JPH0561877A - Quality data display method - Google Patents

Abstract

PURPOSE:To display the details of retrieval and analysis on a screen displaying an analysis result as history at the time of analyzing a defect cause and the occurrence tendency of a fault from fault occurrence information on a product. CONSTITUTION:The result retrieved 2 based on a setting retrieval condition in a procedure 1 is written into a core memory as a source data set 6. Analysis is executed by an analysis method designated in a procedure 7 with the written data set as an object. At that time, the parameter of an analysis object is selected in a procedure 8, and the data processing of an analysis procedure 9 is executed based on this parameter. A numerical operation is executed in accordance with the designated analysis method in the analysis procedure 9, and an operated result is outputted/displayed by a display output system 12 following the analysis method.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a quality data display method for collecting, accumulating information about the quality of products from customers and then searching, analyzing and displaying the information.

[0002]

2. Description of the Related Art Conventionally, for collecting and analyzing information on the quality of products from customers, see, for example, JP-A-63-409.
In Japanese Patent Laid-Open No. 62-62, a method of inputting product failure information by a bar code is proposed, but a data storage / management method and a search / analysis method are not disclosed. Further, the failure information is merely "defective content" and its details are unknown.

[0003]

In the above-mentioned prior art, first of all, no consideration has been given to the specific items and means for collecting quality data, and it is practically used as a system for managing quality. It is poor in terms of sex. Secondly, no consideration was given to the method of storing / managing quality data and the method of searching, and there was a problem in terms of operability including cost performance as a system and system scalability. Thirdly, the function of displaying the status of product failure or quality failure that actually occurs in the field has been left behind, and it has not played a role as a tool for pursuing these factors. In addition, since the user directly uses the function on the large-scale computer, no consideration is given to the detailed condition setting related to the search and analysis, and there is a problem in terms of the dynamics of the editing function and the analysis function or the flexibility for the user.

A first object of the present invention is to collect and accumulate information on the occurrence of product failures in a database, and when analyzing the cause of failure, tendency of failure occurrence, etc. related to the product for some or all of them. There is provided a quality data display method capable of displaying the history of search and analysis as a history on the screen showing the analysis result. A second object of the present invention is to analyze each factor on the product, the tendency of failure occurrence, etc., on the screen showing the analysis result as an icon, that is, as an input device, so that the next stage analysis condition can be input. It is to provide the quality data display method.

[0005]

[Means for Solving the Problems] The first object is to collect the information on the occurrence of failure such as the date, phenomenon and measures from the field and to accumulate it in a database. Or for all,
This can be achieved by displaying the history of search and analysis as a history on the screen showing the analysis result when analyzing factors such as failure factors and failure occurrence tendency of products. The second purpose is to collect information on the occurrence of failures such as date, phenomenon and measures from the field, and to accumulate in a database regarding the processing performed regarding the failure of the product. When the factors, the tendency of failure occurrence, etc. are analyzed, each element on the screen showing the analysis result is used as an icon, that is, as an input device so that the analysis condition of the next stage can be input.

[0006]

The operation of collecting the information about the failure of the product and the measures against it is specifically performed as follows. That is, when a product breaks down under the customer who is the user, information about repairs mainly performed by a customer service representative such as a service person on-site is provided to sales personnel such as distributors and sales offices for each repair. Product design and
The computer network is used to provide online feedback to the factory, which is the main body of manufacturing and inspection. The term "computer network" as used herein refers to a general-purpose large-scale computer, a general-purpose large-scale computer and workstations, or workstations connected hierarchically. Every time a customer service representative repairs on-site, the product format, failure phenomenon, parts, contents of treatment, etc. are written on a card of a certain format, and the contents of the card are installed in the sales department. If information is input from the terminal of a large-scale computer, information about product failures and actions to be taken can be easily collected in the center.
It can be accumulated. In this way, it is possible to analyze factors such as product failure factors, failure occurrence trends, etc., for some or all of the product failure information collected and accumulated in this way. If the history of search and analysis can be displayed as a history on the screen showing the analysis result, or if the analysis condition of the next stage can be input by using each element on the screen showing the analysis result as an icon, Analysis can be performed easily and quickly under detailed search and analysis conditions. By such an analysis, not only the design and improvement of the product under production and the evaluation / inspection method of the used parts can be improved at an early stage, but also the reliability in the design of the new product can be improved.

