JP2002183368A - System and method for analyzing data of failure of product, and recording medium housing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To statistically grasp by dividing the failure generating conditions into forms easy to evaluated through the maintenance information such as a repair utilizing a flaw compensating insurance. SOLUTION: A model number of a vehicle insured of a flaw compensation is converted into the statistical data 205 of an automobile as an object of guarantee with the layered structure showing a maker name, a model, and a vehicle name by using a conversion table 203, and stored together with the guarantee number. A maintenance code specified when maintenance of the vehicle is performed is converted to the statistical failure data 211 with the layered structure showing a portion, a device, parts and a cause of failure by using a conversion table 209. The data 215 of the automobile as an object of the special guarantee is connected to the failure data 211 by using the guarantee number of the guarantee used for the maintenance as a key to form the failure automobile data 217 with the layered structure indicating the maker name, the model, the vehicle name, the failure part, the device, the parts, and the cause. Statistical processing is performed on the basis of the data 205 of the automobile as an object of guarantee and the failure automobile data 217 to obtain the rate of occurrence of failure.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system and a method for statistically ascertaining the occurrence of a defect in a product such as an automobile, a building, a home electric appliance, etc., using information relating to the warranty of the product.

[0002]

2. Description of the Related Art Products have malfunctions, failures,
Failures such as breakage may occur, and adjustments, repairs, replacements, and other maintenance are performed to recover the original functions of the product, and its use is continued. Information on the occurrence of such inconveniences and their countermeasures is fed back to the manufacturer, and the quality of the product is continuously improved.

[0003]

However, if information on the occurrence of each defect and its countermeasure is fed back in a piecemeal manner each time a problem occurs, it is difficult to obtain a comprehensive countermeasure, and it is inefficient. And ineffective. It is also useful for product manufacturers and sales companies to statistically process defect information to understand which parts of which products have a tendency to cause defects. Information tends to remain within the range sold by the manufacturer or distributor of the product, or within a similar chain.

[0004] In recent years, it has been widely practiced that a defect in a product is guaranteed by a manufacturer or a sales company within a certain period of time, and the product is maintained without an economic burden on a purchaser of the product. Defect warranty insurance is increasingly used for maintenance costs incurred by manufacturers and sales companies.

[0005] When the defect guarantee insurance is used, a large amount of defect information is accumulated in the insurance company beyond the series of manufacturers and sales companies. Therefore, if this information is provided to manufacturers and sales companies and can be used effectively, it can greatly contribute to improving the quality of products.

However, the defect information collected by the insurance company is different from the defect information created and collected by the manufacturer and the sales company in the classification and content of the information, and is used by the manufacturer and the sales company. It was difficult.

[0007] A similar problem has occurred in various products for which defects are guaranteed, such as homes and buildings, and home appliances.

The present invention has been made in view of the above circumstances, and has as its object to make it possible to effectively use defect information collected by a different system. Further, the present invention classifies various failure occurrence situations into a format that can be easily evaluated from maintenance information such as repair using defect warranty insurance accumulated in an insurance company, and statistically grasps by restructuring, The purpose is to help improve quality.

[0009]

In order to achieve the above object, a product defect data analysis system according to a first aspect of the present invention is a system for statistically analyzing a defect occurring in a product. Assurance data storage means for storing attribute information of the target product and assurance data relating to the content of the assurance, and assurance for storing an assurance data conversion table for converting the assurance data into assurance target product data for use in statistics. Data conversion table storage means and assurance by means of a statistical divisional expression in which the assurance data is expressed in a hierarchical structure including a statistical manufacturer division, a product classification division, and a product name division with reference to the guarantee data conversion table. First data conversion means for converting the product data into target product data, and the guarantee target product data generated by the first data conversion means Assurance target product data storage means for storing, maintenance data storage means for storing maintenance data relating to the contents of maintenance for a defective product among the products to be guaranteed, and use of the maintenance data for statistics. A maintenance data conversion table storing means for storing a maintenance data conversion table for converting the maintenance data into a defect data, and a part division, a device division, a part division, and a cause division for the maintenance data by referring to the maintenance data conversion table. A second data conversion unit that converts the data into defective data in a statistical partitioned expression expressed by a hierarchical partitioned expression including: a product specifying unit that specifies a target product from the input defective product specifying data; Product data of the specified product is extracted from the product data storage means, A data synthesizing means for generating defective product data by adding the defective product data to the data, and a product defect occurrence frequency for calculating a defect occurrence frequency of the product according to the statistical classification expression using the defective product data and the product data to be guaranteed. Calculation means.

