JP7655827B2 - Service support system and service support method - Google Patents

Description

An embodiment of the present invention relates to a service support system and a service support method.

When a malfunction occurs in a device such as a home appliance, a service representative is notified of a report from the user stating that "the device does not function (as expected)." When a service representative restores the functionality of the device through on-site service, it has been difficult for the service representative to obtain more detailed information about the state of the device and the cause of the malfunction before visiting the location (called the site) where the device requiring on-site service is located. For this reason, service personnel predict several causes of the malfunction based on the report from the user and prepare for on-site service. In order to complete the service in one visit, if there are multiple causes of the malfunction predicted based on the report, various replacement parts are also arranged to be able to deal with any of the causes. In this way, it took time to arrange for various replacement parts and to return unused parts from the various parts arranged in advance.

JP 2002-92206 A

The problem that this invention aims to solve is to provide a service support system and a service support method that reduce the burden of incidental work when responding to service issues that arise.

A service support system according to an embodiment provides a user with information relating to how to deal with a malfunction that has occurred in a target device. The service support system has an estimation processing unit and an output control unit. The estimation processing unit predicts how to deal with the malfunction of the target device based on history information relating to the malfunction of the target device associated with the user's identification information, information relating to an item to be used in combination with the target device, which is obtained from a mail-order system and is purchase history information for the item, and information on the malfunction of the target device . The output control unit outputs the result of the prediction.

FIG. 1 is a diagram showing an overall configuration of a service support system according to an embodiment. FIG. 2 is a schematic configuration diagram of a server device according to the embodiment. FIG. 4 is a diagram for explaining an example of a processing slip DB according to the embodiment. FIG. 13 is a diagram for explaining an example of a list display of a processing slip DB according to the embodiment. FIG. 4 is a diagram for explaining a purchase history information DB according to the embodiment. FIG. 4 is a diagram for explaining a defect cause DB according to the embodiment. FIG. 4 is a diagram for explaining a user attribute information DB according to the embodiment. FIG. 4 is a diagram for explaining an operation history DB according to the embodiment. FIG. 2 is a diagram for explaining an outline of a process related to service support according to the embodiment. 4 is a flowchart of a process related to service support by the service support device of the embodiment. FIG. 11 is a diagram for explaining the relationship between consumables and used parts according to the second embodiment. FIG. 13 is a schematic configuration diagram of a service support device according to a second embodiment.

The following describes the service support system and the service support method according to the embodiment with reference to the drawings. In the following description, components having the same or similar functions are given the same reference numerals. Duplicate descriptions of those components may be omitted. "Based on XX" means "based on at least XX" and may include the case where it is based on another element in addition to XX. "Based on XX" is not limited to the case where XX is directly used, but may also include the case where it is based on XX that has been subjected to calculation or processing. "XX or YY" is not limited to either XX or YY, but may include both XX and YY. This also applies to the case where there are three or more selective elements. "XX" and "YY" are any element (for example, any information).

In the embodiment, a "home appliance" is an example of an electric device, and includes, for example, an air conditioner, a washing machine, a dryer, a rice cooker, or an oven range. A situation in which the functionality of a home appliance is incomplete, or an undesirable event in the home appliance, is called a "malfunction." The service (after-sales service) to restore the functionality of a home appliance that has a malfunction, at the request of the user of the home appliance, is simply called "service response." A person in charge of service response for home appliances is called a service responder. A service responder is, for example, a member of an after-sales service provider. A service responder is sometimes called a "serviceman."

The following explains the example of an "on-site repair service" in which a service visits a user-specified location to repair a home appliance that is located at that location.

First Embodiment
FIG. 1 is a diagram showing the overall configuration of a service support system according to an embodiment.
The service support system 1 provides information for supporting service of home appliances to a service provider of the home appliances.

The service support system 1 can handle information about home appliances installed in multiple residences, such as a first residence 10 and a second residence 20. There is no limit to the number and size of the residences, or the number of home appliances.

A first user U11 residing in a first residence 10 owns one or more home appliances.
The first user U11 has authority to use the service support system 1 to receive service support for one or more home appliances. The authority to use the service support system 1 by the first user U11 may be linked to the account (authentication information) of the first user U11. The first user U11 may be simply referred to as "user U."

In the first residence 10, home appliances such as air conditioners (AC) 11 and 12, a washing machine (WM) 13, and a microwave oven (MWO) 14 are arranged. The air conditioners 11 and 12, the washing machine 13, and the microwave oven 14 are examples of home appliances that are subject to on-site repair services, and are not limited to those shown in the figure, and may be added or removed as appropriate. Each of the above home appliances generates data to be registered in the service support device 3 arranged outside the first residence 10. Each of the above home appliances has a communication function, and directly or indirectly transmits the generated data to the network NW to be registered in the service support device 3.

