JP2015185120A - Information processing equipment, information processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To support detection of a potential factor of failure in a product group.SOLUTION: Information processing equipment comprises: a calculation part for calculating occurrence frequency of failure in a product group to be processed, based on failure information related to failure of a product, and product group identification information for identifying the product group to which the product belongs; and an output control part for outputting the occurrence frequency calculated by the calculation part. For example, the information processing equipment further comprises a determination part which determines that there is a potential factor of occurrence of failure in the product group to be processed, when the occurrence frequency calculated by the calculation part is larger relative to a predetermined threshold which is determined according to an expectation value of the failure occurrence frequency which is statistically calculated. The output control part outputs a determination result determined by the determination part.

Description

  The present invention relates to an information processing apparatus, an information processing method, and a program.

Conventionally, by collecting and analyzing information such as alarms and measurement data based on the events detected by the sensors from the sensors that detect the status of the equipment installed in the equipment, failure or abnormality of the monitored equipment can be detected. It is done to detect.
In addition, a system for presenting countermeasures corresponding to such failures and abnormalities has been proposed (see, for example, Patent Document 1).

JP 2013-92954 A

  However, according to Patent Document 1, it is only possible to present a countermeasure, and it does not specify a factor such as a failure in the product group. On the other hand, the cause of a product group failure may be manually analyzed. When analyzing manually, the existence of potential factors that cause defects in the product group is overlooked due to the lack of technology and experience of the person performing the analysis and the absence of an environment where information on the collected failures can be used. In some cases, it took some time to discover it.

  The present invention has been made in view of such circumstances, and provides an information processing apparatus, an information processing method, and a program for supporting discovery of a potential factor that causes a defect in a product group. .

  The present invention has been made to solve the above problems, and one aspect of the present invention is based on defect information related to product defects and product group identification information for identifying a product group to which the product belongs. An information processing apparatus comprising: a calculation unit that calculates an occurrence frequency of a defect in a target product group; and an output control unit that outputs an occurrence frequency calculated by the calculation unit.

  Further, according to one embodiment of the present invention, the information processing apparatus has a case where the occurrence frequency calculated by the calculation unit is larger than a threshold value determined according to an expected value of the occurrence frequency of defects calculated statistically. A determination unit that determines that there is a potential factor that causes a defect in the product group to be processed, and the output control unit outputs a determination result by the determination unit.

  Further, according to one aspect of the present invention, in the information processing apparatus, the product group identification information is attribute information indicating an attribute of the product, and the output control unit determines the occurrence frequency calculated by the calculation unit. It is characterized by being output in association with the attribute indicated by the attribute information.

  According to another aspect of the present invention, in the information processing apparatus, the product group identification information is time information indicating time, and the output control unit uses the occurrence frequency calculated by the calculation unit as the time information. It is characterized by being output in association with the based time.

  Further, according to one aspect of the present invention, in the information processing apparatus, the product group identification information is state information indicating a defect state of the product, and the output control unit is an occurrence frequency calculated by the calculation unit. Is output in association with the state of the failure indicated by the state information.

  One embodiment of the present invention is an information processing method in an information processing device, wherein the calculation unit performs processing based on defect information related to product defects and product group identification information that identifies a product group to which the product belongs. An information processing method comprising: a calculation process for calculating an occurrence frequency of a defect in a target product group; and an output control process for outputting an occurrence frequency calculated by the calculation unit by the output control unit.

  In one embodiment of the present invention, the occurrence frequency of a defect in a product group to be processed is calculated based on defect information related to a defect in the product and product group identification information for identifying the product group to which the product belongs. It is a program for executing a calculation procedure and an output control procedure for outputting an occurrence frequency calculated in the calculation procedure.

  ADVANTAGE OF THE INVENTION According to this invention, discovery of the potential factor which produces a malfunction in a product group can be supported.