[0010] With this configuration, it is possible to efficiently determine the frequency of occurrence of product defects using the warranty data and the maintenance data collected in different systems.

[0011] The product defect occurrence frequency calculation means receives, for example, information for specifying a product maker, and uses only the defective product data corresponding to the specified product maker and the data to be guaranteed to obtain the statistical data. Calculate the frequency of occurrence of defects in products according to the classification expression.

The product defect occurrence frequency calculating means receives, for example, information for specifying the product type, and uses only the defective product data corresponding to the specified product type and the product data to be guaranteed to produce the statistical classification expression. Calculate the frequency of occurrence of product defects according to the following.

The product defect occurrence frequency calculating means receives, for example, information for specifying a product name, and uses only the defective product data corresponding to the specified product name and the product data to be guaranteed to produce the statistical classification expression. Calculate the frequency of occurrence of product defects according to the following.

In order to achieve the above object, a second aspect of the present invention is provided.
The method for analyzing defect data of a product according to the aspect of the present invention comprises the steps of storing attribute information of a product to be guaranteed and warranty data relating to the content of the warranty, and guarantee data for converting the warranty data for use in statistics. The manufacturer's classification for the statistical data is referred to by referring to the conversion table,
Converting to product data to be guaranteed by statistical classification expression expressed by a hierarchical classification expression including a product type classification and a product name classification; storing the guarantee target product data; A step of storing maintenance data relating to a maintenance procedure for a product in which a failure has occurred; and a step of classifying the maintenance data for statistics while referring to a maintenance data conversion table for converting the maintenance data for use in statistics. A step of converting the data into defect data by a statistical division expression represented by a hierarchical division expression including a device division, a component division, and a cause division; and specifying the target product from the input defective product identification data, Product data subject to assurance of the specified product is added hierarchically to the defect data of the specified product to generate defective product data That step a consists, calculating a trouble occurrence frequency of the product in accordance with the statistical classification represented using guarantee products data and the defective product data.

With this configuration, it is possible to efficiently determine the frequency of occurrence of a product defect using warranty data and maintenance data collected in different systems.

In the step of calculating the frequency of occurrence of a defect in the product, information for specifying a product manufacturer is received, and the statistical information is obtained by using only the defective product data corresponding to the specified product manufacturer and the product data to be guaranteed. The frequency of occurrence of defects in a product may be calculated according to the category expression.

In the step of calculating the product failure frequency, information for specifying a product type is received, and the statistical classification is performed using only the defective product data corresponding to the specified product type and the product data to be guaranteed. The failure occurrence frequency of the product may be calculated according to the expression.

In the step of calculating the frequency of occurrence of defects of the product, information for specifying the product name is received, and the statistical classification is performed using only the defective product data corresponding to the specified product name and the product data to be guaranteed. The failure occurrence frequency of the product may be calculated according to the expression.

The product is, for example, an automobile. In this case, the product type is, for example, a vehicle type, and the product name is a vehicle name.

According to a third aspect of the present invention, there is provided a program for causing an information processing apparatus to execute the above-described defect data analysis method. This program may be stored in a computer-readable recording medium and distributed.

[0021]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a failure data analysis system according to an embodiment of the present invention will be described with reference to an example of a system for analyzing information relating to occurrence and maintenance of a vehicle failure. In the following description, as long as there is no inconsistency in the context, the term failure broadly includes malfunctions, failures, damages, and the like of automobiles, and adjustments to address those failures,
Repairs, replacement of parts, etc. are expressed in a broad sense as maintenance.

[0022] To briefly explain the automobile defect warranty insurance, when purchasing a car, a warranty contract is concluded between the purchaser and the dealer with respect to the car malfunction.
A guarantee as shown in FIG. 3 is issued. If there is any defect in the purchased car, the purchaser maintains the car at a store. The maintenance costs are borne by the dealer within the warranty contract, and the purchaser is not required to pay for the maintenance costs. If the dealer and the insurance company have concluded a defect warranty insurance contract with respect to the maintenance costs borne by the dealer, the costs required for the maintenance will be covered by the defect warranty insurance and the insurance company The insurance is paid to the dealer more. The parties to the guarantee contract and the defect guarantee insurance contract are not limited to dealers, but may be automobile manufacturers.

