JP4704769B2 - Repair estimate output device, repair estimate output method, repair estimate output program, and repair estimate output system - Google Patents

Description

  The present invention relates to a repair estimated amount output device, a repair estimated amount output method, a repair estimated amount output program, and a repair estimated amount output system for estimating an amount (repair amount) required for repair based on the actual amount of money required for repair.

  Estimating the amount of repair and presenting it to the user, in view of the problem that the estimated amount varies depending on the experience and skill of the person who estimates, to prevent variations in the estimated amount due to the experience and skill of the person who estimates (For example, see Patent Document 1)

For example, home appliances have various product categories (TV, refrigerator, etc.), and there are various product types even in the same product category. Furthermore, there are various types of failure symptoms.
The cost of repair is not always constant, even for the same product category or model and the same type of failure symptoms. This is because, for example, even if the symptoms are the same type of failure, the parts that need to be replaced for repair are not necessarily the same, there is a price difference in the parts to be replaced, and multiple parts This is because there are times when it must be exchanged.
JP-A-6-259439

  For this reason, for example, when a product user asks the service center for repairs, the service center operator answers the request, and when the service center operator responds to the request, the repair is actually carried out from the returned repair amount (estimated amount). Often, the cost (invoiced amount) of the cost increases. In particular, when a plurality of parts have to be replaced, or when the number of parts to be replaced is high, the billing amount may be considerably higher than the estimated amount answered by the operator. In such a case, the user who requested the repair is very dissatisfied and may cause trouble (the user only pays the estimated amount answered by the operator).

  However, in the above prior art document (Japanese Patent Laid-Open No. 6-259439), it is possible to prevent variations in the estimated amount, but it is possible to prevent the actual cost for repair from becoming higher than the estimated amount to cause trouble. It is not something that can be done.

  In addition, when the user decides whether to repair and continue using the product or replace it, the actual cost (minimum, average, maximum) of the past repair costs for the same failure symptom, for example, Although it is considered to be effective as a judgment material, there is no description related to this in the above prior art document (Japanese Patent Laid-Open No. 6-259439).

  Accordingly, the present invention provides a repair estimated amount output device, a repair estimated amount output method, a repair estimated amount output program, and a repair estimated amount output system that allow a user of a product to reply with an estimated amount within a range that matches the actual situation. The purpose is to provide.

  The repair estimated amount output device according to the present invention associates product information for identifying a product with a failure symptom in the repair estimated amount output device (2) for estimating a repair amount required for repairing a failed product. Repair amount storage means (2b) for storing an average amount, a minimum amount and a maximum amount of repair amount so far required for repairing the symptom of the failure in the product included in the product information, and input product information And an estimated amount extracting means (2f) for taking out the average amount, the minimum amount and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the trouble symptom and the trouble symptom And an estimated amount output means (2g) for outputting the average amount, the minimum amount, and the maximum amount taken out by the estimated amount extraction means.

  The repair estimated amount output device further includes information content determining means (2e) for determining whether or not a failure symptom is included in the input information, wherein the repair amount storage means includes product information and failure information. The average amount, the minimum amount, and the maximum amount of the repair amount so far required for repair in the product included in the product information in association with the symptom irrelevant information indicating that the type of symptom is not related are stored, and the estimated amount When the information content determination means determines that the failure symptom is included, the extraction means uses the product information and the failure symptom that are input, and uses the product amount information and the failure from the repair amount storage means. The average amount, the minimum amount, and the maximum amount stored in association with the symptom of the patient are taken out, and the product information that is input is used when it is determined by the information content determination means that no failure symptom is included Then said repair Taking out the average value stored in association with the forehead storage means and said product information and said condition independent information and minimum amount and maximum amount.

  The repair estimated amount output method of the present invention relates to product information for distinguishing products and failure symptoms, and averages the repair amount so far required to repair the failure symptoms in the products included in the product information. Repair amount storage means (2b) for storing the amount, the minimum amount, and the maximum amount, and the repair amount performed in the repair estimated amount output device (2) for estimating the repair amount required to repair the product in which the failure has occurred In the estimated output method, the average amount, the minimum amount, and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the product information and the failure symptom inputted. The estimated amount extraction procedure (S205, S207) for extracting the estimated amount and the estimated amount output procedure (S213) for outputting the average amount, the minimum amount, and the maximum amount extracted in the estimated amount extraction procedure.

  The repair estimated amount output program according to the present invention relates product information for distinguishing products to failure symptoms, and averages the repair amount so far required for repairing the failure symptoms in the products included in the product information. A computer as a repair estimated amount output device (2) that includes a repair amount storage means (2b) for storing the amount, the minimum amount, and the maximum amount, and estimates a repair amount required for repairing a product in which a failure has occurred; Extracting the estimated amount by extracting the average amount, the minimum amount and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the input product information and the failure symptom Means (2f), and estimated amount output means (2g) for outputting the average amount, the minimum amount, and the maximum amount extracted by the estimated amount extraction means

  The repair estimated amount output system of the present invention includes a server device (2) for estimating a repair amount required to repair a product in which a failure has occurred, and a client terminal device (3) connected to the server device so as to be able to exchange data. In the estimated repair amount output system (1), the server device correlates with product information for distinguishing products and a symptom of failure, and this is required for repair of the symptom of the failure in a product included in the product information. Repair amount storage means (2b) for storing an average amount, a minimum amount, and a maximum amount of repair amount up to, an information receiving means (2d) for receiving product information and a symptom of failure from the client terminal device, An average amount and a minimum amount stored in association with the product information and the failure symptom from the repair amount storage unit using product information and failure symptoms received by the information receiving unit, Estimated amount extraction means (2f) for extracting a high amount, and estimated amount transmission means (2g) for transmitting the average amount, minimum amount, and maximum amount extracted by the estimated amount extraction means to the client terminal device. The client terminal device includes information transmission means (3c) for transmitting input product information and failure symptoms to the server device, and an average amount, a minimum amount, and a maximum amount of repair amounts transmitted from the server device. Estimated amount receiving means (3d), and a repair amount notifying means (3a) for notifying an average amount, a minimum amount and a maximum amount of repair amount received by the estimated amount receiving means.