It is a block diagram which shows an example of schematic function structure of the information processing apparatus which concerns on one Embodiment of this invention. It is a table | surface which shows an example of the product information which concerns on one Embodiment of this invention. It is a table | surface which shows an example of the failure history information which concerns on one Embodiment of this invention. It is a flowchart which shows an example of the flow of a process by the information processing apparatus which concerns on one Embodiment of this invention. It is a flowchart which shows an example of the flow of the setting process of the threshold value by the information processing apparatus which concerns on one Embodiment of this invention. It is a figure which shows an example of the display mode of the occurrence frequency of the malfunction for every time based on the time information by the information processing apparatus which concerns on one Embodiment of this invention. It is a figure which shows an example of the display mode of the occurrence frequency of the malfunction for every attribute of the product which the attribute information by the information processing apparatus which concerns on one Embodiment of this invention shows. It is a figure which shows an example of the display mode of the occurrence frequency of the malfunction for every cause which the cause information by the information processing apparatus which concerns on one Embodiment of this invention shows.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[Configuration of information processing device]
An information processing apparatus according to an embodiment of the present invention is based on information related to a failure such as a failure or an operation abnormality of an industrial product, and a potential factor (potential for causing a failure for a product group to which the industrial product belongs. This is a device for determining the presence of a faulty factor) or supporting the determination. In the following, the target of the process in which the information processing apparatus determines the presence of a potential failure factor or the process of supporting the determination is referred to as a process target. Further, in the present embodiment, the potential failure factor refers to a factor that causes a failure at a higher frequency than the expected failure occurrence frequency. Therefore, a product group having a potential failure factor refers to a product group in which a failure occurs at a higher frequency than the expected failure occurrence frequency.

  The information processing apparatus 1 is a computer apparatus such as a server, a personal computer, a mobile phone, a tablet, a smartphone, a PHS (Personal Handy-phone System) apparatus, or a PDA (Personal Digital Assistant) apparatus, and a CPU (Central Processing Unit). ) And storage devices. The product belonging to the product group for which the information processing apparatus determines a defect and supports the determination is, for example, an apparatus configured by components such as a plurality of parts, members, and units. Below, as an example, the said apparatus demonstrates as an apparatus which comprises the power supply and air-conditioning installation installed in a building.

FIG. 1 is a block diagram illustrating an example of a schematic functional configuration of an information processing apparatus 1 according to an embodiment of the present invention.
The information processing apparatus 1 includes a storage unit 11, an input unit 12, a display unit 13, and a control unit 14.
The storage unit 11 includes, for example, an HDD (Hard Disc Drive), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a ROM (Read Only Memory), or a RAM (Random Access Firmware, etc.). The storage unit 11 stores various programs to be executed by the CPU, the results of processing executed by the CPU, and the like. Part or all of the control unit 14 functions, for example, when the CPU included in the information processing apparatus 1 executes a program stored in the storage unit 11.

  The storage unit 11 includes a threshold storage unit 111, a product information storage unit 112 that stores product information, and a failure history information storage unit 113 that stores failure history information. Product information and failure history information to be described later are part of defect information related to product defects. The product information and the failure history information include a product ID that is identification information for identifying a product, as will be described later. The product ID is common to product information and failure history information. Therefore, the information included in the product information and the information included in the failure history information can be referred to in association with each other based on the product ID.

  The threshold value storage unit 111 stores threshold value information indicating a first threshold value and a second threshold value used in a determination process for determining the presence of a potential defect factor in a product group described later. The first threshold value is a threshold value set based on theoretical values such as specifications and designs of products belonging to the product group, and is set based on, for example, an average failure interval (MTBF, Mean Time Between Failure (s)). Threshold. The second threshold value is a threshold value set based on a different standard from the first threshold value. For example, the second threshold value is a threshold value set by the user of the information processing apparatus 1 based on a rule of thumb. The first threshold value and the second threshold value are larger than the base value of the occurrence frequency of defects, and are determined in a range in which an unexpected increase in the occurrence frequency of defects can be detected.

FIG. 2 is a table showing an example of product information.
The product information is information on products that constitute a product group to be processed by the information processing apparatus 1. For example, when the product is installed, moved, or removed, information corresponding to the product is added and stored. The table shown in this figure shows product information of a plurality of products, and each row of the table shows product information of each of the plurality of products. The product information includes values of product ID, product name, product classification, product classification type, manufacturer name, date of manufacture, date of installation, date of removal, building name, and floor information. The product ID indicates identification information for uniquely identifying the product. The product name indicates the name of the product. The product category indicates the name of the product category to which the product belongs. The product classification type indicates the type of product classification to which the product belongs. The manufacturer name indicates the name of the manufacturer that manufactured the product. The manufacturer name is an example of information for specifying the manufacturer that manufactured the product.

  The date of manufacture indicates the date on which the product was manufactured. The installation date indicates the date on which the product was installed. The installation date is an example of information for specifying when the product starts operation. The removal date indicates the date when the product was moved or removed from the place where the product was installed. The building name indicates the name of the building where the product is installed. The floor indicates the floor of the building where the product is installed. The building name and floor are an example of information for specifying the installation location of the product. Among these, the product name, product classification, product classification type, manufacturer name, building name, and floor information are examples of attribute information indicating product attributes. The date of manufacture, date of installation, and date of removal are examples of time information indicating time.