FIG. 1 shows the configuration of the entire defect data analysis system. As shown, the system includes an analysis server 11 interconnected via a network NW.
When a sales department terminal 21 ₍₂₁ 1 ~21 _n), consists of maintenance unit terminal 31 ₍₃₁ 1 ~31 _m). The sales department terminal 21 and the maintenance department terminal 31 do not need to be different terminals, and may be the same terminal.

The analysis server 11 is installed in an insurance company or the like, and collects information from the sales department terminal group 21 and the maintenance department terminal group 31 to analyze vehicle failure data, and to determine the failure occurrence rate from various viewpoints. The company will use it to develop and improve its own insurance products and provide analysis results to automakers and dealers to improve product quality.

The sales department terminal group 21 (21 _{1 to} 21 _n )
Is installed in a sales department of an automobile dealership, etc., and information (guarantee data) relating to an automobile warranty contract concluded at the time of selling the automobile is transmitted to the analysis server 11. FIG. 3 shows an example of the guarantee data (guarantee certificate).

The maintenance section terminal group 31 (31 _{1 to} 31 _m )
Is set up in the maintenance department of a car dealership, etc.
Enter the guarantee number, etc. In addition, the maintenance section terminal group 31
Is sent to the analysis server 11.

As shown in FIG. 2, the analysis server 11 includes a communication unit 13, a display unit 14, an input unit 15, a control unit 16
And The communication unit 13 communicates with another device on the network NW. In particular, input data is collected from the sales department terminal group 21 and the maintenance department terminal group 31. The display unit 14 displays various information. The input unit 15 inputs various data and instructions.

The control unit 16 includes a storage unit, a processor, and the like, and collects data from the sales department terminal group 21 and the maintenance department terminal group 31, and performs an analysis process based on the collected data. The details of the analysis processing will be described later with reference to FIG.

The control section 16 has a plurality of storage sections for analysis processing. First, the warranty data storage unit 113 stores the warranty data (of the information published in the warranty shown in FIG. 3, the warranty number, the name of the automobile manufacturer (manufacturer), and the model (model) ), Vehicle name, registration date, etc.).

The maintenance data storage section 123 stores maintenance data as shown in FIG. 4 collected from the maintenance section terminal group 31. The maintenance data includes a unique maintenance code determined by the manufacturer or the dealer. This maintenance code is information for a manufacturer or a dealer to specify a defective portion and its cause. As for the maintenance using the guarantee contract, a guarantee number for identifying the used guarantee contract is stored.

The assurance target vehicle data storage unit 119 stores statistical data such as a maker name, a vehicle type, a vehicle name, and a guarantee number for all vehicles to which a warranty contract is applied. The defective vehicle data storage unit 133 stores, for the vehicle in which the defect has occurred, a manufacturer name, a vehicle type, a vehicle name, a defect location,
Statistical data indicating devices, parts, causes, etc. is stored.

The guarantee data conversion table storage unit 115
For vehicles with a warranty contract, specify the model designation number on the warranty data by the manufacturer category, model category,
Stores a guarantee data conversion table for conversion into statistical hierarchical data such as vehicle name classification. FIG. 5 shows an example of the guarantee data conversion table.

The maintenance data conversion table storage unit 125
A maintenance data conversion table for converting a maintenance code included in the maintenance data into hierarchically structured division data representing a statistically significant location, device, part, and cause of the failure of the insurance company is stored. FIG. 6 shows an example of the maintenance data conversion table.

Next, FIG. 7 shows a functional configuration of a failure data analysis system realized by the analysis server 11. As shown in the figure, the present system is functionally
13, guarantee data conversion table storage unit 115, guarantee data conversion unit 117, guarantee target vehicle data storage unit 119,
Maintenance data storage unit 123, maintenance data conversion table storage unit 125, maintenance data conversion unit 127, car identification unit 12
9. Data synthesizing unit 131, defective vehicle data storage unit 1
33, automobile malfunction occurrence frequency calculation unit 135, display unit 13
7 is provided.