The first user U11 uses a terminal device 15. The terminal device 15 may be, for example, a smartphone, a tablet terminal, or a personal computer. There is no restriction on the type of the terminal device 15. The terminal device 15 communicates with the service support device 3 via the network NW.

A second user U21 residing in the second residence 20 owns one or more home appliances. The second user U21 has the authority to use the service support system 1 to receive service support for the one or more home appliances. The authority for the second user U21 to use the service support system 1 may be linked to the account (authentication information) of the second user U21. When there is no need to distinguish between the second user U21 and the first user U11, they may be collectively referred to as "user U."

In the second residence 20, home appliances such as air conditioners (AC) 21 and 22, a washing machine (WM) 23, and a microwave oven (MWO) 24 are arranged. The air conditioners 21 and 22, the washing machine 23, and the microwave oven 24 are examples of home appliances that are subject to on-site repair services, and are not limited to those shown in the figure, and may be added or removed as appropriate. Each of the above home appliances generates data to be registered in the service support device 3 arranged outside the second residence 20. Each of the above home appliances has a communication function, and directly or indirectly transmits the generated data to the network NW to be registered in the service support device 3.

The second user U21 uses a terminal device 25. The terminal device 25 may be, for example, a smartphone, a tablet terminal, or a personal computer. There is no restriction on the type of the terminal device 25. The terminal device 25 communicates with the service support device 3 via the network NW.

In response to a request from the first user U11, the first service responder S31 visits the home of the first user U11 whose home appliance has a malfunction and provides service for the malfunctioning appliance. The first service responder S31 uses a terminal device 31. The terminal device 31 can be, for example, a smartphone, a tablet terminal, or a personal computer. There is no restriction on the type of the terminal device 31. The terminal device 31 communicates with the service support device 3 via the network NW.

In response to a request from the second user U21, the second service responder S32 visits the home of the second user U21 whose home appliance has a malfunction, and provides service for the malfunctioning appliance. The second service responder S32 uses a terminal device 32. The terminal device 32 may be, for example, a smartphone, a tablet terminal, or a personal computer. There is no restriction on the type of the terminal device 32. The terminal device 32 communicates with the service support device 3 via the network NW.

At the stage shown in FIG. 1, the first service responder S31 has received support from the service support system 1 and has prepared service parts SP for the service response, and is heading to the home of the first user U11 with the service parts SP. The second service responder S32 is in the process of preparing service parts and the like for the service response that will soon be dispatched.

A user U may purchase consumables and the like using a mail order site (mail order system). For example, the mail order site is operated by a mail order management device 4. The mail order management device 4 manages mail order transactions by treating, for example, items to be used in combination with home appliances as the product. The mail order management device 4 may be a so-called computer that forms a mail order system. The mail order management device 4 may be configured to provide a commercial flow similar to that of a known mail order site.

In addition, the mail order management device 4 of the embodiment extracts at least items to be used in combination with home appliances from among the items purchased by the user U, and provides information on the purchase history relating to these items to the service support device 3.
For example, a first user U11 periodically purchases laundry detergent 13A (brand A) and fabric softener 13B (brand X) through mail order. A second user U21 periodically purchases laundry detergent 23A (brand B) and fabric softener 23B (brand X) through mail order. Brand A detergent 13A is, for example, a powder detergent, and brand B detergent 23A is, for example, a liquid detergent. These will be described in detail later.

The service support device 3 included in the service support system 1 will be described with reference to Fig. 2. Fig. 2 is a schematic configuration diagram of the service support device 3 according to the embodiment.
The service support device 3 includes, for example, a control unit 310 and a storage unit 320 .
The control unit 310 includes, for example, a user attribute information acquisition unit 311, a declaration information acquisition unit 312, a purchase history information acquisition unit 313, a feature extraction unit 314, an estimation processing unit 315, a reference data generation unit 316, an output control unit 317, and an operation history information acquisition unit 318. The user attribute information acquisition unit 311, the declaration information acquisition unit 312, the purchase history information acquisition unit 313, the feature extraction unit 314, the estimation processing unit 315, the reference data generation unit 316, the output control unit 317, and the operation history information acquisition unit 318 are collectively referred to as functional units of the control unit 310.

The functional parts of the control unit 310 are realized by a hardware processor, such as a CPU, included in the service support device 3 executing a program (software). However, all or part of these functional parts may be realized by hardware (including circuitry) such as an ASIC, PLD, or FPGA, or may be realized by a combination of software and hardware. Each part of the control unit 310 will be described below.

