WO2017185379A1 - 返修概率预测方法、装置、服务器、终端及存储介质 - Google Patents

返修概率预测方法、装置、服务器、终端及存储介质 Download PDF

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Publication number
WO2017185379A1
WO2017185379A1 PCT/CN2016/080841 CN2016080841W WO2017185379A1 WO 2017185379 A1 WO2017185379 A1 WO 2017185379A1 CN 2016080841 W CN2016080841 W CN 2016080841W WO 2017185379 A1 WO2017185379 A1 WO 2017185379A1
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Prior art keywords
terminal
fault
probability
type
failure
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PCT/CN2016/080841
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English (en)
French (fr)
Inventor
张亮
沈晨凯
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华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN201680007981.XA priority Critical patent/CN107548543B/zh
Priority to PCT/CN2016/080841 priority patent/WO2017185379A1/zh
Publication of WO2017185379A1 publication Critical patent/WO2017185379A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
    • H04L69/40—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass for recovering from a failure of a protocol instance or entity, e.g. service redundancy protocols, protocol state redundancy or protocol service redirection

Definitions

  • the present invention relates to the field of communications technologies, and in particular, to a method, an apparatus, a server, a terminal, and a storage medium for predicting a repair probability.
  • FFR Field Failure Rate
  • the current value of FFR can be calculated after the user actually returns the machine. The time is very lagging.
  • the cost is already generated, and the cost of reducing the FFR is high. There is no plan for predicting the FFR.
  • the embodiment of the invention provides a method, a device, a server, a terminal and a storage medium for predicting the repair probability, so as to solve the problem that the time lag of the repair probability of the terminal is obtained.
  • a method for predicting a repair probability comprising:
  • repair probability of each terminal is a sum of a probability of a fallback corresponding to a failure rate of each fault type of each terminal;
  • a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the failure rate of each failure type of each terminal in the terminal set is obtained, and the probability of the failure corresponding to the failure rate of each failure type of each terminal is determined by the server statistics, thereby obtaining the termination probability of each terminal.
  • the repair probability and the number of repairs of the terminal set finally obtain the repair probability of the terminal set, and the return probability of the terminal set can be calculated without waiting for the user to actually return the machine, and can advance in advance. Line terminal improvements, the cost of reducing the probability of repair is greatly reduced.
  • the acquiring the failure rate of each fault type of each terminal in the terminal set includes:
  • the fault parameter includes at least one fault type and a fault number of each fault type and a terminal usage duration
  • the failure rate of each fault type of each terminal can be conveniently obtained as the basis for calculating the repair probability of the terminal set without waiting for the user.
  • the return probability of the terminal set can be calculated after the actual machine is returned.
  • the determining a probability of a failure corresponding to the failure rate of each fault type of each terminal includes:
  • Determining the failure rate corresponding to the failure rate of each failure type of each terminal by querying the corresponding relationship between the failure rate of each failure type and the probability of the failure according to the failure rate of each failure type of each terminal Probability.
  • the correspondence between the failure rate and the probability of back-off for each type of failure is obtained by server statistics. According to the failure rate of each type of failure of each terminal, the corresponding probability of exit can be obtained and the probability of withdrawal is calculated. Simple and fast.
  • the fault type includes: a system average failure rate, and an application average failure rate.
  • the repair probability of each terminal is taken as 1
  • the repair probability of each terminal is less than or equal to 1.
  • a fault parameter uploading method which is applied to a terminal having a communication function, and the method includes:
  • the fault parameter including at least one fault type and the The number of failures of the barrier type and the duration of use of the terminal, so that the server predicts the probability of repair of the set of terminals according to the fault parameter.
  • the server can conveniently obtain the failure rate of each fault type of each terminal, which is used as the basis for calculating the repair probability of the terminal set, and can calculate the terminal set without waiting for the user to actually return the machine.
  • the probability of repairing can improve the terminal in advance, and the cost of reducing the probability of repair is greatly reduced.
