Patent Publication Number: US-2019196430-A1

Title: Method and apparatus for controlling appliance based on failure prediction

Description:
CROSS-REFERENCE TO RELATED APPLICATION(S) 
     This application is based on and claims priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2017-0178395, filed on Dec. 22, 2017, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     1. Field 
     The present disclosure relates generally to a method and apparatus for controlling an appliance based on failure prediction, and more particularly, to artificial intelligence (AI) systems that may mimic the human brain&#39;s capabilities of perception or determination by using machine learning algorithms and their applications. 
     2. Description of Related Art 
     The Internet is evolving from a human-centered connection network, where information is produced and consumed, to an Internet-of-things (IoT) network, where information is communicated and processed among distributed components. Internet of everything (IoE) technology is a combination of big data processing technology and IoT technology, such as through a connection with a cloud server. 
     Implementing the IoT requires technical elements, such as sensing technology, wired/wireless communication and network infrastructure, service interface, and security technologies. Recent ongoing research for thing-to-thing connection is related to techniques for sensor networking, machine-to-machine (M2M), or machine-type communication (MTC). 
     Within the IoT environment may be offered intelligent Internet technology services that collect and analyze the data generated by the interconnected things in order to create a new value of human life. The IoT may have various applications, such as a smart home, smart building, smart city, smart car or connected car, smart grid, health-care, smart appliance industry, or state-of-art medical services, through the conversion or integration of existing Internet technologies and various industries. 
     A home network system enables control of appliances by wiredly or wirelessly linking the appliances. Advanced home network systems offer various Internet-related services by connecting appliances to an external public data network, such as the Internet protocol (IP) network, directly or via home gateways or customer premises equipment (CPE). Advanced home network systems may also enable their users to directly or indirectly control and manage appliances while interworking with the users&#39; terminals. Such a home network system may offer services desired by users by controlling the appliances according to the users&#39; request. 
     In developing appliances used in home network systems, manufacturers place significant effort towards quality warranty and customer services. Current quality warranty systems predict a failure in an appliance before it occurs, enabling cost-effective operation and enhanced reliability. Manufacturers offer home visit services for automated failure diagnosis and repair, contributing to cost savings and more satisfaction. 
     Human intelligence-class AI systems are being utilized in various industry sectors, and learn on their own and become smarter, unlike existing rule-based smart systems. The more used, the more precisely AI systems may perceive and understand users&#39; preferences. Thus, legacy rule-based smart systems are being gradually replaced with deep learning-based AI systems. 
     AI technology consists of machine learning (e.g., deep learning) and machine learning-based component technology. 
     Machine learning is an algorithm technique that may classify and learn the features of input data. Component technology is for mimicking the perception and decision capabilities of the human brain by using a machine learning algorithm, such as deep learning, and may be divided into several technical fields, such as linguistic understanding, visual understanding, inference/prediction, knowledge expression, and operation control. 
     The following are examples of AI applications. Linguistic understanding is for recognizing and applying/processing a human being&#39;s language or text, and encompasses natural language processing, machine translation, dialog system, answering inquiries, and speech recognition/synthesis. Visual understanding is for perceiving and processing things as human eyes do, and encompasses object recognition, object tracing, image search, human recognition, scene recognition, space understanding, and image enhancement. Inference prediction is for determining and logically inferring and predicting information, encompassing knowledge/probability-based inference, optimization prediction, preference-based planning, and recommendation. Knowledge expression is for automatically processing human experience information, covering knowledge buildup (data production/classification) and knowledge management (data utilization). Operation control is for controlling the motion of robots and driverless car driving, and encompasses movement control (navigation, collision, driving) and maneuvering control (behavior control). 
     With recent technological developments and diversified user demand, however, there is a need in the art for a method and apparatus to both efficiently provide a customer visit service for repairing failures of appliances and to maintain normal operations of the appliances by considering a user&#39;s use pattern and a schedule based on the predicted failures of the appliances. 
     SUMMARY 
     An aspect of the disclosure is to address at least the above-mentioned problems and/or disadvantages and to provide at least the advantages described below. Accordingly, an aspect of the disclosure is to embodiment provide a method and apparatus for controlling an appliance based on failure prediction. 
     Another aspect of the disclosure is to provide a method and apparatus for maintaining the normal operation of an appliance if a failure is predicted. 
     Another aspect of the disclosure is to provide a method and apparatus for delaying the occurrence of a failure in an appliance. 
     Another aspect of the disclosure is to provide a method and apparatus for fixing a predicted derivative failure when an engineer visits to repair a failure of an appliance. 
     Another aspect of the disclosure is to provide a method and apparatus for fixing both a predicted failure of another appliance and a failure of an appliance concurrently, i.e., in the same visit, when an engineer visits to repair the failure of the appliance. 
     In accordance with an aspect of the disclosure, a method of an appliance includes receiving prediction information indicating a predicted failure of the appliance, obtaining a schedule for which use of a repair service for repairing the predicted failure based on the prediction information is available, transmitting a signal for requesting maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the obtained schedule is after a predicted failure time point indicated by the prediction information, receiving the maintenance information, and operating based on the maintenance information. 
     In accordance with another aspect of the disclosure, a method of a user terminal includes receiving prediction information indicating a predicted failure of an appliance, obtaining a schedule for which use of a repair service for repairing the predicted failure based on the prediction information is available, transmitting a signal for requesting maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the obtained schedule is after a predicted failure time point indicated by the prediction information, receiving the maintenance information, and transmitting the maintenance information to the appliance. 
     In accordance with another aspect of the disclosure, an appliance includes an executing unit, a communication unit configured to receive prediction information indicating a predicted failure of the appliance, to transmit a signal for requesting maintenance information used to delay the predicted failure and maintain the normal operation of the appliance, and to receive the maintenance information, and a controller configured to obtain a schedule for which use of a repair service for repairing the predicted failure based on the prediction information is available, to generate the signal if the obtained schedule is after a predicted failure time point indicated by the prediction information, and to control the executing unit to operate based on the maintenance information. 
     In accordance with another aspect of the disclosure, a user terminal includes a communication unit configured to receive prediction information indicating a predicted failure of an appliance, to transmit a signal for requesting maintenance information used to delay the predicted failure and maintain the normal operation of the appliance, to receive the maintenance information, and to transmit the maintenance information to the appliance, and a controller configured to obtain a schedule for which use of a repair service for repairing the predicted failure based on the prediction information is available, and to generate the signal if the obtained schedule is after a predicted failure time point indicated by the prediction information. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above and other aspects, features, and advantages of the present disclosure will be apparent from the following detailed description taken in conjunction with the accompanying drawings, in which: 
         FIG. 1  illustrates a system for managing an appliance based on failure prediction according to an embodiment; 
         FIG. 2  illustrates an appliance which may be controlled based on failure prediction according to an embodiment; 
         FIG. 3  illustrates a managing server configured to manage an appliance based on failure prediction according to an embodiment; 
         FIG. 4  illustrates a user terminal which may control an appliance based on failure prediction according to an embodiment; 
         FIG. 5  illustrates an operation of an appliance according to an embodiment; 
         FIG. 6  illustrates an operation of a managing server for managing an appliance according to an embodiment; 
         FIG. 7  illustrates an operation of a user terminal for maintaining an appliance in a normal operation state according to an embodiment; 
         FIG. 8  illustrates an operation of an appliance according to an embodiment; 
         FIG. 9  illustrates an operation of generating normal operation maintenance information for an appliance in a managing server according to an embodiment; 
         FIG. 10  illustrates an operation of generating a virtual operation pattern in a managing server according to an embodiment; 
         FIGS. 11A, 11B, and 11C  illustrate a scenario of maintaining a normal operation state of an air conditioner based on scheduling and control values of operation parameters of the air conditioner according to an embodiment; 
         FIGS. 12A, 12B, and 12C  illustrate a scenario of maintaining a normal operation state of a washer based on scheduling and control values of operation parameters of the washer according to an embodiment; 
         FIGS. 13A, 13B, and 13C  illustrate a scenario of maintaining a normal operation state of an air conditioner based on a control value of an operation parameter of the air conditioner according to an embodiment; 
         FIGS. 14A, 14B, and 14C  illustrate a scenario of maintaining a normal operation state of a refrigerator based on a control value of an operation parameter of the refrigerator according to an embodiment; 
         FIGS. 15A, 15B, and 15C  illustrate a scenario of maintaining a normal operation state of an appliance through use of a peripheral device according to an embodiment; 
         FIG. 16  illustrates a system of providing a repair service for repairing a predicted failure and a derivative failure of an appliance according to an embodiment; 
         FIG. 17  illustrates an operation of a user terminal for fixing a plurality of failures of an appliance concurrently according to an embodiment; 
         FIGS. 18A and 18B  illustrate information about a derivative failure of an appliance displayed on a user terminal according to an embodiment; 
         FIG. 19  illustrates an operation of a managing server for fixing a primary failure and a derivative failure of an appliance according to an embodiment; 
         FIG. 20  illustrates an operation of a managing server for generating derivative failure information according to an embodiment; 
         FIG. 21  illustrates an operation of a managing server for searching for a derivative failure of an appliance according to an embodiment; 
         FIG. 22  illustrates a system for providing a repair service for repairing a predicted failure of an appliance and a failure of another appliance according to an embodiment; 
         FIG. 23  illustrates an operation of a user terminal for fixing a plurality of predicted failures of a plurality of appliances concurrently according to an embodiment; 
         FIGS. 24A and 24B  illustrate information about a plurality of failures of a plurality of appliances displayed on a user terminal according to an embodiment; 
         FIG. 25  illustrates an operation of a managing server for fixing failures of a plurality of appliances according to an embodiment; and 
         FIG. 26  illustrates an operation of a managing server for generating failure prediction information of the second failure according to an embodiment. 
     
    
    
     Throughout the drawings, like reference numerals will be understood to refer to like parts, components, and structures. 
     DETAILED DESCRIPTION 
     Hereinafter, embodiments are described in detail with reference to the accompanying drawings. Descriptions of well-known functions and/or configurations will be omitted for the sake of clarity and conciseness. 
     For the same reasons, some elements may be exaggerated or schematically shown. The size of each element does not necessarily reflect the actual size of the element. The same reference numeral is used to refer to the same element throughout the drawings and detailed description. 
     Advantages and features of the disclosure, and methods for achieving the same may be understood through the embodiments to be described below taken in conjunction with the accompanying drawings. However, the disclosure is not limited to the embodiments disclosed herein, and various changes may be made thereto. The embodiments disclosed herein are provided only to inform one of ordinary skill in the art of the category of the disclosure, as defined only by the appended claims. 
     It should be appreciated that the blocks in each flowchart and combinations of the flowcharts may be performed by computer program instructions equipped in a processor of a general-use computer, a special-use computer or other programmable data processing devices. The instructions generate means for performing the functions described in connection with a block(s) of each flowchart. Since the computer program instructions may be stored in a computer-available or computer-readable memory that may be oriented to a computer or other programmable data processing devices to implement a function in a specified manner, the instructions may produce a product including an instruction means for performing the functions described in connection with blocks in each flowchart. Since the computer program instructions may be equipped in a computer or other programmable data processing devices, instructions that generate a process executed by a computer as a series of operational steps are performed over the computer or other programmable data processing devices, and operating the computer or other programmable data processing devices may provide steps for executing the functions described in connection with blocks in each flowchart. 
     Each block may represent a module, segment, or part of a code including one or more executable instructions for executing a specified logical function(s). In some replacement execution examples, the functions mentioned in the blocks may occur in different orders. For example, two blocks that are consecutively shown may be performed substantially simultaneously or in a reverse order depending on corresponding functions. 
