Method and system for diagnosis and analysis of products troubles

A computer-implemented method and system for diagnosing and system for diagnosing and analyzing fault information of a product is carried out by (a) creating a fault tree representing causal relations between faults and causes thereof base on information of past faults and information concerning the structure and characteristics of the product, and storing the fault tree in a storage unit, the fault tree having branches allocated with weighting coefficients; (b) inputting new fault information of the product into the computer; (c) searching the fault tree in accordance with the weighting coefficients based on the fault information stored in the storage unit to thereby determine the cause of the fault; (d) generating and outputting information concerning an adjustment or repair of the product suffering from the fault based on the determined cause of the fault as well as the information concerning the structure and the characteristics of the product; (e) supplying information concerning the timing of the occurrence of the fault, symptoms appearing in the fault, the cause of the fault and the adjustment and repair data to a host computer through a data collecting station to thereby construct a database for the fault information; and (f) the quality of the product based on all or a part of information of the database.

BACKGROUND OF THE INVENTION 
The present invention relates to a method and a system for searching for a 
causal relation of trouble or a fault of a product on the basis of 
information concerning the fault of the product to thereby display the 
cause of the fault together with measures for coping with the fault, as 
well as a system and a method for collecting and storing information 
concerning the quality of the product and for searching and analyzing the 
information as stored. 
In the fault finding diagnosis of a machine or apparatus known heretofore, 
a tree representing the causal relations of the faults is displayed on an 
image screen, wherein an event of concern is moved in the direction toward 
the cause of the fault through interactive diagnosis procedure, as is 
disclosed, for example, in JP-A-2-161567. In the case of the invention 
described in this publication, however, no consideration is given to means 
for obtaining the information from the machine or apparatus subjected to 
the diagnosis or means for transmitting the information to a location or 
system for carrying out the diagnosis. Further, there is found suggestion 
concerning the no probability concept representing validity of the causal 
relations which provides one of the basis for the decisions made in the 
course of tree searching. Moreover, no consideration is given to means for 
updating the probabilities and configuration of tree. For these reasons, 
this prior art technique is lacking in practicality for performing the 
fault diagnosis of the machines or apparatuses. 
With regard to the collection and analysis of the information concerning 
the quality of products used by the customers, there is proposed a method 
of acquiring the fault information of the products by making use of bar 
codes, as disclosed, for example, in JP-A-63-40962. However, neither 
teaching nor suggestion is found in this publication concerning the data 
storage/manage method and the search/analysis method. Further, as the 
fault information, there is available only "content of the fault". Thus, 
this prior art method is also lacking in practicality. 
In the case of the prior art techniques mentioned above, it is first noted 
that no consideration is made concerning the accuracy of the data which 
provides the basis for the diagnosis, thus giving rise to a problem with 
respect to the accuracy of the diagnosis performed by the system. 
Secondly, structurization of the data providing the basis for the 
diagnosis or inputting of the causal relations of the faults, to say in 
another way, cannot be realized unless an AI tree is effectively usable, 
presenting a problem with respect to the operability thereof. 
Furthermore, in conjunction with the method of analyzing the quality 
information, it is first noted that consideration is paid to neither the 
items of quality data to be collected nor the means for collecting the 
quality data in reality, giving rise to a problem concerning the 
practicality of the quality control or management of the system. Secondly, 
neither the method of storing and managing the quality data nor the search 
method is taken into consideration, presenting a problem with respect to 
the cost performance of the system as well as the operability inclusive of 
the expansion-susceptibility of the system. Thirdly, the function or 
capability of the system is confined to the display of the faults of 
products actually taking place in the field or locales and the states of 
quality deficiency. Thus, the system play a role as a tool for pursuing 
the causes or factors in which the faults and the deficiencies originate. 
Besides, because the functions of a large scale computer are utilized 
directly by the users, no consideration can be paid to any fine condition 
setting for the search and the analysis, which in turn presents problems 
for the users with respect to the dynamics and the flexibility of the 
editing function and the analysis function. 
SUMMARY OF THE INVENTION 
An object of the present invention is to solve the problems of the prior 
art techniques and provide a method and a system for diagnosing and 
analyzing fault information of products with the aid of a computer to 
thereby perform rapid and effective repair of those products which suffer 
from the fault and prepare the quality information of the products by 
statistically processing the results of the analysis. 
A method for diagnosing and analyzing fault information according to the 
invention comprises the following steps of: 
a) creating a fault tree representing causal relations between faults and 
causes thereof in the past in a tree structure on the basis of information 
concerning the structure and characteristics of the product and storing 
the fault tree in a storage unit, wherein the branches of the fault tree 
are allocated with weighting coefficients, respectively; 
b) inputting new fault information of the product into the computer through 
a terminal apparatus capable of communicating with the computer; 
c) responding to the input of the new fault information for searching for 
the fault tree in accordance with the weighting coefficients on the basis 
of the fault information stored in the storage unit to thereby determine 
the cause of the fault of the product; 
d) generating by the computer the information concerning adjustment or 
repair of the product suffering from the fault on the basis of the cause 
of the fault as well as the information concerning the structure and the 
characteristics of the product and outputting the information concerning 
the adjustment or the repair; 
e) supplying the information concerning the date of occurrence of the fault 
of the product, symptoms appearing in the fault, the cause of the fault 
and the data of the adjustment and the repair to a host computer through a 
data collecting station to thereby provide a database for the fault 
information; and 
f) statistically analyzing by the computer the quality of the product on 
the basis of all or a part of information of the database. 
A system for diagnosing and analyzing the fault information of products 
with the aid of a computer comprises the following units: 
a) a storage unit for storing a fault tree representing past causal 
relations between faults and causes thereof in a tree structure together 
with information concerning structure and characteristics of the product, 
wherein branches of the fault tree are allocated with weighting 
coefficients, respectively; 
b) a terminal apparatus capable of communicating with the computer for 
inputting new fault information of the product; 
c) means responsive to the input of the new fault information for searching 
for the fault tree in accordance with the weighting coefficients and on 
the basis of the fault information stored in the storage means to thereby 
determine the cause of the fault of the product; 
d) a unit for generating information concerning adjustment or repair of the 
product suffering from the fault on the basis of the cause of the fault as 
well as information concerning the structure and the characteristics of 
the product and outputting the information concerning the adjustment or 
the repair; 
e) a unit for supplying information concerning the date of occurrence of 
the fault of the product, symptoms appearing in the fault, the cause of 
the fault and the data concerning the adjustment and repair to a host 
computer through a data collecting station to thereby provide a database 
for the fault information; and 
f) a unit for statistically analyzing the quality of the product on the 
basis of all or a part of the information stored in the database. 