The memory unit 320 of the service support device 3 is realized by, for example, RAM, ROM, HDD, flash memory, or a combination of two or more of these. The memory unit 320 stores a processing slip DB 321, a purchase history information DB 322, a malfunction cause DB 323, a user attribute information DB 324, and an operation history DB 325. The malfunction cause DB 323 stores data related to guides for services of the managed home appliances. The guides for services associate malfunction events with service items related to the malfunctions. This guide data does not depend on a specific user U, but may be based on information related to the services set by the manufacturer or service company. The manufacturer or service company is an example of a provider of after-sales service for the target device (service provider).

FIG. 3A is a diagram illustrating an example of the processing slip DB 321 according to the embodiment.
The transaction slip DB 321 stores each transaction slip data generated for each request (request) from the user U. The transaction slip data shown in FIG.

The processing slip data 321R includes information such as incident identification data 321A for identifying the incident, user U's reporting information 321B, scheduled information 321C for service response, and information at the time of service response 321D.

Incident identification data 321A includes data such as the "document number" and "date received" of the incident, the "classification" of the home appliance that is the subject of the incident, model information ("model") indicating the type of the appliance, and the "serial number." Using this data, the target appliance is identified by its "model" and "serial number." For example, a "washing machine" is an example of a "classification." In addition to "washing machine," "classification" may also include "air conditioner," "microwave oven," "rice cooker," and so on.

The report information 321B further includes user identification information and data on the status of the malfunction. The user identification information may include "user name," "user address," "user phone number," "user ID," and the like. The "user ID" may be an e-mail address or information unique to the user. The data on the report status includes data on the "status" of the target device and its "related information." For example, the "related information" may include information on items (purchases) used in combination with the home appliance.

The data of the above items are acquired at the stage of accepting a service request from the user U. Each transaction slip data is further associated with the following items.
The service response schedule information 321C includes columns for "scheduled visit date and time" and the desired "service representative." When the "scheduled visit date and time" for the service response and the desired "service representative" are determined, they are added here.
The information 321D at the time of service response includes columns such as "Processing content,""Completiondate," and "Confirmation." The data for "Processing content" and "Completion date" are added by the service provider when the service response is performed. The data for "Confirmation" includes a signature by the user U confirming that the work has been performed.

Figure 3B is a diagram for explaining an example in which the processing slip DB 321 of the embodiment is displayed in a list. In the processing slip DB 321 displayed in a list, data similar to that of the processing slip DB 321 shown in Figure 3A is stored in association with one record (processing slip data 321R). The configuration of this list display is arranged so that records with different contents can be compared, and may be modified as appropriate without being limited to this configuration. For example, information on different types of home appliances classified as "washing machine", "oven range", and "rice cooker" is displayed in a list. Information on home appliances classified into different types is assigned to records that have common items.

FIG. 3C is a diagram illustrating the purchase history information DB 322 according to the embodiment.
Purchase history information DB322 includes information such as "category", "user", "purchased item", "purchase date", and "quantity". "Category" and "user" are common to processing slip DB321. "Purchased item", "purchase date", and "quantity" include data indicating the name, "purchase date", and "quantity" related to an item used in combination with a home appliance.

For example, if a washing machine is identified from the "Category" data, items used in combination with the washing machine would include detergent and fabric softener. For an oven range and rice cooker, items would include food ingredients and water used for cooking.

FIG. 3D is a diagram for explaining the defect cause DB 323 according to the embodiment.
Malfunction cause DB323 includes information such as "classification,""model,""status,""item to be used in combination," and "malfunction cause.""Classification,""model,""status," and "item to be used in combination" are related to "classification,""model,""status," and "related information" in processing slip DB321. "Malfunction cause" indicates a cause that leads to a malfunction of a home appliance. Malfunctions of a washing machine may include "drum (tub) not spinning,""cannot pour water,""cannot add detergent," and the like.

FIG. 3E is a diagram illustrating the user attribute information DB 324 according to the embodiment.
The user attribute information DB324 includes items such as information on the attributes of user U (referred to as "user"), information on the type of home appliance of the target device used by user U (referred to as "model"), information on the "operation history" of the target device, and information on "items used in combination with" the target device.

FIG. 3F is a diagram for explaining the operation history DB 325 according to the embodiment.
For example, in the case of a washing machine, the user U can operate the operation panel or terminal device 15 provided on the washing machine to change the "washing operation course" related to washing and drying, and perform operations such as starting, pausing, and stopping the operation. Examples of the washing operation courses include a standard course, a speedy course, a delicates course (careful washing course), an indoor drying course, and a stubbornly soiled course. For example, the amount of water poured into the water receiving tub during washing, the water flow during rinsing, the washing process, and the like differ for each washing operation course.