Further, at that time, the quality data search / analysis can all be performed in the workstation, and the sequence of search / analysis request, processing, and output can be executed in real time, so that the turnaround time of analysis work can be reduced. At the same time, in the workstation, by searching the source data in record units and expanding it in memory, it is possible to analyze all the items of the data related to the product failure and its repair and all combinations of the items. It is possible to perform the analysis.

[0008]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to FIGS. First, FIG. 3 shows the overall configuration of the system when the present invention is implemented. This figure shows the network from the base where the customer inputs quality data to the factory. When a product breaks down under the customer who is the user, information about repairs performed mainly by maintenance personnel in charge of the customer, such as a service person, is provided locally through a sales department such as a distributor or sales office. Online transmission to the factory, which is the main body of product design, manufacturing, and inspection. Specifically, the quality data of the customer is input from the terminal (office computer) 1 of each distributor, and the result edited by the computer 2 of each sales office is the same large-scale computer (installed in the main office) from all sales offices. ) 3 and the results edited there for each factory are once stored from the large-scale computer 3 to a large-scale storage device (having a mailbox function) 4 and then installed in each of a plurality of factories. It is always possible to refer from a large-scale computer (described later) 5.

[0009] A customer service representative such as a service person writes a product format, a phenomenon of failure, parts, contents of treatment, etc. on a card of a fixed format every time the repair is performed locally. The contents are to be input into the system from the terminal of a general-purpose large-scale computer installed in the sales department. The format of this card is shown in FIGS. As can be seen from FIGS. 4 and 5, the contents of the card consist of dozens of items as a whole, but the main items are shown in (1) to (27) below. (1) Product category: Product type and name (2) Yes No charge category: Distinction between paid repair or free repair (3) Reason for no charge ... Reason for performing free repair (4) Serial number ... Each product The number assigned at the time of manufacture to identify (5) Part No .... The number of the part to be repaired (6) Card NO ... Unique number to identify the card (7) Joint NO .... Repair at the same time Number assigned to the serialized parts (8) Reception No .... Card number managed by the distributor or retailer (9) Special sales category: Card issuer classification (sales office or distributor o
r Distributor) (10) Phenomenon… Failure phenomenon (11) Occasionally… Timing or condition when failure is reproduced (12) Number of operating months… Number of months from when the customer starts operating the product until it fails (13) Special agent … Distributor dealing with trouble repair (14) Sales office… Sales office to which the distributor in (13) belongs (15) Requester classification… Repair requester classification (customer or dealer or
(16) Work source classification ... Main body of repair work (in-house or outsourced) (17) Year of failure ... Year and month of repair of failure (18) Period classification ... Whether the target product is within the warranty period or not Discrimination as to whether it is outside (19) Purchase date: The date when the customer purchased the product (20) Entry / exit category: Distinction between whether the target product was received and repaired or repaired on a business trip (21) Action content category … Details of actions taken to repair the trouble (22) Adjustments and adjustments… A symbol that identifies whether or not adjustments or adjustments have been made and the location of the adjustment (23) Repair content classification… Repair purposes such as parts replacement and inspection (24 ) Repair amount ... Expense required for repair (divided into labor cost and parts cost) (25) Statistical year ... Year when repair cost was recorded (26) Part name ... Name of parts subject to repair (27 ) Manufacturer: Manufacturer of the part to be repaired Furthermore, at each factory, for the information consisting of the above items received from the mailbox, Following to be managed by the concrete side (28) to (4
Add the items shown in (0). (28) Product type: Product type and model (29) Year of manufacture: Year of manufacture of the product (year setting depends on the product) (30) Year of manufacture: Year of manufacture of the product (31) Product Year: The year when the product of the same type was first shipped (32) Product number: Identification number for managing the product in lot units at the time of production (33) Circuit NO: Number for identifying the parts on the board ( 34) Defective uniform number… A code for identifying a failure phenomenon with a particularly high management standard (35) Countermeasures… (33) Measures for the phenomenon with defective uniform number (36) Defective treatment… Occurring at the factory's responsibility Defects (In that case, free of charge even outside the warranty period) (37) Treatment ... Identification symbol for accident treatment (38) Countermeasure number ... Production number for countermeasures against large defects (39) Operating period classification ... Manufacturing (40) Repair history ... Past repair history Information on repairs and products for the above failures is analyzed along with product sales records. Of interest. The sales record here means the quantity of products delivered from the sales office to the distributor, the quantity of products delivered from the distributor to the distributor, or the actual sales amount from the distributor by type, month, and sales office. Any of the quantity of products delivered to the customer.