  It should be noted that “(sign)” referred to in this column only exemplifies a corresponding configuration in a column (the best mode for carrying out the invention) to be described later, and does not indicate any claim in the claims. The interpretation is not limited.

  According to the present invention, an operator who has received an inquiry from a user can reply to the product user with an estimated amount (minimum amount, average amount, maximum amount) in a range that matches the actual situation. As a result, it is possible to prevent the cost actually required for repair from becoming the cause of trouble from the estimated amount presented to the user. Further, it can be used as a material for determining whether the user repairs the failed product and continues to use it or replaces it.

  Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings.

  First, the configuration of the repair estimated amount output system in the embodiment of the present invention will be described with reference to FIG. FIG. 1 is a diagram showing a system configuration of a repair estimated amount output system in the present embodiment. The repair estimated amount output system 1 shown in FIG. 1 includes a server device (repair estimated amount output device) 2 and a client terminal device 3 connected to the server device 2 so as to be able to exchange data. Although there may be a plurality of client terminal devices 3, only one is shown in FIG. In this embodiment, each of the product category and the model is product information for distinguishing the product. However, only one of the product category and the model is used as the product information. May be.

  The client terminal device 3 is used, for example, by an operator of a service center, and the client terminal device 3 transmits information input by the operator to the server device 2. Further, the client terminal device 3 receives the minimum amount, the average amount, and the maximum amount of the repair amount estimated to be repaired by the server device 2 from the server device 2, and receives the received minimum amount, average amount, and maximum amount. Is displayed. However, in some cases, the client terminal device 3 receives no approximate estimate from the server device 2 and indicates no approximate estimate.

  Here, as patterns of information transmitted from the client terminal device 3 to the server device 2, (1) product type and failure symptom (may include product category), (2) product category and failure symptom (product (3) Model (may include product category but does not include failure symptom), (4) Product category (not include product category and failure symptom) . The four patterns are used when the user who makes an inquiry to the service center knows the product category (for example, television) to which the failed product belongs, but does not know the product type, but knows that the product has failed. This is because it is assumed that there are cases where the symptom of the failure is unknown. In the present embodiment, it is assumed that the user who makes an inquiry to the service center does not know the product category.

  The server device 2 estimates the minimum, average, and maximum repair amount required for repair from the information received from the client terminal device 3 (details will be described later), and the estimated minimum, average, and maximum repair amount Is transmitted to the client terminal device 3. However, there is a case where the server apparatus 2 transmits “no rough estimate” to the client terminal apparatus 3.

  Next, functions of the server device 2 in FIG. 1 will be described with reference to FIG. FIG. 2 is a functional block diagram showing a functional configuration of the server apparatus 2 of FIG. As shown in FIG. 2, the server device 2 includes a repair history database 2a, an approximate estimate database 2b, an aggregation processing unit 2c, an information reception determination unit 2d, a received content determination unit 2e, an estimated amount extraction unit 2f, and an estimated amount transmission process. Each part functions as the part 2g.

  The repair history database 2a stores the contents of repairs actually performed by the worker for failures that have occurred in the product in the past, an example of which is shown in FIG. As shown in FIG. 3, the repair record data held in the record of the repair history database 2a includes the product category to which the product to be repaired belongs, the model of the product, and the symptom of the failure to be repaired (image blurring, Not to dehydrate) and the actual repair cost for repair.

  The rough estimate database 2b stores a total result of totaling past repair contents stored in the repair history database 2a, and an example thereof is shown in FIG. As shown in FIG. 4, the rough estimate data held in the record of the rough estimate database 2b includes a product category, a product type, a failure symptom, the number of repairs, an average amount, a minimum amount, and a maximum amount.

However, as described above, when the user who has inquired the service center knows the product category to which the failed product belongs, but does not know the product type, the user knows that the product has failed, but the symptoms of the failure Since it is assumed that there is a case where it is not known, the rough estimate database 2b holds the following four rough estimate data.
(A) Regardless of the product type and failure symptom, repair result data is aggregated for products belonging to the product category. The “product category” of the rough estimate data includes the target product category and “model”. Is not related to model, "symptom of failure" is not related to symptom, "number of repairs" is the number of repairs of products belonging to the target product category, and "average amount" is the repair cost of products belonging to the target product category The minimum amount of the product belonging to the target product category is stored in the “minimum amount”, and the maximum amount of the repair cost of the product belonging to the target product category is stored in the “maximum amount”.
(B) Regardless of the symptom of failure, this is a summary of repair performance data for products belonging to a model, and the estimated product data “product category” of the rough estimate data is the target product category, “model” is the target model, There is no symptom relationship for "symptom of failure", "number of repairs" is the number of repairs of products belonging to the target model, "average amount" is the average amount of repair costs for products belonging to the target model, and "minimum amount" Is stored in the minimum repair cost of the product belonging to the target model, and the maximum repair cost of the product belonging to the target model is stored in the “maximum amount”.

(C) Regardless of the product type, the repair result data is aggregated for products belonging to the product category regarding the failure symptoms. The “product category” of the rough estimate data is the target product category and the “model”. Is not related to the model, "symptom of failure" is the symptom of the target failure, "number of repairs" is the number of repairs of products in the target product category in the symptom of the target failure, and "average value" is the target failure The average repair cost of products belonging to the target product category in the symptoms of `` Symptoms '', `` Minimum amount '' is the minimum repair cost of products belonging to the target product category in the symptom of the target failure, `` Highest '' is the target The maximum repair cost of the product belonging to the target product category in the symptoms of failure is stored.
(D) This is a summary of repair performance data for products belonging to the model with respect to the symptoms of the failure. The “product category” of the rough estimate data is the target product category, the “model” is the target model, and the “failure "Symptoms" indicates the target failure symptom, "Repairs" indicates the number of repairs of the product belonging to the target model in the target failure symptom, and "Average" indicates the product belonging to the target model in the target failure symptom The average repair cost of the product, “Minimum” is the minimum repair cost of the product belonging to the target model in the target failure symptom, and “Maximum” is the product belonging to the target model in the target malfunction symptom The highest repair cost is stored.

  The tabulation processing unit 2c uses the repair record data stored in the repair history database 2a to tabulate the four types of approximate estimate data (A) to (D).