Next, the operation of the fault data analysis system having the above configuration will be described. (Step 1) First, when a guarantee contract is concluded with a car when purchasing the car, the purchaser of the car applies for a guarantee contract at a car dealer.

At this time, a warranty card is issued from the dealer, and the warranty card includes, as shown in FIG. 3, information for specifying the purchaser, such as name, address, contact information (telephone number), and car. Manufacturer information, car name, model,
Model designation number, classification number, chassis number, displacement, registration number, mileage at delivery, registration date, delivery date, initial registration date, vehicle inspection expiration date, registration category, vehicle category, and warranty The information includes the warranty number, the type of warranty, the warranty period, and the warranty fee. Hereinafter, the information for specifying the vehicle and the information on the guarantee are collectively referred to as guarantee data 201.

(Step 2) These pieces of information are input to the sales department terminal 21 after issuing the warranty. The sales department terminal 21 transmits the input information to the analysis server 11.
The control unit 16 of the analysis server 11 receives the information via the communication unit 13 and stores the information in the guarantee data storage unit 113. Instead of communication, a copy of the warranty may be submitted to the insurance company, or the warranty data may be stored on a floppy (registered trademark) disk or magnetic tape, and then submitted to the insurance company. In this case, the guarantee data is input to the analysis server 11 via the input unit 15. Guarantee data can be submitted to the insurance company at any time.

(Step 3) Control unit 1 of analysis server 11
Reference numeral 6 denotes a process for converting the warranty data into a hierarchically-guaranteed vehicle data including a manufacturer name, a vehicle type, a vehicle name and the like using the model designation number included in the warranty data in order to use the warranty data for statistics. The conversion is performed by the conversion unit 117.

As described above, the guarantee data conversion table 203 (FIG. 5) in which the manufacturer classification information, the vehicle type classification information, and the vehicle name classification information corresponding to the vehicle type designation number are registered is stored in the guarantee data conversion table storage unit 115. Since it is stored, the guarantee data conversion unit 117 converts the model designation number into maker classification information, vehicle type classification information, and vehicle name classification information using the warranty data conversion table 203.

For example, according to the example of FIG. 3, the model designation number S987 is {manufacturer TMNH, passenger car, car name B}.
Is converted to information. By using the model designation number, it is not necessary to input data such as a car name or a car name when inputting data relating to warranty, so that erroneous input can be prevented and the data length can be shortened. .

(Step 4) Further, the guarantee data conversion unit 117 adds a guarantee number included in the guarantee data to the converted data (guarantee number, manufacturer classification information, vehicle type classification information, vehicle name classification information). ) Is created and stored in the guaranteed vehicle data storage unit 119. For example, if the guarantee number is 0001 and the model designation number is S987, $ 0
001, manufacturer TMNH, passenger car, vehicle name B #, which is to be guaranteed, is created and stored in the guaranteed vehicle data storage unit 119.

(Step 5) In the event that trouble such as malfunction, failure, breakage, etc. occurs in the car to be guaranteed, the purchaser of the car brings the car to a dealer to adjust, repair, and replace parts. We have you perform maintenance such as. By presenting the warranty at that time, the purchaser of the vehicle does not need to pay for the maintenance.

Here, in the case where the defect guarantee insurance is used, the dealer who has maintained the automobile is in the maintenance section terminal 3
From 1, charge the insurance company for the expenses required for the maintenance of the vehicle as insurance money. At that time, the car is covered by the warranty, the mileage of the car, what kind of trouble occurred, what the cause was, and what kind of maintenance It is necessary to write information such as whether the contract was carried out or how much the maintenance cost was, in the insurance claim document. Hereinafter, such information is referred to as insurance claim information. Information about what kind of trouble has occurred, what the cause is, and what kind of maintenance has been performed is referred to as maintenance data 207.

(Step 6) The maintenance data 207 input to the maintenance section terminal 31 is transmitted to the analysis server 11, and
The analysis server 11 receives this information and stores it in the maintenance data storage unit 123. Instead of the communication, the insurance claim document may be submitted to the insurance company, or the insurance claim information may be stored on a floppy disk or a magnetic tape and submitted to the insurance company. In this case, the insurance claim information is transmitted to the analysis server 1 via the input unit 15.
1 is input. Claims to the insurance company can be made at any time.