In a mode for carrying out the present invention, when a fault occurs in a 
product in the field where it is operated by a customer, the user of the 
product, a maintenance engineer such as a serviceman who is in charge of 
disposing of customers' claims, is dispatched to the field and repairs the 
product, wherein information concerning the repair is fed back to a 
factory which responsible for designing, manufacturing and inspecting the 
product from a business division such as a special agent and a business 
office through a computer network on a repair-by-repair basis. With the 
computer network, it is intended to mean a network in which 
general-purpose large scale computers are interconnected hierarchically, 
or in which a general-purpose computer and workstations are interconnected 
hierarchically or in which workstations are interconnected hierarchically. 
Further, the maintenance serviceman is obliged to input the type of the 
product, the symptoms of the fault and the contents of the disposal 
through the medium of a small scale terminal whenever he or she has 
repaired the product in the field. 
According to the invention, when a fault occurs in a machine or apparatus 
being used by a customer, the cause of the fault can be pinpointed by 
searching for the fault tree on the basis of the symptom, whereby the 
measures for adjustment or repair can be designated. By virtue of this 
feature, the number of times the maintenance serviceman is dispatched to 
the field for the repair, the turn-around time for completion of the 
repair and the number of parts required for the repair can be reduced, 
whereby service costs can be decreased while increasing the reliability of 
the product, which will ultimately lead to expansion of the share in the 
market. 
Further, information regarding the repair performed primarily in the field 
by the maintenance serviceman can instantaneously be fed back to the 
factory which is responsible for designing, manufacturing and inspecting 
the product on a repair-by-repair basis by way of the business division 
such as a specific agent or business office. Accordingly, improvement of 
the design of the product being manufactured, evaluation of the parts as 
well as improvement of evaluation/inspection method can be realized in an 
earlier stage. Besides, enhanced reliability can be ensured in designing a 
new model. Furthermore, since the search/analysis of the quality data can 
be performed solely in the workstation, a sequence of the search/analysis 
request, the processing and the output can be executed on a real-time 
basis, whereby the turn-around time involved in the analysis work can be 
reduced. Moreover, by searching and developing the source data on a memory 
on a record-by-record basis in the workstation, the analysis for each item 
of data concerning the fault and the repair of the product or analysis for 
all combinations of the data items can be performed.

DESCRIPTION OF THE PREFERRED EMBODIMENTS 
The present invention will be described in conjunction with an exemplary 
embodiment thereof by reference to FIGS. 1 to 48. 
FIG. 1 shows a general arrangement of a system to which the present 
invention is applied. A product planned by a marketing department is 
developed and designed to subsequently undergo a reliability evaluation, 
whereon a production schedule is established. The finished products as 
manufactured are then shipped for sales after inspection. When a fault 
occurs in the product put into operation by a customer, information is 
sent to a service department which is responsible for the repair. In that 
case, the cause of the fault is estimated with the aid of a fault 
diagnosis facility to thereby advise the measures to be taken for 
disposing of the fault. Real data such as the date of occurrence of the 
fault, phenomena or symptoms thereof, causes of the fault, measures as 
taken actually and the like are sent to a host computer center to be 
stored as records in a database. On the basis of the database, trend of 
the fault occurrence and the factors of the fault are analytically 
determined with the aid of a marketing product quality information 
collecting/analyzing facility. The results of the analysis are fed back to 
departments or divisions which are in charge of design, manufacture, 
inspection and others, to be thereby reflected onto development and design 
of new products as well as manufacturing and inspection of the products 
being currently on the production lines. 
FIG. 2 illustrates an arrangement of a facility for estimating the cause of 
a fault as occurred and indicating the measures for dealing with the 
fault. When a fault takes place in an apparatus or machine being used by a 
customer, phenomena or symptoms of the fault are inputted to a hand-held 
computer 5 in the locale for conducting the diagnosis. In dependence on 
the result of the diagnosis, indications for adjustment, repair or the 
like measure is given. The data which provide the basis for the 
investigation of the cause for the fault in the diagnosis as well as 
methods of adjustment, repair and the like procedure are stored in IC 
cards on a product-by-product basis so that the IC card can selectively be 
exchanged in dependence on the product of concern. The real data resulting 
from the fault diagnosis and the repair service are up-loaded from the 
hand-held computer 5 to a data collection/management station 4 on a 
once-per-week basis from the local bases each located at the level of a 
branch office which is in charge of arranging in order the claims of 
customers in a local area over which the branch office is in charge of 
control. The local base which is equipped with the data 
collection/management station 4 is in the position to conduct the 
diagnosis of the fault and designate the adjustment and repair methods 
with the aid of a work station 2 and an image file system for replying to 
the inquiries from those servicemen who are not in possession of the 
hand-held computer 5. The individual local bases mentioned above are 
connected to a host-computer center which is in charge of nationwide 
control and management and to which all the real data of the fault 
diagnoses and the repairs are uploaded to be rearranged, wherein the 
rearranged data can be down-loaded to the local bases. 
Referring to FIG. 3, the local base equipped with the work station 2 and 
the image filing system 4 as shown in FIG. 2 will be described in detail. 
In this figure, there are illustrated information and advice supplied by 
the system in the course of executing a procedure upon occurrence of a 
fault in an apparatus of a customer up to the removal of the fault 
together with the information stored internally to this end. Upon 
occurrence of a fault, a telephone message of the fault occurrence is sent 
from the customer to a maintenance service department. In the course of 
transactions through the telephone, the maintenance service department 
gets information concerning the name and model or type of the product of 
concern, symptoms of the fault, the time and the conditions at and under 
which the fault has taken place and others. In the maintenance service 
department, the information obtained from the customer is inputted to the 
work station to thereby cause a diagnosis procedure to be started. 
The fault diagnosis is effectuated by searching a tree representing the 
causal relations of the faults. The tree representing the causal relations 
of faults will be referred to as the fault tree (or FT in abbreviation). 