The information reception determination unit 2d determines whether or not information is received from the client terminal device 3, and outputs the information received from the client terminal device 3 to the reception content determination unit 2e and the estimated amount extraction unit 2f.
The reception content determination unit 2e determines whether or not the information input from the information reception determination unit 2d includes a failure symptom and determines whether or not the input information includes a model. . Then, the received content determination unit 2d outputs the determination result to the estimated amount extraction unit 2f.

  When the determination result input from the received content determination unit 2e indicates that the reception information includes both the failure symptom and the model, the estimated amount extraction unit 2f stores the model and the failure symptom in the approximate estimation database 2b. As a key, the estimated estimate data in which the content of the “failure symptom” and the content of the “model” match each of the failure symptom and the type input from the information reception determination unit 2d is searched. The estimated amount extraction unit 2f extracts the average amount, the minimum amount, and the maximum amount from the “average amount”, “minimum amount”, and “maximum amount” of the estimated estimated data found as a result of the search, and extracts the average amount The minimum amount and the maximum amount are output to the estimated amount transmission processing unit 2g. The estimated amount extraction unit 2 f outputs “no estimated estimate” to the estimated amount transmission processing unit 2 g if no approximate estimated data matching the search result is found.

  Further, the estimated amount extraction unit 2f, when the determination result input from the received content determination unit 2e indicates that the reception information includes a failure symptom but does not include a model, In “2b”, “product category” is used for each of the product category input from the information reception determination unit 2d using the product category, the model, and the failure symptom as a key, no type relationship, and the failure symptom input from the information reception determination unit 2d. Approximate estimation data in which the contents of “model” and “failure symptoms” match are retrieved. The estimated amount extraction unit 2f extracts the average amount, the minimum amount, and the maximum amount from the “average amount”, “minimum amount”, and “maximum amount” of the estimated estimated data found as a result of the search, and extracts the average amount The minimum amount and the maximum amount are output to the estimated amount transmission processing unit 2g. The estimated amount extraction unit 2 f outputs “no estimated estimate” to the estimated amount transmission processing unit 2 g if no approximate estimated data matching the search result is found.

  Further, the estimated amount extracting unit 2f, when the determination result input from the received content determining unit 2e indicates that the received information does not include the failure symptom but includes the type, the estimated estimated database 2b. Approximate estimated data in which the contents of “model” and “failure symptom” match each of the model input from the information reception determination unit 2d and no symptom relation, using the model and the symptom of failure as keys. To do. The estimated amount extraction unit 2f extracts the average amount, the minimum amount, and the maximum amount from the “average amount”, “minimum amount”, and “maximum amount” of the estimated estimated data found as a result of the search, and extracts the average amount The minimum amount and the maximum amount are output to the estimated amount transmission processing unit 2g. The estimated amount extraction unit 2 f outputs “no estimated estimate” to the estimated amount transmission processing unit 2 g if no approximate estimated data matching the search result is found.

  Further, the estimated amount extraction unit 2f, when the determination result input from the received content determination unit 2e indicates that the received information does not include the failure symptom or model, the estimated amount database 2b The contents of “product category”, the contents of “model”, and the “symptom of failure” for the product category input from the information reception determination unit 2d using the model and the failure symptom as keys and no relationship between the model and no symptom relationship, respectively. Search for rough estimate data that matches the contents of. The estimated amount extraction unit 2f extracts the average amount, the minimum amount, and the maximum amount from the “average amount”, “minimum amount”, and “maximum amount” of the estimated estimated data found as a result of the search, and extracts the average amount The minimum amount and the maximum amount are output to the estimated amount transmission processing unit 2g. The estimated amount extraction unit 2 f outputs “no estimated estimate” to the estimated amount transmission processing unit 2 g if no approximate estimated data matching the search result is found.

  The estimated amount transmission processing unit 2g transmits the average amount, the minimum amount, and the maximum amount input from the estimated amount extraction unit 2f to the client terminal device 3. Alternatively, the estimated amount transmission processing unit 2g transmits to the client terminal device 3 no approximate estimate input from the estimated amount extraction unit 2f.

Next, functions of the client terminal device 3 of FIG. 1 will be described with reference to FIG. FIG. 5 is a functional block diagram showing a functional configuration of the client terminal device 3 of FIG. As illustrated in FIG. 5, the client terminal device 3 includes units that function as a display unit 3a, an input unit 3b, an information transmission processing unit 3c, and an information reception processing unit 3d.
The display unit 3a is a display device including, for example, a CRT (Cathode Ray Tube), a liquid crystal display, and the like, and a repair estimate operation screen shown in FIG. 6 as an example is displayed on the display unit. FIG. 6A shows before execution, and FIG. 6B shows after execution.

As shown in FIG. 6, on the repair estimate operation screen, a product category input field 31 for inputting the product category of the product requested for repair and a model for inputting the model of the product requested for repair. There are an input field 32 and a symptom input field 33 for inputting a symptom of a failure that has occurred in the product requested for repair.
The repair estimate operation screen has an execution button 34 that is pressed when the input contents of the product category input field 31, the model input field 32, and the symptom input field 33 are transmitted to the server device 2. .
Further, on the estimated repair amount operation screen, a minimum amount display area 35, an average amount display area 36, and a maximum amount display area 37 for displaying the minimum amount, the average amount, and the maximum amount sent from the server device 2, respectively. There is. In addition, the repair estimated amount operation screen includes a box 38 that is checked when an approximate estimate is not sent from the server device 2.

The input unit 3b is an input device configured by a pointing device such as a keyboard and a mouse. Using the input unit 3b, the operator was able to hear only the product category input field 31, the model input field 32, and the symptom input field 33 that could be heard from the user who inquired the estimated repair amount. The contents are input and the execution button 34 is clicked.
However, the input pattern includes (a) an input to the model input field 32 and an input to the symptom input field 33 (including a case where the input is made to the product category input field 31 and a case where it is not inputted), and (b) a product category. Input to the input field 31 and input to the symptom input field 33 (no input to the model input field 32), (c) input to the model input field 32 (whether or not input to the product category input field 31) (D) input to the product category input field 31 (input to the model input field 32 and no input to the symptom input field 33).