  • a repair probability prediction apparatus comprising:
  • a first acquiring unit configured to acquire a failure rate of each fault type of each terminal in the terminal set
  • a determining unit configured to determine a probability of a back-off corresponding to a failure rate of each of the fault types of each terminal
  • the first obtaining unit is further configured to acquire a repair probability of each terminal, where a repair probability of each terminal is a sum of a probability of a fallback corresponding to a failure rate of each fault type of each terminal ;
  • the first obtaining unit is further configured to acquire the number of repairs of the set of terminals, where the number of repairs of the set of terminals is a sum of repair probabilities of each terminal in the set of terminals;
  • the first obtaining unit is further configured to acquire a repair probability of the terminal set, where a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the principle and the beneficial effects of the device can be referred to the first aspect and the possible implementation manners of the first aspect and the beneficial effects. Therefore, the implementation of the device can be referred to the implementation of the method. The repetitions are not repeated here.
  • a fault parameter uploading apparatus comprising:
  • a recording unit configured to record at least one type of failure occurring and a number of failures of the type of failure occurring when the terminal fails;
  • a uploading unit configured to upload a fault parameter to the server, where the fault parameter includes at least one fault type and a fault number of the fault type and a terminal usage duration, so that the server predicts the repair of the terminal set according to the fault parameter. Probability.
  • a server comprising: a processor, a memory;
  • the memory is configured to store instructions and data, the data including a correspondence between a failure rate and a probability of a fallback of each type of failure;
  • the processor is configured to execute the instructions to:
  • a repair probability of each terminal is a sum of a probability of a fallback corresponding to a failure rate of each fault type of each terminal;
  • a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the processor invokes instructions stored in the memory to implement the solution in the method design of the above first aspect.
  • the implementation of the problem and the beneficial effects of the server reference may be made to the first aspect and the possibilities of the first aspect.
  • the implementation of the server and the beneficial effects therefore, the implementation of the server can refer to the implementation of the method, and the repeated description will not be repeated.
  • a terminal includes a processor and a transmitter;
  • the processor is configured to record, when the terminal is faulty, the type of at least one type of fault that occurs and the number of faults of the type of fault that occurs;
  • the transmitter is configured to upload a fault parameter to the server, where the fault parameter includes at least one fault type and a fault number of the fault type and a terminal usage duration, so that the server predicts the repair of the terminal set according to the fault parameter. Probability.
  • a non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, the non-volatile computer readable storage medium being applied to have processing
  • the server of the apparatus when executed by the server, causes the server to perform the first aspect of the present invention and various possible embodiments of the first aspect, and thus the implementation of the non-transitory computer readable storage medium can be referred to The implementation of the first aspect and the first aspect of the present invention will not be repeated.
  • a non-transitory computer readable storage medium storing one or more programs
  • the one or more programs include instructions, the non-transitory computer readable storage medium being applied to a terminal having a processor that, when executed by the terminal, causes the terminal to perform the following event: When the terminal is faulty, recording at least one type of fault occurring and the number of faults of the fault type occurring; uploading a fault parameter to the server, the fault parameter including at least one fault type and the number of faults of the fault type and The terminal uses the duration to cause the server to predict the repair probability of the terminal set according to the fault parameter.
  • a method, device, server, terminal, and storage medium for predicting a repair probability obtained by an embodiment of the present invention obtains a failure rate of each fault type of each terminal in the terminal set, and determines each terminal of each terminal according to server statistics.
  • the failure probability corresponding to the fault rate of the fault type is obtained, thereby obtaining the repair probability of each terminal and the number of repairs of the terminal set, and finally obtaining the repair probability of the terminal set, and the repair probability of the terminal set can be calculated without waiting for the user to actually return the machine.
  • the terminal can be improved in advance, and the cost of reducing the repair probability is greatly reduced.