In operation history DB325, information such as the model, operation course, the detergent and fabric softener used in combination at the time, and operation date and time is recorded as operation history information of the washing machine. Note that the examples shown here are related to washing machines, but other types of home appliances may also be included.

Figure 4 is a diagram for explaining an overview of the processing related to service support in the embodiment. Figure 5 is a flowchart of the processing related to service support by the service support device 3 in the embodiment.

First, in the initial stage, the control unit 310 adds the malfunctions extracted from the history information of past malfunctions and the information on the corresponding causes to the malfunction cause DB 323 (step S0). Note that if the malfunction cause DB 323 containing sufficient information is already provided in the storage unit 320, the processing of this step S0 can be omitted.

Each functional unit of the control unit 310 executes, for example, the following processes.
The user attribute information acquisition unit 311 acquires attribute information of the user U designated by the user U from the terminal device 15, and adds this to the user attribute information DB 324 (step S1).

Note that, although it depends on the model of the home appliance, a home appliance having a function for notifying the outside of its operating state notifies the service support device 3 of operation history information relating to its operating state upon request. The operation history information acquisition unit 318 acquires operation history information of each model (step S11) and adds this information to the operation history DB 325. Note that the above step S11 may be omitted if the data in the operation history DB 325 is not used.

The purchase history information acquisition unit 313 acquires purchase history information of "purchased items" related to items to be used in combination with home appliances from the mail order management device 4 (step S12) and adds this to the purchase history information DB 322. Note that the information on items to be used in combination with home appliances may include purchase history information of consumables. The purchase history information acquisition unit 313 may acquire purchase history information of the above items from the mail order management device 4 serviced by the manufacturer or an external vendor, and add it to the purchase history information DB 322 of the memory unit 320. Note that the above step S12 may be omitted if specified by the user U.

The declaration information acquisition unit 312 accepts a service request from the user U and acquires the declaration information of the user U corresponding to this service request (step S2). For example, the declaration information acquisition unit 312 acquires the declaration information necessary for the service, including the attribute information of the user U and information on the model of the target device used by the user U. Furthermore, the declaration information acquisition unit 312 adds the processing slip data 321R, which becomes a new record, to the processing slip DB 321 of the storage unit 320.

The purchase history information acquisition unit 313 acquires information on the items to be used in combination with the home appliance from the purchase history information DB 322 (step S3). For example, the items to be used in combination with the home appliance may be consumables.

The feature extraction unit 314 estimates how the device and consumables are used (step S4). For example, the feature extraction unit 314 uses the identification information of the user U as a key to refer to the purchase history information DB 322 to obtain information on the purchase history of the consumables of the user U, and estimates how the device and consumables are used from the information on the purchase history of the consumables. In this case, the feature extraction unit 314 may extract the features of the user U using at least one of the information related to the user attribute information DB 324, and use this result to estimate how the device and consumables are used. The usage here may include information such as the frequency of use, the number of uses per unit period, and the operating course.

The estimation processing unit 315 estimates the malfunction of the target device or a method for dealing with the malfunction, and causes the output control unit 317 to output the result (step S5). For example, the estimation processing unit 315 predicts the malfunction of the target device or a method for dealing with the malfunction, using information from the user U about the target device, related to the target device or an item used in combination with the target device. The output control unit 317 causes the terminal device 31 to output the result of the prediction.

The reference data generating unit 316 identifies whether or not the range of the population corresponding to the defect cause DB 323 needs to be adjusted (step S6). If the range of the population needs to be adjusted, the reference data generating unit 316 adjusts the range of the population determined based on the defect cause DB 323. If the range of the population does not need to be adjusted, the result of the prediction derived earlier may be used as the result of this analysis process. This completes the series of processes.

The above process makes it possible to estimate the cause of or a solution to the problem occurring in user U's home appliance based on the reported information received as a service request, and to provide the results of this estimation to the service staff.

More specific application examples will be explained.

Scenario 1:
Here is an example of a problem with a washing machine: "The washing machine drum won't spin."
From the malfunction description "The drum of the washing machine does not spin," various causes are considered, such as deformation of the device, sensor abnormality, motor abnormality, computer (controller) abnormality, etc. Deformation of the device, sensor abnormality, motor abnormality, and computer (controller) abnormality are examples of malfunctions of the target device.

This causal relationship information is stored in the defect cause DB 323 of the memory unit 320 as data based on the service company's data or the knowledge of the service personnel.