Next, FIG. 6 shows the relationship between product failures and quality defects that actually occur in the field and their factors. This figure illustrates some of the relationships between the above-mentioned card contents and their factors. Example 1) Cases in which the distribution of failure occurrences by dealers or sales offices dealing with failure repairs is due to climate differences due to regional differences such as temperature and humidity and differences in service systems 2) Product manufacturing year and product number・ A case where the failure occurrence distribution by manufacturing date / product number (lot) is due to the manufacturing history such as mixing of defective parts or changes in manufacturing specifications. Example 3) The failure occurrence distribution by year / month when the failure is repaired, Cases caused by climate due to seasonal differences such as temperature and humidity Example 4) Cases in which the failure occurrence distribution by product type, parts (modules) subject to repair, and phenomenon of failure is due to a specific product type and parts 5) The customer's distribution of failure occurrences by the number of months from the start of product operation until it fails, or by class, is caused by a specific failure pattern such as initial failure, random failure, or wear failure. Figure 7 shows a large-scale computer in each factory that issues a data transfer request from each factory to the above-mentioned large-scale storage device (which has a mailbox function), accumulates and manages the received quality data for each factory, and the quality. It shows a configuration with a workstation for searching and analyzing data. A large-scale storage device 6 is housed in the large-scale computer 5, and customer quality data of all past products of all products related to the factory are stored in the large-scale storage device 6. Although these data are used to search and analyze the quality data, the search and analysis are actually performed at the workstation 7. The external storage device 8 has a database of quality data, and the results searched and analyzed from the database are output to the external storage device 9 or the printer 10. By the way, the workstation 7 is connected to the large-scale computer 5 through a high-speed network, and when the data required in the database in the workstation 7 does not exist and a request for the data occurs, the required data is obtained. The part is transferred from the large-scale storage device 6 via the network.

FIG. 8 also shows a software configuration for retrieving and analyzing quality data in the workstation. Hereinafter, each module sharing the individual functions shown in FIG. 8 will be described. (I) User interface is for starting each module.
It manages termination. (II) The screen display application (AP) controls the display of a color graphic monitor using a graphic package. (III) The screen management module starts and ends the screen display application. (IV) The application start / management module starts / ends each module. (V) The failure analysis module has an analysis function of distribution, correlation, trend and the like. (VI) The failure occurrence prediction module has a failure occurrence distribution prediction function based on hazard analysis. (VII) The alarm management module is
It has a function of managing the progress status of the target setting value of the part. (VIII) The free search module instructs the search of the intermediate file or the database according to the specified search item. (IX) The intermediate file management module manages the intermediate files and activates the database search language. The (X) database management module is a database manager that manages, updates, and searches the database. The (XI) M-2050 communication module is for controlling data communication between a large-scale computer and a workstation using an inter-file communication package.

1 and 2 show the processing contents for performing the search and analysis of the quality data according to the present invention in the workstation. Hereinafter, FIG. 1 and FIG.
The following is a description of each procedure shown in (1) along with the flow of performing search / analysis. That is, the search is performed in the procedure 2 based on the search condition set in the procedure 1. Procedure 2 activates the database management function of procedure 3. Procedure 3 searches the database according to the search condition. However, if the data set of the database does not satisfy the search condition, the host access function of procedure 4 causes a large area except for the common part between the search condition and the database, that is, the part not existing in the database. Transfer from the computer and register in the database. The result retrieved by the procedure 2 is written in the core memory as the source data set 6. At this time, the data value can be directly referred to for the item selected in the data set item selection of the procedure 5. The analysis is performed on the data set written in the core memory. The analysis method is specified in procedure 7, the parameters to be analyzed are selected in procedure 8, and the data processing of analysis procedure 9 is performed based on them. In analysis procedure 9, numerical calculation is performed according to the analysis method specified in procedure 7, and the calculation result is displayed in output format 1 according to the analysis method.
2, the numerical operation according to each analysis method here means to calculate any of the management items shown in FIG. 9 according to the definition for each data item shown in FIG.