     As used herein, the term “unit” indicates a software element or a hardware element, such as a field-programmable gate array (FPGA) or an application specific integrated circuit (ASIC). Although a unit plays a certain role, the term “unit” is not limited to indicating a software or hardware element, and may be configured in a storage medium that may be addressed or configured to reproduce one or more processors. Accordingly, a “unit” may include elements, such as software elements, object-oriented software elements, class elements, and task elements, processes, functions, attributes, procedures, subroutines, segments of program codes, drivers, firmware, microcodes, circuits, data, databases, data architectures, tables, arrays, and variables. A function provided in an element or a “unit” may be combined with additional elements, may be split into sub elements or sub units, and may be implemented to reproduce one or more central processing units (CPUs) in a device or a security multimedia card. 
     Although the description of embodiments herein mentions various particular systems and signal standards, the subject matter of the disclosure may also be applicable to other systems or services having similar technical backgrounds without departing from the scope of the disclosure, and this may be determined by one of ordinary skill in the art. 
     According to an embodiment, a user terminal may be an electronic device equipped with a communication feature, may provide a user interface (UI) to the user of the user terminal, and may communicate with at least one server over an external network and at least one appliance over a home network directly or via at least one network node, such as a home gateway, CPE, or router. The electronic device may be a portable electronic device, wearable electronic device, or mountable electronic device, for example. 
     The portable electronic device may include, but is not limited to, at least one of a smartphone, feature phone, tablet PC, laptop computer, video phone, electronic book reader, portable digital assistant (PDA), portable media player (PMP), moving picture experts group (MPEG) layer audio 3 (MP3) player, mobile medical device, electronic dictionary, electronic key, camcorder, or camera. 
     The wearable electronic device may include, but is not limited to, at least one of an accessory-type device, such as a watch, ring, bracelet, anklet, necklace, glasses, contact lenses, or head-mounted device (HMD), a fabric- or clothes-integrated device, such as electronic clothes or exercise clothing, a body attaching-type device, such as a skin pad or tattoo, or a body implantable device, such as an implantable circuit. 
     According to embodiments, the electronic device may be one or a combination of the above-listed devices, and may be a flexible electronic device. The electronic device disclosed herein is not limited to the above-listed devices and may include new electronic devices depending on the development of technology. 
     Various terms and expressions as used herein may be defined as follows.
         Appliance refers to smart appliances and electronic devices that may be installed in homes or offices and are equipped with the Internet access feature.   Managing server refers to a server that may be operated by the appliance manufacturer or manager and may communicate with a user terminal and/or at least one appliance. The managing server may include a failure prediction knowledge database (DB) that may be used to predict failures of the appliances based on the gathered operation data.   A failure prediction knowledge DB stores information used to predict a failure in various appliances, such as at least one of operation data, failure history, a control method for failure delay, failure repair history, manufacture information, environment information, and customer profile information.   Operation data is related to the operation of the appliance and may include at least one of sensor data gathered from at least one sensor in the appliance and an operation history.   An operation history refers to data that records operations as per the actual use of the appliance, and may include at least one of run-time, operation mode, operation period, operation count, and operation parameter of an appliance (or each component of the appliance). Operation parameter refers to information necessary for operation in each operation mode, such as a set temperature for an air conditioner, a load, dehydration level and dry level set for a washer, or a set temperature and a defrost cycle for a refrigerator.   Normal operation maintenance information is required for maintaining the normal operation state (i.e., in which there is no failure) of an appliance, and may be generated by considering a predicted failure of the appliance. For example, the normal operation maintenance information may define at least one of an operation per time (on/off or an operation mode) of the appliance and an operation pattern indicating a control value of an operation parameter for each operation, normal operation time information indicating a time duration during which it is predicted that normal operation in which a failure does not occur is possible if the normal operation maintenance information is applied, and at least one peripheral device which will be used for replacing or supplementing the appliance. For example, the normal operation maintenance information may define at least one normal operation maintenance mode which may delay the predicted failure of the appliance.   A normal operation maintenance mode denotes an operation mode for delaying a predicted failure of an appliance such that the appliance maintains the state in which the appliance normally operates, and may also be referred to as failure delay mode. Each normal operation maintenance mode defines at least one of a failure item of a predicted failure, an operation per time (on/off or an operation mode) of an appliance and an operation pattern indicating a control value of an operation parameter for each operation, normal operation time information indicating a time duration during which it is predicted that normal operation is possible if corresponding normal operation maintenance information is applied, and at least one peripheral device which will be used for replacing or supplementing the appliance.   An operation pattern indicates an operation required per time and a control value(s) of an operation parameter(s) for a corresponding operation of an appliance. For example, an operation pattern for an air conditioner may be 9:00 am-12:00 pm: weak wind &amp; set temperature 70 degrees Fahrenheit (F), 3:00 pm-4:00 pm: weak wind &amp; set temperature 72 degrees F., and 8:00 pm-8:30 pm: automatic. For another example, an operation pattern for a washer may be Monday: load 85 kg &amp; dehydration level 3 &amp; dry level 2, Wednesday: load 5 kg &amp; dehydration level 3 &amp; dry level 3, and Friday: load 5 kg &amp; dehydration level 3 &amp; dry level 2.   A user preference criterion defines an operation pattern which a user requests or prefers. For example, a user preference criterion for an air conditioner may include at least one of a minimum set temperature and minimum run time. For another example, a user preference criterion for a washer may include at least one of an operation count per week, an operation date, a minimum load, a minimum dehydration level, and a minimum dry level.   Failure prediction information indicates a predicted failure of an appliance, and may be generated by a managing server based on a failure prediction knowledge DB. The failure prediction information may include at least one of a failure item, a predicted failure time point, and the degree of risk of the predicted failure.   A derivative failure denotes another failure which may derive due to a failure which occurs in an appliance or a predicted failure of the appliance. Derivative failure information indicating a derivative failure may be generated based on the failure history of the same or similar type appliances. A failure item within a failure prediction knowledge DB may be linked to at least one derivative failure.   Recommended schedule information indicates a schedule recommended by a managing server such that a repair service may be used. For example, the recommended schedule information indicates the hour, day, month, and year.   The same premises spaces denote a space identified by the same address such as a home or an office.       

     The disclosure describes techniques for extending the state at which an appliance normally operates by delaying a failure of the appliance based on a predicted failure of the appliance. 
     The disclosure provides a provision of a home visit repair service which may repair a failure occurring in an appliance or a predicted failure of the appliance and a derivative failure related to the failure occurring in the appliance or the predicted failure of the appliance through one visit. 
     The disclosure provides a provision of a home visit repair service which may repair a failure occurring in an appliance or a predicted failure of the appliance and a failure which is predicted for another appliance within the same home as the appliance through one visit. 
     As used herein, the term “user” may denote a human or an artificial intelligent electronic device using the electronic device. 
       FIG. 1  illustrates a system for managing an appliance based on failure prediction according to an embodiment. 
     Referring to  FIG. 1 , a home system  100  includes one or more appliances  102 ,  104 , and  106 , at least one of which may be a smart appliance with an Internet access feature and may communicate with a user terminal  120  and/or a managing server  110  using a wired or wireless communication scheme, such as wireless-fidelity (Wi-Fi), Zigbee®, Bluetooth®, near-field communication (NFC), or z-wave. At least one of appliances  102 ,  104 , and  106  may communicate with the managing server  110  directly or via the user terminal  120 , a home gateway, or a CPE, may be one of a refrigerator, washer, air conditioner, oven, robot cleaner, television, air circulator, air purifier, and dehumidifier, for example, and may be a smart appliance that is not shown or mentioned herein. 
     The appliances  102 ,  104 , and  106  may be configured to receive control commands from the user terminal  120  or the managing server  110 , operated as per the control commands, and to transmit requested information and/or operation data to the user terminal  120  or the managing server  110 . For example, the appliances  102 ,  104 , and  106  may receive failure predication information and/or normal operation maintenance information from the managing server  110  through the user terminal  120  or directly from the managing server  110 , and operate in one of at least one normal operation maintenance mode defined by the normal operation maintenance information. The appliances  102 ,  104 , and  106  may have a user interface to receive user input about whether to execute a normal operation maintenance mode, display the at least one normal operation maintenance mode defined by the normal operation maintenance information, and request of a user to select a normal operation maintenance mode preferred by the user. 
     The managing server  110  has a failure prediction knowledge DB  114  which stores information that may be used for predicting failures of the appliances  102 ,  104 , and  106  and a failure prediction engine  112  for predicting failures which may occur in the appliances  102 ,  104 , and  106  based on the failure prediction knowledge DB  114 . The managing server  110  may generate failure prediction information for the appliances  102 ,  104 , and  106  and normal operation maintenance information according to the failure prediction information using the failure prediction knowledge DB  114  and the failure prediction engine  112 , and provide the appliances  102 ,  104 , and  106  with the failure prediction information and/or the normal operation maintenance information. 
     It will be described herein that the managing server  110  may further store and manage information related to a home visit repair service for the appliances  102 ,  104 , and  106 , a failure history, and failure repair history. However, a customer service (CS) server, which is a separate network entity for gathering, storing, and managing the information related to the home repair service for the appliances  102 ,  104 , and  106 , the failure history, and failure repair history information, may be configured to communicate with the managing server  110  according to an implementation. In other words, the managing server  110  may be implemented with one or more logical/physical entities, may manage at least one user terminal  130  that is registered in association with the appliances  102 ,  104 , and  106 , and may communicate the information related to the appliances  102 ,  104 , and  106  to the registered user terminal  120 . 
     The user terminal  120  may communicate with the one or more appliances  102 ,  104 , and  106  which may be located at the same home or at different homes directly or through a home gateway or a CPE, and may receive failure prediction information and/or normal operation maintenance mode information for at least one of the appliances  102 ,  104 , and  106  from the managing server  110  to transmit the information to a corresponding appliance. The user terminal  120  may gather operation data from the appliances  102 ,  104 , and  106 , and transmit the gathered operation data to the managing server  110 . The user terminal  120  may receive user input about whether to execute a normal operation maintenance mode through a user interface, display information about at least one normal operation maintenance mode defined by the normal operation maintenance information, and request of a user to select a normal operation maintenance mode preferred by the user among the displayed at least one normal operation maintenance mode. 
       FIG. 2  illustrates an appliance which may be controlled based on failure prediction according to an embodiment. The appliance may be configured with at least one of a native function executing unit  210  (also referred to herein as an “executing unit”), a controller  220 , a communication unit  230 , a storage unit  240 , and a user interface (UI) unit  250 . 
     The native function executing unit  210  includes software and hardware components for executing the native functions of the appliance. In examples, when the appliance is an air conditioner, the native function executing unit  210  may include a fan, compressor, condenser, evaporator, expansion valve, and various sensors for gathering data. When the appliance is a washer, the native function executing unit  210  may include a door, light, power source, tub, speed changer, motor, pump, heater, temperature adjuster, and various sensors. When the appliance is a refrigerator, the native function executing unit  210  may include a door, light, power source, fan, evaporator, condenser, compressor, defrost circuit (e.g., a defrost sensor, heater, or timer), and various sensors. The native function executing unit  210  may receive control values for operation parameters necessary to operate the components from the controller  220  and may operate each component using the operation parameters. 
     The controller  220  may manage operation data of an appliance, gather sensor data by monitoring the operation history of the native function executing unit  210 , and transmit the operation data to a managing server and/or a user terminal through the communication unit  230 . The operation data may include at least one of the operation history and sensor data gathered from at least one sensor within the native function executing unit  210 . The operation history denotes data in which an operation of the native function executing unit  210  is recorded, and may include at least one of run time, operation mode, operation cycle, and operation count. The controller  220  may receive failure prediction information and/or normal operation maintenance information from the managing server to control an operation of the native function executing unit  210  according to the received information. 
     The communication unit  230  includes a communication interface that supports the controller  220  to be able to communicate with the user terminal and/or the managing server over the Internet. As an example, the communication unit  230  may include a wired communication module and/or a wireless communication module that supports at least one of Wi-Fi, zigbee®, bluetooth®, NFC, and z-wave and may access the managing server and/or user terminal directly or via a home gateway or CPE. 