Further, analysis procedure performed by using the fault tree will be 
referred to as FTA (Fault Tree Analysis). The fault tree is initially 
configured on the basis of the information contained in the design 
specifications such as those of the structure and the characteristics of 
an apparatus or machine of concern or on the basis of the fault 
information obtained from the customers concerning similar apparatus or 
machines, whereon the fault tree configuration is updated every time the 
diagnosis is performed with the effect thereof being confirmed. Concerning 
the fault tree search strategy, description will be made later on. In the 
course of the diagnosis, there can arbitrarily be displayed image 
information of relevant documents such as precedent cases of fault 
recovery, circuit diagnosis, specifications tables and others. Such 
documents can previously be registered and stored in an image filing 
system so that the relevant parts of the documents can be displayed, 
printed or facsimiled by making access to the image filing system from the 
work station in the course of the diagnosis or after the diagnosis on the 
basis of the result thereof. The results of the diagnosis are displayed 
together with a document showing in concrete a portion or part in which 
the fault originated as well as a method of disposing of the fault and the 
procedures for examination or inspection and repairing. On the basis of 
the results of the diagnosis, the repair as well as the effect brought 
about thereby can be confirmed. 
The fault diagnosis procedure or diagnosis process outlined above by 
reference to FIG. 3 is shown in more concrete in FIGS. 4 and 5 together 
with examples of information for making access to the result of the 
diagnosis as well as those of the information for display. 
FIG. 4 shows a method of setting up conditions for the fault diagnosis 
together with location of the data required in the diagnosis process. A 
database which stores marketing product quality information and test data 
referenced in the course of the diagnosis process is shown at the 
left-hand side in the figure. The marketing product quality information 
represents the information concerning the faults and the repairs of 
products on the market, which information is collected by a marketing 
product quality information analysis system and stored in the database in 
terms of records each for one fault case. The test data represent those 
which result from the test of performance of a new product before delivery 
to the market and which are collected by a utility test system. An example 
of a document registered in the image filing system is shown at the 
right-hand side. A process flow of the diagnosis is shown at an 
intermediate portion in a top-down fashion. In the first place, the type 
or model of a product suffering from a fault as well as a phenomenon or 
symptom indicating the fault most straightforwardly are inputted as the 
initial conditions for the diagnosis. A fault tree which coincides with 
the initial condition is generated on a memory and displayed on a display 
screen. In the case of the example now under consideration, a fault tree 
having an apex node labeled an event or symptom "not cool" is displayed. 
When the occurrence of the fault corresponds to a node labeled "in the 
middle of operation" in the fault tree, this node is designated. Then, a 
fault tree having the apex node labeled "in the middle of operation" is 
displayed. Repetition of this procedure leads to a result of the 
diagnosis. On the basis of this result, probabilities which are attributes 
of the individual nodes of the fault tree are updated. 
Through dialogical interaction between the computer and the operator, the 
former gets information concerning the contents of the fault of a product 
of concern. As the contents of the fault are converted to items in more 
and more detail, the search progresses to the elements corresponding to 
lower and lower hierarchical levels (leaves) of the fault tree. When 
inputting of the information by the operator is interrupted in the course 
of repetition of the dialogic interaction, the computer then checks by 
itself weighting coefficients (occurrence probabilities) imparted to the 
nodes to thereby select the node having a maximum weighting coefficient at 
the hierarchical level reached currently, whereupon the search proceeds to 
a next lower hierarchical level. Through repetition of the operation 
described above, there can ultimately be reached a cause level in the 
hierarchy of the fault tree. 
FIG. 5 shows a result of the diagnosis obtained through the procedure 
illustrated in FIG. 4. In the diagnosis result shown at an upper left 
portion, those parts which are registered at the distal end of the fault 
tree as reached are displayed in the descending order of the fault 
occurrence probabilities together with the type and the symptom set up 
initially as the initial condition for the diagnosis. 
FIG. 6 shows a hierarchical structure of a tree representing causal 
relations of the fault to be searched in the fault diagnosis. The fault 
tree shown in FIG. 6 illustrates a whole structure of a fault tree for an 
air conditioner. At first, in dependence on whether the structure of the 
air conditioner is of a separate type or an integral type, the tree 
branches correspondingly, which is then followed by successive branchings 
in dependence on whether an inverter control method or a constant Fate 
control method is adopted, whether the function of the air conditioner is 
for both air cooling and heating or only for the air-cooling and whether a 
power source is a single-phase 200 V or three-phase 200 V, respectively. 
Further, the tree branches to a hierarchical level representing the 
symptom of the fault and then to a level representing the cause of the 
fault. 
FIG. 7 shows, by way of example, those portions of the whole structure of 
the fault tree for the air conditioner shown in FIG. 6 which are relevant 
to the symptom "not cool" of the air-conditioner of model A001. More 
specifically, a fault tree having the top node allocated to the symptom 
which represents straightforwardly the fault of "not cool" is shown, in 
which as the tree is traced toward lower level (rightwardly), the symptom 
becomes more and more detailed, entering the interior of the machine 
deeper and deeper. An element representing an event which is the cause of 
the fault belongs to the second level from the bottom level to which those 
elements representing events for disposing of the fault in dependence on 
the causes belong. 
FIG. 8 shows a data structure for implementing the fault tree in a work 
station. This data structure includes the ID numbers of the individual 
nodes constituting the fault tree, the ID numbers of parent nodes, the ID 
numbers of children nodes, symptom names or test procedure, parts to be 
disposed of, case management number for the document search and others. A 
FTA form table contains and manages those data which indicate the 
relations between the individual fault trees and the product types. In a 
FTA data manage table, the fault trees are managed on the basis of unit 
symptom representing the fault most straightforwardly. On the other hand, 
the individual elements belonging to the fault trees managed with this 
table is managed by an element-based data table which registers therein 
the ID numbers of the individual elements, symptom names and the 
occurrence probabilities corresponding to the individual elements. 
Parent-children relations between the elements are managed by a structure 
definition table in which the ID number of the element representing the 
parent of the individual elements as well as the identifier numbers of the 
elements representing the children nodes are registered. 
FIGS. 9 to 15 show images displayed in succession in the course of 
diagnosis procedure executed by the system. 
FIG. 9 shows an image for allowing the type of a product suffering from a 
fault and symptoms thereof as acquired from the customer directly or 
through the medium of a serviceman who contacted the customer to be 
inputted as the conditions for the diagnosis. For inputting the model or 
type of the product and the symptoms, associated, blank columns are 
designated by using a mouse, in response to which associated lists make 
appearance, respectively. On the basis of the lists, the type and the 
symptoms to be inputted are selected. There can be set up two symptoms at 
maximum as the condition for the diagnosis. After having set up the 
conditions for the diagnosis in this image, the fault diagnosis procedure 
is started. 
FIG. 10 shows a part of the fault tree in the course of the diagnosis. In 
the case of this example, the symptom "not cool" at the current 
hierarchical level is shown together with three operation modes 
"immediately after installation", "in the middle of operation" and 
"sometimes" at the children nodes imparted with respective occurrence 
probabilities. The diagnosis proceeds to a next step by selecting one from 
these children nodes in a dialogical fashion. 