  In the table shown in FIG. 2, the product information registered in the top row has a product ID value “A001”. The value of the product name is “AX-rectifier”. The product classification value is “distributed power supply device”. Further, the value of the product classification type is “A rectifier”. The value of the manufacturer name is “Manufacturer A”. The value of the date of manufacture is “2008/04/04”. Also, the installation date is “2008/06/12”. The value of the removal date is “2009/10/11”. The value of the building name is “A building”. The floor value is “B2F”.

  That is, in the table shown in FIG. 2, the product information registered at the top is that the product name with the product ID value “A001” is “AX-rectifier”, and the product classification type is It is included in the product classification “distributed power supply device” which is “A rectifier device”. Further, the product information indicates that a product having a product ID value “A001” is manufactured to “2008/04/04” by “maker A”. In addition, the product information has a product ID value “A001” installed on the “B2F” floor of a building named “A building” on “2008/06/12” and “2009/10/11” Indicates that it has been relocated or removed from its installation location.

FIG. 3 is a table showing an example of failure history information.
The failure history information indicates information related to the failure of the product in which the failure is detected. In the present embodiment, since the failure history information is added and stored when a failure occurs, the number of failure history information indicates the number of failures. The table shown in this figure shows failure history information related to a plurality of failures, and each row of the table shows failure history information of each of the plurality of failures. The failure history information includes each value of information of failure ID, device ID, alarm, failure status, cause, recovery method, response method, and failure occurrence date and time. The failure ID indicates identification information for uniquely identifying a defect. The product ID indicates identification information for uniquely identifying the product.

  The alarm indicates the content of an alarm issued when a product or a monitoring device that monitors the product detects a malfunction. The product ID in the failure history information indicates identification information of a product in which a failure is detected. The failure status indicates the status of the failure determined by the responder for the product in which the failure is detected. The cause indicates the cause of the failure. The recovery method indicates the recovery action taken to correct the failure. An alarm, a failure status, a cause, and a recovery method are examples of information for specifying the content of a failure. The response method indicates the response content of the person corresponding to the defect. The corresponding person indicates identification information for identifying the corresponding person corresponding to the defect, for example, the name of the corresponding person. The failure occurrence date and time indicates the date and time when the malfunction was detected by the product or the product monitoring device. The failure occurrence date and time is information for specifying the time when the failure occurred. Of these, the alarm, failure status, cause, recovery method, and response method information are examples of status information indicating the status of the malfunction. The failure occurrence date and time is an example of time information indicating time. The attribute information, time information, and status information are examples of product group identification information that identifies a product group.

  In the table shown in FIG. 3, the failure history information registered in the top row has a failure ID value of “1”. The value of the product ID is “A011”. The alarm value is “rectifier unit failure”. Also, the value of the failure status is “unit abnormality”. The cause value is “product defect”. The value of the recovery method is “replacement”. Also, the value of the response method is “immediate response”. In addition, the value of the responder is “a”. Further, the value of the failure occurrence date and time is “2003/1/1 5:03”.

  That is, in the table shown in FIG. 3, the failure history information registered at the top is information relating to a failure identified with a failure ID value of “1”, and a product ID value of “A011”. Indicates failure history information related to product defects. In addition, the failure history information indicates that a product whose product ID value is “A011” is issued an alarm to notify “2003/1/1 5:03” of “rectifier unit failure”, This indicates that it is determined that “unit abnormality” due to “bad” has occurred. In addition, in the failure history information, the responder “a” has performed “immediate response” of “replacement” of a unit, for example, for a malfunction of a product whose product ID value is “A011”. Indicates.

Returning to FIG. 1, the description will be continued.
The input unit 12 includes an input device such as a mouse, a keyboard, or a touch panel, for example, and receives input from a user. The content of the operation received by the input unit 12 is displayed as, for example, a GUI (Graphical User Interface) on the display device included in the display unit 13. The input unit 12 receives a registration request for information indicating the second threshold, product information, or failure history information, and outputs the registration request to the control unit 14. Further, the input unit 12 accepts input of product group information indicating a product group to be processed and outputs it to the control unit 14.
The display unit 13 includes a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display.