(Step 7) In order to use the maintenance data 207 for statistics, the analysis server 11 performs a process for converting the maintenance data 207 into data having a hierarchical structure including a site, a device, a part, and a cause where a failure has occurred.

The maintenance data 207 is in accordance with the detailed classification of the automobile manufacturer so that it is possible to specifically grasp which component unit of which apparatus of the automobile has a problem and how the maintenance has been performed. It is determined by the code.

For example, replacement of engine compartment side rail RH, replacement of ABS motor kit, repair of hood rear outer seal, side door opening frame R
H-painting, etc., are classified into numbers ranging from 10,000 to 20,000.
Therefore, although the data of the defective portion itself is indeed detailed, it is too detailed for statistically grasping the status of the entire defect, which is not appropriate.

Here, it is possible to regard the location of occurrence of a defect as a part as a large classification, a device as a middle classification, and a part as a small classification. For example, the parts can be classified into about ten ranges, such as engine relations, clutch relations, drive transmission relations, wheel drive steering relations, brake relations, body relations, and the like.

Further, the apparatus can be classified into about 20 sections, such as an engine body, a cooling apparatus, a fuel apparatus, a supply / exhaust apparatus, a steering apparatus, a brake apparatus, and the like. There are hundreds of parts for cylinder heads, pistons, crankshafts, fuel pumps, foot brakes, etc.

Therefore, in this embodiment, FIG.
The maintenance data conversion table 209 in which the maintenance code and the part classification information, the equipment classification information, the part classification information, and the cause classification information corresponding to the maintenance code are registered in the maintenance data conversion table storage unit 125 as shown in FIG. ing. That is, the maintenance data conversion unit 127 uses the maintenance data conversion table 209 stored in the maintenance data conversion table storage unit 125 to store the maintenance data 207 in hierarchical structure division information (part division information, apparatus division information, part division information). Information, cause classification information).

For example, in the example of FIG. 6, the maintenance code “E0
"00001" is converted into information that the faulty part is "engine", the faulty device is "engine body", the faulty part is "cylinder head", and the faulty cause is "wear", and the faulty part and faulty cause can be specified. .

(Step 8) Maintenance data converter 127
Is further divided into hierarchically structured section data (part section information,
The defect data (warranty number, part classification information, device classification information, parts classification information) is added to the device classification information, component classification information, and cause classification information) to add a warranty number indicating that the vehicle in which the defect has occurred is a vehicle subject to warranty. , Cause classification information) 21
1 is generated. (Step 9) On the other hand, the warranty number in the maintenance data 207 is notified to the vehicle specifying unit 129 as the defective vehicle specifying data 213.

The vehicle specifying unit 129 selects one of the data stored in the vehicle data storage unit 119 to be guaranteed.
Warranty target vehicle data 2 related to the notified warranty number 2
05 is extracted and supplied to the data synthesizing unit 131 as specific guarantee target vehicle data 215.

(Step 10) The data synthesizing unit 131
Fault data 211 and specific assurance target vehicle data 215
And the defect data 211 using the warranty number as a key.
And the specific guarantee target vehicle data 215. As a result, hierarchized defective vehicle data 217 including a warranty number, a manufacturer name, a vehicle type, a vehicle name, a defective part, a defective device, a defective part, and a defective cause is generated and stored in the defective vehicle data storage unit 133.

(Step 11) Next, a method of analyzing the state of occurrence of a vehicle malfunction will be described. The basic analysis method is obtained by a calculation formula in which the total number of guaranteed vehicles is the denominator, and the number of failed vehicles is the numerator. When a more detailed analysis is performed, the calculation formula may be applied after specifying the calculation formula on a manufacturer basis or limiting the calculation formula on a vehicle model basis. Further, with respect to the part where the failure has occurred, the breakdown of the number of failure occurrences of the device included in the part may be calculated.

For example, when calculating the ratio of occurrence of a specific trouble with a specific vehicle name of a specific manufacturer, the total number of vehicles to be guaranteed for the specific vehicle name of the specific manufacturer is used as a denominator.
The ratio is determined using the number of vehicles in which a specific defect has occurred among the vehicles to be guaranteed for the specific vehicle name of the specific manufacturer as a numerator, and is displayed on the display unit 137. In displaying the analysis result, it may be displayed as a statistical table, or may be displayed using a graph so that numerical data can be visually grasped.