FIGS. 11 to 14 show images generated successively in following the stepwise 
dialogical search of the fault tree. 
FIG. 15 shows the results of the diagnosis. 
FIG. 16 shows a processing procedure for updating the probabilities affixed 
to the individual nodes of the fault tree in accordance with the results 
of the diagnosis described previously by reference to FIG. 4. 
FIG. 17 shows a route through which the real data of the fault diagnosis 
and the repair are up-loaded from the locale, as described hereinbefore in 
conjunction with FIG. 2. The figure shows a network which extends to a 
factory from a local base at which the product quality data acquired from 
a customer are inputted. More specifically, upon occurrence of a fault in 
a product at an installation site of a user or customer, a maintenance 
engineer such as a serviceman who is responsible for dealing with the 
customers' claims repairs the product, whereon the information concerning 
the repair is transmitted on-line to the factory which are responsible for 
designing, manufacturing and inspection of the product through a business 
division such as a special agent or a business office on a 
repair-by-repair basis. More specifically, the product quality data 
acquired from a customer is inputted to a terminal 1701 installed at a 
special agent and sent to a computer 1702 installed at an associated 
business division, wherein data resulting from the edition performed by 
the computer 1702 is transferred to a similar large scale computer 1703 
which edits the data supplied from all the business division, so that they 
can be utilized in the factory, the result of this edition being stored in 
a large scale storage unit 1704 connected to the large scale computer 
1703. The large scale storage unit 1704 is imparted with a mail-box 
function so that large scale computers 1705 installed at factories or 
workshops such as "shop-1 computer", "shop-2 computer", "shop-3 computer", 
"shop 4 computer", and so forth can always make access to the large scale 
storage unit 1704 for reference. 
The maintenance engineer for the customers such as the serviceman inputs to 
the hand-held computer the type or model of the product as repaired, fault 
symptoms, part(s) as used, contents of the measures as taken and others in 
a predetermined format, a typical structure of which is shown in FIG. 18. 
The contents of the format include several ten items, of which primary 
ones (1) to (27) are mentioned below. 
(1) Classification of product . . . type and name of product. 
(2) Classification of charge/charge-free . . . discrimination of the repair 
as to whether it is to be charged or charge-free. 
(3) Reason for charge-free . . . reason why repair is free of charge. 
(4) Manufacturing number . . . ID number attached to each product for 
identification at the time of manufacture. 
(5) Part No. . . . ID number of the part used in the repair. 
(6) Card No. . . . unique number for the card identification. 
(7) Joint No. . . . ID number allocated serially to a part repaired 
simultaneously. 
(8) Reception No. . . . card number managed by a special agent or a 
distributor. 
(9) Division/agent/distributor classification . . . distinction of card 
issuers (business division or special agent or distributor). 
(10) Symptom . . . symptoms of fault. 
(11) Situation . . . times or conditions at or under which the fault takes 
place repetitionally. 
(12) Period of operation in month . . . number of months elapsed from the 
start of operation of the product at a customer to the occurrence of 
fault. 
(13) Special agent . . . special agent who disposed of the fault. 
(14) Business division . . . business division to which the special agent 
(13) belongs. 
(15) Classification of client . . . classification of repair request source 
(customer or distributor or special agent). 
(16) Classification of repairer . . . identification of repairer (internal 
or external). 
(17) Date of failure . . . date of repair. 
(18) Classification of guarantee . . . distinction as to whether or not a 
product of concern is within the term of guarantee. 
(19) Date of purchase of . . . date when a product of concern was purchased 
by the customer. 
(20) Classification of visitor/hospital repair . . . distinction as to 
whether repair was performed by dispatching an engineer to the locale or 
conducted after hospitalized in a factory. 
(21) Classification of repair contents . . . treatment performed for the 
removal of the fault. 
(22) Adjustment/rearrangement . . . factum of adjustment or rearrangement 
and symbol indicating a part adjusted or rearranged. 
(23) Classification of repair contents . . . discriminative identification 
of repair contents such as exchange of parts, inspection or the like. 
(24) Repair charge . . . cost involved in a fault removal (classified into 
the service fee and the cost of a part or parts). 
(25) Statistical date . . . date when the repair charge is registered. 
(26) Part name . . . name of a part retrofit. 
(27) Maker . . . name of manufacturer who manufactured the part subjected 
to the retrofit. 
In the factory, the information received from the mail-box and including 
the items mentioned above are added with undermentioned items (28) to (40) 
which are managed on the side of the manufacturer. 
(28) Type of product . . . model and type of a product. 
(29) Manufactural year . . . the manufactural year in which a product was 
manufactured (the manufactural year as set may differ from one to another 
product). 
(30) Year and month of manufacture . . . year and month in which a product 
was manufactured. 
(31) Product year . . . the year in which a product of the same model was 
first delivered to the market. 
(32) Lot number . . . identification number for managing products on the 
basis of production lots. 
(33) Circuit No. . . . numbers identifying parts on a substrate. 
(34) Trouble ID number . . . codes for identifying troubles of high 
importance for management. 
(35) Classification of measures . . . measures for coping with symptoms 
allocated with the trouble ID number mentioned above (33). 
(36) Disposal of failure . . . failure ascribable to the responsibility of 
the factory (charge-free even after lapse of the guarantee). 
(37) Disposal . . . identification codes of the measures taken for recovery 
from the failures. 
(38) Trouble lot number . . . lot number of the measure for coping with a 
large number of troubles of same symptom. 
(39) Classification of operating periods . . . classification of periods 
elapsed from the manufacture to the occurrence of failure. 
(40) Repair history . . . history of repairs in the past. 
The information concerning the repair and the product mentioned above is 
subjected to the analysis together with real sale data of a product. With 
the real sale data, it is intended to mean a quantity of products 
delivered from business divisions to special agents or a quantity of 
products delivered from the special agents to the distributors or a 
quantity of products shifted to customers from the distributors as 
determined for each type, month and business division, respectively. 
FIG. 19 shows faults of a product occurring in reality in the locale or 
field and deficiency in quality as well as relations between these 
factors. More specifically, this figure illustrates exemplarily the 
contents of the card mentioned above and the relations among the factors. 
EXAMPLE 1 
Case in which fault distribution in each special agent or business division 
which dealt with the fault removal depends on difference in service 
facilities and climate such as temperature and humidity which differs from 
one to another district. 
EXAMPLE 2 
Case in which fault occurrence distribution in each manufactural year, 
manufacturing number, manufacture year and month and production lot is 
attributable to the manufacturing history such as mixed use of faulty 
parts and change in the product specifications. 