     The storage unit  240  may include a read-only memory (ROM), which stores a control program to operate the appliance, and a random-access memory (RAM), which stores signals or data input from outside of the appliance or is used as a storage area for tasks performed on the appliance. In examples, the storage unit  240  stores operation data related to the appliance, such as sensor data and operation history gathered through the actual operation of the native function executing unit  210 , and stores normal operation maintenance information used for controlling the native function executing unit  210 . 
     The UI unit  250  may provide failure prediction information, normal operation maintenance information, and home visit repair service schedule, delivered from the controller  220  to the user or may receive a user input and deliver the input to the controller  220 . To that end, the UI unit  250  may include a display, a touchscreen, at least one physical button, at least one light emitting diode (LED), a microphone, and/or a speaker. 
     While the native function executing unit  210 , controller  220 , communication unit  230 , storage unit  240 , and UI unit  250  are described in the appliance as separate units in  FIG. 2 , the appliance may be implemented in a form in which at least two of these components are integrated. 
     Each of the native function executing unit  210 , the controller  220 , the communication unit  230 , the storage unit  240 , and the UI unit  250  may be implemented with at least one processor. The appliance may also be implemented with at least one processor. 
       FIG. 3  illustrates a managing server configured to manage an appliance based on failure prediction according to an embodiment. The managing server may be configured with at least one of a communication unit  310 , a controller  320 , and a storage unit  330 . 
     The communication unit  310  includes a communication interface that supports the controller  320  to enable communication through the Internet with at least one appliance, user terminal, and/or at least one network entity. The network entity may be, such as a CS server that manages the CS for the appliance. 
     The controller  320  predicts a failure of an appliance based on operation data of at least one appliance received from the communication unit  310 , and generates failure prediction information indicating the predicted failure. The controller  320  may generate normal operation maintenance information required for maintaining the normal operation of the appliance by delaying the predicted failure related to the failure prediction information. The failure prediction information and/or normal operation maintenance information may be transmitted to a corresponding appliance and/or user terminal through the communication unit  310 . The controller  320  may communicate with a CS server that manages the repair service through the communication unit  310 , send a request for the repair service to the CS server, and receive, through the communication unit  310 , information related to the repair service, the failure history, and failure repair history, from the CS server. The controller  320  may deliver, to the CS server, information available for the repair service, such as operation data, failure history, failure repair history, manufacture information, environment information about the environment (mean temperature, mean humidity, or installation height) where the appliance is installed, and customer profile information. If there is a predicted failure for a corresponding appliance, the controller  320  may further provide the CS server with failure prediction information and/or normal operation maintenance information. 
     The storage unit  330  may include a ROM, which stores a control program to operate the managing server, and a RAM, which stores signals or data input from outside of the managing server or is used as a storage area for tasks performed on the managing server. The storage unit  330  further includes a failure prediction knowledge DB  332  that stores information available for predicting a failure in at least one appliance. The failure prediction knowledge DB  332  may store at least one of operation data, failure histories, control methods for delaying failure, failure repair histories, manufacture information, environment information, and customer profile information. The storage unit  330 , the failure prediction knowledge DB  332 , or a separate storage space may store failure prediction information and/or normal operation maintenance information generated by the controller  320  for each appliance. 
     While the communication unit  310 , the controller  320 , and the storage unit  330  are described in the managing server as separate units in  FIG. 3 , the managing server may be implemented in a form in which at least two of the communication unit  310 , the controller  320 , and the storage unit  330  are integrated. Each of the communication unit  310 , the controller  320 , and the storage unit  330  may be implemented with at least one processor. The managing server may also be implemented with at least one processor. 
       FIG. 4  illustrates a user terminal which may control an appliance based on failure prediction according to an embodiment. The user terminal may be configured with at least one of a communication unit  410 , a controller  420 , a sensing unit  430 , and a user interface (UI) unit  440 . The communication unit  410  includes a communication interface that supports the controller  420  to be able to communicate with at least one appliance and/or the managing server over the Internet. As an example, the communication unit  410  may include a wired communication module and/or a wireless communication module that supports at least one of Wi-Fi, zigbee®, bluetooth®, NFC, and z-wave and may access the appliance directly or via a home gateway or CPE. The communication unit  410  may include a broadband communication module such as 3rd generation partnership project (3GPP) or long-term evolution (LTE) and may communicate with the managing server via the Internet. 
     The controller  420  may receive failure prediction information and/or normal operation maintenance information for an appliance from a managing server through the communication unit  420 , and transmit the failure prediction information and/or normal operation maintenance information to the appliance. In examples, the controller  420  may transmit, to the appliance, information about at least one normal operation maintenance mode which a user selects through the UI unit  440  from among a plurality of normal operation maintenance modes defined by the normal operation maintenance information, or may gather operation data from the appliance and transmit the gathered operation data to the managing server. 
     The storage unit  430  may include a ROM, which stores a control program to operate the user terminal, and a RAM, which stores signals or data input from outside of the user terminal or is used as a storage area for tasks performed on the user terminal. The storage unit  430  may store the normal operation maintenance information to be used for controlling the appliance. 
     The UI unit  440  may provide information, such as failure prediction information, normal operation maintenance information, or a repair service schedule, delivered from the controller  420  to the user or may receive a user input and deliver the input to the controller  420 . To that end, the UI unit  440  may include a display, a touchscreen, at least one physical button, at least one light emitting diode (LED), a microphone, and/or a speaker. 
     While the communication unit  410 , the controller  420 , the storage unit  430 , and the UI unit  440  are described in the user terminal as separate units in  FIG. 4 , the user terminal may be implemented in a form in which at least two of these components are integrated. Each of the communication unit  410 , the controller  420 , the storage unit  430 , and the UI unit  440  may be implemented with at least one processor. The user terminal may also be implemented with at least one processor. 
     At least one of the controllers  220 ,  320 , and  420  of  FIGS. 2 to 4  may be produced in at least one hardware chip and equipped in an electronic device. For example, the controller may be formed in a dedicated hardware chip for AI or in a part of an existing general-purpose processor, such as a CPU or application processor, or a graphic dedicated processor, such as a graphics processing unit (GPU), and be equipped in various electronic devices. In this case, the dedicated hardware chip for AI may be a dedicated processor specified for probability computations, which may quickly process AI computation tasks, such as machine learning, with better parallel processing performance than existing general-purpose processors. 
       FIG. 5  illustrates an operation of an appliance according to an embodiment. Referring to  FIG. 5 , an appliance transmits, to a managing server, operation data according to the execution of a unique operation in step  505 . The operation data may include at least one of an operation history and sensor data of the appliance, is periodically transmitted to the managing server, or is transmitted to the managing server according to a predetermined event or according to a request of the managing server. 
     The appliance receives failure prediction information indicating a predicted failure of the appliance from the managing server in step  510 . The failure prediction information is generated by the managing server if the managing server determines that a failure of the appliance is predicted based on operation data gathered from the appliance. The failure prediction information may include at least one of a failure item of the predicted failure, and a predicated failure time point, such as at least one date when a failure may occur or the first date and the last date when the failure may occur. The appliance may receive recommended schedule information indicating a recommended schedule of a repair service to repair the predicated failure along with the failure prediction information, and indicating the schedule of an engineer who may visit to provide the repair service and at least one recommended time point/item determined by considering the predicted failure time point. 
     The appliance determines whether a repair service for repairing the predicted failure is available before it reaches the predicated failure time point included in the failure prediction information in step  515 . For this, the appliance may display the failure prediction information and receive user input for whether the user may use the repair service before the predicated failure time point. For example, the appliance may determine a service availability schedule indicating a time point or duration at which a user may use the repair service for repairing the predicted failure by user input, and compare the determined service availability schedule with the predicted failure time point. If the user input indicating that a user uses the repair service before the predicted failure time point is received, that is, if the determined service availability schedule is before the predicted failure time point, the appliance may transmit a request signal for the repair service to the managing server in step  540 . For example, the request signal may include a date and time, which are determined based on the recommended schedule information provided from the managing server. 
     If the user input indicating that the user does not use the repair service before the predicted failure time point is received, that is, if the determined service availability schedule is after the predicted failure time point, the appliance transmits a request signal for normal operation maintenance information required for maintaining the normal operation state to the managing server in step  520 . The request signal may include information about a user preference criterion which the user requests for an operation of the appliance. The user preference criterion defines an operation pattern of the appliance which the user requests or prefers, such as at least one of the performance of the appliance or the failure delay availability time, which the user requests. A user preference criterion for an air conditioner may include at least one of a minimum set temperature and minimum run time. A user preference criterion for a washer may include at least one of operation counts per week, an operation date, a minimum load, a minimum dehydration level, and a minimum dry level. 
     The appliance receives, from the managing server, the normal operation maintenance information required for maintaining the normal operation state of the appliance in response to the request signal for the normal operation maintenance information in step  525 . The normal operation maintenance information may define at least one normal operation maintenance mode, and each normal operation maintenance mode defined by the normal operation maintenance information may include at least one of a failure item of a predicted failure, an operation per time of the appliance and an operation pattern indicating a control value of an operation parameter for each operation, normal operation time information (or a delayed failure time point) indicating a time duration during which it is predicted that normal operation is possible if a corresponding normal operation maintenance mode is applied, and information about at least one peripheral device which will be used for replacing or supplementing the appliance. 
     The appliance displays information of at least one normal operation maintenance mode defined by the normal operation maintenance information and receives user input for selecting a normal operation maintenance mode which is applied to the appliance based on the at least one normal operation maintenance mode in step  530 . The appliance executes a native function of the appliance according to a normal operation maintenance mode selected by the user input in step  535 . The appliance operates according to the normal operation maintenance mode, so the appliance may delay the occurrence of a failure to a time point after a predicted failure time point and a user may more leisurely use a repair service. 
     Although  FIG. 5  illustrates an operation of an appliance according to an embodiment, various changes could be made to  FIG. 5 . For example, although shown as a series of operations, various operations in  FIG. 5  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 6  illustrates an operation of a managing server for managing an appliance according to an embodiment. Referring to  FIG. 6 , a managing server gathers operation data of an appliance in step  605 . The operation data occurs according to whether the appliance executes a native function, and may include at least one of an operation history and sensor data of the appliance. The managing server may generate a failure prediction knowledge DB which may be used for predicting failures of appliances using the operation data and operation data gathered from other appliances. For example, the failure prediction knowledge DB may include at least one of operation data, operation history, a control method for failure delay, failure repair history, manufacture information, environment information, and customer profile information. 
     The managing server determines whether there is a predicted failure of the appliance using the failure prediction knowledge DB in step  610 . If there is the predicted failure, the managing server generates failure prediction information indicating the predicted failure and transmits the failure prediction information to the appliance in step  615 . 
     The managing server determines whether a request signal for normal operation maintenance information is received from an appliance related to the predicted failure in step  620 . If the request signal for the normal operation maintenance information is not received, the managing server returns to step  605 . 
     If the request signal for the normal operation maintenance information is received, the managing server generates normal operation maintenance information required for maintaining the normal operation state of the appliance by delaying the predicted failure in step  625 . For example, the normal operation maintenance information may indicate at least one normal operation maintenance mode which may delay the predicted failure and which may include at least one of a failure item of a predicted failure, an operation per time of the appliance and an operation pattern indicating a control value of an operation parameter for each operation, normal operation time information (or a delayed failure time point) indicating a time duration during which it is predicted that normal operation is possible if corresponding normal operation maintenance information is applied, and information about at least one peripheral device which will be used for replacing or supplementing the appliance. 
     The managing server transmits the generated normal operation maintenance information to the appliance in step  630 . At this time, failure prediction information related to the generated normal operation maintenance information may be transmitted to the appliance along with the generated normal operation maintenance information. 
     Although  FIG. 6  illustrates an operation of a managing server for managing an appliance according to an embodiment, various changes could be made to  FIG. 6 . For example, although shown as a series of operations, various operations in  FIG. 6  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 7  illustrates an operation of a user terminal for maintaining an appliance in a normal operation state according to an embodiment. Referring to  FIG. 7 , a user terminal receives failure prediction information indicating a predicted failure of an appliance from a managing server in step  705 . The failure prediction information may be generated by the managing server if the managing server determines that a failure of the appliance is predicted based on operation data gathered from the appliance. The user terminal may receive recommended schedule information indicating a recommended schedule of a repair service for repairing the predicted failure along with the failure prediction information. 