  The information transmission processing unit 3c determines whether or not the execution button 34 has been pressed. If it is determined that the execution button 34 has been pressed, the input input in the product category input field 31, the model input field 32, and the symptom input field 33 is performed. The contents are transmitted to the server device 2.

  The information reception processing unit 3d determines whether or not information has been received from the server device 2, and if it is determined that the information has been received, the received information further includes the minimum, average, and maximum repair estimates. Or whether there is no rough estimate. Then, when the information reception processing unit 3d determines that the received information is the minimum, average, and maximum amount of the estimated repair amount, it displays the minimum amount on the estimated repair amount operation screen displayed on the display unit 3a. The area 35, the average amount display area 36, and the maximum amount display area 37 are displayed. Further, when the information reception processing unit 3d determines that the received information has no rough estimate, the information reception processing unit 3d checks the box 38.

Hereinafter, the repair history counting process performed in the server apparatus 2 described with reference to FIGS. 2 to 4 will be described with reference to FIGS. 7 to 10. 7 to 10 are flowcharts showing the procedure of the repair history counting process performed in the server device 2.
Steps S101 to S115 are processing steps for performing a totaling process for totaling repair performance data for products belonging to the model regarding the failure symptom, and the totalization processing unit 2c pays attention to the first record in the repair history database 2a (step S101). S101). The totalization processing unit 2c determines whether or not there is repair record data in the record of interest (step S102). If it is determined that there is repair record data (S102: YES), the process proceeds to the process of step S103, and the repair record is obtained. If it is determined that there is no data (S102: NO), the process proceeds to step S116.

  The totalization processing unit 2c sets the “product category” for each of the product category, the model, and the failure symptom of the repair performance data of the record that is focused on using the product category, the model, and the failure symptom as keys in the rough estimate database 2b. The rough estimated data in which the content, the content of the “model” and the content of the “symptom of failure” are matched is searched, and it is determined whether there is a rough estimated data that matches (step S103). If matching rough estimate data is found (S103: YES), the process proceeds to step S104. If no matching rough estimate data is found (S103: NO), the process proceeds to step S110.

  The totalization processing unit 2c multiplies the value of the “average amount” of the found rough estimate data and the value of “the number of repairs”, and obtains the value of “repair cost” of the repair result data of the record that focuses on the multiplied value. Add the value and divide the value by adding 1 to the value of “Number of repairs” in the estimated estimate data found, and update the value of “Average amount” in the estimated estimate data found to be the divided value (average amount ← ( (Average amount × number of repairs + repair cost) / (number of repairs + 1)) (step S104).

  The aggregation processing unit 2c determines whether or not the “repair amount” value of the repair record data of the record of interest is larger than the “maximum amount” value of the estimated approximate data found (step S105). If it is determined that the value is larger (S105: YES), the process proceeds to step S106, and the aggregation processing unit 2c “repair” of the repair result data of the record that focuses on the “maximum amount” value of the found rough estimate data. The value is updated to “cost” (maximum amount ← repair cost) (step S106), and the process proceeds to step S107. On the other hand, if it is determined that it is not large (S105: NO), the process proceeds to step S107.

  The aggregation processing unit 2c determines whether or not the “repair amount” value of the repair record data of the record of interest is smaller than the “minimum amount” value of the estimated approximate data found (step S107). If it is determined that the value is smaller (S107: YES), the process proceeds to step S108, and the totalization processing unit 2c “repair” of the repair result data of the record focusing on the “minimum amount” value of the found estimated estimate data. The value is updated to “cost” (minimum amount ← repair cost) (step S108), and the process proceeds to step S109. On the other hand, if it is determined that it is not small (S107: NO), the process proceeds to step S109.

  The totalization processing unit 2c updates the value of the “number of repairs” in the found approximate estimation data to a value obtained by adding 1 (the number of repairs ← the number of repairs + 1) (step S109), and proceeds to the process of step 115.

The totalization processing unit 2c includes the contents of the “product category” of the repair result data of the record focused on the rough estimate database 2b, the “type” of the repair result data, and the “symptom of failure” of the repair result data. An entry of approximate estimate data with contents is newly added (step S110).
The totalization processing unit 2c sets the value of the “number of repairs” in the newly added estimated estimate data to 1 (the number of repairs ← 1) (step S111).

The totalization processing unit 2c sets the “average amount” value of the newly added estimated estimate data as the “repair cost” value of the repair performance data of the record being noticed (average amount ← repair cost) (step S112). .
The totalization processing unit 2c sets the “maximum amount” value of the newly added estimated estimate data as the “repair cost” value of the repair performance data of the record in which attention is paid (maximum amount ← repair cost) (step S113). .
The totalization processing unit 2c sets the value of “repair cost” of the repair result data of the record that is focused on the value of “minimum amount” of the newly added estimated estimate data (minimum amount ← repair cost) (step S114), The process proceeds to step S115.
The aggregation processing unit 2c pays attention to the next record in the repair history database 2a (step S115), and returns to the process of step S102.

  Steps S116 to S130 are processing steps for performing a totaling process for totaling repair performance data for products belonging to the product category with respect to the failure symptom, and the totalization processing unit 2c pays attention to the first record in the repair history database 2a ( Step S116). The totalization processing unit 2c determines whether or not there is repair record data in the record of interest (step S117). If it is determined that there is repair record data (S117: YES), the process proceeds to the process of step S118, and the repair record is obtained. If it is determined that there is no data (S117: NO), the process proceeds to step S131.

  The tabulation processing unit 2c has the relationship between the product category and the model of the repair result data of the record focused on the product category, the model, and the failure symptom as a key in the rough estimate database 2b, and the failure symptom of the repair result data, respectively. Is searched for approximate estimated data in which the contents of “product category”, “model”, and “failure symptom” match, and it is determined whether there is the approximate estimated data that matches (step S118). If matching approximate estimation data is found (S118: YES), the process proceeds to step S1119. If no matching approximate estimation data is found (S118: NO), the process proceeds to step S125.