EXAMPLE 3 
Case in which fault occurrence distribution per year and month in which 
repair was performed is ascribable to climate factors such as difference 
in temperature and humidity. 
EXAMPLE 4 
Case in which fault symptom occurrence distribution per part (module) 
subjected to the repair and per product type is attributable to specific 
product models and parts. 
EXAMPLE 5 
Case in which fault occurrence distribution per the number of months 
elapsed from the start of operation of a product till occurrence of fault 
or per class of the fault is ascribable to a specific fault pattern such 
as initial fault, accidental fault and worn fault. 
FIG. 20 shows a large scale computer installed at each factory for storing 
and managing quality data associated with the factory, which data are 
acquired from the large scale storage unit 1704 shown in FIG. 17 by 
issuing a transfer request, together with a work station designed for 
performing search and analysis of the quality data. Connected to the large 
scale computer 5 is a large scale storage unit 6 which stores 
customer-originated quality data for all the fault cases of all the 
products manufactured in the individual factories in the past. Search and 
analysis of the quality data are performed in the work station 7 which is 
equipped with an external storage unit 8 storing a database of the quality 
data. The result of the search and the analysis performed on the basis of 
the database are outputted to an external storage unit 9 or to a printer 
10. The work station 7 is connected to the large scale computer 5 through 
a high-speed network. Upon appearance of a request for data which do not 
exist in the database of the work station, they are sent to the work 
station through the network. 
FIG. 21 shows a configuration of software for performing search and 
analysis of the quality data in the work station 7 shown in FIG. 20. In 
the following, description will be made concerning individual modules 
having respective functions illustrated in FIG. 20. (i) A user interface 1 
serves for controlling activation and deactivation of the individual 
modules. (ii) An image display application 2 controls color graphic 
monitor displays by using a graphic package. (iii) An image control module 
3 serves for activation and deactivation of the image display application. 
(iv) An application activation/control module 4 serves for activation and 
deactivation of the individual modules. (v) A fault analysis module 5 is 
imparted with analysis functions for analyzing distributions, 
correlations, trends and others. (vi) A fault occurrence predicting module 
6 has a function for predicting a fault occurrence distribution by 
resorting to a hazard analysis. (vii) An alarm control module 7 has a 
function for managing costs estimated for the faults and availability of 
parts for the retrofit, the number of which is previously estimated. 
(viii) A free search module 8 indicates search of an intermediate file or 
the database on the basis of search items as designated. (ix) An 
intermediate file manage module 9 is in charge of management of the 
intermediate files and activation of a database search language. (x) A 
database manage module 10 is a database manager for performing management, 
updating and search of the database. (xi) A M-2050 COMMUNICATION module 11 
serves for controlling the data communications between the large scale 
computer and the work station by making use of inter-file communication 
packages. 
FIG. 22 shows contents of processings for performing the quality data 
search in the workstation. In the following, individual procedures 
involved in the processing flow for performing the search and the analysis 
will be described by reference to FIG. 22. On the basis of the search 
query set up through a procedure 1, search is performed through a 
procedure 2. The procedure 2 activates the database manage function of a 
procedure 3. Through the procedure 3, the database is searched in 
accordance with the search query or condition. Unless the data set of the 
database satisfies the search query or condition, apart of the data which 
is not common to the search query and the database, i.e. the data which 
does not exist in the database is transferred from the large scale 
computer by making use of a host access function of a procedure 4 and 
registered in the database. The result of the search performed through the 
procedure 2 is written in a core memory as a source data set 6. At that 
time, data values can directly be referred to for those items which are 
selected through a data set item selecting procedure 5. Analysis is 
performed on the data set written in the core memory. Through a procedure 
7, an analysis method is designated, which is followed by a procedure 8 
for selecting parameters involved in the analysis, whereon processing is 
performed through an analysis procedure 9. The analysis procedure 9 
performs arithmetic operation in accordance with the analysis method 
designated in the procedure 7. The result of the arithmetic operation is 
outputted in the form of an output format 12 which complies with the 
analysis method. With the arithmetic operation in accordance with the 
analysis method, it is intended to mean to perform calculation for each 
data item shown in FIG. 23B in accordance with a given one of management 
items shown in FIG. 23A. 
In the processing flow described above, a database manage/search method 
will be considered. When a search request is issued through the procedure 
2 shown in FIG. 22, the database manage function of the procedure 3 shown 
in FIG. 22 is activated, whereon the database is searched in the light of 
the search query. In that case, unless the data set of the database of the 
work station satisfies the search condition, a part of the data which is 
not common to the search query and the database, i.e. the data which does 
not exist in the database, is acquired from the large scale computer 
through the procedure 4 shown in FIG. 22 to be registered in the database. 
A processing procedure to this end is shown in FIG. 24. Starting from the 
search query statement, a query statement for the nonexistent data is 
created. In the light of this query, the large scale computer performs the 
search, the result of which is transferred to the work station. When there 
is available a sufficient disk space in the work station for storage, the 
data transferred from the large scale computer is registered. If 
otherwise, those query statements which indicate data groups which may be 
deleted from the disk are selected and the corresponding data are deleted. 
Thereafter, the transferred data are registered. 
FIGS. 25 and 26 show comprehensively products of sets for all the cases 
there inclusion relations between the data sets and the search queries are 
arithmetically determined and the case where the search query statements 
for the nonexistent data are created on the basis of the given search 
query statements. For all of the cases, the results of determination of 
the products between the conditions indicated in a first column (leftmost 
column) and a second column (center column) are shown in a third column 
(rightmost column). In the following, description will be made orderly of 
the individual cases. 
A: (upper row) A product between a condition of being equal to x and a 
condition of being equal to x indicates a condition of being equal to x. 
(lower row) A product between a condition of being equal to x and a 
condition of being equal to y represents an empty set. 
B: A product between a condition of being equal to x and a condition of 
being smaller than y indicates the condition of being equal to x in the 
case 1 where x&lt;y, while representing an empty set in the case 2 where x&gt;y. 
C: A product between a condition of being equal to x and a condition of 
being greater than y indicates the condition of being equal to x in the 
case 1 where x&gt;y, while representing an empty set in the case 2 where x&lt;y. 
D: A product between a condition of being equal to x and a condition of 
being greater than y and smaller than z represents an empty set in the 
case 1 where x&lt;y or in the case 2 where x&gt;z, while indicating a condition 
of being equal to x in the other cases than 3, 1 and 2. 