The control unit 14 includes a registration unit 141, a calculation unit 142, a determination unit 143, and an output control unit 144.
The registration unit 141 registers various information in the storage unit 11 based on the registration request received by the input unit 12. For example, the registration unit 141 stores information indicating the second threshold in the threshold storage unit 111. Also, the registration unit 141 stores product information in the product information storage unit 112, for example. Further, the registration unit 141 stores, for example, failure history information in the failure history information storage unit 113.

  The calculation unit 142 calculates the occurrence frequency of defects in the product group based on the defect information stored in the storage unit 11. When the input unit 12 receives input of product group information, the calculation unit 142 refers to the product information stored in the product information storage unit 112 and the failure history information stored in the failure history information storage unit 113, and the product group information indicates Product information including a product ID for identifying a product belonging to the product group and failure history information are acquired. The calculation unit 142 acquires the number of occurrences of defects by counting the acquired failure history information. For example, the calculation unit 142 classifies the failure history information based on the values of each item of the product information and the failure history information, and obtains the number of occurrences of defects in the product group. For example, the calculation unit 142 calculates a failure rate in the product group based on the acquired number of occurrences of defects. The number of occurrences of failures and the failure rate calculated by the calculation unit 142 are examples of occurrence frequencies of failures. The calculation unit 142 outputs frequency information indicating the calculated occurrence frequency of the defect to the determination unit 143 or the output control unit 144.

  The determination unit 143 determines the presence of a potential defect factor in the product group based on the frequency information acquired from the calculation unit 142 and the threshold information stored in the threshold storage unit 111. The determination unit 143 acquires threshold information from the threshold storage unit 111. For example, the determination unit 143 compares the occurrence frequency of the failure indicated by the frequency information with the first threshold value and the second threshold value indicated by the threshold information. For example, when the occurrence frequency of the defect is larger than the first threshold and the second threshold, the determination unit 143 determines that the product group is highly likely to have a potential defect factor. In addition, for example, the determination unit 143 may cause the product group to have a potential failure factor when the occurrence frequency of the failure is large with respect to one of the first threshold value and the second threshold value but not with respect to the other. Judge that there is. For example, when the occurrence frequency of the defect is smaller than the first threshold value and the second threshold value, the determination unit 143 determines that the possibility that the product group has a potential defect factor is low. The determination unit 143 outputs a determination result regarding the presence of a potential failure factor in the product group to the output control unit 144.

  The output control unit 144 generates image data based on the processing result by the calculation unit 142, the processing result by the determination unit 143, and information stored in the storage unit 11, and outputs the generated image to the display unit 13 for display. . For example, the output control unit 144 causes the display unit 13 to display the defect occurrence frequency indicated by the frequency information acquired from the calculation unit 142 in association with the information indicating the product group. For example, the output control unit 144 causes the display unit 13 to display a determination result regarding the presence of a defect in the product group acquired from the determination unit 143 in association with information indicating the product group. In addition, when the determination result by the determination unit 143 indicates that the product may have a defect, the output control unit 144 displays a warning display or the like on the display unit to alert the user.

FIG. 4 is a flowchart illustrating an example of the flow of processing by the information processing apparatus 1.
The flowchart shown in this figure shows an example of the flow of processing when the first threshold is smaller than the second threshold. When the first threshold is smaller than the second threshold, the determination conditions in steps S103 and S106 described later may be switched. The following processing is executed at predetermined time intervals, for example. First, the calculation unit 142 identifies a product group to be processed, and acquires failure history information and product information of products belonging to the product group to be processed (step S101). Next, the calculation unit 142 calculates the occurrence frequency of defects of products belonging to the product group based on the acquired failure history information and product information (step S102). Next, the determination unit 143 determines whether or not the occurrence frequency of the defect calculated by the calculation unit 142 is equal to or higher than a first threshold (Step S103). When the occurrence frequency of the defect is smaller than the first threshold (step S103; NO), the determination unit 143 determines that there is no defect because the product group to be processed is less likely to have a potential defect factor. (Step S104). Next, the output control unit 144 outputs, for example, the determination result by the determination unit 143 to the display unit 13 (step S105). And the control part 14 complete | finishes a process.

  Further, when the occurrence frequency of the defect is larger than the first threshold (step S103; YES), the determination unit 143 determines whether the occurrence frequency of the defect is equal to or higher than the second threshold (step S106). When the occurrence frequency of the defect is smaller than the second threshold value (step S106; NO), the determination unit 143 determines that the product group to be processed may have a potential defect factor and needs attention. (Step S107). Then, the output control unit 144 performs the process of step S105. If the defect detection frequency is greater than the second threshold (step S106; YES), the determination unit 143 is likely to have a potential defect factor for the product group to be processed. (Step S108). Then, the output control unit 144 performs the process of step S105.