     The user terminal determines whether the repair service for repairing the predicted failure is available before it reaches the predicated failure time point included in the failure prediction information in step  710 . For this, the user terminal may display the failure prediction information and receive, from the user, user input for whether the user may use the repair service before the predicated failure time point. If a user input indicating that the user will use the repair service before the predicted failure time point is received, the user terminal may transmit a request signal for the repair service to the managing server in step  715 . The request signal may include a date and time, which are determined based on the recommended schedule information provided from the managing server. 
     If a user input indicating that the user will not use the repair service before the predicted failure time point is received, the user terminal transmits a request signal for normal operation maintenance information required for maintaining the normal operation state to the managing server in step  720 . For example, the request signal may include information about a user preference criterion which the user requests for an operation of the appliance and which defines at least one of performance and failure delay availability time of the appliance which the user requests or prefers. 
     The user terminal receives, from the managing server, the normal operation maintenance information in response to the request signal for the normal operation maintenance information in step  725 . The normal operation maintenance information may define at least one normal operation maintenance mode including at least one of a failure item of the predicted failure, an operation per time of the appliance and an operation pattern indicating a control value of an operation parameter for each operation, normal operation time information (or a delayed failure time point) indicating a time duration during which it is predicted that normal operation is possible if the normal operation maintenance mode is applied, and information about at least one peripheral device which will be used for replacing or supplementing the appliance. 
     The user terminal displays information of at least one normal operation maintenance mode defined by the normal operation maintenance information and receives user input for selecting a normal operation maintenance mode which will be applied to the appliance based on the at least one normal operation maintenance mode in step  730 . The user terminal controls the appliance according to a normal operation maintenance mode selected by the user input in step  735 . The user terminal may transmit information about the operation pattern to the appliance for controlling the appliance such that the appliance operates according to an operation pattern which is based on the selected normal operation maintenance mode. For example, the information about the operation pattern includes at least one of an operation per time and a control value of an operation parameter for each operation. The user terminal may transmit, to at least one peripheral device which will be used for replacing at least part of functions of an appliance for which a failure is predicted, a control command including at least one of an operation per time (e.g., on/off or an operation mode) and control values of operation parameters of each operation. Occurrence of a failure of the appliance may be delayed after the predicted failure time point by controlling the appliance to operate according to the normal operation maintenance mode, to enable a user to more leisurely use a repair service. 
     Although  FIG. 7  illustrates an operation of a user terminal for maintaining the normal operation state in an appliance according to an embodiment, various changes could be made to  FIG. 7 . For example, although shown as a series of operations, various operations in  FIG. 7  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 8  illustrates an operation of an appliance according to an embodiment. Referring to  FIG. 8 , an appliance reports, to a managing server, operation data which occurs according to the execution of a native function in step  805 . The operation data is reported to a user terminal, and may be transmitted to the managing server by the user terminal. The appliance receives, from the user terminal, information about an operation pattern for maintaining the normal operation in step  810 . The information includes at least one of an operation per time and a control value of an operation parameter for each operation, and is generated by the user terminal according to one normal operation maintenance mode which is selected by the user terminal among at least one normal operation maintenance mode determined by the managing server. 
     The appliance operates in the normal operation maintenance mode according to at least one of the operation per time and the control value of the operation parameter for each operation indicated by the information about the operation pattern in step  815 . 
     Although  FIG. 8  illustrates an operation of an appliance according to an embodiment, various changes could be made to  FIG. 8 . For example, although shown as a series of operations, various operations in  FIG. 8  could overlap, or occur in parallel, in a different order, or multiple times. 
     As described above, an appliance may delay the occurrence of a failure after a predicted failure time point by operating according to a normal operation maintenance mode, to enable a user to more leisurely use a repair service. The managing server may determine the normal operation maintenance mode which may be applied to the appliance by considering a predicted failure, and operation data and an operation pattern of the appliance. 
       FIG. 9  illustrates an operation of generating normal operation maintenance information for an appliance in a managing server according to an embodiment. 
     Referring to  FIG. 9 , a managing server receives a request signal for normal operation maintenance information required for maintaining the normal operation state of an appliance of which a failure is predicted in step  905 . For example, the request signal may be received from an appliance which operates as shown in step  520  of  FIG. 5  or from a user terminal which operates as shown in step  720  of  FIG. 7 . 
     The managing server generates one or more virtual operation patterns which may delay a predicted failure of an appliance by considering an operation history of the appliance in step  910 . Each virtual operation pattern may include an operation required per time and a control value(s) of an operation parameter(s) for a corresponding operation of the appliance. In examples, a virtual operation pattern for an air conditioner includes at least one of run time, such as in hours per day, an operation mode, such as strong wind, medium wind, weak wind, or dehumidification, and a set temperature. A virtual operation pattern for a washer includes at least one of run time, such as in days per week, load weight, an operation mode, such as washing, dehydration, or dry, and an operation level. 
     The managing server generates failure prediction information according to each virtual operation pattern in step  915 . That is, the managing server predicts a failure which may occur when the appliance operates according to each virtual operation pattern, and generates the failure prediction information including an occurrence time point and the degree of risk of the predicted failure. 
     The managing server transmits, to a user terminal, candidate information indicating at least one candidate of a normal operation maintenance mode which corresponds to each virtual operation pattern in step  920 , and receives, from the user terminal, user preference criterion information indicating an operation pattern which a user requests for the appliance or which the user prefers in step  925 . That is, the user preference criterion information indicates an operation pattern in which the user requests the appliance to operate at a minimum. In examples, a user preference criterion for an air conditioner may include at least one of a minimum set temperature and minimum run time. A user preference criterion for a washer may include at least one of operation counts per week, an operation date, a minimum load, a minimum dehydration level, and a minimum dry level. The user preference criterion information may be generated based on each candidate of a normal operation maintenance mode indicated by the candidate information received from the managing server, and may further include information about a time duration, such as three days, five days, or seven days, during which it is desired that the normal operation of the appliance is possible. 
       FIG. 9  illustrates step  920 , in which the managing server transmits the candidate information to the user terminal, and step  925 , in which the managing server receives the user preference criterion information from the user terminal; however, at least one of step  920  and step  925  may be omitted according to implementation. In examples, the managing server may receive a request signal including the user preference criterion information in step  905  instead of omitting steps  920  and  925 . If the candidate information is transmitted to the user terminal, the user terminal may transmit a response signal indicating at least one candidate which is selected according to user input based on the candidate information in step  920 . The candidate information is transmitted to the appliance, and the managing server may receive the response signal indicating the at least one candidate which is selected according to the user input from the appliance. 
     The managing server determines whether each candidate of the normal operation maintenance mode determined in step  920  according to the user preference criterion information received in step  925  or step  905  satisfies the user preference criterion in step  930 . If there is no candidate of the normal operation maintenance mode which satisfies the user preference criterion, the managing server returns to step  910 . If there is a candidate of the normal operation maintenance mode which satisfies the user preference criterion, the managing server generates normal operation maintenance information indicating the normal operation maintenance mode which satisfies the user preference criterion in step  935 . If there is one or more normal operation maintenance modes which satisfy the user preference criterion, the normal operation maintenance information may indicate the one or more normal operation maintenance modes, such as by further including information indicating a normal operation maintenance mode which is recommended among the one or more normal operation maintenance modes. 
     The managing server transmits, in step  940 , the generated normal operation maintenance information to an appliance or a user terminal which transmits the request signal for the normal operation maintenance information in step  905 . For example, the managing server may transmit failure prediction information which corresponds to each normal operation maintenance mode to a corresponding appliance or user terminal along with the normal operation maintenance information. 
     Although  FIG. 9  illustrates an operation of generating normal operation maintenance information for an appliance in a managing server according to an embodiment, various changes could be made to  FIG. 9 . For example, although shown as a series of operations, various operations in  FIG. 9  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 10  illustrates an operation of generating a virtual operation pattern in a managing server according to an embodiment. The managing server may generate the virtual operation pattern in step  910  according to at least one of an embodiment as shown in  FIG. 10  and embodiments which are not described in the disclosure. 
     Referring to  FIG. 10 , a managing server gathers operation data in which an operation of an appliance is recorded from the appliance in step  1005 . For example, the operation data may include at least one of an operation history of the appliance and sensor data gathered from at least one sensor within the appliance. The managing server searches for a control method for delaying a predicted failure of the appliance using the operation data to maintain a normal operation state of the appliance from a failure prediction knowledge DB in step  1010 . The control method may include at least one of control based on an operation per time and a control value of an operation parameter for each operation, and based on at least one peripheral device to be used for replacing or supplementing the appliance. The managing server determines a control method which may be applied to the appliance based on the searched result in step  1015 , and determines a virtual operation pattern including the determined control method in step  1020 . 
     Although  FIG. 10  illustrates an operation of generating a virtual operation pattern in a managing server according to an embodiment, various changes could be made to  FIG. 10 . For example, although shown as a series of operations, various operations in  FIG. 10  could overlap, or occur in parallel, in a different order, or multiple times. 
     Embodiments and scenarios for delaying a predicted failure of an appliance and in which a user terminal communicates with a managing server to maintain a normal operation of an appliance will be described below; however, it will be noted that a similar description may be applied to a case when the appliance, not the user terminal, communicates with the managing server to maintain the normal operation of the appliance. 
       FIGS. 11A, 11B, and 11C  illustrate a scenario of maintaining the normal operation state of an air conditioner based on scheduling and control values of operation parameters of the air conditioner according to an embodiment. 
     Referring to  FIG. 11A , a user terminal  1102  may receive and display failure prediction information  1105  indicating a failure, which is predicted based on operation data of an air conditioner  1100 , from a managing server. In  FIG. 11A , the failure prediction information  1105  is displayed in the form “equal to or less than 20% of refrigerant amount after 5 days”. The user terminal  1102  may display information  1110  and  1112  which inquires of a user whether a repair service is available before a predicted failure time point is reached, i.e., within “5 days”. Specifically, the user terminal  1102  may display a phrase  1110  which proposes a repair service and the recommended schedule  1112  for when the repair service is available. 
     If user input indicating that the user will not use the repair service within “5 days” is received, the user terminal  1102  may display normal operation maintenance information received from the managing server to delay the predicted failure, in a phrase  1115  which inquires of the user whether to use a normal operation maintenance mode. If user input indicating that the user will use the normal operation maintenance mode is received, the user terminal  1102  displays information of one or more normal operation maintenance modes  1120  obtained through the normal operation maintenance information. In  FIG. 11A , the information of the normal operation maintenance modes  1120  includes mode  1 : +3 days, mode  2 : +7 days, and mode  3 : +8 days. In this manner, each normal operation maintenance mode may include information about how long the predicted failure may be delayed. 
     If user input is received selecting one of the displayed normal operation maintenance modes  1120 , such as a normal operation maintenance mode  2  ( 1125 ), the user terminal  1102  transmits information about normal operation maintenance mode  2  to an air conditioner  1100 , enabling the air conditioner  1100  to operate in normal operation maintenance mode  2 . The normal operation maintenance mode  2  includes an operation pattern of the air conditioner  1100  which is determined such that a refrigerant amount of the air conditioner  1100  will be maintained at 20% or more after 5 days. 
       FIG. 11B  illustrates a virtual operation pattern  1130  of an air conditioner  1100  which is generated based on operation data. The virtual operation pattern  1130  includes 11:00 am-12:00 pm: strong wind &amp; set temperature 18 degrees, 2:00 pm-6:00 pm: strong wind &amp; set temperature 22 degrees, and 8:00 pm-8:30 pm: dehumidification &amp; set temperature 24 degrees. If the air conditioner  1100  continuously operates with the virtual operation pattern  1130 , it is predicted that a failure  1135 , i.e., refrigerant shortage, will likely occur in the air conditioner  1100  after 5 days. 