For example, the estimation processing unit 315 obtains information on the first user U11's purchase history of consumables from the purchase history information DB 322 using the identification information (user ID) of the first user U11 as a key. From information such as the brand name in the purchase history, the estimation processing unit 315 extracts that "powder detergent has been purchased repeatedly." From the extraction result, the estimation processing unit 315 obtains information on the usage method that suggests that "the detergent used by the first user U11 is powder detergent. The first user U11 has been using powder detergent for a relatively long period of time." The above "powder detergent" is an example of information on an item to be used in combination with the target device.

As described above, the malfunction cause DB 323 stores information about the malfunction of the washing machine, such as "the drum does not rotate." The estimation processing unit 315 refers to the malfunction cause DB 323 and extracts from it a malfunction example of "the drum does not rotate" in which "powder detergent" is used. In this way, the estimation processing unit 315 identifies that the cause of the malfunction is "deformation."
The estimation processing unit 315 extracts cases that match the malfunction cases stored in the malfunction cause DB 323. Based on this, the service support device 3 outputs the extraction result to the terminal device 31 of the service representative SM 31, thereby reducing the burden of incidental work when providing service for the malfunction that has occurred.

The above extraction results also identify that the cause of the malfunction is unlikely to be a sensor abnormality, a motor abnormality, or a computer (control unit) abnormality. Similarly, the service support device 3 may output information about unlikely causes to the terminal device 31 of the service representative SM31.

As mentioned above, various phenomena can be the cause of an abnormality, but in the case of user U who uses powder detergent, it can be determined that there is a high possibility that the detergent has stuck to the outside of the drum, causing deformation, for example, due to detergent sticking. Note that if powder detergent is dissolved before using it in the washing machine, the above-mentioned sticking is unlikely to occur. This makes it possible to address problems that occur when powder detergent is used without being dissolved.

Scenario 2:
Here is an example of a problem with an oven range that causes a "burning smell."
For example, the heating function of the oven range 14 is in an operational state, but when the heating function is enabled, a "burning smell" may be generated. This state is not an abnormality of the oven range 14, but it is not suitable for use in a desirable situation.

When the estimation processing unit 315 of the service support device 3 receives such reported information from the user U, it refers to the malfunction cause DB 323 and extracts cases that match the reported information. For example, suppose that the status of the reported information indicates that a "burnt smell" occurred while cooking the food ingredient "meat" or after cooking it.

The inference processing unit 315 extracts cases in which the ingredient "meat" matches the condition "burnt smell" from the malfunction cause DB 323. From this, the inference processing unit 315 identifies that the cause of the malfunction is the "oil film."
In this way, based on information that matches the malfunction cases stored in the malfunction cause DB 323, the service support device 3 outputs the extraction results to the terminal device 31 of the service representative SM 31, thereby reducing the burden of ancillary work when providing service for the malfunction that has occurred.

Scenario 3:
An example of a problem with a washing machine similar to that of scenario 1 above, "The drum of the washing machine does not rotate," will be given below.
The estimation processing unit 315 refers to the malfunction cause DB 323 and extracts a malfunction example of "the drum does not rotate" when "powder detergent" is used. From this, the estimation processing unit 315 identifies that the cause of the malfunction is likely to be "deformation."
Furthermore, it is assumed that it has been identified from the purchase history information DB 322 that "powder detergent" has been used continuously for a relatively long period of time.
The service support device 3 outputs the extraction results to the terminal device 31 of the service representative SM 31, indicating that a case matching the defect stored in the defect cause DB 323 has been extracted, and that supporting information has been obtained from the purchase history information DB 322.

In this way, if information related to how the target user U uses the washing machine and information about the combination of consumables, etc. is known in advance when responding to or preparing for service, it becomes easier to deduce abnormalities and to arrange for the parts needed for repairs.

According to this, if more parts than are needed for repairs are distributed in preparation for service, excessive distribution can result in shortages of service parts in inventory. If parts distribution can be carried out efficiently, it can be possible to prevent shortages and reduce the cost of transporting parts.

In addition, information on the user U's operation history may be used instead of information on the user U's purchase history of consumables. The user U can use application software (called an app) on the terminal device 15 (smartphone) to select the operation mode (operation course) of the device and send commands to operate the device. Information on the consumables specified by the user U can be obtained from data on the user U's operation history using this app. The estimation processing unit 315 may extract from the operation history that "the user repeatedly purchases powder detergent."

According to the above embodiment, the service support system 1 includes an estimation processing unit 315 and an output control unit 317. The estimation processing unit 315 predicts a malfunction of the target device or a method of dealing with the malfunction, using information from the user U about the target device or about an item used in combination with the target device. The output control unit 317 outputs the result of the prediction. This enables the service support system 1 to reduce the burden of incidental work when responding to a malfunction that has occurred. Note that the washing machine 13 in the above description is an example of a target device.