  • FIG. 1 is a schematic flowchart of a method for predicting a repair probability according to an embodiment of the present invention
  • 2a is a schematic diagram of a probability of a certain type of failure according to a theoretical calculation
  • 2b is a schematic diagram of the probability of the terminal being decommissioned after the fault rate threshold is artificially set according to the quality level requirement
  • FIG. 3 is a schematic flowchart of a fault parameter uploading method according to an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of a device for predicting a repair probability according to an embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of a fault parameter uploading apparatus according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a server and a terminal according to an embodiment of the present invention.
  • Embodiments of the present invention provide a method, a device, a server, a terminal, and a storage medium for predicting a repair probability Quality, by obtaining the failure rate of each failure type of each terminal in the terminal set, and determining the probability of the failure corresponding to the failure rate of each failure type of each terminal through server statistics, thereby obtaining the repair probability of each terminal and The number of repairs of the terminal set finally obtains the repair probability of the terminal set, and the repair probability of the terminal set can be calculated without waiting for the user to actually return the machine, and the terminal improvement can be performed in advance, and the cost of reducing the repair probability is greatly reduced.
  • GSM Global System of Mobile communication
  • CDMA code division multiple access
  • WCDMA Wideband Code Division Multiple Access
  • GPRS General Packet Radio Service
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • a terminal may be referred to as a user equipment (User Equipment, referred to as "UE"), a mobile station (Mobile Station, abbreviated as "MS”), and a mobile terminal (Mobile). Terminal), computer, microcomputer, refrigerator, air conditioner, etc.
  • the terminal may communicate with one or more core networks via a Radio Access Network (RAN), for example, the terminal may be a mobile phone (or "cellular" phone), with a mobile terminal.
  • RAN Radio Access Network
  • Computers and the like for example, may also be portable, pocket-sized, hand-held, computer-integrated or in-vehicle mobile devices that exchange voice and/or data with the wireless access network.
  • the terminal further includes a terminal with wired access with multiple bearer features.
  • FIG. 1 is a schematic flowchart of a method for predicting a repair probability according to an embodiment of the present invention, where the method includes the following steps:
  • the set of terminals refers to a collection of a plurality of terminals that are sold to the user and that the user is using or has used. If each terminal fails, there may be one or more types of failures.
  • the failure rate refers to how many times a certain fault occurs per unit time, that is, the failure rate of each failure type is the number of failures. The ratio of the duration of use to the terminal.
  • the fault parameter of the used terminal may be uploaded to the server by the user, or the fault parameter may be automatically uploaded to the server when the terminal fails, or the terminal side collects the fault number of each fault type and when the fault occurs.
  • the duration of the terminal is used, and the statistical information is stored in the memory of the terminal, and the fault parameters saved in the memory are automatically uploaded to the server within the set time interval.
  • the fault parameter includes at least one fault type.
  • the fault parameter may further include a fault count of each fault type and a terminal usage duration when the fault occurs, and the terminal usage duration is experienced when the terminal user first starts the terminal to when the fault occurs. The length of time.
  • the server when the fault parameter is collected by the server, when the server receives the fault type sent by the terminal, the number of faults of the fault type can be automatically counted.
  • the duration of the fault can be counted as follows:
  • the server sends a message, and the message may include time information.
  • the server receives the fault type sent by the terminal, it acquires the time when the terminal fails, calculates the time difference between the initial startup time of the terminal and the terminal failure, and calculates the duration of the terminal when the fault occurs. .
  • the terminal When the fault parameter is counted by the terminal side, the terminal automatically counts the number of fault occurrences of each fault type, and records the initial startup time of the terminal, and separately records the duration of use of the terminal when a certain type of fault occurs, thereby obtaining the terminal use of each fault type. duration.
  • the server may obtain the failure rate of each fault type of each terminal in the terminal set, and the server may be a fault collection server.
  • acquiring a failure rate of each fault type of each terminal in the terminal set includes: receiving a fault parameter uploaded by the terminal, where the fault parameter includes at least one fault type, and optionally, the fault parameter may further include each type The number of failures of the fault type and the duration of use of the terminal; according to the fault parameter, the failure rate of each fault type of each terminal is calculated, and the failure rate of each fault type of each terminal is the number of failures of each fault type and the terminal The ratio of the duration of use.