       FIG. 11C  illustrates an operation pattern  1140  according to a normal operation maintenance mode  2  selected by a user. The operation pattern  1140  includes 9:00 am-12:00 pm: weak wind &amp; set temperature 23 degrees, 3:00 pm-4:00 pm: weak wind &amp; set temperature 24 degrees, and 8:00 pm-8:30 pm: automatic. Occurrence of a failure  1135  may be delayed for about 12 days by applying the operation pattern  1140  to an air conditioner ( 1145 ), such that the air conditioner may normally operate without refrigerant shortage for about 12 days, to enable a user to more leisurely determine a schedule for a repair service. 
       FIGS. 12A, 12B, and 12C  illustrate a scenario of maintaining the normal operation state of a washer based on scheduling and control values of operation parameters of the washer according to an embodiment. 
     Referring to  FIG. 12A , a user terminal  1202  may receive failure prediction information  1205  indicating a failure which is predicted based on operation data of a washer  1200  from a managing server, and display the failure prediction information  1205  as “Motor of washer will fail after the washer is used 5 times”. The user terminal  1202  may display information  1210  which inquires of a user whether to use a normal operation maintenance mode in order to delay the predicted failure, by displaying information of one or more normal operation maintenance modes  1215  according to normal operation maintenance information received from a managing server in order to delay the predicted failure. In  1215 , mode  1 : +3 days, mode  2 : +7 days, and mode  3 : +8 days. In this manner, each normal operation maintenance mode may include information about how long the predicted failure may be delayed. 
     If user input is received selecting one of the displayed normal operation maintenance modes  1215 , such as a normal operation maintenance mode  2 , the user terminal  1202  displays information  1220  about an operation pattern of normal operation maintenance mode  2 , and displays a phrase  1225  which inquires whether to accept automatic control according to the normal operation maintenance mode  2 . If user input indicating acceptance of the automatic control according to the normal operation maintenance mode  2  is received, the user terminal  1202  transmits information about normal operation maintenance mode  2  to a washer  1200 , enabling the washer  1200  to operate in normal operation maintenance mode  2  ( 1230 ) in an automatic control. Normal operation maintenance mode  2  includes an operation pattern such as laundry 5 kg, dehydration level 3, and dry level 3, and the washer  1200  which operates in normal operation maintenance mode  2  limits the load, dehydration level, and dry level according to the operation pattern of laundry weighing 5 kg, dehydration level 3, and dry level 3. 
       FIG. 12B  illustrates a virtual operation pattern  1240  of a washer  1200  which is generated based on operation data. The virtual operation pattern  1240  includes Monday: load 8 kg, dehydration level 4 &amp; dry level 3, Wednesday: load 10 kg, dehydration level 5 &amp; dry level 5, and Friday: load 8 kg, dehydration level 4 &amp; dry level 4. If the washer  1200  continuously operates with the virtual operation pattern  1240 , it is predicted that a motor failure  1245  will likely occur in the washer  1200  after the washer  1200  is used 5 times. 
       FIG. 12C  illustrates an operation pattern  1250  according to a normal operation maintenance mode  2  selected by a user and including maximum load 5k g, maximum dehydration level 3, and a maximum dry level 3. A virtual operation pattern which is predicted when the operation pattern  1250  according to normal operation maintenance mode  2  is applied is limited to Monday: load 5 kg, dehydration level 3 &amp; dry level 2, Wednesday: load 5 kg, dehydration level 3 &amp; dry level 3, and Friday: load 5 kg, dehydration level 3 &amp; dry level 2. Occurrence of a failure  1245  may be delayed for about 3 weeks by applying the operation pattern  1250  to a washer  1200  ( 1255 ), such that the washer  1200  may normally operate without a motor failure for about 3 weeks, to enable a user to more leisurely determine a schedule for a repair service. 
       FIGS. 13A, 13B, and 13C  illustrate a scenario of maintaining the normal operation state of an air conditioner based on a control value of an operation parameter of the air conditioner according to an embodiment. 
     Referring to  FIG. 13A , a user terminal  1302  may receive failure prediction information  1305  indicating a failure, which is predicted based on operation data of an air conditioner  1300 , from a managing server, and display the failure prediction information  1305 . In  FIG. 13A , the failure prediction information  1305  is displayed in the form “A compressor will likely be damaged after 7 days”. The user terminal  1302  may display information  1310 , which inquires of a user whether to use a normal operation maintenance mode in order to delay the predicted failure, and which is about one or more normal operation maintenance modes  1315  according to normal operation maintenance information received from the managing server in order to delay the predicted failure. In  FIG. 13A , information of a plurality of normal operation maintenance modes  1315  is displayed as mode  1 : +3 days, mode  2 : +7 days, and mode  3 : +8 days. In this manner, each normal operation maintenance mode may include information about how long the predicted failure may be delayed. 
     If user input is received selecting one of the displayed normal operation maintenance modes  1315 , such as a normal operation maintenance mode  2 , the user terminal  1302  transmits information about the normal operation maintenance mode  2  to an air conditioner  1300 , enabling the air conditioner  1300  to operate in normal operation maintenance mode  2  ( 1320 ) including control values of a compressor frequency and/or electronic expansion valve (EEV) opening, among operation parameters for the air conditioner  1300 . 
     Referring to  FIG. 13B , an air conditioner  1300  includes a compressor  1332 , a condenser  1334 , an evaporator  1336 , and an EEV  1338 . The compressor  1332  compresses refrigerant in an air state by a compression motion to transfer a high temperature and high pressure refrigerant to the condenser  1334 , which converts a refrigerant gas outputted from the compressor  1332  into a low temperature and high pressure liquid refrigerant to transfer the liquid refrigerant to the EEV  1338 . Conversion of the low temperature and high pressure liquid refrigerant into a low temperature and low pressure liquid refrigerant is performed by the EEV  1338  in order to easily evaporate refrigerant in the evaporator  1336 . The liquid refrigerant enters a state that easily evaporates when it encounters a duct that suddenly widens at an exit through the EEV  1338 . The evaporator  1336  absorbs the hot air of the interior while transitioning liquid refrigerant into a gaseous state in order to transfer the hot air to an outdoor unit. At this time, the super heat degree of suction  1350  of the compressor  1332  is calculated by subtracting low pressure saturation temperature P(t) of the evaporator  1336  from suction pressure T(t)  1330 . 
     Referring to  FIG. 13C , if the super heat degree of suction  1350  is a negative value  1345 , refrigerant within a compressor may be leaked, and noise or damage to a compressor may occur. As such, a managing server may predict a failure such as leakage of refrigerant or damage to a compressor based on suction pressure of a compressor  1332  and low pressure saturation temperature P(t)  1340  (see  FIG. 13B ) of an evaporator  1336  from among operation data gathered from an air conditioner  1300 , by calculating the super heat degree of suction  1350  based on the suction pressure of the compressor  1332  and the low pressure saturation temperature P(t)  1340  of the evaporator  1336  and tracing the change in the calculated super heat degree of suction  1350 . 
     A normal operation maintenance mode, which may be applied to the predicted failure, may include control values of compressor frequency and/or an EEV opening. The managing server provides the air conditioner  1300  with normal operation maintenance information indicating at least one normal operation maintenance mode including control values of compressor frequency and/or an EEV opening through the user terminal  1302 , such that the air conditioner  1300  may operate according to these control values to delay the occurrence of a failure such as leakage of refrigerant or damage to a compressor. 
       FIGS. 14A, 14B, and 14C  illustrate a scenario of maintaining the normal operation state of a refrigerator based on a control value of an operation parameter of the refrigerator according to an embodiment. 
     Referring to  FIG. 14A , a user terminal  1402  may receive failure prediction information  1405  indicating a failure which is predicted based on operation data of a refrigerator  1400  from a managing server, and display the failure prediction information  1405 . In a shown example, the failure prediction information  1405  is displayed in the form “A refrigerator will likely be flooded after 8 days”. The user terminal  1402  may display information  1410  which inquires of a user whether to use a normal operation maintenance mode in order to delay the predicted failure, according to normal operation maintenance information received from the managing server in order to delay the predicted failure. In  FIG. 14A , the information of the plurality of normal operation maintenance modes  1415  is displayed as mode  1 : +3 days, mode  2 : +7 days, and mode  3 : +8 days. In this manner, each normal operation maintenance mode may include information about how long the predicted failure may be delayed. 
     If user input is received selecting one of the displayed normal operation maintenance modes  1415 , such as a normal operation maintenance mode  2 , the user terminal  1402  transmits information about normal operation maintenance mode  2  to the refrigerator  1400  to operate the refrigerator  1400  in normal operation maintenance mode  2  ( 1420 ), which includes a control value of a defrost cycle among operation parameters for the refrigerator  1400 . As such, the refrigerator  1400  operates in normal operation maintenance mode  2  according to the control value of the defrost cycle. 
     Referring to  FIG. 14B , a refrigerator  1400  includes a compressor  1434 , a condenser  1432 , and an evaporator  1430 , and further includes a defrost system  1436  that adheres to the evaporator  1430 , for periodically melting ice which accumulates in the evaporator  1430 . The defrost system  1436  includes a defrost heater, a defrost sensor, and a defrost timer, and is configured to melt ice stuck to the evaporator  1430  by controlling the defrost heater with the defrost sensor and the defrost timer. 
     Referring to  FIG. 14C , a defrost heater  1450  may be turned on whenever a defrost timer  1440 , which operates according to a defrost cycle, expires in order to melt ice of an evaporator  1430 , and may be turned off in response to a defrost sensor  1445 . If a failure occurs in the defrost timer  1440 , refrigeration performance is degraded and the defrost heater  1450  may not normally operate, causing water to accumulate in the refrigerator  1400 . If a failure occurs in the defrost sensor  1445 , a defrost system  1436  may not normally operate. A normal operation maintenance mode, which may be applied to a predicted failure of the defrost system  1436  such as the defrost timer  1440  or the defrost sensor  1445 , may include a control value of a defrost cycle for the defrost timer  1440 . A managing server may learn a defrost pattern based on information such as the inner temperature of a freezer/refrigerator room, a change in a temperature, and whether the door is open, gathered from a refrigerator  1400 , and sense abnormalness of a defrost cycle by monitoring the learned defrost pattern. If the abnormalness of the defrost cycle is sensed, the managing server predicts a failure of the defrost system  1436  and determines a control value for a defrost cycle or a defrost control command (e.g., ON/OFF) using a defrost pattern which has already been learned. Normal operation maintenance information indicating at least one normal operation maintenance mode including the determined control value for the defrost cycle or defrost control command is provided to the refrigerator  1400  through the user terminal  1402 , and the refrigerator  1400  may delay a failure which may occur in the refrigerator  1400  by operating according to the control value for the defrost cycle or the defrost control command. 
       FIG. 15A  illustrates a scenario of maintaining the normal operation state of an appliance through use of a peripheral device according to an embodiment. 
     Referring to  FIG. 15A , a user terminal  1502  may receive failure prediction information  1505  indicating a failure which is predicted based on the operation data of an appliance  1500  (e.g., an air conditioner) from a managing server, and display the failure prediction information  1505  as “A fan of an air conditioner will likely fail after 5 days”. 
     The user terminal  1502  may display information  1510  which inquires of a user whether to use a normal operation maintenance mode in order to delay the predicted failure. The user terminal  1502  displays information of one or more normal operation maintenance modes  1515  according to normal operation maintenance information received from a managing server in order to delay the predicted failure, as mode  1 : +3 days, mode  2 : 7 days, and mode  3 : +8 days. In this manner, each normal operation maintenance mode may include information about how long the predicted failure may be delayed. 
     If user input is received selecting one of the displayed normal operation maintenance modes  1515 , such as a normal operation maintenance mode  2  including information for automatic control of at least one specific peripheral device, the user terminal  1502  may display information  1525  of a peripheral device which may be used for replacing or supplementing the appliance  1500 . The user terminal  1502  displays a phrase  1520  which inquires whether to accept the automatic control for the peripheral device. In  FIG. 15A , the information  1525  of the peripheral device includes fan and air purifier information. The user terminal  1502  may receive user input which selects at least one peripheral device of which a user desires to accept automatic control based on the information  1525  of the peripheral device. 