The service support system 1 may estimate the characteristics of user U using at least one of the following information about user U: information about user U's attributes, information about the model of the target device used by user U, information about the operation history of the target device, and information about items used in combination with the target device, via the feature extraction unit 314. The service support system 1 can use the similarities in the characteristics of user U to adjust the data used in various processes to make them more appropriate.

For example, the estimation processing unit 315 can refer to examples of malfunctions stored in the malfunction cause DB 323 and use information about the malfunction of the target device held by the provider of after-sales service for the target device (such as a service company) to predict the content of the malfunction in the target device in which a malfunction has occurred. This allows the service staff to predict the current malfunction from the content of the malfunction based on the historical information about the malfunction.

For example, the estimation processing unit 315 predicts the nature of a malfunction of a target device to be repaired from information about items to be used in combination with the target device. The output control unit 317 may output the results of the prediction of the malfunction so as to provide the information to the service personnel in charge of repair.

(Modification of the first embodiment)
A modification of the first embodiment will be described.
The reference data generating unit 316 may generate reference data for a target device in which a malfunction has occurred, in which the details of the malfunction or a countermeasure method for the target device are associated with information on an item to be used in combination with the target device. The reference data is an example of data indicating the characteristics of the malfunction.

For example, the reference data generation unit 316 generates reference data for a target device that has been repaired, which associates the service parts (parts used) used in the repair with information about items to be used in combination with the target device. The estimation processing unit 315 can use the reference data and information from user U about other target devices to predict service parts to be used in repairing the other target devices.

Second Embodiment
A second embodiment will be described.
The example of the first embodiment is based on the premise that it is already clear that there is a correlation between the items (consumables) used in combination with a specific malfunction situation and its cause. Instead, in the present embodiment, a case will be described that is applicable when it is not clear that there is such a correlation.

Let's take a washing machine as an example. We will focus on the correlation between the consumables detergent and fabric softener, and the parts (used parts) replaced during service. Detergent includes either detergent for removing dirt from fabrics such as clothes, or detergent for removing dirt from the inside of the tub, or both.

The service support device 3A provided in the service support system 1A will be described with reference to Figures 6 and 7. Note that the service support system 1 and the service support device 3 in Figure 1 are replaced with the service support system 1A and the service support device 3A, respectively. Figure 6 is a diagram for explaining the relationship between consumables and parts used in the second embodiment. Figure 7 is a schematic diagram of the service support device 3A in the second embodiment.

A service support device 3A shown in FIG. 7 includes a failure handling history DB 326 in place of the failure cause 323 stored in the storage unit 320 of the service support device 3.
Each functional unit of the control unit 310 uses a correspondence table of a malfunction response history DB 326 instead of the malfunction cause DB 323 described above.

The correspondence table of the defect response history DB 326 shown in FIG. 6 shows the combination identification number and items indicating the type of detergent and fabric softener, which are consumables, on the left side, and items indicating the parts used on the right side. The brands of detergent and fabric softener and the names of the parts used shown in this figure have been anonymized, but the actual names may be used.

For example, a combination with an identification number of 1 indicates that two types of parts identified as "Part A" and "Part B" were used during service for user U, who uses both "Brand A" detergent and "Brand X" fabric softener.
In addition, the combination with the identification number 2 indicates that a part identified as "part A" was used during service for user U who uses detergent "brand A" and does not use fabric softener.
In addition, the combination with the identification number 3 indicates that a part identified as "Part B" was used when providing service to user U, who uses both "Brand B" detergent and "Brand X" fabric softener.

In addition, the combination of identification number 4 indicates that two types of parts identified as "Part A" and "Part C" were used when providing service to user U, who uses both detergent "Brand A" and fabric softener "Brand Y."
In addition, the combination of identification number 5 indicates that a part identified as "Part B" was used when providing service to user U, who uses both detergent "Brand C" and fabric softener "Brand Z."
In addition, the combination with the identification number 6 indicates that a part identified as "Part C" was used when providing service to user U, who uses both detergent "Brand B" and fabric softener "Brand Y."
The above is one example showing the relationship between consumables and usage parts, but there may be a wide variety of combinations of detergents, fabric softeners, and usage parts within the above range.

Each combination shown in this correspondence table is generated based on history information at the time of service provision. History information at the time of service provision is an example of reference data.
The estimation processing unit 315 of the service support system 1A refers to the malfunction response history DB 326 using the relationship between the combination of the item used in combination with the target device and the malfunction event, and predicts how to deal with the malfunction. This allows the service support system 1A to obtain information on replacement parts required when providing service for the malfunction that has occurred. This makes it possible to reduce the load of incidental work. Note that the washing machine 13 in the above description is an example of the target device.