  • the obtained number of failures of each failure type of each terminal and the duration of use of the terminal can easily obtain the failure rate of each failure type of each terminal as a basis for calculating the repair probability of the terminal set.
  • the duration of use is T
  • the faults that occur are (1, 2..n)
  • the number of faults is (C1, C2, ..., Cn)
  • the failure rates of (1,2..n) faults are: C1/T, C2/T, ..., Cn/T.
  • a certain failure rate corresponds to a certain probability of exiting. Generally, the higher the failure rate, the back-off of the terminal. The higher the rate.
  • the corresponding relationship between the failure rate and the probability of the failure of each type of failure is stored in the server. Therefore, according to the failure rate of each type of failure of each terminal, by querying the corresponding relationship, The probability of the failure corresponding to the failure rate of each failure type of each terminal is known.
  • the fault type may include: a system failure rate or an application failure rate.
  • a terminal failure may only include a system failure rate or an application failure rate, or both types of failure rates may be included.
  • the correspondence relationship can be obtained by server statistics, for example, the performance of the relationship between the performance, the price, the failure rate of the brand, and the probability of the back-off of the multiple or multiple generations of terminals, and the corresponding relationship between the failure rate and the probability of the back-off is basically Dynamically stable.
  • server statistics for example, for the entire terminal set, when the server statistics obtain N types of faults; taking the first fault type as an example, the server statistics obtain n kinds of failure rates (a1, a2, a3, ... an); for the first type Fault type.
  • the failure rate is a1
  • the server statistics show that the actual number of downtimes is x, and the failure rate is a1 but the number of failures is y.
  • the failure rate may be a specific failure rate.
  • the value can also be the failure rate interval.
  • the fault type is a system fault as an example
  • the server obtains a correspondence between the fault rate of the system fault and the probability of the back-off according to the above method, wherein the system fault rate may be a specific fault rate value.
  • the failure rate may also be a failure rate interval.
  • the embodiment of the present invention indicates the system failure rate in an interval form; as shown in Table 1 below:
  • the probability of the system corresponding to the failure rate is determined by querying the correspondence table between the system failure rate and the probability of the outage. For example, when the server gets When the system failure rate uploaded by the terminal is 15, the system determines the failure rate interval of the system failure rate corresponding to 10-20 by querying the correspondence table between the system failure rate and the probability of exiting. The probability of the corresponding machine is 0.8, so it is determined. When the system failure rate is 15, the corresponding probability of exit is 0.8.
  • the repair probability P (user, fault-type, fualt-cout, time) to represent (abbreviated Pj), that is, the probability of repair and user (user), fault type (fault-type), the number of failures (fualt-cout) and the duration of use (time) are related.
  • the repair probability Pj of each terminal is calculated as:
  • the repair probability of each terminal is the sum of the probability of the fallback corresponding to the failure rate of each failure type of each terminal.
  • the repair probability of each terminal is less than or equal to 1. Therefore, if the sum of the failure rates corresponding to the failure rate of each fault type of a certain terminal is greater than 1, the probability of the terminal's back-off is taken as 1.
  • the terminal number is (1, 2, 3, ... j.., m)
  • the number of possible complaints/decommissions in the terminal set that is, the number of repairs of the terminal set is defined as Cr, according to the formula (2) Calculate Cr as:
  • the number of repairs of the terminal set is the sum of the repair probabilities of each terminal in the set of terminals.
  • a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the repair probability FFR of the terminal set can be calculated according to formula (3):
  • the repair probability of the terminal set is a ratio of the number of repairs of the terminal set to the total number of terminals of the terminal set.