As described above, it is possible to integrate the warranty data and the maintenance data, which are completely different systems, to determine the frequency of occurrence of a vehicle failure.

It should be noted that the vehicle failure data analysis system only needs to include the above-mentioned components, and may be physically a system dedicated for vehicle failure data analysis or a general-purpose information processing device. For example, by starting software that defines the operation of each means in an information processing apparatus having a general configuration including a processing device, input means, storage means, and output means, the vehicle failure data analysis system of the present invention can be implemented. Can be realized.

The present invention is not limited to the above-described embodiment, and various modifications and applications are possible.

For example, in the above-described embodiment, the data obtained by the automobile defect warranty insurance and the maintenance is used for calculating the frequency of occurrence of a defect. However, other arbitrary products, for example, real estate such as a house, a building, etc. For home electric appliances as well, the frequency of occurrence of defects may be calculated using the data obtained by the defect warranty insurance and the repair. FIG. 8 shows an example of the maintenance data conversion table when the product is a house.

In the above embodiment, an example is shown in which the analysis server, the sales department terminal, and the maintenance department terminal are connected via a network, but they need not be connected via a network. For example, data obtained at a store may be recorded on a recording medium such as a floppy disk or MO and read by an analysis server, or the information provided in a document may be read directly from the input unit of the analysis server. You may make it input.

It should be noted that the system of the present invention can be realized by using an ordinary computer system without using a dedicated system. For example, by installing the program from a medium (a floppy disk, a CD-ROM, or the like) storing a program for executing the above-described operation in a computer, a server or the like that executes the above-described processing can be configured. In the case where the above-described functions are realized by the OS sharing or the OS and the application being jointly used, only the part other than the OS may be stored in the medium.

It is also possible to superimpose a program on a carrier wave and distribute the program via a communication network. For example, the program may be posted on a bulletin board (BBS) of a communication network and distributed via the network. Then, by starting this program and executing it in the same manner as other application programs under the control of the OS, the above-described processing can be executed.

[0064]

As described above, according to the present invention,
Using the warranty data, the rate of occurrence of product defects can be analyzed.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of a failure data analysis system according to an embodiment of the present invention.

FIG. 2 is a diagram showing a configuration of an analysis server shown in FIG.

FIG. 3 is a diagram illustrating an example of a warranty.

FIG. 4 is a diagram showing an example of maintenance data.

FIG. 5 is a diagram illustrating an example of a guarantee data conversion table.

FIG. 6 is a diagram showing an example of a maintenance data conversion table.

FIG. 7 is a diagram showing a flow of a failure analysis process.

FIG. 8 is a diagram showing an example of a maintenance data conversion table when a target is a house.

[Explanation of symbols]

 Reference Signs List 11 analysis server 13 communication unit 14 display unit 15 input unit 16 control unit 113 guarantee data storage unit 115 guarantee data conversion table storage unit 117 guarantee data conversion unit 119 warranty target vehicle data storage unit 123 maintenance data storage unit 125 maintenance data conversion table storage Unit 127 Maintenance data conversion unit 129 Vehicle identification unit 131 Data synthesis unit 133 Faulty vehicle data storage unit 135 Vehicle fault occurrence frequency calculation unit 137 Display unit

 ────────────────────────────────────────────────── ─── Continuing from the front page (72) Inventor Toshiyuki Ansei 1-2-1 Marunouchi, Chiyoda-ku, Tokyo F-term in Tokyo Metropolitan Marine Life Insurance Co., Ltd. 5B075 KK07 ND20 ND23 NR03 NR20 UU40

Claims (12)