E: A product between a condition of being smaller than x and a condition of 
being smaller than y indicates a condition of being smaller than y in the 
case 1 where x&gt;y, while indicating a condition of being smaller than x in 
the case 2 where x&lt;y. 
F: A product between a condition of being smaller than x and a condition of 
being greater than y indicates a condition of being greater than x and 
smaller than y in the case 1 where x&gt;y, while representing an empty set in 
the case 2 where x&lt;y. 
G: A product between a condition of being smaller than x and a condition of 
being greater than y and smaller than z represents an empty set in the 
case 1 where x&lt;y, while indicating a condition of being greater than y and 
smaller than z in the case 2 where x&gt;z, and indicates a condition of being 
smaller than x in the other cases than 3, 1 and 2. 
H: A product between a condition of being greater than x and a condition of 
being greater than y indicates a condition of being greater than y in the 
case 1 where x&lt;y, while indicating a condition of being greater than x in 
the case 2 where x&gt;y. 
I: A product between a condition of being greater than x and a condition of 
being smaller than z represents an empty set in the case 1 where x&gt;z, 
while indicating a condition of being greater than y and smaller than z, 
and indicates a condition of being greater than x and smaller than z in 
the other cases than 3, 1 and 2. 
J: A product between a condition of being greater than x and smaller than y 
and a condition of being greater than z and smaller than w represents an 
empty set in the case 1 where y&lt;z, represents an empty set in the case 2 
where y&lt;z, represents an empty set in the case 2 where w&lt;z, indicates a 
condition of being greater than z and smaller than w in the case 3 where 
x&lt;z and w&lt;y, indicates a condition of being greater than z and smaller 
than y, indicates a condition of being greater than z and smaller than y 
in the case 4 where x&lt;z and w&gt;z, indicates a condition of being greater 
than x and smaller than y in the case 5 where x&gt;z and w&gt;y, and indicates a 
condition of being greater than x and smaller w in the case 6 where x&gt;z 
and w&lt;y. 
FIG. 27 is a functional diagram for illustrating processings involved in 
carrying out the data search in the work station. A search query manage 
program according to the present invention is composed of (1) creation of 
nonexistent search queries, (2) deletion of search query and creation of 
the deleted search query, (3) addition of queries, and (4) alteration and 
registration of resident query statements. Further, the creation of the 
non-existent query statement includes (1-2) arithmetic determination of 
the products between the query statements and the arithmetic determination 
of the products with complementary sets. The arithmetic determination 
(1-2) of the product between the query statements includes combination 
(1-2-1) of the results of calculation for determining the product of 
elements, while arithmetic determination of the products with the 
complementary sets includes the calculation (1-3-1) of complementary sets 
of elements and combinations (1-3-2) of products of the elements. Through 
the procedure (2) for deletion of the query statement and creation of the 
deleted query statement is accompanied with (2-1) creation of the 
nonexistent query statements. 
FIGS. 28 to 32 show in PAD diagrams further details of the major functions 
shown in FIG. 27. Referring to FIG. 28, it can be seen that when the query 
statement manage program is activated, either one of the functions (1) 
creation of a nonexistent query statement, (2) deletion of a query 
statement and creation of a deleted query statement, (3) addition of a 
query statement or (4) alteration and registration of a resident query 
statement is effectuated. FIG. 29 shows a procedure through which the 
function (1) of inquiry for a query condition and a nonexistent query 
statement shown in FIG. 28 is executed. This procedure will be described 
below stepwise. 
step 1: a query statement file is opened in a reference mode; 
step 2: a query condition table is created; 
step 3: input query statement is checked; 
step 4: products of all the query statements contained in the query 
statement table and the individual input query statements are computed, 
whereon those of having the empty result are deleted from the query 
statement table. 
step 5: Products of complementary sets of all the query statements 
contained in the query statement table and individual input query 
statements are computed, and fop the empty result, a message "included" is 
outputted. If otherwise, the products are sequentially multiplied by one 
another. 
FIG. 30 shows a procedure through which the function (2) of deletion of 
query statement and creation of the deleted query statement shown in FIG. 
28 is implemented. This procedure will be described stepwise. 
step 1: the query statement file is opened in an update mode; 
step 2: input query statement is deleted from the query 
statement file; 
step 3: function of inquiry about the query statement and creation of the 
nonexistent query statement is activated. 
FIG. 31 shows a procedure through which the function of alteration and 
registration of the resident query statement shown in 28 is activated. 
This procedure will be described below stepwise. 
step 1: the query statement file is opened in the update mode; 
step 2: input query statement is written in a query statement file; 
step 3: thee query statement file is closed. 
FIG. 32 illustrates a procedure through which the function (3) for addition 
of the query statement shown in FIG. 28 is implemented. This procedure 
will be described below stepwise. 
step 1: the query statement file is added in an addition mode; 
step 2: the input query statement is added to the query statement table; 
step 3: the query statement file is closed. 
FIG. 33 Shows file specifications for the query statement file destined for 
storing the search query statements which are subjected to the arithmetic 
operation. Further, FIG. 34 shows file specifications for an input/output 
parameter file adapted for storing elements of the query statements which 
are used for the data transaction with a program of a higher rank. 
Next description will be made of individual functions for performing the 
arithmetic operations on the results of the processings described above in 
accordance with the analysis method designated by the procedure 7 and 
outputting the results of the arithmetic operation in the form of the 
output format 12 which complies with the analysis method. 
(i) Transition diagram 
An example of a transition diagram is shown in FIG. 35. Owing to this 
function, the fault occurrence number, the repair cost and the fault ratio 
can each be classified up to five hierarchical levels at maximum and 
plotted time-serially. Parenthetically, the data values can be found in a 
data table. 
(ii) Bar graph 
An example of bar graph is illustrated in FIG. 36. Owing to this function, 
the fault occurrence number, the repair cost and the fault ratio can be 
illustrated hierarchically in category. Further, a specific categorical 
item may be displayed hierarchically in another category. Parenthetically, 
data value can be seen in the data table. 
(iii) Pareto diagram 
An example of a Pareto diagram is shown in FIG. 37. Owing to this function, 
the fault occurrence number, the repair cost and the repair rate can be 
categorically classified into hierarchical levels and displayed after 
having been sorted in the order of magnitude. Further, cumulative values 
of ratios of the individual item values to a sum value are plotted. The 
data value can be seen in the data table. 
(iv) Constituent ratio diagram 
An example of a constituent ratio diagram is shown in FIG. 38. Owing to 
this function, the fault occurrence number, the repair cost and the fault 
ratio are classified into main and subsidiary categories, wherein the main 
category is taken along the abscissa with the subsidiary category being 
taken along the ordinate to display the fault occurrence number, the 
repair cost and the fault ratio in terms of the constituent ratios. 