  The totalization processing unit 2c multiplies the value of the “average amount” of the found rough estimate data and the value of “the number of repairs”, and obtains the value of “repair cost” of the repair result data of the record that focuses on the multiplied value. Add the value and divide the value by adding 1 to the value of “Number of repairs” in the estimated estimate data found, and update the value of “Average amount” in the estimated estimate data found to be the divided value (average amount ← ( (Average amount × number of repairs + repair cost) / (number of repairs + 1)) (step S119).

  The aggregation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is larger than the “maximum amount” value of the estimated approximate data found (step S120). If it is determined that the value is larger (S120: YES), the process proceeds to the process of step S121, and the tabulation processing unit 2c pays attention to the “maximum amount” value of the found rough estimate data in the field “ The value is updated to “repair cost” (maximum amount ← repair cost) (step S121), and the process proceeds to step S122. On the other hand, if it is determined that it is not large (S121: NO), the process proceeds to step S122.

  The aggregation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is smaller than the “minimum amount” value of the estimated approximate data found (step S122). If it is determined that the value is smaller (S122: YES), the process proceeds to step S123, and the totalization processing unit 2c “repair” of the repair history data of the record in which the value of the “minimum amount” of the found approximate estimate data is noted. The value is updated to “cost” (minimum amount ← repair cost) (step S123), and the process proceeds to step S124. On the other hand, if it is determined that it is not small (S122: NO), the process proceeds to step S124.

  The totalization processing unit 2c updates the value of the “number of repairs” in the found rough estimate data to a value obtained by adding 1 (the number of repairs ← the number of repairs + 1) (step S124), and proceeds to the process of step 130.

The totalization processing unit 2c enters the estimated estimate data of the contents of the "product category" in the repair result data of the record focused on the approximate estimate database 2b and the type relationship and the contents of the "failure symptom" in the repair history data. Is newly added (step S125).
The totalization processing unit 2c sets the value of “number of repairs” in the newly added approximate estimate data to 1 (the number of repairs ← 1) (step S126).

The totalization processing unit 2c sets the “average amount” value of the newly added estimated estimate data as the “repair cost” value of the repair result data of the record being noticed (average amount ← repair cost) (step S127). .
The totalization processing unit 2c sets the “maximum amount” value of the newly added estimated estimate data as the “repair cost” value of the repair performance data of the record being noticed (maximum amount ← repair cost) (step S128). .
The tabulation processing unit 2c sets the value of “repair cost” of the repair performance data of the record that is paying attention to the value of “minimum amount” of the newly added rough estimate data (minimum amount ← repair cost) (step S129), The process proceeds to step S130.
The aggregation processing unit 2c pays attention to the next record in the repair history database 2a (step S130), and returns to the process of step S117.

  Steps S131 to S145 are processing steps for performing a totaling process for totaling repair performance data for products belonging to the model regardless of the type of failure symptom. The totalization processing unit 2c stores the first record in the repair history database 2a. Pay attention (step S131). The totalization processing unit 2c determines whether or not there is repair record data in the record of interest (step S132). If it is determined that there is repair record data (S132: YES), the process proceeds to the process of step S133, and the repair record is obtained. If it is determined that there is no data (S132: NO), the process proceeds to step S146.

  The totalization processing unit 2c sets the product category, the repair history data of the record focused on the product category, the model, and the failure symptom in the rough estimate database 2b as the key, the repair history data type, and no symptom relation. The estimated estimated data in which the contents of “product category”, the contents of “model”, and the contents of “symptom of failure” match are searched, and it is determined whether or not there is matching estimated data (step S133). If matching approximate estimation data is found (S133: YES), the process proceeds to step S134. If no matching approximate estimation data is found (S133: NO), the process proceeds to step S140.

  The totalization processing unit 2c multiplies the value of the “average amount” of the found rough estimate data and the value of “the number of repairs”, and obtains the value of “repair cost” of the repair result data of the record that focuses on the multiplied value. Add the value and divide the value by adding 1 to the value of “Number of repairs” in the estimated estimate data found, and update the value of “Average amount” in the estimated estimate data found to be the divided value (average amount ← ( Average amount × number of repairs + repair cost / (number of repairs + 1)) (step S134).

  The tabulation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is larger than the “maximum amount” value of the estimated approximate data found (step S135). If it is determined that the value is larger (S135: YES), the process proceeds to the process of step S136, and the tabulation processing unit 2c pays attention to the “maximum amount” value of the found approximate estimate data in the field “ The value is updated to “repair cost” (maximum amount ← repair cost) (step S136), and the process proceeds to step S137. On the other hand, if it is determined that it is not large (S135: NO), the process proceeds to step S137.

  The aggregation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is smaller than the “minimum amount” value of the estimated approximate data found (step S137). If it is determined that the value is smaller (S137: YES), the process proceeds to step S138, and the totalization processing unit 2c “repair” of the repair result data of the record focusing on the value of the “minimum amount” of the found estimated estimate data. The value is updated to “cost” (minimum amount ← repair cost) (step S138), and the process proceeds to step S139. On the other hand, if it is determined that it is not small (S137: NO), the process proceeds to step S139.

  The totalization processing unit 2c updates the value of the “number of repairs” in the found approximate estimate data to a value obtained by adding 1 (the number of repairs ← the number of repairs + 1) (step S139), and proceeds to the process of step 145.

The tabulation processing unit 2c newly adds an entry for the estimated estimate data that indicates that there is no symptom relation between the contents of the "product category" of the repair result data and the "model" of the repair history data of the record focused on the approximate estimate database 2b. (Step S140).
The totalization processing unit 2c sets the value of “number of repairs” in the newly added approximate estimate data to 1 (the number of repairs ← 1) (step S141).

The totalization processing unit 2c sets the “average amount” value of the newly added approximate estimated data as the “repair cost” value of the repair performance data of the record being noticed (average amount ← repair cost) (step S142). .
The totalization processing unit 2c sets the “maximum amount” value of the newly added estimated estimate data as the “repair cost” value of the repair performance data of the record being noticed (maximum amount ← repair cost) (step S143). .
The totalization processing unit 2c sets the value of “repair cost” of the repair result data of the record that is focused on the value of “minimum amount” of the newly added rough estimate data (minimum amount ← repair cost) (step S144), The process proceeds to step S145.
The aggregation processing unit 2c pays attention to the next record in the repair history database 2a (step S145), and returns to the process of step S132.