  • the failure rate of each failure type of each terminal in the terminal set is acquired, and the rework probability corresponding to the failure rate of each failure type is determined according to the server statistics, thereby obtaining the rework of each terminal. Probability and the number of repairs of the terminal set, finally obtaining the terminal set
  • the repair probability does not need to wait until the user actually returns to the machine to calculate the repair probability of the terminal set, and can improve the terminal in advance, and the cost of reducing the repair probability is greatly reduced.
  • repair probability of the terminal set can also be calculated based on the fault tolerance model theory:
  • the degree of tolerance of the user is called the fault tolerance of the fault on the terminal (English: Fault-Tolerance, FT for short). If the user cannot tolerate such a fault, they may complain, complain or even withdraw.
  • FTM Fault-Tolerance-Measurement
  • the FTM is proportional to the number of failures FC.
  • the longer the time required for the inspection process the more serious the fault, the smaller the FTM value; conversely, the shorter the time, the less serious the fault and the larger the FTM value. Therefore, the relationship between FTM and the duration of use T is inversely proportional.
  • FTM The dimension of FTM is “time/hour”. The smaller the FTM value is, the lower the fault tolerance is. The larger the FTM value is, the higher the fault tolerance is. The FTM describes the failure rate threshold that is not tolerated.
  • failure rate x number of failures / length of use
  • the failure rate of the i-type fault of a given terminal reaches a certain failure rate threshold FTM of the terminal (for each terminal or all terminals, multiple failure rate intervals can be set, and each failure rate interval has one
  • the failure probability threshold P(i, FTM) of the terminal is:
  • the return rate of the terminal set can be finally calculated from the backoff probability P(i, FTM) of a certain terminal.
  • FIG. 2a is a schematic diagram of the probability of a back-off probability of a certain fault type calculated according to the theory, wherein the shaded area is the calculated exit probability P(i, FTM) of the terminal, and FIG. 2b is the artificial set according to the quality level.
  • the probability of the terminal's exit probability obtained after determining the failure rate threshold, as shown in Fig. 2a and Fig. 2b the predicted backoff probability of Fig. 2b is obviously higher than the predicted backoff probability of Fig. 2a, that is, the shaded area of Fig. 2b is It is larger than the shaded area of FIG. 2a. Therefore, the probability of the terminal being finally obtained according to the artificially set failure rate threshold is significantly higher than the probability of the terminal being calculated according to the theoretical calculation, so that the quality of the terminal is higher.
  • the correspondence between the failure rate interval and the back-off probability obtained according to the server statistics is the correspondence relationship obtained by the higher quality of the terminal, and the threshold of the failure rate interval corresponds to a greater probability of the back-off.
  • a method for predicting a repair probability is obtained by acquiring a failure rate of each type of failure of each terminal in the terminal set, and determining, by using server statistics, a failure rate corresponding to each failure type of each terminal.
  • the probability of the machine is obtained, and the repair probability of each terminal and the number of repairs of the terminal set are obtained, and finally the repair probability of the terminal set is obtained, and the repair probability of the terminal set can be calculated without waiting for the user to actually return the machine, and the terminal can be improved in advance to reduce the repair.
  • the cost of probability is greatly reduced.
  • FIG. 3 is a schematic flowchart of a method for uploading a fault parameter according to an embodiment of the present invention, which is applied to a terminal having a communication function, and the method includes the following steps:
  • the terminal side counts the type of failure that occurred and the number of failures of the type of failure that occurred, and saves the statistical information in the memory of the terminal.
  • the user uploads the fault parameter of the terminal used to the server, or automatically uploads the fault parameter to the server when the terminal fails, or the terminal side counts the number of faults of each fault type and the duration of the terminal when the fault occurs, and the statistical information It is saved in the memory of the terminal, and the fault parameters saved in the memory are automatically uploaded to the server within the set time interval.
  • the fault parameter includes at least one fault type.
  • the fault parameter may further include a fault count of each fault type and a terminal usage duration when the fault occurs, and the terminal usage duration is experienced when the terminal user first starts the terminal to when the fault occurs. The length of time.