[Claims] 1. A system for statistically analyzing a defect occurring in a product, comprising: warranty data storage means for storing attribute information of a product to be guaranteed and warranty data relating to the content of the warranty; A guarantee data conversion table storing means for storing a guarantee data conversion table for converting the data into a guarantee target product data to be used for the product, a manufacturer classifier for statistical use of the guarantee data while referring to the guarantee data conversion table, and a product. First data conversion means for converting into assurance target product data in a statistical divisional expression expressed in a hierarchical expression including a type division and a product name division, and the assurance target generated by the first data conversion means Means for storing product data for assurance to store product data; and Maintenance data storage means for storing maintenance data relating to the contents of the maintenance; maintenance data conversion table storage means for storing a maintenance data conversion table for converting the maintenance data into failure data for use in statistics; A second data conversion means for converting the maintenance data into failure data in a statistical divisional expression expressed by a hierarchical structure divisional expression including a statistical part division, a device division, a part division, and a cause division with reference to a conversion table; , From the input defective product specifying data, a product specifying means for specifying a target product, and assurance target product data of the specified product are extracted from the assurance target product data storage means, and the defect of the specified product is determined. Data combining means for generating defective product data by adding to the data; With the elephant product data, the product defect data analysis system, characterized by and a product defect occurrence frequency calculating means for calculating the defect occurrence frequency of the product in accordance with the statistical classification representation. 2. The product fault occurrence frequency calculating means receives information for specifying a product manufacturer, and uses only the faulty product data corresponding to the specified product manufacturer and the product data to be guaranteed to obtain the statistical data. The product defect data analysis system according to claim 1, wherein the product defect occurrence frequency is calculated according to the classification expression. 3. The product defect occurrence frequency calculation means receives information for specifying a product type, and uses only the faulty product data corresponding to the specified product type and the product data to be guaranteed to produce the statistical classification expression. 3. The method according to claim 1, wherein a frequency of occurrence of a defect of the product is calculated according to the following.
Product failure data analysis system described in. 4. The product defect occurrence frequency calculation means receives information for specifying a product name, and uses the statistical classification expression by using only the defective product data corresponding to the specified product name and the data to be guaranteed. 4. The method according to claim 1, further comprising:
Product failure data analysis system according to any of the above. 5. The product according to claim 1, wherein the product is an automobile, the product type is a vehicle type, and the product name is a vehicle name.
5. The product failure data analysis system according to any one of claims 4 to 4. 6. A step of storing attribute information of a product to be guaranteed and guarantee data relating to the contents of the guarantee, and referring to a guarantee data conversion table for converting the guarantee data for use in statistics. Converting the assurance data into assurance-targeted product data in a statistical divisional expression expressed by a hierarchical divisional expression including a statistical manufacturer division, product classification division, and product name division; and storing the guarantee-targeted product data. A step of storing maintenance data relating to a maintenance procedure for a product in which a defect has occurred among the products to be guaranteed, and referring to a maintenance data conversion table for converting the maintenance data for use in statistics. Meanwhile, the maintenance data is expressed in a hierarchically structured partition expression including a statistical section, an apparatus section, a part section, and a cause section. And converting the defect data by use classification representation from the input defective product identified data to identify the product of interest, the warranty product data of products the specific,
Generating defect product data by hierarchically adding to the defect data of the specified product; and calculating a defect occurrence frequency of the product in accordance with the statistical classification expression using the defect product data and the warranty target product data. And product defect data analysis method. 7. The step of calculating the frequency of occurrence of defects of the product includes receiving information for identifying a product manufacturer, and using only the defective product data and the product data to be guaranteed which correspond to the identified product manufacturer. 7. The method for analyzing product defect data according to claim 6, wherein the defect occurrence frequency of the product is calculated according to the statistical classification expression. 8. In the step of calculating the frequency of occurrence of a defect in the product, information for specifying a product type is received, and the statistical information is obtained by using only the defective product data corresponding to the specified product type and the product data to be guaranteed. 8. The method for analyzing defect data of a product according to claim 6, wherein the frequency of occurrence of the defect of the product is calculated according to the category expression. 9. In the step of calculating the frequency of occurrence of a defect in the product, information for specifying a product name is received, and the statistical information is obtained by using only the defective product data corresponding to the specified product name and the data of the product to be guaranteed. 9. The product defect data analysis method according to claim 6, wherein the product defect occurrence frequency is calculated in accordance with the use category expression. 10. The product according to claim 6, wherein the product is an automobile, the product type is a vehicle type, and the product name is a vehicle name.
10. The method for analyzing defect data of a product according to any one of claims 9 to 9. 11. A program for causing an information processing apparatus to execute the product defect data analysis method according to claim 6. Description: 12. A computer-readable recording medium storing a program for executing the product defect data analysis method according to claim 11.