     If user input which accepts automatic control for at least one peripheral device according to whether the information  1525  of the peripheral device is received, the user terminal  1502  transmits a control command  1530   a  for requesting an operation to a corresponding peripheral device  1525   a,  enabling the peripheral device  1525   a  to operate while replacing or supplementing the appliance  1500 . For example, if the appliance  1500  is an air conditioner, the peripheral device  1525   a  may be an air circulator or an air purifier. The user terminal  1502  may transmit a control command  1530  to the appliance  1500  for requesting the operation to stop. 
       FIG. 15B  illustrates an operating scenario when a failure of a fan is predicted ( 1505 ) in an air conditioner  1500  according to an embodiment. Referring to  FIG. 15B , at least one normal operation maintenance mode provided from a managing server to a user terminal may include information  1525  for automatic control for a peripheral device indicating automatic control for an air circulator and/or an air purifier. The air circulator and/or the air purifier may operate according to a control command from the user terminal to replace or supplement at least part of the functions of the air conditioner  1500 . 
       FIG. 15C  illustrates an operating scenario when a failure of a dry function is predicted ( 1545 ) in a washer  1540  according to an embodiment. Referring to  FIG. 15C , if a failure of a dry function is predicted ( 1545 ) in a washer  1540 , at least one normal operation maintenance mode provided from a managing server to a user terminal may include information  1550  for automatic control of a peripheral device. In  FIG. 15C , the information  1550  for the automatic control of the peripheral device indicates automatic control of an air conditioner and/or a dehumidifier. The air circulator and/or the dehumidifier may operate according to a control command from the user terminal to replace or supplement the dry function of the washer  1540 . 
       FIG. 16  illustrates a system of providing a repair service for repairing a predicted failure and a derivative failure of an appliance according to an embodiment. 
     Referring to  FIG. 16 , a managing server  1610  is configured to communicate with one or more appliances  1600 ,  1602 , and  1604 , to predict at least one failure which may occur in the appliances  1600 ,  1602 , and  1604 , and to manage a repair service in which an engineer may visit a home where a corresponding appliance is located in order to repair the predicted failure. The managing server  1610  may directly communicate with the appliances  1600 ,  1602 , and  1604 , or may communicate with the appliances  1600 ,  1602 , and  1604  through at least one user terminal  1620 . A description of a structure of the appliances  1600 ,  1602 , and  1604 , the managing server  1610 , and the user terminal  1620  may be with reference to  FIGS. 2, 3, and 4  which have been described above. The term “user terminal” may be interchangeable with other terms such as mobile station, terminal, user device, and device. 
     The managing server  1610  may have a failure prediction knowledge DB  1610   a  which stores information which may be used for predicting a failure of the appliances  1602 ,  1604 , and  1606 , predicts a failure which may occur in the appliances  1602 ,  1604 , and  1606  based on the failure prediction knowledge DB  1610   a,  determines a schedule for a repair service for repairing the failure through a communication with the user terminal  1620 , and transmits schedule information for the repair service and information about the predicted failure to an engineer&#39;s terminal  1630 . 
     If a primary failure is predicted at the appliance  1602 , the managing server  1610  may additionally predict a secondary failure which may be derived from the primary failure. For example, the managing server  1610  stores and manages a failure history and a failure repair history of the plurality of appliances  1602 ,  1604 , and  1606 . If the primary failure is predicted at the appliance  1602 , the managing server  1610  may additionally predict whether there is a secondary failure (i.e., derivative failure) which is predicted to additionally occur by the primary failure based on the failure history and the failure repair history of the plurality of appliances  1602 ,  1604 , and  1606 , which are the same or similar types. If the derivative failure is predicted, the managing server  1610  may fix both the predicted failure and the derivative failure in one repair service. 
     The user terminal  1620  may receive information about a plurality of predicted failures of an appliance from the managing server  1610 , and request to fix the plurality of predicted failures concurrently, i.e., through one repair service, to the managing server  1610  through user input. 
     Embodiments in which a user terminal communicates with a managing server to request a repair service for fixing a plurality of failures of an appliance concurrently will be described below, however, it will be noted that a similar description may be applied to when the appliance, not the user terminal, communicates with the managing server to request the repair service for fixing the plurality of failures concurrently. 
       FIG. 17  illustrates an operation of a user terminal for fixing a plurality of failures of an appliance concurrently according to an embodiment. Referring to  FIG. 17 , a user terminal transmits, to a managing server, a request signal for a repair service for a primary failure which is predicted for an appliance in step  1705 . For example, the user terminal may transmit, to the managing server, a request signal for a repair service which requests to use the repair service before a predicted failure time point of the primary failure as shown in step  715  in  FIG. 7 . 
     The user terminal receives, from the managing server, derivative failure information about a derivative failure which is predicted for the appliance in step  1710 . The derivative failure information indicates the derivative failure which is determined by the managing server that may be derived due to the primary failure in the appliance, and includes at least one of a failure item, a predicted failure time point, the degree of risk of the derivative failure similar to failure prediction information of the primary failure, and information about the primary failure which derives the derivative failure and at least one recommended treatment scheme related to the primary failure and the derivative failure. The recommended treatment scheme refers to information used for repairing or solving each failure. 
     The user terminal displays the derivative failure information in step  1715 , by displaying at least one of the failure prediction information for the primary failure and schedule information of the repair service. 
     Although  FIG. 17  illustrates an operation of a user terminal for concurrently fixing a plurality of failures of an appliance, various changes could be made to  FIG. 17 . For example, although shown as a series of operations, various operations in  FIG. 17  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIGS. 18A and 18B  illustrate information about a derivative failure of an appliance displayed on a user terminal according to an embodiment. Referring to  FIG. 18A , a user terminal  1820  may display information  1805  related to a repair service received from a managing server after requesting the repair service for a predicted failure (i.e., a primary failure) of an appliance  1800 , such as an air conditioner. The information  1805  related to the repair service may include failure prediction information for a primary failure, such as “add refrigerant of air conditioner”, and schedule information, such as 03:00 pm, next Tuesday. Additionally, the user terminal  1820  may receive and display derivative failure notification information  1810  which notifies that there is a derivative failure which may be derived due to the primary failure. After displaying the derivative failure notification information  1810 , the user terminal  1820  may display derivative failure information  1825  provided from the managing server as shown in  FIG. 18B . 
     Referring to  FIG. 18B , a user terminal  1820  may display derivative failure information  1825  provided from a managing server, such as a refrigerant shortage. In  FIG. 18B , the derivative failure is compressor failure, and the derivative failure information  1825  includes a plurality of recommended treatment schemes for fixing refrigerant shortage and compressor failure. The first recommended treatment scheme includes only add refrigerant, the predicted-required time is 30 minutes, and the predicted cost is 50 dollars. The second recommended treatment scheme includes add refrigerant  1832  and replace compressor part  1834 , the predicted-required time is 45 minutes, and the predicted cost is 87 dollars. The third recommended treatment scheme includes add refrigerant and replace compressor after one month, the predicted-required time is 2 hours, and the predicted cost is 190 dollars. 
     The user terminal  1820  may display information  1830  which inquires of a user a treatment scheme which a user desires along with the derivative failure information  1825 , and which includes a diagnosis of only predicted primary failure and diagnosis of primary failure &amp; derivative failure. Alternatively, the information  1830  which inquires of the user the treatment scheme which the user desires may include the first, the second, and the third recommended treatment schemes provided by the derivative failure information  1825 . Alternatively, the user terminal  1820  may receive, from the user, information about a schedule of a repair service in which the primary failure and the derivative failure may be concurrently fixed. 
     If user input indicating a treatment scheme and/or schedule of a repair service which the user wants is received, the user terminal  1820  may transmit, to the managing server, information about the treatment scheme and/or schedule indicated by the user input. 
       FIG. 19  illustrates an operation of a managing server for fixing a primary failure and a derivative failure of an appliance according to an embodiment. Referring to  FIG. 19 , a managing server receives, from a user terminal, a request signal for a repair service for a predicted primary failure of an appliance in step  1905 , which requests to use the repair service before a predicted failure time point of the primary failure as shown in step  620  in  FIG. 6 . 
     The managing server determines whether there is a derivative failure which may be derived from the primary failure, and generates derivative failure information indicating the derivative failure if there is a derivative failure in step  1910 . For example, the managing server may search for the derivative failure related to the primary failure from a failure prediction knowledge DB which stores such information as operation data, failure history, the control method for failure delay, failure repair history, manufacture information, environment information, and a customer profile, for a plurality of appliances. 
     The managing server transmits the derivative failure information to the user terminal in step  1915 , including at least one of a failure time, a predicted failure time point, the degree of risk of the derivative failure similar to the failure prediction information of the primary failure, information about the primary failure which derives the derivative failure, and information about at least one recommended treatment scheme related to the primary failure and the derivative failure. The user terminal may select whether to fix the primary failure and the derivative failure concurrently through one repair service by receiving the derivative failure information. 
     Although  FIG. 19  illustrates an operation of a managing server for fixing a primary failure and a derivative failure of an appliance according to an embodiment, various changes could be made to  FIG. 19 . For example, although shown as a series of operations, various operations in  FIG. 19  could overlap, occur in parallel, occur in a different order, or occur multiple times. 
       FIG. 20  illustrates an operation of a managing server for generating derivative failure information according to an embodiment. Referring to  FIG. 20 , a managing server predicts a virtual operation pattern of an appliance by considering an operation history of the appliance in step  2005 . For example, the virtual operation pattern may include an operation per time and a control value(s) of an operation parameter(s) for a corresponding operation, and may be generated by considering a user schedule, a schedule set for the appliance, and a past operation history of the appliance. 
     The managing server generates primary failure prediction information indicating a primary failure according to the generated virtual operation pattern in step  2010 . The managing server predicts the primary failure which may occur if the appliance operates according to the generated virtual operation pattern, and generates the primary failure prediction information including an occurrence time point and the degree of risk of the predicted primary failure. 
     The managing server compares the generated virtual operation pattern with a current operation pattern of the appliance in step  2015 . The current operation pattern may include an operation per time according to the actual operation of the appliance and a control value(s) of an operation parameter(s) for a corresponding operation. The managing server determines whether the degree of similarity between the generated virtual operation pattern and the current operation pattern is greater than a threshold value in step  2020 . If the degree of similarity is not greater than the threshold value, the managing server determines that the generated virtual operation pattern is not similar to the current operation pattern, and returns to step  2005 . If the degree of similarity is greater than the threshold value, the managing server determines that the generated virtual operation pattern is similar to the current operation pattern, and proceeds to step  2025 , in which the managing server searches for a derivative failure related to the primary failure prediction information. 
     Specifically, the managing server may search for the derivative failure in a failure prediction knowledge DB which stores operation data, failure history, the control method for failure delay, failure repair history, manufacture information, environment information, and a customer profile for a plurality of appliances in step  2025 . For example, the managing server may search for the derivative failure related to the primary failure prediction information based on the failure history and the failure repair history for a plurality of appliances which are the same type as or similar to the appliance related to the primary failure prediction information. The managing server may search for whether there is a secondary failure which occurs within a predetermined threshold duration from a time point at which the primary failure occurs indicated by the primary failure prediction information in the plurality of appliances which are the same or similar types. If the number of times the secondary failure occurs during the threshold duration after occurrence of the primary failure is greater than a predetermined threshold value in the plurality of appliances, the secondary failure is determined as a derivative failure for the primary failure. 
     The managing server determines whether there is a derivative failure related to the primary failure indicated by the primary failure prediction information in step  2030 . If there is no derivative failure, the managing server terminates the operation. If there is a derivative failure, the managing server may generate derivative failure information including a failure item, a predicted failure time point, and the degree of risk for the derivative failure in step  2035 . The derivative failure information may be transmitted from the managing server to a corresponding appliance or a user terminal. 