Here, of the processing flow described above,
Explain the database management and search method,
In the workstation, when a search request is generated by the procedure 2 in FIG. 1, the database management function of the procedure 3 in FIG. 1 is activated and the database is searched according to the search condition. At this time, if the data set of the database of the workstation does not satisfy the search condition, the part other than the common part of the search condition and the database, that is, the part not existing in the database is transferred from the large-scale computer to the database by the procedure 4 in FIG. register. The processing procedure in this case is shown in FIG. A conditional expression for the missing part is created from the search conditional expression, a large-scale computer is searched according to the condition, and the result is transferred. If the workstation's disk has enough space, register the transferred data.
If there is not enough space on the disk of the workstation, select the conditional expression that represents the data group that can be deleted from the disk, delete the corresponding data, and then register the data.

FIGS. 12 and 13 also show the case where the product of the set is calculated in all cases when the inclusion relation between the data set and the search condition is calculated and when the conditional expression of the missing part is created from the search condition expression. It is a comprehensive description. In each case, the product of the condition shown in the first column (leftmost column) and the condition shown in the second column (middle column) is shown in the third column (right column). is there. Hereinafter, each case will be described in order. A (upper row): The product of the condition of being equal to x and the condition of being equal to x indicates that the condition is equal to x.

A (bottom): The product of the condition of being equal to x and the condition of being equal to y indicates an empty set.

B: The product of the condition that it is equal to x and the condition that it is smaller than y is the condition that it is equal to x if x <y, and that it is an empty set if x> y.

C: The product of the condition that it is equal to x and the condition that it is greater than y is that x> y, and x is the empty set.

D: The product of the condition of being equal to x and the condition of being larger than y and being smaller than z is an empty set if x <y, and an empty set if x> z,
In other cases, it means that the condition is equal to x.

E: The product of the condition of being smaller than x and the condition of being smaller than y indicates that the condition is smaller than y if x> y and smaller than x if x <y.

F: The product of the condition that it is smaller than x and the condition that it is larger than y is that x> y is larger than x and smaller than y, and x <y is an empty set. ..

G: The product of the condition that it is smaller than x and the condition that it is larger than y and smaller than z is an empty set if x <y, and larger than y if z> z and z
The condition is that it is smaller than, and if it is not, y
It is shown that the condition is larger and smaller than x.

H: The product of the condition of being larger than x and the condition of being larger than y indicates that if x <y, the condition is larger than y, and if x> y, the condition is larger than x.

I: The product of the condition of being larger than x and the condition of being larger than y and smaller than z is an empty set if x> z, and larger than y if x <y and z
It is a condition that it is smaller than, otherwise, x
It is shown that the condition is larger and smaller than z.

J: The product of the condition that it is larger than x and smaller than y and the condition that it is larger than z and smaller than w is an empty set if y <z, and an empty set if w <x. greater than z if x <z and w <y,
And smaller than w, x <z and w>
If y is larger than z and smaller than y, if x> z and w> y, larger than x and y
If x> z and w <y, the condition is smaller than x and smaller than w.

FIG. 14 shows the functional structure of the entire system as external specifications. As shown in the drawing, the conditional expression management program relating to the present invention is roughly classified into (1) creation of an insufficient conditional expression, (2) deletion of conditional expressions and creation of deleted conditional expressions, (3) addition of conditional expressions, and (4) ) It consists of changes and registration of resident conditional expressions. Of these, (2) deletion of conditional expressions and creation of deleted conditional expressions are accompanied by (2-1) creation of insufficient conditional expressions, but (1) creation of insufficient conditional expressions requires further (1-1) Read the conditional expression file, (1-2) Calculate the product of conditional expressions, and
(1-3) Computation of the product with the complement. (1-2) The calculation of the product of the conditional expression is further made from the combination of the calculation of the product of the (1-2-1) element, and the calculation of the product with the (1-3) complement is (1-3 -1) It consists of a combination of calculating the complementary set of elements and (1-3-2) calculating the product of elements.