  Steps S146 to S160 are processing steps for performing a tabulation process for tabulating repair performance data for products belonging to the product category regardless of both the product type and the type of failure symptom. Attention is focused on the first record in the history database 2a (step S146). The totalization processing unit 2c determines whether or not there is repair record data in the record of interest (step S147), and if it determines that there is repair record data (S147: YES), proceeds to the process of step S148, and repair history If it is determined that there is no data (S147: NO), the counting process is terminated.

  The tabulation processing unit 2c displays “product category” for each of the product category, the model relationship and the symptom relationship in the repair performance data of a record that is focused on the product category, the model, and the failure symptom in the rough estimate database 2b. ”,“ Model ”content, and“ failure symptom ”content are searched for approximate estimate data, and it is determined whether there is a match approximate estimate data (step S148). If matching approximate estimation data is found (S148: YES), the process proceeds to step S149. If no matching approximate estimation data is found (S148: NO), the process proceeds to step S155.

  The totalization processing unit 2c multiplies the value of the “average amount” of the found rough estimate data and the value of “the number of repairs”, and obtains the value of “repair cost” of the repair result data of the record that focuses on the multiplied value. Add the value and divide the value by adding 1 to the value of “Number of repairs” in the estimated estimate data found, and update the value of “Average amount” in the estimated estimate data found to be the divided value (average amount ← ( (Average amount × number of repairs + repair cost) / (number of repairs + 1)) (step S149).

  The aggregation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is larger than the “maximum amount” value of the estimated approximate data found (step S150). If it is determined that the value is larger (S150: YES), the process proceeds to step S151, and the aggregation processing unit 2c selects “repair” in the repair record data of the record that is paying attention to the “maximum amount” value of the found approximate estimated data. The value is updated to “cost” (maximum amount ← repair cost) (step S151), and the process proceeds to step S152. On the other hand, if it is determined that it is not large (S150: NO), the process proceeds to step S152.

  The aggregation processing unit 2c determines whether or not the “repair cost” value of the repair record data of the record of interest is smaller than the “minimum amount” value of the estimated approximate data found (step S152). If it is determined that the value is smaller (S152: YES), the process proceeds to step S153, and the totalization processing unit 2c selects “repair” of the repair record data of the record in which the value of the “minimum amount” in the found rough estimate data is focused. The value is updated to “cost” (minimum amount ← repair cost) (step S153), and the process proceeds to step S154. On the other hand, if it is determined that it is not small (S152: NO), the process proceeds to step S154.

  The totalization processing unit 2c updates the value of the “number of repairs” in the found approximate estimate data to a value obtained by adding 1 (the number of repairs ← the number of repairs + 1) (step S154), and proceeds to the process of step 160.

The tabulation processing unit 2c newly adds an entry of approximate estimate data indicating that there is no type relationship and no symptom relationship between the contents of the “product category” of the repair result data of the record focused on the approximate estimate database 2b (step S155). ).
The aggregation processing unit 2c sets the value of the “number of repairs” of the newly added estimated estimate data to 1 (the number of repairs ← 1) (step S156).

The totalization processing unit 2c sets the “average amount” value of the newly added estimated estimate data as the “repair cost” value of the repair performance data of the record being noticed (average amount ← repair cost) (step S157). .
The totalization processing unit 2c sets the value of “repair cost” of the repair record data of the record in which the “maximum amount” value of the newly added estimated estimate data is focused (maximum amount ← repair cost) (step S158). .
The totalization processing unit 2c sets the value of “repair cost” of the repair result data of the record that is focused on the value of “minimum amount” of the newly added rough estimate data (minimum amount ← repair cost) (step S159), The process proceeds to step S160.
The aggregation processing unit 2c pays attention to the next record in the repair history database 2a (step S160), and returns to the process of step S147.

Hereinafter, output processing of estimated amounts (average amount, minimum amount, maximum amount) performed in the server device 2 described with reference to FIGS. 2 to 4 will be described with reference to FIGS. 11 to 12. FIG. 11 to FIG. 12 are flowcharts showing the procedure of estimated amount output processing performed in the server device 2.
The information reception determination unit 2d determines whether information has been received from the client terminal device 3 (step S201). If it is determined that no information has been received (S201: NO), the process returns to step S201. On the other hand, if it is determined that the information has been received (S201: YES), the process proceeds to step S202.

  The information content determination unit 2e determines whether or not a failure symptom is included in the information input from the information reception determination unit 2d (information received from the client terminal device 3) (step S202). If it is determined that a failure symptom is included (S202: YES), the process proceeds to step S203. On the other hand, if it is determined that a failure symptom is not included (S202: NO), the process proceeds to step S208. Proceed to processing.

  The information content determination unit 2e determines whether or not the type is included in the information input from the information reception determination unit 2d (information received from the client terminal device 3) (step S203). If it is determined that the model is included (S203: YES), the process proceeds to step S204. On the other hand, if it is determined that no failure symptom is included (S204: NO), the process proceeds to step S206. move on.

The estimated amount extraction unit 2f matches the contents of the “model” and the “failure symptom” with the received model and the failure symptom in the approximate estimate database 2b. The approximate estimate data to be searched is searched, and it is determined whether there is matching approximate estimate data (step S204).
If approximate estimated data that matches as a result of the search is found (S204: YES), the process proceeds to the process of step S205, and the estimated amount extraction unit 2f displays the “average amount”, “minimum amount”, and “ The average amount, the minimum amount, and the maximum amount are extracted from each of the “maximum amount” (step S205). Then, the estimated amount transmission processing unit 2g transmits the average amount, the minimum amount, and the maximum amount extracted in step S205 to the client terminal device 3 (step S213), and returns to the processing of step S201.
If the approximate estimated data that matches as a result of the search is not found (S204: NO), the process proceeds to step S214, and the estimated amount transmission processing unit 2g transmits no approximate estimate to the client terminal device 3 (step S214). Return to processing.