     Although  FIG. 20  illustrates an operation of a managing server for generating derivative failure information according to an embodiment, various changes could be made to  FIG. 20 . For example, although shown as a series of operations, various operations in  FIG. 20  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 21  illustrates an operation of a managing server for searching for a derivative failure of an appliance according to an embodiment. Referring to  FIG. 21 , a managing server  2110  predicts a primary failure of an appliance  2102  and searches for a derivative failure from a failure prediction knowledge DB  2120  which stores failure prediction knowledge information  2122  for the appliance  2102 . The failure prediction knowledge information  2122  includes at least one of operation data, operation history, the control method for failure delay, failure repair history, manufacture information, environment information, and customer profile information related to the appliance  2102 . In  FIG. 21 , the failure prediction knowledge information  2122  for the appliance  2102  includes manufacturing date: May, 2014, manufacturing factory: factory in Gwangju, Korea, operation type: scroll type, installation type: room air conditioner, failure history (i.e., diagnosis): refrigerant leakage, failure repair history: add refrigerant. 
     The failure prediction knowledge DB  2120  includes failure prediction knowledge information  2124  for a plurality of appliances which are the same type as or a similar type to the appliance  2102 . The failure prediction knowledge information  2124  includes manufacturing date: June, 2013, manufacturing factory: factory in Suzhou, China, operation type: rotary type, installation type: room air conditioner, failure history 1 (i.e., diagnosis): refrigerant leakage, failure history 2 (i.e., diagnosis): compressor damage, failure repair history: add refrigerant and repair compressor. 
     The managing server  2110  predicts refrigerant leakage as the primary failure of the appliance  2102 , and searches for another failure related to the refrigerant leakage from the failure prediction knowledge information  2124  for the plurality of appliances. If compressor damage as the secondary failure related to the refrigerant leakage is searched, the managing server  2110  determines that there is compressor damage as the secondary failure related to the refrigerant leakage of the appliance  2102 . For example, if difference between a time point at which refrigerant leakage occurs in the plurality of appliances and a time point at which compressor damage occurs is within a predetermined threshold duration, and/or the number of times compressor damage occurs after refrigerant leakage occurs is greater than a predetermined threshold count, the managing server  2110  may determine the compressor damage as a derivative failure. 
     As described in embodiments, an additional future failure which may be derived in an appliance of which a failure is predicted and the failure are repaired concurrently through one repair service, thereby minimizing a user inconvenience due to an unnecessary additional repair service and maintaining a normal operation state of the appliance. 
       FIG. 22  illustrates a system for providing a repair service for repairing a predicted failure of an appliance and a failure of another appliance according to an embodiment. Referring to  FIG. 22 , a managing server  2210  is configured to communicate with one or more appliances  2200 ,  2202 , and  2204  within the same home  2200  (or the same office), predict at least one failure which may occur in the appliances  2200 ,  2202 , and  2204 , and manage a repair service in which an engineer may visit a home where a corresponding appliance is located in order to repair the predicted failure. The managing server  2210  may directly communicate with the appliances  2200 ,  2202 , and  2204 , or may communicate with the appliances  2200 ,  2202 , and  2204  through at least one user terminal  2220 . A description of a structure of the appliances  2200 ,  2202 , and  2204 , the managing server  2210 , and the user terminal  2220  may be with reference to  FIGS. 2, 3, and 4  which have been described above. 
     The managing server  2210  may have a failure prediction knowledge DB  2210   a  which stores information which may be used for predicting a failure of appliances  2202 ,  2204 , and  2206 , and predicts a failure which may occur in the appliances  2202 ,  2204 , and  2206  based on the failure prediction knowledge DB  2210   a,  determines a schedule of a repair service for repairing the failure through a communication with the user terminal  2220 , and transmits schedule information for the repair service and information about the predicted failure to an engineer&#39;s terminal  2230 . 
     If the first failure is predicted in the first appliance  2202  in the home  2200 , the managing server  2210  may additionally predict the second failure which may occur in the second appliance  2204  within the same home  2200 . For example, a failure prediction knowledge DB  2210   a  of the managing server  2210  stores and manages operation data, failure history, the control method for failure delay, failure repair history, manufacture information, environment information, and customer profile information of the plurality of appliances  2202 ,  2204 , and  2206 , and the environment information or the customer profile information may include an address of a home or an office where the plurality of appliances  2202 ,  2204 , and  2206  are installed. If the first failure is predicted in the first appliance  2202 , the managing server  2210  may additionally predict whether there is the second failure which may occur in the appliances  2204  and  2206  based on a failure history and a failure repair history of the appliances  2204  and  2206  which are located on the same premises and which are the same or similar type. The same premises space may denote, for example, a space which is identified with the same address such as a home or an office. If the second failure is predicted, the managing server  2210  may fix the first failure of the first appliance  2202  and the second failure of the second appliance  2205  or  2206  concurrently through one repair service. 
     The user terminal  2220  may receive information about a plurality of predicted failures of the first and the second appliances from the managing server  2210 , and request to fix the plurality of predicted failures concurrently through one repair service to the managing server  2210  through user input. 
     Embodiments in which a user terminal communicates with a managing server to request a repair service for fixing a plurality of failures of appliances concurrently will be described below. However, it will be noted that a similar description may be applied to when an arbitrary appliance, not the user terminal, communicates with the managing server to request the repair service for fixing the plurality of failures. 
       FIG. 23  illustrates an operation of a user terminal for fixing a plurality of predicted failures of a plurality of appliances concurrently according to an embodiment. Referring to  FIG. 23 , a user terminal transmits, to a managing server, a request signal for a repair service for the first failure which is predicted for the first appliance in step  2305 . For example, the user terminal may transmit, to the managing server, the request signal for the repair service for requesting to use the repair service before a predicted failure time point of the first failure as described in step  715  in  FIG. 7 . 
     The user terminal receives, from the managing server, failure prediction information for the second failure which is predicted for the second appliance and recommended schedule information indicating a recommended schedule of a repair service for fixing the first and the second appliances concurrently in step  2310 . The failure prediction information may include at least one of a failure item, a predicted failure time point, and the degree of risk of the second failure. The recommended schedule information indicates a schedule of a repair service which may fix the first failure of the first appliance and the second failure of the second appliance concurrently. 
     The user terminal displays derivative failure information and recommended schedule information for the second failure and determines a new schedule of the repair service for fixing the first and the second failures concurrently in step  2315 . The user terminal transmits information about the determined new schedule to the managing server in step  2320 . 
     Although  FIG. 23  illustrates an operation of a user terminal for fixing a plurality of predicted failures of a plurality of appliances concurrently according to an embodiment, various changes could be made to  FIG. 23 . For example, although shown as a series of operations, various operations in  FIG. 23  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIGS. 24A and 24B  illustrate information about a plurality of failures of a plurality of appliances displayed on a user terminal according to an embodiment. Referring to  FIG. 24A , a user terminal  2420  may display information  2405  related to a repair service for a predicted failure (i.e., the first failure) of the first appliance  2400 , such as an air conditioner received from a managing server after requesting the repair service. The information  2405  related to the repair service may include failure prediction information for the first failure, such as add refrigerant of an air conditioner, and schedule information, such as 03:00 pm on next Tuesday. The user terminal  2420  may receive, from the managing server, information  2410  related to the second failure predicted for a refrigerator as the second appliance  2415  within the same home, and display the information  2410 . The information  2410  related to the second failure may include failure prediction information for the second failure, such as light of refrigerator is abnormal, and recommended schedule information, such as 03:00-06:00 pm on next Thursday. 
     The user terminal  2420  may determine a schedule of a repair service for fixing the first and the second failures concurrently through user input by considering the recommended schedule information within the information  2410  related to the second failure. Failure prediction information for the second failure is generated by the managing server by monitoring operation data gathered for the refrigerator  2415 , such as a power pattern  2415   a.  For example, the managing server may predict a failure for at least one another appliance which is located within the same home as the first appliance  2400  and determine the second failure of the second appliance which may be fixed along with the first failure of the first appliance  2400 . 
     The information  2410  related to the second failure may be transmitted from the managing server to an engineer  2430  in charge of a repair service. The engineer  2430  may fix the first failure of the first appliance and the second failure of the second appliance through one repair service using failure prediction information for the first failure which has already been provided and the information  2410  related to the second failure. Further, the engineer  2430  may send a message  2431  after fix the first failure of the first appliance and the second failure of the second appliance. 
     Referring to  FIG. 24B , a user terminal  2460  may display information  2455  related to a repair service for a predicted failure of an appliance  2450 , such as a washer received from a managing server after requesting the repair service. The information  2455  related to the repair service may include self-diagnosis contents for the predicted failure, for example, that abnormal vibration occurs and a predicted reason is unbalanced floor, and a message requesting to check whether to perform self-diagnosis for the self-diagnosis contents. The user terminal  2460  may input a predicted reason by considering the information  2455  related to the predicted failure. 
     Further, the information  2455  related to the predicted failure and the predicted reason may be transmitted to an engineer  2475  in charge of a repair service. The engineer  2475  may transmit a message  2480  indicating a solution for the failure of the appliance using the information  2455  related to the predicted failure and the predicted reason. 
       FIG. 25  illustrates an operation of a managing server for fixing failures of a plurality of appliances according to an embodiment. Referring to  FIG. 25 , a managing server receives, from a user terminal, a request signal for a repair service for a predicted first failure of the first appliance in step  2505 , which requests to use the repair service before a predicted failure time point of the first failure as shown in step  620  in  FIG. 6 . 
     The managing server predicts the second failure of the second appliance based on a failure history and a failure repair history of appliances which are located on the same premises as the first appliance by using an address of a home or an office where the first appliance is installed, and generates failure prediction information for the second failure in step  2510 . In examples, the managing server may generate the failure prediction information for the second failure if the difference between the predicted failure time point of the first failure and a predicted failure time point of the second failure is less than a predetermined threshold value. The managing server may generate the failure prediction information for the second failure if the second failure of the second appliance is predicted and the difference between a time point at which the warranty duration of the second appliance expires and a schedule of a repair service for repairing the first failure is less than a predetermined threshold value. 
     The managing server transmits, to a user terminal, the failure prediction information for the second failure and recommended schedule information indicating a recommended schedule of a repair service for fixing the first failure and the second failure concurrently in step  2515 . The failure prediction information may include at least one of a failure item, a predicted failure time point, and the degree of risk of the second failure. The recommended schedule information indicates a schedule of a repair service which may fix the first failure of the first appliance and the second failure of the second appliance concurrently. 
     The managing server may receive, from the user terminal, information about a new schedule of the repair service for fixing the first failure and the second failure concurrently in step  2520 , and may transmit, to an engineer in charge of the repair server, the information about the new schedule of the repair service and failure prediction information for the first failure and the second failure. The managing server may provide the engineer with information about a method which may be used for fixing (i.e., repairing) the first failure and the second failure. 
     Although  FIG. 25  illustrates an operation of a managing server for fixing failures of a plurality of appliances according to an embodiment, various changes could be made to  FIG. 25 . For example, although shown as a series of operations, various operations in  FIG. 25  could overlap, or occur in parallel, in a different order, or multiple times. 
       FIG. 26  illustrates an operation of a managing server for generating failure prediction information of the second failure according to an embodiment. Referring to  FIG. 26 , a managing server searches for a failure prediction knowledge DB of appliances which are located on the same premises by considering environment information or customer profile information of the first appliance for which a repair service is requested to predict failure of the appliances in step  2605 . The managing server determines whether there is a second appliance which has a predicted second failure which may be fixed through the repair service in step  2610 , by considering a predicted failure time point of the first failure, a predicted failure time point of the second failure, a warranty of the second appliance, and a schedule of the repair service. 
     The managing server generates failure prediction information indicating the second failure of the second appliance in step  2615 . The managing server may generate recommended schedule information of a repair service for fixing the first failure and the second failure concurrently, such as by considering an engineer&#39;s schedule. The failure prediction information and the recommended schedule information of the second failure may be transmitted from the managing server to a corresponding appliance or user terminal. 