FIG. 15 to FIG. 19 are further detailed configurations of the main functions shown in FIG. 14 and are expressed as PAD diagrams. Of these, in FIG. 15, when the conditional expression management program is started, depending on the value of the input parameter,
Either (1) creating a shortage conditional expression, (2) deleting conditional expressions and creating conditional expressions, (3) adding conditional expressions, or (4) changing and registering resident conditional expressions Indicates that it works. FIG. 16 shows a procedure in which the function of (1) inquiry of conditional expression and creation of insufficient conditional expression in FIG. 15 operates. The procedure is as follows. step1: Open the conditional expression file in reference mode. step2: Create a conditional expression table. step3: Check the input condition formula. step4: Calculate the product of all the conditional expressions in the conditional expression table and each input conditional expression, and delete the empty ones from the conditional expression table. step5: Calculate the product of the complement of all conditional expressions in the conditional expression table and each input conditional expression, and output the message "included" if the result is empty. If the result is not empty, multiply the products incrementally.

Next, referring to FIG. 17, this shows the procedure in which the function of (2) deletion of conditional expression and creation of deleted conditional expression in FIG. 15 operates. This procedure is also explained below. step1: Open the conditional expression file in update mode. step2: Delete the input conditional expression from the conditional expression file. step3: (1) Activate the function of querying conditional expressions and creating insufficient conditional expressions.

Further, referring to FIG. 18, this shows a procedure in which the function of (4) resident conditional expression change and registration in FIG. 15 operates. This is also explained below. step1: Open the conditional expression file in update mode. step2: Write the input conditional expression in the conditional expression file. step3: Close the conditional expression file.

Further, referring to FIG. 19, this shows the procedure for operating the additional function of the conditional expression (3) in FIG. This is also explained below. step1: Open the conditional expression file in append mode. step2: Add the input conditional expression to the conditional expression file. step3: Close the conditional expression file.

Now, FIG. 20 shows the file specification of the conditional expression file in which the retrieval conditional expression to be calculated is stored, and FIG. 21 shows the elements of the conditional expression for exchanging data with the upper program. Although the file specifications of the input / output parameter file to be stored are shown, as a result of the processing described above, numerical calculation is performed according to the analysis method specified in procedure 7, and the calculation result is displayed and output according to the analysis method. The individual functions output by the form 12 are as follows. (I) Transition diagram Figure 22 shows an example of a transition diagram. With this function, the number of failures,
The repair amount and failure rate are stratified up to 5 types and plotted in time series. The data values can be seen in the data table. (II) Bar Graph An example of a bar graph is shown in FIG. This function displays the number of failures, repair amount, and failure rate by category.
In addition, it is possible to display specific category items by classifying them into different categories. The data values can be seen in the data table. (III) Pareto Chart Figure 24 shows an example of a Pareto chart. With this function, the number of failures, repair amount, and failure rate are classified into categories and sorted and displayed in order of size. Furthermore, the cumulative value of the ratio of the value of each item to the whole is plotted. The data values can be seen in the data table. (IV) Composition ratio diagram An example of composition ratio diagram is shown in Fig. 25. With this function, the number of failures, repair amount, and failure rate are classified into two categories, main and sub, and the main category is displayed on the horizontal axis and the sub category is displayed on the vertical axis in the form of composition ratio. The data values can be seen in the data table. (V) Pie chart An example of a pie chart is shown in FIG. This function displays the number of failures, repair amount, and failure rate by category.
In addition, it is possible to display specific category items by classifying them into different categories. The data values can be seen in the data table. (VI) Scatter diagram Figure 27 shows an example of a scatter diagram. This function displays a pair of data as one point. The data values can be seen in the data table. (VII) Schedule A case of the schedule is shown in FIG. For the service card data retrieved by this function, sort and sort items
(Up to 3 levels are possible), extract specific data and display in table format.

Numerical calculations are performed according to the specified analysis method as described above, and the individual functions for outputting the calculation results in the output format according to the analysis method are further expanded to prevent product failures that may actually occur in the field. For the purpose of pursuing these factors from quality defects, the process of narrowing down the factors and the output of the calculation results can be executed in parallel.
The contents of this processing are illustrated in FIGS. Here, an example of analysis for the product series of air conditioners is shown. First, in the product line of air conditioners, select products that should be subject to design improvements and inspection method improvements. For this purpose, the number of failures, the repair amount, the failure rate, and the like may be displayed in layers by product type. The result is shown in FIG. Here, a product whose format in which repair costs are particularly high is T is selected as an analysis target. In this case, if the mouse is clicked with the cursor on the bar indicating the repair amount of T in FIG. 29,
Only data for products in that format can be included in the analysis. In the product of type T, select the part that should be the target of design improvement and inspection method improvement. For this purpose, the number of failures, the repair amount, the failure rate, etc. may be displayed by classifying by parts or phenomena. First, FIG. 30 shows the result of stratifying the repair amount of a product of type T by component. At this time, as shown in the right column of the figure, the conditions for limiting the data to be analyzed are sequentially added to the table as search conditions. Here, a compressor, which is a component that causes a relatively large amount of repair money, is selected as an analysis target. Also in this case, if the cursor is clicked with the cursor on the bar showing the repair amount of the compressor in FIG. Can be narrowed down as an analysis target. Next, in the product whose type is T and in which a failure has occurred in the compressor, select the parts that should be subject to design improvement and inspection method improvement. For this reason, the result of stratifying the repair amount by phenomenon is shown in FIG.
As a result of the processing to narrow down the above factors, the product type is T
Then, it is clarified that the failure of the compressor caused by the start failure is one of the most important objects of the design improvement and the inspection method improvement.