The estimated amount extraction unit 2f includes the contents of “product category” and “model” for each of the product category, the type not received, and the received failure symptom in the estimated estimate database 2b using the product category, model, and failure symptom as keys. ”And the content of“ failure symptom ”are searched for approximate estimated data, and it is determined whether there is matching approximate estimated data (step S206).
If approximate estimated data that matches as a result of the search is found (S206: YES), the process proceeds to step S207, and the estimated amount extraction unit 2f displays the “average amount”, “minimum amount”, and “ The average amount, the minimum amount, and the maximum amount are extracted from each of the “maximum amount” (step S207). Then, the estimated amount transmission processing unit 2g transmits the average amount, the minimum amount, and the maximum amount extracted in step S207 to the client terminal device 3 (step S213), and returns to the processing of step S201.
If the approximate estimated data that matches is found as a result of the search (S206: NO), the process proceeds to step S214, and the estimated amount transmission processing unit 2g transmits no approximate estimate to the client terminal device 3 (step S214). Return to processing.

  The information content determination unit 2e determines whether or not the type is included in the information input from the information reception determination unit 2d (information received from the client terminal device 3) (step S208). If it is determined that the model is included (S208: YES), the process proceeds to step S209. On the other hand, if it is determined that a failure symptom is not included (S208: NO), the process proceeds to step S211. move on.

The estimated amount extraction unit 2f approximates the contents of the “model” and the “failure symptom” in the approximate estimate database 2b, each of the model received with the model and the symptom of failure as a key, and no symptom relation. The estimated data is searched, and it is determined whether there is a matching approximate estimated data (step S209).
If approximate estimated data that matches as a result of the search is found (S209: YES), the process proceeds to step S210, and the estimated amount extraction unit 2f displays the “average amount”, “minimum amount”, and “ The average amount, the minimum amount, and the maximum amount are extracted from each of the “maximum amount” (step S210). Then, the estimated amount transmission processing unit 2g transmits the average amount, the minimum amount, and the maximum amount extracted in step S210 to the client terminal device 3 (step S213), and returns to the process of step S201.
If the approximate estimated data that matches as a result of the search is not found (S209: NO), the process proceeds to step S214, and the estimated amount transmission processing unit 2g transmits no approximate estimate to the client terminal device 3 (step S214). Return to processing.

The estimated amount extraction unit 2f stores the contents of the “model” and the “model” in the approximate estimate database 2b for each of the product category, no type relationship, and no symptom relationship received using the product category, type, and failure symptom as keys. The rough estimated data in which the content and the content of the “failure symptom” match are searched, and it is determined whether there is matching rough estimated data (step S211).
If approximate estimated data that matches as a result of the search is found (S211: YES), the process proceeds to the process of step S212, and the estimated amount extraction unit 2f displays the “average amount”, “minimum amount”, and “ The average amount, the minimum amount, and the maximum amount are extracted from each of the “maximum amount” (step S212). Then, the estimated amount transmission processing unit 2g transmits the average amount, the minimum amount, and the maximum amount extracted in step S212 to the client terminal device 3 (step S213), and returns to the processing of step S201.
If the approximate estimated data that matches as a result of the search is not found (S211: NO), the process proceeds to step S214, and the estimated amount transmission processing unit 2g transmits no approximate estimate to the client terminal device 3 (step S214). Return to processing.

Hereinafter, the output processing of the estimated amount performed in the client terminal device 3 described with reference to FIGS. 5 and 6 will be described with reference to FIG. FIG. 13 is a flowchart illustrating a procedure of estimated amount output processing performed in the client terminal device 3.
First, the display unit 3a displays a repair estimated amount operation screen by a predetermined operation by the operator with respect to the input unit 3b (step S301). At this time, the operator uses the input unit 3b to input the product category input field 31, the model input field 32, and the symptom input field 33 to the input field that can be heard from the inquiring user (FIG. 6 ( a) See), and the execution button 34 is clicked after input.

  The information transmission processing unit 3c determines whether or not the execution button 35 has been pressed (step S302). If it is determined that the execution button 34 has not been pressed (S302: NO), the process returns to step S302. On the other hand, if it is determined that the execution button 34 has been pressed (S302: YES), the process proceeds to step S303, and the information transmission processing unit 3c determines whether the product category input field 31, the model input field 32, and the symptom input field 33 Among them, the input content in the input field that has been input is transmitted to the server device 2 (step S303).

  After transmitting the input content, the information reception processing unit 3d determines whether information has been received from the server device 2 (step S304). If it is determined that no information has been received (S304: NO), the process returns to step S304. On the other hand, if it is determined that the information has been received (S304: YES), the process proceeds to step S305, and the information reception processing unit 3d has the average amount, the minimum amount, and the maximum amount as the information received from the server device 2. Whether or not (step S305). If it is determined that the received information is the average amount, the minimum amount, and the maximum amount (S305: YES), the process proceeds to step S306, and the information reception processing unit 3d displays the repair estimate displayed on the display unit 3a. The minimum amount, the average amount, and the maximum amount received from the server device 2 are displayed in the minimum amount display area 35, the average amount display area 36, and the maximum amount display area 37 of the amount operation screen (step S306). finish. On the other hand, if it is determined that the received information is not the average amount, the minimum amount, and the maximum amount (S305: NO), the process proceeds to step S307, and the information reception processing unit 3d repairs the information displayed on the display unit 3a. The box 38 without estimated estimate on the estimated amount operation screen is checked (step S306), and the process ends.

  According to the present embodiment described above, the operator who has received an inquiry from the user can reply to the product user with an estimated amount (minimum amount, average amount, maximum amount) in a range that matches the actual situation. As a result, it is possible to prevent the cost actually required for repair from becoming the cause of trouble from the estimated amount presented to the user. Further, it can be used as a material for determining whether the user repairs the failed product and continues to use it or replaces it.

  Although the preferred embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various design changes can be made within the scope described in the claims. is there.

  It should be noted that a program for realizing the functions of each processing unit described above is recorded on a computer-readable recording medium, the program recorded on the recording medium is read into a computer system, and executed to execute the above-described various processes. You may go. The “computer system” here includes an OS and hardware such as peripheral devices. The “computer system” includes a WWW system provided with a homepage providing environment (or display environment). The “computer-readable recording medium” refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM, and a CD-ROM, and a storage device such as a hard disk built in the computer system. Further, the “computer-readable recording medium” refers to a volatile memory (RAM) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, those holding programs for a certain period of time are also included.