There are two possible cases for the history information at the time of service handling: The reference data generating unit 316 determines the history information at the time of service handling according to one of the following cases, and generates a correspondence table for the defect handling history DB 326.
First case:
In the first case, each combination shown in this correspondence table may be generated based on the history information of the service response in which the used parts were replaced. In this case, it may be possible to include cases in which the defect was not resolved by replacing the used parts, but these are expected to be a minority among all the samples showing the above combinations. This may be considered to have little effect on the analysis of the above-mentioned trend of association.

Second case:
In a second case, each combination shown in the correspondence table may be generated based on history information of service cases in which the defect was resolved by replacing the used parts. In this case, cases in which the defect was not resolved even after replacing the used parts or cases in which the defect reoccurred are not included, so that the accuracy of analyzing the tendency of the association can be improved.

The historical information from the time of service response shows trends in chemical effects as well as trends that depend on the usage method of user U. This will be explained below.

As a comparative example, before offering a device to the market, a manufacturer designs and evaluates it based on knowledge, and commercializes the device once it has been confirmed to have the desired reliability. As an example of a home appliance, a washing machine basically uses water and detergent to wash the laundry, but the way in which the user U uses the washing machine varies, such as the amount of laundry to be washed in one go, the number of times, and the state of dirt. In addition, there are cases in which fabric softener is also used. The detergent and fabric softener are selected based on the preferences of the user U. New detergent and fabric softener products are released every year. The number of such combinations increases every year. In this way, even if evaluations are performed to the extent possible during the development stage of a home appliance or the evaluation stage for commercialization, it is difficult to perform evaluations that reproduce all cases of actual usage in a market where the situation is changing.

The service support system 1A of this embodiment focuses on events related to defects that have occurred in the market, uses data related to these events to generate a correspondence table for the defect response history DB326, and uses this to recommend a response policy for service. By appropriately updating the data in the correspondence table for the defect response history DB326, it becomes possible to respond appropriately to changes in market conditions.

In this embodiment, it is assumed that users U who select the same brands of detergent and fabric softener to be used in combination tend to experience common problems.

For example, it can be inferred that a user U who selects a brand of detergent characterized by its "high cleaning effect on muddy stains" washes a relatively large amount of clothes with "muddy stains." In this case, it can be inferred that when washing clothes using the above brand of detergent, the user tends to select an operating mode that effectively removes stains.

In this way, by linking information about actual defects that have occurred in the market to detergent brands, it is possible to collect data not only on the "characteristics of the detergent" but also on the "characteristics related to the usage method of user U who uses that detergent." By classifying user U's usage method in relation to detergent brands, more accurate information can be obtained.

The above data can also be applied to evaluations during the development stage of washing machines (home appliances). By conducting tests using various brands of detergent, it is possible to reproduce phenomena that may occur due to the characteristics of the detergent or fabric softener brand. In this case, by adding the usage tendencies of user U to the test conditions, it becomes possible to perform evaluations that are closer to actual usage.

The scale of the correspondence table will now be described.
The examples shown in the correspondence table of Fig. 6 are limited, but are not limited to these. To create this correspondence table, for example, cases in which either a detergent or fabric softener that is readily available on the market was used may be extracted from the information on the maintenance history of each user, and the parts used in the service content at that time may be associated with data on the status of resolution of the defect after the service.

For example, if the number of extracted cases is small, it is best to use the information for all cases as is. If the number of extracted cases is large, or if there are many overlapping cases, organize the information to avoid overlaps and show the frequency associated with the cases, which also allows you to check the tendency (frequency) of occurrence.

According to the above embodiment, the reference data generation unit 316 generates a defect response history DB 326 (reference data) that associates parts (response methods) related to handling the defect of the target device with information about items used in combination with the target device for the target device in which a defect has occurred. The estimation processing unit 315 can predict parts (response methods) related to handling the defect of the other target devices using the reference data in the defect response history DB 326 and information from users related to the other target devices. This makes it possible to estimate parts that may be required when responding to a service request.

Service personnel who make on-site repairs of home appliances would predict what parts would be needed for the repairs based on the report information provided by users U and the like, and arrange for them in advance, but by using the service support system 1A, the burden of preparation work can be reduced.

For example, the service support system 1A predicts service parts that can resolve the reported defect based on information from past service responses, and recommends the prediction results. This allows the service support system 1A to support work in the preparation stage of service responses.

By applying this recommendation, it is possible to identify "unnecessary parts" rather than "necessary parts." For example, as mentioned above, there are various possible causes for a malfunction such as "the drum of the washing machine does not spin." If the above analysis identifies that the motor is likely the cause of the malfunction, then the motor can be arranged, but it may not be possible to arrange for the parts around the tub. In such cases, it becomes possible to make an on-site repair visit to the user's home without waiting for the parts around the tub to be arranged. This allows the malfunction to be resolved early, leading to improved service.

According to the above embodiment, by estimating parts that may be required during service, it is possible to reduce the burden of incidental work during service for a malfunction that has occurred.

For example, the reference data generation unit 316 generates reference data for a target device that has been repaired, which associates information about the service parts used in the repair with information about items used in combination with the target device. The estimation processing unit 315 may use the reference data and information from the user about the other target devices to predict service parts to be used in repairing the other target devices.

The estimation processing unit 315 may predict the service parts required to repair the target device and provide the information to the service technician in charge of the repair.

According to at least one embodiment described above, the service support system of the embodiment includes an estimation processing unit and an output control unit. The estimation processing unit predicts a malfunction of the target device or a method for dealing with the malfunction, using information from the user about the target device and about an item used in combination with the target device. The output control unit outputs the result of the prediction. This makes it possible to reduce the burden of incidental work when providing service for a malfunction that has occurred.

Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

For example, if the use of the target device varies depending on the family composition, the service support device 3 may use family information registered using an app on the terminal device 15 for the above analysis process.

1...service support system, 3...service support device, 310...control unit, 311...user attribute information acquisition unit, 312...declaration information acquisition unit, 313...purchase history information acquisition unit, 314...feature extraction unit, 315...estimation processing unit, 316...reference data generation unit, 317...output control unit, 318...operation history information acquisition unit, 320...storage unit, 10...first residence, 20...second residence, 15, 25, 31, 32...terminal device, U...user

Claims (10)

A service support system that provides information on how to deal with a problem occurring in a user's target device,
an estimation processing unit that predicts a method of dealing with the malfunction of the target device based on history information on a malfunction of the target device associated with the identification information of the user, purchase history information of an item used in combination with the target device, the purchase history information being obtained from a mail-order system, and information on the malfunction of the target device ;
and an output control unit that outputs a result of the prediction. 2. The service support system according to claim 1, further comprising: a feature extraction unit that estimates the characteristics of the user by using at least one of the following information about the user: information about the user's attributes, information about the model of the target device used by the user, information about the operation history of the target device, and information about items used in combination with the target device. The estimation processing unit:
The service support system according to claim 1 , further comprising: predicting the content of the malfunction of the target device from information on the malfunction of the target device held by a service provider related to the target device. The estimation processing unit:
The service support system according to claim 1 , further comprising: predicting parts required for repairing the target device in which the defect has occurred, based on information related to repairs held by a service provider relating to devices related to the target device. a reference data generating unit that generates reference data for the target device in which the malfunction has occurred, the reference data associating the content of the malfunction or a countermeasure method for the target device with information on an article to be used in combination with the target device;
The estimation processing unit:
The service support system according to claim 1 , further comprising: a predictor for predicting the content or a countermeasure for a problem in the other target device using the reference data and information from a user regarding the other target device. a reference data generating unit that generates reference data for the repaired target device, the reference data associating information on a service part used in the repair with information on an item to be used in combination with the target device;
The estimation processing unit:
The service assistance system of claim 1 , further comprising: predicting service parts for use in repairing the other target devices using the reference data and information from a user regarding the other target devices. The estimation processing unit:
predicting the content of the malfunction of the target device based on history information regarding a malfunction of the target device associated with the identification information of the user, purchase history information of the item, and information regarding the malfunction of the target device;
The service support system according to claim 4 , wherein the output control unit outputs a result of the prediction regarding the content of the malfunction so as to provide the information to a service person in charge of the repair. Reference data associating type information of the target device, history information on service parts used to repair the target device, and information on the item ;
Type information of the target device to be repaired;
Based on information on the malfunction of the target device,
predicting service parts required to repair the target device and providing the information to a service technician in charge of the repair;
The service support system according to claim 4. The service support system according to claim 1 , wherein the items to be used in combination with the target device include any one of consumables, foodstuffs, and water related to the target device. A computer of a service support system that provides information on how to deal with a malfunction occurring in a target device of a user ,
predicting a method of dealing with the malfunction of the target device based on history information related to the malfunction of the target device associated with the identification information of the user, purchase history information of the product obtained from a mail-order system and information on the malfunction of the target device;
and outputting a result of the prediction.

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