The processing method illustrated in FIGS. 29 to 31 is described below. 32A and 32B show data relationships for performing factor analysis. Factor analysis is a detailed analysis of the contents of specific factors from analysis data.
It can be deployed. The source data management table manages source data for analysis.
Each row represents one breakdown repair. The data relating to one failure repair consists of multiple items, and each item manages independent information. Perform data analysis by performing the specified data processing method on each column of each item. The source data number table is for storing the number of data items stored in the source data management table. The analysis means management table is for managing information for analyzing the original data, and is composed of analysis items, data processing methods, and analysis methods. The analysis item stores the item number (1 to L) of the original data to be analyzed. The data processing method stores the type of calculation performed on the specified analysis item. The analysis method stores the display type for displaying the analysis result. The specified data processing method is calculated for the analysis items managed in the analysis means management table. The analysis result is displayed according to the specified analysis method. Further, the factor analysis management table stores the content of one item designated by the analysis means management table, which is information necessary for performing factor analysis, and the analysis data displayed according to the analysis method, as the factor analysis content. The factor analysis number table manages the number of data stored in the factor analysis table. When multiple data are stored in the factor analysis management table, one item of data in the source data management table is sequentially compared for the number of times of factor analysis to see if the factor analysis contents of the analysis items match. If the analysis items are the same, it is determined that the data is the target of factor analysis, and the data processing method stored in the analysis means management table is analyzed.

FIG. 33 shows a specific factor analysis processing flow.
This processing flow is related to the data shown in FIG.
Assuming that data has been set in advance in the source data management table and source data number table, the number of factor analyzes in the factor analysis number table is first cleared. Next, the analysis method, the analysis item, and the data processing method, which are the information managed in the analysis procedure management table, are designated and set in the table. Analyze the source data according to the information set in the analysis procedure management table. The analysis result is displayed according to the analysis method which is the information of the analysis procedure management table. Then, based on the analysis result, it is determined whether or not to analyze and expand the content in detail for the specific factor. When performing analysis regarding a specific factor, one of the analysis items displayed by the analysis method of the analysis means management table is specified. The designated factor analysis content is saved in the factor analysis management table. Further, the contents of the analysis means management table (analysis method, analysis item, data processing method) showing the current analysis contents are saved in the factor analysis management table. After that, 1 is added to the factor analysis number counter and the saving of the current analysis information is completed. When performing the specific factor analysis, the information managed in the analysis procedure management table is designated. If the specific factor analysis process is not performed, it is determined whether to restore the previous specific factor analysis, which is the content of the previous analysis, and if it is restored, the following process is performed. The analysis method, analysis item, and data processing method are set in the analysis means management table from the factor analysis management table. 1 is subtracted from the factor analysis count table to restore the analysis data. Primitive data analysis is performed by the information set from the factor analysis management table to the analysis procedure management table, and the analysis result is displayed. When the restoration of the specific factor analysis is not performed, the entire processing ends.

FIG. 34 shows a raw data analysis processing flow. This flow follows the information of the analysis means management table,
The data processing method is applied to the contents of the primitive management table. First, the atomic data read counter is cleared. Next, the analysis item contents are read from the source data management table. It is determined whether or not the factor analysis is performed depending on whether the value in the factor analysis frequency table is zero. When performing factor analysis, the factor analysis comparison number counter is cleared. The factor analysis contents are read from the factor analysis management table, and it is determined whether the factor analysis contents and the analysis items stored in the factor analysis management table of the original data are the same.
If they are equal, 1 is added to the comparison number counter, and when the value of the comparison number counter is equal to the factor analysis number, the read position data equal to the source data read counter value of the source data management table determines the specific factor analysis data. After that, the analysis items in the analysis means management table are analyzed according to the data processing method. If the source data items and factor analysis contents are not equal, or if factor analysis is not performed, data processing is not performed. Next, 1 is added to the source data read counter, and the analysis item contents are processed from the source data management table in accordance with the source data read counter value until the value of the source data number table becomes equal to the number of times of reading.

Next, a method of estimating the future failure occurrence status from the current failure occurrence and product shipping status will be described. First, the procedure of the method is shown below. step1: Obtain the total number of operating units N (t) and the number of failures r (t) in the number of operating months t. step2: Calculate the failure rate by λ (t) = r (t) / N (t). step3: Plot (t, lnΣλ (t)) on the hazard probability paper. step4: Fit a straight line or a broken line to the plot points and select the one that has a good fit. step5: Parameter of failure distribution (Weibull distribution) (m,
η) is obtained from the slope and intercept of the straight line. step6: Obtain the cumulative failure rate F (t) of the predicted month t using the parameters obtained in step5. step7: Calculate the cumulative number of failures in the predicted month from ΣnF (t) (n: number of units sold each month). step8: Calculate the cumulative failure for the predicted month by using Σn / F (t) / N (N: N = ΣN (t) total unit sales).

Next, FIG. 35 specifically shows the processing.
As shown in the left column of the figure, when the breakdown is repaired, the product type, breakdown phenomenon, parts, details of the treatment, etc. are reported by the card. The time when the product started operating is different. Therefore, as shown in the upper left of the right column of the figure, the failure rate is calculated for each number of operating months. The cumulative hazard value is calculated from this failure rate and plotted against the number of operating months. The failure occurrence is estimated based on the slope and intercept of the linear approximation of this plot. Weibull distribution is used as a model for estimation. Using the slope m and the intercept m · ln η obtained by linear approximation as Weibull parameters, the failure occurrence is estimated by the function f (t) shown in the lower left. In the Weibull distribution, m <
The case of 1 is a pattern in which many initial failures occur, and m
In the case of> 1, it is a pattern in which many wear failures occur.
If m = 1, the failure is accidental.

Although the present invention has been described above, since the search / analysis of quality data can be performed entirely at the workstation and the sequence of search / analysis request, processing, and output is executed in real time, the turnaround time of analysis work is reduced. There is a reduction effect. In addition, when a product breaks down for a customer who is the user, information about repairs mainly performed by customer service maintenance personnel such as service personnel on-site is provided to sales personnel such as dealers and sales offices for each repair. Since it is possible to provide immediate feedback to the factory, which is the main body of product design / manufacturing / inspection, through the department, it is possible to improve the design and improvement of the product in production and the evaluation / inspection method of used parts at an early stage. Not only is this possible, but reliability can be improved in the design of new products. Furthermore, in the workstation, by searching the source data in record units and expanding it in the memory, the analysis of each item of data related to product failure and its repair and all combinations of items are targeted. Analysis is possible.

[0038]

As described above, according to the first aspect of the present invention, after collecting and accumulating information on the occurrence of product failure in the database,
Quality data that enables the history of searches and analysis to be displayed as a history on the screen that shows the analysis results when analyzing factors such as failure factors and failure trends related to products for some or all of them. In the case where the display method is according to claim 2, when analyzing factors such as a defect factor and a failure occurrence tendency relating to a product, each element on the screen showing the analysis result is displayed as an icon, that is, an input device in the next step. A quality data display method in which analysis conditions can be input is obtained.

[Brief description of drawings]

FIG. 1 is a diagram showing a partial processing content for performing a search and analysis of quality data according to the present invention in a workstation.

FIG. 2 is a diagram showing the remaining processing contents for performing the search and analysis of the quality data according to the present invention in the workstation.

FIG. 3 is a diagram showing an overall configuration of a system when the present invention is implemented.

FIG. 4 is a diagram showing the first half of the format of a card for collecting information or adding information.

FIG. 5 is a diagram showing the latter half of the format of a card for collecting information or adding information.

FIG. 6 is a diagram showing a relationship between product failures and quality defects actually occurring in the field and those factors.