     Although  FIG. 26  illustrates an operation of a managing server for generating failure prediction information of the second failure according to an embodiment, various changes could be made to  FIG. 26 . For example, although shown as a series of operations, various operations in  FIG. 26  could overlap, or occur in parallel, in a different order, or multiple times. 
     According to embodiments, a method for controlling an appliance based on failure prediction includes receiving, from a managing server, failure prediction information indicating a predicted failure of the appliance, determining a service available schedule indicating a time point at which a repair service for repairing the predicted failure is available based on the failure prediction information according to user input, transmitting, to the managing server, a request signal for normal operation maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the determined service available schedule is after a predicted failure time point indicated by the failure prediction information, receiving, from the managing server, the normal operation maintenance information, and controlling the appliance to operate according to the normal operation maintenance information. 
     The method further includes inputting, from a user, a user preference criterion including at least one of performance and a duration for which a failure is capable of being delayed, which are provided in a normal operation maintenance mode indicated by the normal operation maintenance information, before transmitting, to the managing server, the request signal for the normal operation maintenance information, wherein the request signal for the normal operation maintenance information includes information related to the user preference criterion. 
     The normal operation maintenance information includes an operation pattern indicating an operation per time and a control value of an operation parameter for each operation of the appliance, information of at least one replacement part or replacement device to be used for replacing or supplementing the appliance for delaying the predicted failure of the appliance, and/or normal operation time information indicating a predicted time duration for which the normal operation of the appliance is possible if the operation pattern or the at least one replacement part or replacement device is used. 
     The method further includes transmitting, to the managing server, a request signal for the repair service if the determined service available schedule is before the predicted failure time point indicated by the failure prediction information, receiving, from the managing server, derivative failure information indicating a derivative failure which is predicted to additionally occur in the appliance in connection with the predicted failure, and displaying the derivative failure information. 
     The derivative failure is predicted by the managing server based on operation data gathered from a plurality of appliances which are the same type as or a similar type to the type of the appliance and a failure history of the plurality of appliances. 
     The derivative failure information is generated by the managing server based on the predicted failure time point of the predicted failure, a predicted failure time point of the derivative failure, and/or a number of times the derivative failure occurs in a plurality of appliances which are the same type as or a similar type to a type of the appliance. 
     The method further includes transmitting, to the managing server, a request signal for the repair service if the determined service available schedule is before the predicted failure time point indicated by the prediction information, receiving, from the managing server, first failure prediction information indicating a second failure which is predicted to occur in a second appliance which is located on the same premises as the appliance and recommended schedule information indicating a recommended schedule of a repair service for repairing the predicted failure and the second failure concurrently, and displaying the first failure prediction information and the recommended schedule information. 
     According to embodiments, a method for controlling an appliance based on failure prediction by a user terminal includes receiving, from a managing server, failure prediction information indicating a predicted failure of the appliance, determining a service available schedule indicating a time point at which a repair service for repairing the predicted failure is available based on the failure prediction information according to user input, transmitting, to the managing server, a request signal for normal operation maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the determined service available schedule is after a predicted failure time point indicated by the failure prediction information, receiving, from the managing server, the normal operation maintenance information, and transmitting, to the appliance, the normal operation maintenance information. 
     The normal operation maintenance information includes an operation pattern indicating an operation per time and a control value of an operation parameter for each operation of the appliance, information of at least one replacement part or replacement device to be used for replacing or supplementing the appliance for delaying the predicted failure of the appliance, and/or normal operation time information indicating a predicted time duration for which the normal operation of the appliance is possible if the operation pattern or the at least one replacement part or replacement device is used. 
     The method further includes transmitting, to the managing server, a request signal for the repair service if the determined service available schedule is before the predicted failure time point indicated by the failure prediction information, receiving, from the managing server, derivative failure information indicating a derivative failure which is predicted to additionally occur in the appliance in connection with the predicted failure, and displaying the derivative failure information. 
     The derivative failure is predicted by the managing server based on operation data gathered from a plurality of appliances which are the same type as or a similar type to the type of the appliance and a failure history of the plurality of appliances. 
     The derivative failure information is generated by the managing server based on the predicted failure time point of the predicted failure, a predicted failure time point of the derivative failure, and/or a number of times the derivative failure occurs in a plurality of appliances which are the same type as or a similar type to the type of the appliance. 
     The method further includes transmitting, to the managing server, a request signal for the repair service if the determined service available schedule is before the predicted failure time point indicated by the prediction information, receiving, from the managing server, first failure prediction information indicating a second failure which is predicted to occur in a second appliance which is located on the same premises as the appliance and recommended schedule information indicating a recommended schedule of a repair service for repairing the predicted failure and the second failure concurrently, and displaying the first failure prediction information and the recommended schedule information. 
     According to embodiments, an apparatus of an appliance controlled based on failure prediction includes a native function executing unit, a communication unit configured to receive, from a managing server, failure prediction information indicating a predicted failure of the appliance, to transmit, to the managing server, a request signal for normal operation maintenance information, and to receive, from the managing server, the normal operation maintenance information, and a controller configured to determine a service available schedule indicating a time point at which a repair service for repairing the predicted failure is available based on the failure prediction information according to user input, to generate the request signal for the normal operation maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the determined service available schedule is after a predicted failure time point indicated by the failure prediction information, and to control the native function executing unit to operate according to the normal operation maintenance information. 
     The request signal for the normal operation maintenance information further includes information about a user preference criterion indicating at least one of performance and a duration for which a failure is capable of being delayed, which are provided in a normal operation maintenance mode indicated by the normal operation maintenance information. 
     The normal operation maintenance information includes an operation pattern indicating an operation per time and a control value of an operation parameter for each operation of the appliance, information of at least one replacement part or replacement device to be used for replacing or supplementing the appliance for delaying the predicted failure of the appliance, and/or normal operation time information indicating a predicted time duration for which the normal operation of the appliance is possible if the operation pattern or the at least one replacement part or replacement device is used. 
     The controller is configured to transmit, to the managing server, a request signal for the repair service through the communication unit if the determined service available schedule is before the predicted failure time point indicated by the failure prediction information, to receive, from the managing server, derivative failure information indicating a derivative failure which is predicted to additionally occur in the appliance in connection with the predicted failure through the communication unit, and to display the derivative failure information. 
     The derivative failure is predicted by the managing server based on operation data gathered from a plurality of appliances which are the same type as or a similar type to the type of the appliance and a failure history of the plurality of appliances. 
     The derivative failure information is generated by the managing server based on the predicted failure time point of the predicted failure, a predicted failure time point of the derivative failure, and/or a number of times the derivative failure occurs in a plurality of appliances which are the same type as or a similar type to the type of the appliance. 
     The controller is configured to transmit, to the managing server, a request signal for the repair service through the communication unit if the determined service available schedule is before the predicted failure time point indicated by the prediction information, to receive, from the managing server, first failure prediction information indicating a second failure which is predicted to occur in a second appliance which is located on the same premises as the appliance and recommended schedule information indicating a recommended schedule of a repair service for repairing the predicted failure and the second failure concurrently through the communication unit, and to display the first failure prediction information and the recommended schedule information. 
     According to embodiments, an apparatus of a user terminal for controlling an appliance based on failure prediction includes a communication unit configured to receive, from a managing server, failure prediction information indicating a predicted failure of the appliance, to transmit, to the managing server, a request signal for normal operation maintenance information, to receive, from the managing server, the normal operation maintenance information, and to transmit, to the appliance, the normal operation maintenance information, and a controller configured to determine a service available schedule indicating a time point at which a repair service for repairing the predicted failure is available based on the failure prediction information according to user input, and to generate the request signal for the normal operation maintenance information used to delay the predicted failure and maintain the normal operation of the appliance if the determined service available schedule is after a predicted failure time point indicated by the failure prediction information. 
     The normal operation maintenance information includes an operation pattern indicating an operation per time and a control value of an operation parameter for each operation of the appliance, information of at least one replacement part or replacement device to be used for replacing or supplementing the appliance for delaying the predicted failure of the appliance, and/or normal operation time information indicating a predicted time duration for which the normal operation of the appliance is possible if the operation pattern or the at least one replacement part or replacement device is used. 
     The controller is configured to transmit, to the managing server, a request signal for the repair service through the communication unit if the determined service available schedule is before the predicted failure time point indicated by the failure prediction information, to receive, from the managing server, derivative failure information indicating a derivative failure which is predicted to additionally occur in the appliance in connection with the predicted failure through the communication unit, and to display the derivative failure information. 
     The derivative failure is predicted by the managing server based on operation data gathered from a plurality of appliances which are the same type as or a similar type to the type of the appliance and a failure history of the plurality of appliances. 
     The derivative failure information is generated by the managing server based on the predicted failure time point of the predicted failure, a predicted failure time point of the derivative failure, and/or a number of times the derivative failure occurs in a plurality of appliances which are the same type as or a similar type to the type of the appliance. 
     The controller is configured to transmit, to the managing server, a request signal for the repair service through the communication unit if the determined service available schedule is before the predicted failure time point indicated by the prediction information, to receive, from the managing server, first failure prediction information indicating a second failure which is predicted to occur in a second appliance which is located on the same premises as the appliance and recommended schedule information indicating a recommended schedule of a repair service for repairing the predicted failure and the second failure concurrently through the communication unit, and to display the first failure prediction information and the recommended schedule information. 
     As described above, a plurality of predicted failures of a plurality of appliances which are located on the same premises, such as a home or an office, are repaired concurrently through one repair service, which reduces a user&#39;s inconvenience due to an unnecessary additional repair service and maintains a normal operation state of the appliance. 
     Embodiments may be implemented as computer readable code in a computer readable recording medium in a specific perspective. The computer readable recording medium is a data storage device that may store data readable by a computer system, such as read only memories (ROMs), random access memories (RAMs), CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, and data transmission over the Internet. The computer readable recording medium may be distributed by computer systems over a network, and accordingly, the computer readable codes may be stored and executed in a distributed manner. Functional programs, codes, and code segments to attain embodiments may be readily interpreted by skilled programmers in the art to which the disclosure pertains. 
     The apparatuses and methods according to embodiments may be implemented in hardware, software, or a combination of hardware and software. Such software may be stored in a volatile or non-volatile storage device such as a ROM or other storage devices, a memory, such as RAM, a memory chip, a device or an integrated circuit, or a storage medium, such as a compact disc (CD), digital video disc (DVD), magnetic disk, or magnetic tape, which enables optical or magnetic recording while simultaneously read out by a machine (e.g., a computer). The methods according to embodiments may be implemented by a computer or a portable terminal including a controller and a memory, and the memory may be a machine-readable storage medium that may properly retain program(s) containing instructions for implementing the embodiments. 
     Accordingly, the disclosure encompasses a program containing codes for implementing the device or method set forth in the claims of this disclosure and a machine (e.g., computer)-readable storage medium storing the program. The program may be electronically transferred via any media such as communication signals transmitted through a wired or wireless connection and the disclosure includes the equivalents thereof. 
     The apparatuses according to embodiments may receive the program from a program providing device wiredly or wirelessly connected thereto and store the program. The program providing apparatus may include a memory for storing a program including instructions enabling a program processing apparatus to perform a method according to an embodiment and data necessary for a method according to an embodiment, a communication unit for performing wired or wireless communication with a graphic processing apparatus, and a controller transmitting the program to the graphic processing apparatus automatically or as requested by the graphic processing apparatus. 
     A method according to embodiments may be provided in a computer program product, which may include software (S/W) programs or computer-readable storage media storing the S/W programs or products traded between the seller and the buyer. For example, the computer program products may include S/W program-type products (e.g., downloadable applications (apps)) that are electronically distributed through the device  10  or the manufacturer of the device  10  or electronic market. For electronic distribution, at least part of the S/W programs may be stored in storage media or temporarily generated. In this case, the storage media may be storage media of the manufacturer&#39;s or electronic market&#39;s server or the relay server. 
     While the present disclosure has been shown and described with reference to embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents.