuracy, and at the same time, it automatically analyzes and monitors that the target part is approaching the replacement time. By displaying on the screen, it is possible for the maintenance staff to grasp the status of each elevator (the target part constituting the elevator) without trouble. As a result, the burden on maintenance personnel can be reduced.

  Also, in this embodiment, by grasping that the time for replacement has approached in advance, parts can be prepared in advance, and the parts can be replaced before failure occurs. It is possible to minimize the occurrence of a serious failure such as an elevator constituted by

  Further, in the present embodiment, when the target component is approaching the replacement time is displayed on a monitor or the like, detailed information is grasped by designating (for example, clicking) the displayed shipping destination (mark). Is possible. For this reason, the maintenance staff can determine which part of the elevator in operation is approaching the replacement time and determine whether to replace the part.

  In addition, since the reliability analysis result (analysis result) can be confirmed by maintenance personnel or the like, the failure mode (shape parameter m) of the part here can be recognized, and an initial failure has occurred. It is possible to implement design feedback for those that are wear-out or wear-out but have a fast failure occurrence time, and lead to improvement at an earlier stage. Similarly, it is possible to confirm the failure occurrence probability density function f (t) and the cumulative hazard function H (t) and to improve the function.

  In addition, if the result of the analysis is confirmed and there is no consistency with the field situation, it becomes possible to confirm and correct the environmental information and risk information, and to plan a more accurate replacement time.

  Moreover, it is possible to construct a replacement plan with higher accuracy by collecting data due to the lifetime, such as temperature, humidity, and the number of activations, for each product (each).

  In the present embodiment, the explanation has been made on the assumption that the total number of shipments of the target parts is calculated as a parameter. For example, by setting the number of shipments of the target parts shipped to a specific area as a parameter, for example, It is also possible to calculate the replacement time of the target part by region.

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. Moreover, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment.

The block diagram which shows the structure of the components improvement plan system of the elevator which concerns on embodiment of this invention. The figure which shows an example of the data structure of the shipping extraction information stored in the extraction result database. The figure which shows an example of the data structure of the maintenance extraction information stored in the extraction result database. The flowchart which shows the process sequence of the components improvement plan system 10 of an elevator. The figure which shows an example of the data structure of the reliability analysis information stored in the reliability analysis database 18. FIG. The figure which shows an example of the graph 200 by which the value of the unreliability function F (t) of the target component contained in the reliability analysis information stored in the reliability analysis database 18 is shown. The figure which shows an example of the graph 300 in which the value of the failure occurrence probability density function f (t) of the target component contained in the reliability analysis information stored in the reliability analysis database 18 is shown. The figure which shows an example of the graph 400 in which the value of LnH (t) which is the natural logarithm of the accumulation hazard function H (t) of the object component contained in the reliability analysis information stored in the reliability analysis database 18 is shown. The figure which shows an example of the graph 500 at the time of implementing risk management with respect to the value of the unreliability function F (t) of the target component contained in the reliability analysis information stored in the reliability analysis database 18. The figure which shows an example of the result analyzed using MT method. The figure which shows an example of the result analyzed using analysis software. The figure which shows the influence which it has on the operation time of the object components for every factor based on the analysis result shown in FIG. The figure which shows an example of the display screen 700 displayed when notifying that replacement | exchange time of an object part has come. The figure for demonstrating the process of the management part 154 when the video information of target equipment is collected by the sensor or the monitoring camera.

Explanation of symbols

    DESCRIPTION OF SYMBOLS 10 ... Elevator life parts automatic replacement planning system, 11 ... Shipping information database, 12 ... Maintenance information database, 13 ... Risk management database, 14 ... Usage environment information database, 15 ... Computer, 16 ... Input / output unit, 17 ... Extraction result Database 18, reliability analysis database 151, information extraction unit 152, calculation unit, 153 analysis unit, 154 management unit, 154 a data comparison unit, 154 b determination unit

Claims (8)

Shipping information storage means for storing shipping information including parts identification information for identifying parts constituting the elevator and customer identification information for identifying a shipping destination to which the parts are shipped;
Maintenance information including failure occurrence information indicating that a failure has occurred in a component identified by the component identification information is stored in association with the component identification information included in the shipment information stored in the shipment information storage means. Maintenance information storage means;
A usage environment information storage unit that stores usage environment information indicating a usage state of a component identified by the component identification information in association with the component identification information included in the shipping information stored in the shipping information storage unit;
The maintenance information storage means associated with the part identification information for identifying the target part designated by the user and included in the shipment information including the customer identification information for identifying the same shipping destination Extracting means for extracting the use environment information stored in the use environment information storage means in association with the maintenance information stored in
Analyzing means for analyzing a failure factor of the target part based on failure occurrence information included in the extracted maintenance information and the extracted use environment information;
An elevator parts improvement planning system comprising: output means for outputting an analysis result by the analysis means. Based on the failure occurrence information included in the maintenance information stored in the maintenance information storage means, it is stored in the maintenance information storage means in association with the part identification information for identifying the target part in which no failure has occurred. Acquisition means for acquiring the use environment information stored in the use environment information storage means in association with the maintenance information and the parts identification information,
Based on the acquired maintenance information and use environment information, a creation means for creating reference data serving as a reference that does not cause a failure;
The created reference data and the maintenance information stored in the maintenance information storage means in association with the part identification information for identifying the target part in which the failure has not occurred are associated with the part identification information. Detection means for detecting a defect of the target part by comparing with the use environment information stored in the use environment information storage means,
The elevator part improvement planning system according to claim 1, wherein the output means outputs defect information indicating the detected defect. Measuring means for measuring the heat distribution of the target part;
The elevator parts improvement planning system according to claim 1, further comprising monitoring means for monitoring an abnormality of the target part based on the measured heat distribution. A shipment quantity calculation means for calculating the shipment quantity of the target part;
Based on the failure occurrence information included in the maintenance information stored in the maintenance information storage means in association with the component identification information for identifying the target component, of the target components, A failure number calculation means for calculating the number of failures;
Generation means for generating reliability analysis information representing the reliability of the target part based on the number of shipments of the target part calculated by the shipment number calculation means and the number of failure of the target part calculated by the failure number calculation means When,
The elevator part improvement planning system according to claim 1, further comprising: a replacement time calculating unit that calculates a replacement time of the target part based on the generated reliability analysis information. Further comprising risk management storage means for storing risk management information indicating a replacement work time or a lead time of the parts required for work when replacing the parts constituting the elevator,
5. The elevator part according to claim 4, wherein the replacement time calculation unit calculates a replacement time based on risk management information stored in the risk management storage unit together with the generated reliability analysis information. Improvement planning system.   5. The elevator according to claim 4, wherein the replacement time calculation means calculates the replacement time based on the use environment information stored in the use environment information storage means together with the generated reliability analysis information. Parts improvement planning system. A collecting means for collecting field data indicating an operation status of a target part constituting the elevator;
5. The notification device according to claim 4, further comprising: notification means for notifying that a replacement time of a target part constituting the elevator has come based on the collected field data and the calculated replacement time. Elevator parts improvement planning system. Shipping information storage means for storing shipping information including part identification information for identifying parts constituting the elevator and customer identification information for identifying a shipping destination to which the parts are shipped, and stored in the shipping information storage means Maintenance information storage means for storing maintenance information including failure occurrence information indicating that a failure has occurred in a component identified by the component identification information, in association with the component identification information included in the shipped information, Use environment information storage means for storing use environment information indicating the use state of the part identified by the part identification information in association with the part identification information included in the shipment information stored in the shipment information storage means. An elevator parts improvement planning method applied to an elevator parts improvement planning system,
The maintenance information storage means associated with the component identification information for identifying the target component designated by the user and included in the shipment information including the customer identification information for identifying the same shipping destination Extracting the use environment information stored in the use environment information storage means in association with the maintenance information and the part identification information stored in
Analyzing a failure factor of the target part based on failure occurrence information included in the extracted maintenance information and the acquired use environment information;
And a step of outputting an analysis result obtained by the analyzing means.

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