FIG. 7 is a diagram showing a configuration of a large-scale computer in each factory that stores and manages quality data corresponding to each factory and a workstation that searches and analyzes the quality data.

FIG. 8 is a diagram showing a software configuration for searching and analyzing quality data in the workstation 7.

FIG. 9 is a diagram showing management items as a reference when performing a numerical operation according to an analysis request when the present invention is carried out.

FIG. 10 is a diagram showing data items serving as a reference when performing a numerical operation according to an analysis request when the present invention is implemented.

FIG. 11 is a diagram for explaining processing when the data set in the database in the workstation does not satisfy the search condition.

FIG. 12 covers a part of cases of the product of a set in the case of calculating an inclusion relation between a data set and a search condition and in a case of creating a conditional expression of a missing part from the search conditional expression. Figure shown

FIG. 13 covers the remaining cases of the product of sets in the case of calculating the inclusion relation between a data set and a search condition, and in the case of creating a conditional expression for the missing part from the search condition expression. Figure shown

FIG. 14 is a diagram showing a functional configuration as an external specification of the entire system.

FIG. 15 is a diagram showing, as a PAD diagram, a further detailed configuration of the main functions shown in FIG.

FIG. 16 is a diagram showing, as a PAD diagram, a further detailed configuration of the main functions shown in FIG.

FIG. 17 is a diagram showing, as a PAD diagram, a further detailed configuration of the main functions shown in FIG.

18 is a PAD diagram showing the detailed structure of the main functions shown in FIG. 14 in the same manner. FIG.

FIG. 19 is a diagram showing, as a PAD diagram, a further detailed configuration of the main functions shown in FIG.

FIG. 20 is a diagram showing a file specification of a conditional expression file that stores a search conditional expression as an operation target.

FIG. 21 is a diagram showing a file specification of an input / output parameter file for storing elements of a conditional expression, for exchanging data with a higher-level program.

FIG. 22 is a diagram showing a display output format (case of transition diagram) in which numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 23 is a diagram showing a display output mode (bar graph example) in which numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 24 is a diagram showing a display output mode (a case of a Pareto chart) in which numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 25 is a diagram showing a display output mode (a case of a composition ratio diagram) in which numerical calculation is performed according to a specified analysis method, and the calculation result is according to the analysis method.

FIG. 26 is a diagram showing a display output format (example of a pie chart) in which a numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 27 is a diagram showing a display output mode (scatter diagram example) in which numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 28 is a diagram showing a display output form (case of a schedule) in which numerical calculation is performed according to a specified analysis method and the calculation result is according to the analysis method.

FIG. 29 is a diagram showing a numerical analysis performed according to a specified analysis method, and when the calculation result is displayed and output according to the analysis method, the individual functions are further expanded, and in addition, due to product failure or quality defect, Diagram showing processing to narrow down factors by product type

FIG. 30 is a diagram showing an analysis result of a product format as an analysis target.

FIG. 31 is a diagram showing an analysis result of an analysis part object.

FIGS. 32 (a) and 32 (b) are views showing data relationships for performing factor analysis.

FIG. 33 is a diagram showing a flow for performing a specific factor analysis process.

FIG. 34 is a diagram showing a flow for processing the contents of the source data management table according to the information of the analysis means management table.

FIG. 35 is a diagram showing a processing procedure of failure occurrence estimation.

[Explanation of symbols]

5 ... Large-scale computer, 6 ... Large-scale storage device, 7 ... Workstation, 8 ... External storage device, 9 ... External storage device, 10
… Printer

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Koichi Hinata No. 800 Tomita, Ohira-cho, Shimotsuga-gun, Tochigi Prefecture Tochigi Plant, Hitachi Ltd. Hitachi, Ltd. Tochigi factory

Claims (2)

[Claims] 1. A process performed on a product failure,
Information on failure occurrence such as date, phenomenon and measures is collected from the site and accumulated in a database, and when analyzing factors such as defective factors and failure occurrence related to products for some or all of them, the analysis result is A quality data display method characterized by displaying the history of searches and analyzes as a history on the display screen. 2. With respect to processing performed for product failure,
Information on failure occurrence such as date, phenomenon and measures is collected from the site and accumulated in a database, and when analyzing factors such as defective factors and failure occurrence related to products for some or all of them, the analysis result is A quality data display method in which each element on the displayed screen is used as an icon, that is, an input device, and analysis conditions in the next stage can be input.