FIG. 5 is a flowchart illustrating an example of a threshold setting process performed by the information processing apparatus 1.
First, the determination unit 143 acquires the occurrence frequency of the defect calculated by the calculation unit 142 (step S201). Next, the determination unit 143 performs a trend analysis on the acquired frequency of occurrence of defects (step S202). In the trend analysis, for example, the determination unit 143 applies a model based on past performance data and design data of similar product groups to the occurrence frequency of the failure calculated by the calculation unit 142, and the average value of the occurrence frequency of the failure Get statistical information such as expected value and variance value. Next, the determination unit 143 sets a threshold based on the acquired statistical information (step S203). For example, the determination unit 143 calculates a range in which 95% of the sample values of the above-described defect occurrence frequency are predicted to converge, and sets the upper limit value as the second threshold value.

FIG. 6 is a diagram illustrating an example of a display mode of the occurrence frequency of defects for each hour based on the time information by the information processing apparatus 1.
In the graph shown in this figure, the vertical axis indicates the occurrence frequency of defects, for example, the number of occurrences of defects or the failure rate. The horizontal axis indicates time, for example, failure occurrence date, operation date, or manufacture date. A polygonal line L11 indicates a change with time in the occurrence frequency of defects in the product group to be processed. A straight line L12 indicates the first threshold value. A straight line L13 indicates the second threshold value. Region A11 and region A12 indicate portions where the occurrence frequency of defects in the product group to be processed is equal to or higher than the first threshold and lower than the second threshold. A region A13 indicates a portion where the frequency of occurrence of defects in the product group to be processed is equal to or greater than the second threshold.

  In the example illustrated in FIG. 6, for example, a case where the horizontal axis indicates the failure occurrence date will be described. The failure date is, for example, the year and month values of the failure occurrence date and time included in the failure history information. The calculation unit 142 acquires failure history information having a product ID value of a product belonging to the product group to be processed. Then, the calculation unit 142 classifies the acquired failure history information based on the year and month values of the failure occurrence date and time. The calculation unit 142 calculates the occurrence frequency of defects every month based on the classified failure history information. The output control unit 144 generates a graph in which the occurrence frequency of the defect calculated by the calculation unit 142 is plotted for each month. As a result, the information processing apparatus 1 can indicate, for example, the relationship between the season and a potential failure factor, the relationship between an event occurring on a specific day, such as a lightning strike, and the occurrence of a failure. .

  In the example illustrated in FIG. 6, for example, a case where the operation date is plotted on the horizontal axis will be described. The operation date is, for example, the value of the year and month that have passed from the date indicated by the installation date included in the product information to the date and time of occurrence of the failure included in the failure history information. The calculation unit 142 acquires product information having a product ID value of a product belonging to the product group to be processed and failure history information. Here, the calculation unit 142 handles product information having the same product ID value and failure history information in association with each other. The calculation unit 142 has elapsed since the product was operated based on the difference between the installation date value and the failure date and time value in the associated product information and failure history information. Get the year and month. The calculation unit 142 classifies the failure history information based on the acquired operation date. The calculation unit 142 calculates the occurrence frequency of defects on a monthly basis based on the classified failure history information. The output control unit 144 generates a graph in which the calculated occurrence frequency of defects is plotted for each month. Thereby, the information processing apparatus 1 can show the relevance of the potential malfunction factor and the operation period of the product, for example.

  In the example shown in FIG. 6, for example, the case where the production date is plotted on the horizontal axis will be described. The production date is, for example, a year and month value included in the product information. The calculation unit 142 acquires product information having a product ID value of a product belonging to the product group to be processed and failure history information. Here, the calculation unit 142 handles product information having the same product ID value and failure history information in association with each other. The calculation unit 142 classifies the failure history information associated with the product information based on the date of manufacture date of the product information. The calculation unit 142 calculates the occurrence frequency of defects on a monthly basis based on the classified failure history information. The output control unit 144 generates a graph in which the calculated occurrence frequency is plotted for each month. Thereby, the information processing apparatus 1 can show the relevance of the potential malfunction factor and the product manufacturing environment, for example.

FIG. 7 is a diagram illustrating an example of a display mode of the occurrence frequency of defects for each product attribute indicated by the attribute information by the information processing apparatus 1.
FIG. 7A is a graph showing the frequency of occurrence of defects for products manufactured by three manufacturers, Company A, Company B, and Company C, by year of manufacture.
In the example shown in this figure, the vertical axis indicates the failure rate. The horizontal axis indicates the years of operation. A broken line L211 indicates a change with time of the failure rate of the product group manufactured in 2002. A polygonal line L212 indicates a change with time of the failure rate of the product group manufactured in 2003. A polygonal line L213 indicates a change over time in the failure rate of a product group manufactured in 2004.

  In the example shown in this figure, the product group is composed of products manufactured in the same year. More specifically, in the product information, products having the same year value on the date of manufacture constitute a product group to be processed. When the transition of failure rate is analyzed for the example shown in this figure, the failure rate of the products with a service period of 6 to 9 years shown in the area A21 is high, and in particular, a product group manufactured in 2002 is a potential. May have a failure factor. Moreover, the failure rate of the product group of the operation years 2 and 3 shown in area | region A22 is a little high. And since the failure rate of the product group manufactured especially in 2003 is high, the product group manufactured in 2003 may have a malfunction.

  FIG. 7B to FIG. 7D are graphs showing the graph shown in FIG. 7A for each product manufacturer. Accordingly, in the graphs shown in FIGS. 7B to 7D, the vertical axis indicates the failure rate, as in the graph shown in FIG. Similarly, in the graphs shown in FIGS. 7B to 7D, the horizontal axis represents the number of years of operation. In the example shown in FIG. 7B to FIG. 7D, the product group is composed of products manufactured by the same manufacturer in the same year. More specifically, in the product information, products having the same manufacturing year / month / year value and the same manufacturer name value form a product group to be processed.

  FIG. 7B is a graph showing the frequency of occurrence of defects for products manufactured by Company A by year of manufacture. FIG. 7 (c) is a graph showing the frequency of occurrence of defects for products manufactured by Company B by year of manufacture. FIG. 7 (d) is a graph showing the frequency of occurrence of defects for products manufactured by Company C by year of manufacture.

  In the examples shown in these drawings, the polygonal lines L221, L231, and L241 indicate changes over time in the failure rate of the product group manufactured in 2002, respectively. The broken lines L222, L232, and L242 indicate changes over time in the failure rate of the product group manufactured in 2003, respectively. Plot lines L223, L233, and L243 indicate changes over time in the failure rate of the product group manufactured in 2004, respectively.

  When analyzing the transition of failure rate for the examples shown in these figures, the failure rate of the product with the operating years of 6 to 9 years shown in the area A21 was manufactured by Company A shown in FIG. 7 (b). Remarkably high in the product graph. On the other hand, in the graph about the product manufactured by Company B shown in FIG. 7C and the graph about the product manufactured by Company C shown in FIG. No noticeable anomalies are observed in the product failure rate. And in the operation years from 6 to 9, the failure rate of the product of company A is high for all products manufactured in 2002, 2003, and 2004. Therefore, the user of the information processing apparatus 1 can easily infer that the product group manufactured by the company A has a potential failure factor that appears in about 6 to 9 years of operation.

  Similarly, when the transition of the failure rate is analyzed for the examples shown in these figures, the failure rate of the products with the operating years 2 and 3 shown in the area A22 is the company C shown in FIG. 7 (d). Is significantly higher in the graph for the product produced. On the other hand, in the graph about the product manufactured by Company A shown in FIG. 7B and the product about the product manufactured by Company B shown in FIG. No significant abnormality is observed in the failure rate. The failure rate of products manufactured by Company C in 2002 and 2003 is particularly high in the operation years 2 and 3. Therefore, the user of the information processing apparatus 1 can easily infer that the product group manufactured by the company C has a potential malfunction factor that appears in about two or three years of operation. In this manner, the information processing apparatus 1 calculates the occurrence frequency of defects by classifying and specifying the product group specified by the manufacturing year in more detail according to another attribute called the manufacturer that manufactures the product. As a result, the information processing apparatus 1 can provide the user with information about the details of potential failure factors in the product group, and can assist in finding potential factors that cause failures in the product group.

FIG. 8 is a diagram illustrating an example of a display mode of the occurrence frequency of defects for each cause indicated by the cause information by the information processing apparatus 1.
8A to 8C are graphs showing the frequency of occurrence of defects in products manufactured by the three companies, Company A, Company B, and Company C, for each cause of failure.
In the examples shown in these drawings, the vertical axis indicates the number of occurrences of defects. The horizontal axis shows the cause of the malfunction. Further, in the examples shown in these drawings, the product group is composed of products that have failed due to the same cause among products manufactured by the same manufacturer. More specifically, products having the same cause value in the failure history information and having the same manufacturer name value in the product information form a product group to be processed.

  For the examples shown in these figures, when the number of failures for each cause in each graph is analyzed, for example, in the graph for the product manufactured by Company C shown in FIG. The frequency of defects in the group is significantly high. Therefore, the user of the information processing apparatus 1 can easily guess that the product group manufactured by the company C has a potential failure factor related to the cause 2.

  Moreover, about the example shown by these figures, when analyzing the tendency of the number of occurrence of the trouble for every cause between graphs, for example, Company A shown in Drawing 8 (a)-Drawing 8 (c), Regarding the products manufactured by Company B and Company C, the occurrence frequency of defects in the product group of cause 3 is high. Therefore, the user of the information processing apparatus 1 can infer that, in the product group to be analyzed, a part commonly used by each company has a potential failure factor related to the cause 3.

As described above, the information processing apparatus 1 according to the present embodiment calculates the occurrence frequency of defects in the product group to be processed based on the defect information.
As a result, the information processing apparatus 1 can present the occurrence frequency of defects for each product group to be processed to the user, so that the user of the information processing apparatus 1 can have a potential defect in the product group to be processed. The existence of the factor can be easily determined. As a result, the user of the information processing apparatus 1 can take measures such as repair, part replacement, or introduction stop for the products belonging to the product group in which the potential failure factor is found. Thus, the information processing apparatus 1 can support discovery of a potential factor that causes a defect in the product group.

Further, the information processing apparatus 1 compares the occurrence frequency of defects in the product group with a predetermined threshold to determine the presence of a potential defect factor in the product group.
Thereby, since the user of the information processing device 1 does not have to determine the presence of a potential failure factor in the product group based on the personal technique and experience, It is possible to reduce the labor for analyzing the existence of the failure factor and reduce labor. In addition, since the information processing apparatus 1 relatively does not require the user with technology or experience, the information processing apparatus 1 determines the presence of a potential failure factor in the product group even if the user has insufficient technology or experience. be able to. In addition, the information processing apparatus 1 can suppress oversight of a potential failure factor due to lack of user experience or attention. Thus, the information processing apparatus 1 can support discovery of a potential factor that causes a defect in the product group.

Further, the information processing apparatus 1 specifies a product group based on the product attributes.
As a result, the information processing apparatus 1 classifies the products based on the product attributes such as the manufacturer and installation location of the product, and outputs the frequency of occurrence of defects in the product group. For example, the information processing apparatus 1 can calculate the frequency of occurrence of defects for each manufacturer even when a plurality of manufacturers manufacture the same product. It is possible to prevent the product data having a potential failure factor from being leveled and buried by the product data having no failure factor. Further, the user of the information processing apparatus 1 can estimate a potential failure factor based on the product attribute. Thus, the information processing apparatus 1 can support discovery of a potential factor that causes a defect in the product group.

Further, the information processing apparatus 1 specifies a product group based on the state of product defects.
Thereby, the user of the information processing apparatus 1 can examine the potential failure factor in the product group in more detail.

Note that the information processing apparatus 1 may perform the determination process for the product group to which the product identified by the product ID belongs every time failure history information is registered.
Note that the information processing apparatus 1 may manage any information included in the failure history information and the product information in association with each other. For example, the information processing apparatus 1 may manage information indicating product defects and product group identification information in association with each other.

  Note that the information processing apparatus 1 may specify a product group by any one or any combination of the attribute information, time information, and state information described above. Further, the information processing apparatus 1 may specify a product group based on information other than the attribute information, time information, and state information described above. For example, the information processing apparatus 1 specifies a product group based on any one or any combination of attribute information, time information, and state information of components such as parts, members, or units constituting the product. Good.

  Note that the information processing apparatus 1 may change the first threshold value and the second threshold value according to the product group to be processed. For example, the information processing apparatus 1 may change the first threshold value and the second threshold value according to a specific parameter. More specifically, the information processing apparatus 1 may change, for example, the first threshold value and the second threshold value according to the value of the operation years. Further, the information processing apparatus 1 may determine the presence of a potential failure factor in the product group based on one threshold value. Further, the information processing apparatus 1 may determine the presence of a potential defect factor in the product group based on, for example, threshold values acquired by three or more different methods. In this case, the information processing apparatus 1 may have a function of selecting an arbitrary threshold value used for determination.

  Further, the information processing apparatus 1 may change the product group to be processed based on the determination result based on the threshold value. For example, the information processing apparatus 1 specifies information for identifying a product group when the value of the occurrence frequency of a defect calculated for the product group to be processed is a value between a first threshold value and a second threshold value. To change the product group to be processed. Then, the information processing device 1 calculates the occurrence frequency of the defect in the product group to be processed after the change, and based on the comparison between the calculated occurrence frequency of the defect and the first threshold and the second threshold, The presence of various failure factors. More specifically, using FIG. 7, for example, the failure rate indicated in the area A <b> 22 in FIG. 7A is a value between the first threshold value and the second threshold value, and attention is required. If determined, the information processing apparatus 1 adds manufacturer information as information for specifying the product group, and changes the product group to be processed to Company A, Company B, and Company C. Then, the information processing apparatus 1 calculates the frequency of occurrence of defects for each manufacturer shown in FIGS. 7B to 7D and performs determination based on the threshold again. Thereby, the information processing apparatus 1 can identify the product group which has a potential malfunction factor more efficiently.

In addition, the information processing apparatus 1 may display the frequency of occurrence of defects in any display form other than a graph, such as a cross tabulation table. The output by the information processing apparatus 1 may be performed by transmitting information to a printing machine or another apparatus.
Note that each functional unit of the information processing apparatus 1 may be provided in a plurality of apparatuses. Then, the function of the information processing apparatus 1 may be realized by processing by each of the plurality of apparatuses and communication between the apparatuses.

  In addition, you may make it implement | achieve a part of information processing apparatus 1 in each embodiment mentioned above, for example, one part or all part of the control part 14 with a computer. In that case, a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read into a computer system and executed. The “computer system” here is a computer system built in the information processing apparatus 1 and includes hardware such as an OS (Operating System) and peripheral devices.

  The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Furthermore, the “computer-readable recording medium” is a medium that dynamically holds a program for a short time, such as a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line, In this case, a volatile memory inside a computer system that serves as a server or a client may be included that holds a program for a certain period of time. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

  Moreover, you may implement | achieve part or all of the information processing apparatus 1 in embodiment mentioned above as integrated circuits, such as LSI (Large Scale Integration). Each functional unit of the information processing apparatus 1 may be individually made into a processor, or a part or all of them may be integrated into a processor. Further, the method of circuit integration is not limited to LSI, and may be realized by a dedicated circuit or a general-purpose processor. In addition, when an integrated circuit technology that replaces LSI appears due to the advancement of semiconductor technology, an integrated circuit based on the technology may be used.

  As described above, the embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to the above, and various design changes and the like can be made without departing from the scope of the present invention. It is possible to

  DESCRIPTION OF SYMBOLS 1 ... Information processing apparatus, 11 ... Storage part, 111 ... Threshold storage part, 112 ... Product information storage part, 113 ... Failure history information storage part, 12 ... Input part, 13 ... Display part, 14 ... Control part, 141 ... Registration , 142... Calculation unit, 143... Determination unit, 144.

Claims (7)

A calculation unit that calculates the occurrence frequency of defects in the product group to be processed, based on defect information related to a defect in the product and product group identification information that identifies the product group to which the product belongs;
An output control unit that outputs the occurrence frequency calculated by the calculation unit;
An information processing apparatus comprising: If the occurrence frequency calculated by the calculation unit is larger than a threshold value determined according to the statistically calculated failure occurrence frequency, a potential factor causing the failure in the product group to be processed A determination unit that determines that there is
With
The output control unit outputs a determination result by the determination unit.
The information processing apparatus according to claim 1. The product group identification information is attribute information indicating an attribute of the product,
The output control unit outputs the occurrence frequency calculated by the calculation unit in association with the attribute indicated by the attribute information.
The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. The product group identification information is time information indicating time,
The output control unit outputs the occurrence frequency calculated by the calculation unit in association with the time based on the time information;
The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. The product group identification information is state information indicating a state of a defect of the product,
The output control unit outputs the occurrence frequency calculated by the calculation unit in association with a failure state indicated by the state information.
The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. An information processing method in an information processing apparatus,
A calculation process in which the calculation unit calculates the occurrence frequency of defects in the product group to be processed based on the defect information on the defect of the product and the product group identification information for identifying the product group to which the product belongs;
An output control unit that outputs an occurrence frequency calculated by the calculation unit; and
An information processing method comprising: On the computer,
A calculation procedure for calculating the occurrence frequency of defects in the product group to be processed based on the defect information on the defect of the product and the product group identification information for identifying the product group to which the product belongs;
An output control procedure for outputting the occurrence frequency calculated in the calculation procedure;
A program for running

Images