  The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

The system block diagram of the repair estimated amount output system in embodiment of this invention. The functional block diagram which shows the function structure of the server apparatus of FIG. The figure which shows an example of the repair log | history database of FIG. The figure which shows an example of the rough estimate database of FIG. The functional block diagram which shows the function structure of the client terminal device of FIG. The figure which shows an example of the repair estimated amount operation screen displayed on the display part of FIG. The flowchart which shows the procedure of the total process of the repair history performed in the server apparatus of FIG. The flowchart which shows the procedure of the total process of the repair history performed in the server apparatus of FIG. The flowchart which shows the procedure of the total process of the repair history performed in the server apparatus of FIG. The flowchart which shows the procedure of the total process of the repair history performed in the server apparatus of FIG. The flowchart which shows the procedure of the output process of the estimated amount performed in the server apparatus of FIG. The flowchart which shows the procedure of the output process of the estimated amount performed in the server apparatus of FIG. The flowchart which shows the procedure of the output process of the estimated amount performed in the client terminal device of FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Repair estimated amount output system 2 Server apparatus 2a Repair history database 2b Approximate estimated database 2c Total processing part 2d Information reception judgment part 2e Received content judgment part 2f Estimated amount extraction part 2g Estimated price transmission processing part 3 Client terminal apparatus 3a Display part 3b Input unit 3c Information transmission processing unit 3d Information reception processing unit

Claims (5)

In the repair estimated amount output device that estimates the amount of repair required to repair a faulty product,
The product information for distinguishing the product and the symptom of the failure are associated with each other, and the average amount, the minimum amount and the maximum amount of the repair amount so far required for repairing the symptom of the failure in the product included in the product information are stored. Repair amount storage means to perform,
Extracting the estimated amount by extracting the average amount, the minimum amount and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the input product information and the failure symptom Means,
An estimated amount output means for outputting an average amount, a minimum amount and a maximum amount extracted by the estimated amount extraction means , and
The repair amount storage means stores estimated data divided into four cases according to presence / absence of a failure symptom and presence / absence of a product type, and the estimated amount output means is classified according to the four cases. An estimated repair amount output device for outputting estimated data for any one of the estimated data corresponding to the input . It further comprises an information content determination means for determining whether or not a failure symptom is included in the input information,
The repair amount storage means associates the product information with the symptom irrelevant information indicating that the type of the symptom of the failure is irrelevant, and the average amount and the minimum of the repair amount so far required for repair in the product included in the product information Remember the amount and the maximum amount,
The estimated amount extraction means uses the product information and the failure symptom that are input when the information content determination means determines that a failure symptom is included, from the repair amount storage means to the product information. The average amount, the minimum amount, and the maximum amount stored in association with the failure symptom are extracted, and the product that is input when the information content determination means determines that the failure symptom is not included 2. The repair according to claim 1, wherein an average amount, a minimum amount, and a maximum amount stored in association with the product information and the symptom irrelevant information are retrieved from the repair amount storage means using information. Estimated amount output device. The product information for distinguishing the product and the symptom of the failure are associated with each other, and the average amount, the minimum amount and the maximum amount of the repair amount so far required for repairing the symptom of the failure in the product included in the product information are stored. A repair amount estimation output method performed in the repair estimate amount output device according to claim 1 or 2, wherein the repair amount storage means includes a repair amount storage means for estimating a repair amount required to repair a faulty product.
Extracting the estimated amount by extracting the average amount, the minimum amount and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the input product information and the failure symptom Procedure and
An estimated amount output procedure for outputting the average amount, the minimum amount and the maximum amount taken out in the estimated amount extraction procedure, and
The repair amount storage means stores estimated data divided into four cases according to presence / absence of a failure symptom and presence / absence of a product type, and the estimated amount output means is classified according to the four cases. An estimated repair amount output method of outputting estimated data in any one case corresponding to an input from the estimated data . The product information for distinguishing the product and the symptom of the failure are associated with each other, and the average amount, the minimum amount and the maximum amount of the repair amount so far required for repairing the symptom of the failure in the product included in the product information are stored. A computer as a repair estimated amount output device that includes a repair amount storage means for estimating a repair amount required to repair a faulty product,
Extracting the estimated amount by extracting the average amount, the minimum amount and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the input product information and the failure symptom And an estimated amount output means for outputting an average amount, a minimum amount and a maximum amount extracted by the estimated amount extraction means , and
The repair amount storage means stores estimated data divided into four cases according to presence / absence of a failure symptom and presence / absence of a product type, and the estimated amount output means is classified according to the four cases. An estimated repair amount output program for outputting estimated data for any one of the estimated data corresponding to the input . In a repair estimated amount output system having a server device for estimating a repair amount required for repairing a product in which a failure has occurred and a client terminal device connected to the server device so as to be able to exchange data,
The server device
In association with product information for distinguishing products and failure symptoms, the average, minimum and maximum amounts of repairs required so far for repairing the failure symptoms in the products included in the product information are stored. Repair amount storage means to perform,
Information receiving means for receiving product information and failure symptoms from the client terminal device;
The average amount, the minimum amount, and the maximum amount stored in association with the product information and the failure symptom from the repair amount storage means using the product information and failure symptoms received by the information receiving means. An estimated amount extraction means for taking out
An estimated amount transmitting means for transmitting the average amount, the minimum amount, and the maximum amount extracted by the estimated amount extracting means to the client terminal device,
The client terminal device
Information transmitting means for transmitting input product information and failure symptoms to the server device;
Estimated amount receiving means for receiving the average amount, the minimum amount and the maximum amount of the repair amount transmitted from the server device;
Repair amount notification means for notifying the average amount, the minimum amount, and the maximum amount of the repair amount received by the estimated amount receiving means , and
The repair amount storage means stores estimated data divided into four cases corresponding to the presence or absence of a failure symptom and the presence or absence of a product type, and the repair amount notification means is classified into the four cases. An estimated repair amount output system that outputs estimate data in any one case corresponding to input from the estimated data .

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