Parenthetically, the data value can be found from the data table. 
(v) Circular graph 
An example of a circular graph is shown in FIG. 39. Owing to this function, 
the fault occurrence number, the repair cost and the fault ratio can be 
categorically displayed. It is possible to display hierarchically a 
specific categorical item in another category. The data value can be seen 
in the data table. 
(vi) Dispersion diagram 
An example of a dispersion diagram is shown in FIG. 40. Owing to this 
function, a pair of data can be displayed in the form of a single point. 
The data value can be found in the data table. 
(vii) Specifications table 
An example of a specifications table is shown in FIG. 41. Owing to this 
function, data of the service cards as retrieved by the search can be 
rearranged in terms of the items and sorted (thrice at maximum), whereon 
specific data are extracted to be displayed in the form of a table. 
As will be appreciated from the above, with the aim of pursing the main 
cause of the faults of the products taking place actually in the field and 
deficiencies in the quality by performing arithmetic operation in 
accordance with the designated analysis methods and expanding the 
individual functions for outputting the results of the arithmetic 
operations in the output formats which comply with the analysis method, 
the processing for screening out the main cause and the outputting of the 
results of arithmetic operation can be executed in parallel with each 
other. Contents of such processing are exemplarily shown in FIGS. 42 to 
44. 
An example of the analysis performed on a product series of air 
conditioners will be considered, by way of example. At first, in the 
product series of air conditioners, the product which is to be improved 
with regard to the design and the inspection method is selected. To this 
end, the fault occurrence number, the repair cost, the fault ratio and 
others may hierarchically be classified in terms of the type or model and 
displayed. Result of this procedure is illustrated in FIG. 42. In this 
case, a product of a type T incurring a greatest monetary amount in the 
repair is selected as the object for the analysis. To this end, a bar 
indicating the repair cost of the product T shown in FIG. 42 is designated 
by a cursor and selected by clicking with a mouse. Thus, only the data of 
the products of this type are subjected to the analysis. In the products 
of the type T, those portions which are to be improved with regard to the 
design and the inspection are selected. This can be accomplished by 
classifying the fault occurrence numbers, the repair costs, the fault 
occurrence ratios for each constituent part and symptom. FIG. 43 shows a 
result of classification of the repair costs of the product type T for 
each of the constituent parts. In this conjunction, conditions for 
limiting the data subjected to the analysis are added sequentially to the 
table as the search queries, as indicated in a right column in FIG. 43. At 
this time point, a compressor requiring relatively lots of cost for the 
repair is selected as the object for the analysis. In this case, a bar 
indicating the monetary amount involved in repairing the compressor is 
designated by the cursor and selected by clicking with the mouse in the 
image shown in FIG. 43 in a similar manner as described previously. 
Consequently, only the data of the compressors of the products of the type 
T which experienced the fault can be screened out as the object for the 
analysis. Subsequently, in the products of the type T incorporating the 
compressors experienced the fault, those constituent parts which are to be 
improved in respect to the design and the inspection are selected. In this 
conjunction, a result of classification of the repair costs on the basis 
of the symptoms is illustrated in FIG. 44. As a result of the processings 
for screening out the main factor of the cause of fault, it can be 
determined that the product of the type T which incorporates the 
associated compressor experienced a fault in operation is one of the 
objects which is most important for improvement in the design and the 
inspection scheme. 
The processings illustrated in FIGS. 42 to 44 will be described below in 
detail. 
FIG. 45 shows a correlated data diagram for the fault factor analysis. With 
the fault factor analysis, it is intended to mean more detailed analysis 
and development of the content of the fault factors specified on the basis 
of the analysis data. 
The source data manage table is provided for managing the source data for 
the analysis, wherein each row represents one fault repair case. Data 
concerning one fault repair case includes a plurality of items each of 
which manages information independently. The data analysis is performed by 
carrying out a data processing method designated for one vertical row of 
the individual items. A source data number table is designed to store the 
number of data stored in the source data manage table. 
An analysis tool manage table is provided for managing information to be 
utilized in performing analysis on the source data and contains an item 
for analysis, a data processing method and an analysis method. The 
analysis item stores the item number (1-L) of the source data for which 
the analysis is performed. The data processing method item contains the 
type of arithmetic operation to be performed on the analysis item 
designated. The analysis method item stores the type of image for 
displaying the result of the analysis as performed. For the analysis items 
managed by the analysis tool manage table, arithmetic operation is 
performed in accordance with the data processing method as designated. The 
result of the analysis is displayed in accordance with the analysis method 
as designated. 
A factor analysis table serves for storing as the content of factor 
analysis the content of one item designated by the analysis data which is 
the information required for the factor analysis and which is designated 
by the analysis tool manage table in accordance with the analysis method. 
A factor analysis number table serves for managing the number of data 
stored in the factor analysis table. When a plurality of data are stored 
in the factor analysis manage table, comparison is performed successively 
a number of times corresponding to the factor analysis number for 
determining whether or not the factor analysis content of the analysis 
items coincides with the one case data of the source data manage table. 
When coincidence is found for all the analysis, items, decision is made 
that the data are to be subject to the factor analysis, whereon the 
analysis is performed on the data processing method stored in the analysis 
tool manage table. 
FIG. 46 shows a specific factor analysis processing flow. 
In this processing flow, it is assumed that the data are previously set in 
the source data manage table and the source data number table in the data 
correlation diagram shown in FIG. 45. 
At first, the factor analysis number in the factorial analysis number table 
is cleared. Subsequently, the analysis method, the item for analysis and 
the data processing method which constitute the information managed by the 
analysis procedure manage table are designated and placed in the table. 
Source data is analyzed in accordance with the information set in the 
analysis procedure manage table. The result of the analysis is displayed 
in accordance with the analysis method which is the information contained 
in the analysis procedure manage table. Subsequently, on the basis of the 
analysis result, decision is made as to whether or not the content of a 
specific factor is to be analyzed and developed in more detail. When the 
analysis is to be performed on the specific factor, the content of one of 
the items for the analysis being displayed is designated in dependence on 
the analysis method contained in the analysis tool manage table. The 
designated content for the factor analysis is saved in the factor analysis 
manage table. Further, the contents (analysis method, item for analysis 
and data processing method) of the analysis tool manage table indicating 
the current content for the analysis are saved in the factor analysis 
manage table. Subsequently, a factor analysis number counter is 
incremented by one, whereupon saving of the current analytical information 
is completed. For performing a specific factor analysis, information 
managed in the analysis procedure manage table is designated. Unless the 
processing for the specific factor analysis is performed, decision is made 
as to whether or not the preceding specific factor analysis is to be 
restored or not. If it is to be restored, processing mentioned below is 
performed. From the factor analysis manage table, the analysis method, the 
item for the analysis and the data processing method are set in the 
analysis tool manage table. The factor analysis number counter is 
decremented by one to thereby restore the analysis data. When the 
information has been set in the analysis procedure manage table from the 
factor analysis manage table, the source data analysis is performed, the 
result of which is then displayed. Unless the specific factor analysis is 
restored, the whole processing now under consideration is completed. 
FIG. 47 shows a source data analysis processing flow. 
This flow illustrates the data processing method carried out on the 
contents of the source manage table in accordance with the information 
contained in the analysis tool manage table. 
In the first place, a source data read counter is cleared. Next, content of 
the item for the analysis is read out from the source data manage table. 
It is then decided whether the factor analysis is to be performed or not 
in dependence on whether the value of the factor analysis number table is 
zero or not. When the factor analysis is to be performed, a factor 
analysis comparison number counter is cleared. Content of the factor 
analysis is then read out from the factor analysis manage table, whereon 
decision is made as to whether or not the content of the factor analysis 
coincides with the item for the analysis which is stored in the factor 
analysis manage table for the source data. When coincidence is found, the 
comparison number counter is incremented by one. When the value of the 
comparison number counter becomes equal to the factor analysis number, it 
is then decided that the read position data equal to the value of the 
source data read counter is the data for the analysis of the specific 
factor. Subsequently, the item for the analysis contained in the analysis 
tool manage table is analyzed in accordance with the data processing 
method. Unless the item of the source data is equal to the content of the 
factor analysis or unless the factor analysis is to be performed, no data 
processing is carried out. Next, the source data read counter is 
incremented by one. In this manner, the contents of the items for the 
analysis read out from the abovementioned source data manage table are 
processed in accordance with the value of the source data read counter 
until the value of the source data number table becomes equal to the 
number of times the read operation was performed. 
Next, description will turn to a scheme for estimating fault occurrences in 
the future on the basis of the current fault occurrence and the product 
shipping data. First, procedures involved in this scheme are mentioned 
below. 
step 1: a total number N(t) of operating products and a number r(t) of 
faults as occurred are determined over a number of months (t) in which the 
products were put into operation. 
step 2: a fault ratio is determined in accordance with 
.lambda.(t)=r(t)/N(t). 
step 3: (lnt, ln.SIGMA..lambda. (t)) is plotted on a hazard probability 
sheet. 
step 4: Straight lines or polygonal lines are applied to the plotted points 
and the line exhibiting a best fit is selected. 
step 5: parameters (m, .eta.) of the fault distribution (Weibull 
distribution) are determined on the basis of the gradient and intercept of 
the straight line. 
step 6: a cumulative fault ratio F(t)=.intg.f(t)dt in an assumed month t is 
determined by using the parameter determined in the step 5 and based on 
the 
##EQU1## 
equation f(t)=. step 7: A cumulative fault occurrence number in an assumed 
month is determined in accordance with .SIGMA.n(t).multidot.F(t) (where 
n(t) represents the number of products as sold in each month (t)). 
step 8: An accumulated rate of faults in an assumed month is determined in 
accordance with .SIGMA.n(t).multidot.F(t)N (where N=.SIGMA.N(t)), 
representing a total number of products as sold). 
FIG. 48 shows the processing in more concrete. 
As is shown in this figure at a leftmost column, at a time point when a 
fault,takes place in a product, type of that product, symptom of the 
fault, parts, contents of the disposal and other information are reported 
in the form of a card. In this conjunction, it is to be noted that the 
time pint at which the products were started to operate differs from one 
to another, in the contrast to the case of life test. Under the 
circumstances, the failure ratio is calculated on the basis of the number 
of months in which the products were operated, as indicated at an upper 
left field in the rightmost column of FIG. 48. Starting from the fault 
ratio, the cumulative hazard values are determined and plotted relative to 
the number of the months over which the product was operated. On the basis 
of the slope and the intercept of a straight line approximating the plot, 
the fault occurrence estimation is performed. As a model for this 
estimation, the Weibull distribution is made use of. By using as the 
Weibull parameters the slope m and the intercept m.multidot.1n.eta. 
determined through the linear approximation, the fault occurrence is 
estimated in accordance with a function f(t) shown in a lower left 
portion. In the Weibull distribution, it globally applies that m&lt;1 
represents a pattern in which a relatively large number of faults occur in 
an earlier stage after the products having been put into operation, while 
m&gt;1 represents a pattern in which faults are ascribable to wearing. In the 
case of a pattern represented by m=1, the fault is of accidental nature. 
According to the present invention, it is possible to pinpoint the cause of 
a fault occurring in a machine by searching along a fault tree starting 
from a symptom of the fault upon occurrence thereof in the course of use 
of the machine by a customer, to thereby indicate the appropriate measures 
such as adjustment, repair and the like. By virtue of this feature, the 
number of visits on the customer for the repair, the turn-around time 
taken till the complete recovery, the number of constituent parts required 
in the repair and the like can be reduced, to an advantageous effect. 
Since the search and analysis of the quality data can be performed in the 
work station according to the invention, the sequence of the 
search/analysis request, the processing and the output can be executed on 
a real-time basis, whereby the turn-around time involved in the analysis 
work can be reduced, to another advantageous effect. 
According to the invention, information concerning the repairs collected 
primarily in the field by the customer's product maintenance engineers 
such as servicemen who are dispatched to the customers upon occurrence of 
faults in their machines can instantaneously be fed back on a 
repair-by-repair basis to a factory which is responsible for the design, 
manufacture and the inspection of the machine by way of the business 
divisions such as the specific agent, business office or the like. Owing 
to this feature, it is possible to perform design improvement of the 
products being manufactured as well as improvement of the 
evaluation/inspection systems for the parts as used in an earlier stage. 
Besides, reliability can be improved in the design of new products. 
Since the search/analysis of the quality data can be performed in the work 
station without relying on external means, the sequence of the search, the 
analysis request, the processing and the output can be executed on a 
real-time basis, whereby the turn-around time involved in the analysis 
work can be reduced. 
Further, by searching the source data on a record-by-record basis and 
developing the data on the memory in the workstation, there can be 
realized not only the analysis for each item of data concerning the fault 
and the repair of a product but also the analysis for all combinations of 
the items.