  • the server may obtain the failure rate of each fault type of each terminal in the terminal set.
  • the failure rate of each failure type of each terminal is the ratio of the number of failures to the duration of use of the terminal. Therefore, the server can conveniently obtain the failure rate of each failure type of each terminal according to the obtained number of failures of each failure type of each terminal and the terminal usage time, as a basis for calculating the repair probability of the terminal set.
  • the server determines a probability of a fallback corresponding to the failure rate of each fault type of each terminal, and obtains a repair probability of each terminal, where the repair probability of each terminal is each fault type of each terminal.
  • the repair probability, the repair probability of the terminal set is a ratio of the number of repairs of the terminal set to the total number of terminals of the terminal set.
  • the server can learn the fault rate of each fault type of each terminal in the terminal set according to the fault parameter, and can determine according to the server statistics.
  • the probability of the failure rate corresponding to each fault type of each terminal is obtained, thereby obtaining the repair probability of each terminal and the number of repairs of the terminal set, and finally obtaining the repair probability of the terminal set, which can be calculated without waiting for the user to actually return the machine.
  • the repair probability of the terminal set can improve the terminal in advance, and the cost of reducing the repair probability is greatly reduced.
  • FIG. 4 is a schematic structural diagram of a device for predicting a repair probability according to an embodiment of the present invention.
  • the device 1000 includes: a first acquiring unit 11 and a determining unit 12;
  • the first obtaining unit 11 is configured to acquire a failure rate of each fault type of each terminal in the terminal set.
  • the set of terminals refers to a collection of a plurality of terminals that are sold to the user and that the user is using or has used. If each terminal fails, there may be one or more types of failures.
  • the failure rate refers to how many times a certain fault occurs per unit time, that is, the failure rate of each fault type is the ratio of the number of failures to the duration of the terminal.
  • the fault parameter of the used terminal may be uploaded to the server by the user, or the fault parameter may be automatically uploaded to the server when the terminal fails, or the terminal side collects the fault number of each fault type and when the fault occurs.
  • the duration of the terminal is used, and the statistical information is stored in the memory of the terminal, and the fault parameters saved in the memory are automatically uploaded to the server within the set time interval.
  • the fault parameter includes at least one fault type.
  • the fault parameter may further include a fault count of each fault type and a terminal usage duration when the fault occurs, and the terminal usage duration is experienced when the terminal user first starts the terminal to when the fault occurs. The length of time.
  • the server when the fault parameter is counted by the server, when the server receives the fault type sent by the terminal, the number of faults of the fault type is automatically counted, and the duration of the fault can be counted as follows: when the terminal starts for the first time, the server is sent to the server. Sending a message, the message may include time information.
  • the server receives the fault type sent by the terminal, it acquires the time when the terminal fails, calculates the time difference between the initial startup time of the terminal and the terminal failure, and calculates the duration of the terminal when the fault occurs.
  • the terminal When the fault parameter is counted by the terminal side, the terminal automatically counts the number of fault occurrences of each fault type, and records the initial startup time of the terminal, and separately records the duration of use of the terminal when a certain type of fault occurs, thereby obtaining the terminal use of each fault type. duration.
  • the server may obtain the failure rate of each fault type of each terminal in the terminal set, and the server may be a fault collection server.
  • the first obtaining unit 11 includes: a receiving unit, configured to receive a fault parameter uploaded by the terminal, where the fault parameter includes at least one fault type, and optionally, the fault parameter may further include a fault number of each fault type. a terminal usage time; a calculation unit, configured to calculate a failure rate of each failure type of each terminal according to the fault parameter, and an failure rate of each failure type of each terminal is a failure number of each failure type and a terminal use The ratio of the duration.
  • the obtained number of failures of each failure type of each terminal and the duration of use of the terminal can easily obtain the failure rate of each failure type of each terminal as a basis for calculating the repair probability of the terminal set.
  • the duration of use is T
  • the faults that occur are (1, 2..n)
  • the number of faults is (C1, C2, ..., Cn)
  • the failure rates of (1,2..n) faults are: C1/T, C2/T, ..., Cn/T.
  • the determining unit 12 is configured to determine a probability of a back-off corresponding to the failure rate of each of the fault types of each terminal.
  • a certain failure rate corresponds to a certain probability of exit. Generally, the higher the failure rate, the higher the probability of the terminal's exit.
  • the server has a corresponding relationship between the failure rate and the probability of the failure of each type of failure. Therefore, the determining unit 12 is specifically configured to: determine an failure rate according to each type of failure of each terminal. The probability of the failure rate corresponding to the failure rate of each fault type of each terminal is determined by querying the correspondence between the failure rate and the probability of the failure of each fault type.
  • the fault type may include: a system failure rate or an application failure rate.
  • a terminal failure may only include a system failure rate or an application failure rate, or both types of failure rates may be included.
  • the correspondence relationship can be obtained by server statistics, for example, the performance of the relationship between the performance, the price, the failure rate of the brand, and the probability of the back-off of the multiple or multiple generations of terminals, and the corresponding relationship between the failure rate and the probability of the back-off is basically Dynamically stable.
  • server statistics for example, for the entire terminal set, when the server statistics obtain N types of faults; taking the first fault type as an example, the server statistics obtain n kinds of failure rates (a1, a2, a3, ... an); for the first type Fault type.
  • the server statistics show that the actual number of downtimes is x, and the failure rate is a1 but the number of users not retiring is y (understandably, this part of the user is the first type of failure. Higher tolerance), for the first type of fault
  • the type of the failure rate when the failure rate is a1 is x/(x+y). It can be understood that, in the embodiment of the present invention, the failure rate may be a specific failure rate value or a failure rate interval.
  • the fault type is a system fault as an example
  • the server obtains a correspondence between the fault rate of the system fault and the probability of the back-off according to the above method, wherein the system fault rate may be a specific fault rate value. And may be a failure rate interval, and the embodiment of the present invention represents the system failure rate in an interval form; as shown in Table 1.
  • the probability of the system corresponding to the failure rate is determined by querying the correspondence table between the system failure rate and the probability of the outage. For example, when the server obtains a system failure rate of 15 uploaded by the terminal, the system determines the failure rate interval corresponding to the system failure rate corresponding to 10-20 by querying the correspondence table between the system failure rate and the probability of the back-off. The probability is 0.8, so when the system failure rate is determined to be 15, the corresponding probability of exit is 0.8.
  • the first obtaining unit 11 is further configured to acquire a repair probability of each terminal, where a repair probability of each terminal is a sum of a backoff probability corresponding to a failure rate of each fault type of each terminal.
  • the repair probability P (user, fault-type, fualt-cout, time) to represent (abbreviated Pj), that is, the probability of repair and user (user), fault type The (fault-type), the number of failures (fualt-cout), and the duration of use are related.
  • the repair probability Pj of each terminal can be calculated.
  • the repair probability of each terminal is the sum of the probability of the fallback corresponding to the failure rate of each failure type of each terminal.
  • the repair probability of each terminal is less than or equal to 1. Therefore, if the sum of the failure rates corresponding to the failure rate of each fault type of a certain terminal is greater than 1, the probability of the terminal's back-off is taken as 1.
  • the first obtaining unit 11 is further configured to acquire the number of repairs of the set of terminals, where the number of repairs of the set of terminals is a sum of repair probabilities of each terminal in the set of terminals.
  • the terminal number is (1, 2, 3, ... j.., m)
  • the number of possible complaints/decommissions in the terminal set that is, the number of repairs of the terminal set is defined as Cr, according to the formula (2) Cr can be calculated.
  • the number of repairs of the terminal set is the sum of the repair probabilities of each terminal in the set of terminals.
  • the first obtaining unit 11 is further configured to acquire a repair probability of the terminal set, where a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the repair probability FFR of the terminal set can be calculated according to formula (3).
  • the repair probability of the terminal set is a ratio of the number of repairs of the terminal set to the total number of terminals of the terminal set.
  • a repair probability prediction apparatus obtains a failure rate of each failure type of each terminal in a terminal set, and determines a probability of a failure corresponding to a failure rate of each failure type according to server statistics. Therefore, the repair probability of each terminal and the number of repairs of the terminal set are obtained, and finally the repair probability of the terminal set is obtained, and the repair probability of the terminal set can be calculated without waiting for the user to actually return the machine, and the terminal can be improved in advance to reduce the cost of the repair probability. Greatly reduced.
  • FIG. 5 is a schematic structural diagram of a fault parameter uploading apparatus according to an embodiment of the present invention.
  • the apparatus may be a terminal having a communication function, and the apparatus 2000 includes:
  • the recording unit 21 is configured to record, when the terminal fails, the type of at least one type of failure that occurs and the number of failures of the type of failure that occurs.
  • the recording unit 21 counts the type of failure that occurred and the number of failures of the type of failure that occurred, and stores the statistical information in the memory of the terminal.
  • the uploading unit 22 is configured to upload a fault parameter to the server, where the fault parameter includes at least one fault type and a fault number of the fault type and a terminal usage duration, so that the server predicts the terminal set according to the fault parameter. Rework probability.
  • the user uploads the fault parameter of the terminal used to the server, or automatically uploads the fault parameter to the server when the terminal fails, or the terminal side counts the number of faults of each fault type and the duration of the terminal when the fault occurs, and the statistical information It is saved in the memory of the terminal, and the fault parameters saved in the memory are automatically uploaded to the server within the set time interval.
  • the fault parameter includes at least one fault type.
  • the fault parameter may further include a fault count of each fault type and a terminal usage duration when the fault occurs, and the terminal usage duration is experienced when the terminal user first starts the terminal to when the fault occurs. The length of time.
  • the server may obtain the failure rate of each fault type of each terminal in the terminal set.
  • the failure rate of each failure type of each terminal is the ratio of the number of failures to the duration of use of the terminal.
  • the server is based on each fault class of each terminal obtained. The number of failures of the type and the length of use of the terminal can easily obtain the failure rate of each failure type of each terminal as the basis for calculating the repair probability of the terminal set.
  • the server determines a probability of a fallback corresponding to the failure rate of each fault type of each terminal, and obtains a repair probability of each terminal, where the repair probability of each terminal is each fault type of each terminal.
  • the repair probability, the repair probability of the terminal set is a ratio of the number of repairs of the terminal set to the total number of terminals of the terminal set.
  • the server by uploading the fault parameter of the terminal to the server, the server can learn the fault rate of each fault type of each terminal in the terminal set according to the fault parameter, and can determine according to the server statistics.
  • the probability of the failure rate corresponding to each fault type of each terminal is obtained, thereby obtaining the repair probability of each terminal and the number of repairs of the terminal set, and finally obtaining the repair probability of the terminal set, which can be calculated without waiting for the user to actually return the machine.
  • the repair probability of the terminal set can improve the terminal in advance, and the cost of reducing the repair probability is greatly reduced.
  • FIG. 6 is a schematic structural diagram of a server 3000 and a terminal 4000 according to an embodiment of the present invention.
  • the server 3000 may include: a processor 31, a memory 32;
  • the memory 32 is configured to store instructions and data, where the data includes a correspondence between a failure rate of each type of failure and a probability of exiting;
  • the processor 31 is configured to execute instructions stored in the memory 32 to implement:
  • a repair probability of each terminal is a sum of a probability of a fallback corresponding to a failure rate of each fault type of each terminal;
  • a repair probability of the terminal set is a ratio of a number of repairs of the terminal set to a total number of terminals of the terminal set.
  • the server 3000 may further include a receiver 33 (in the figure, a dotted line is connected Connect)
  • the receiver 33 is configured to receive a fault parameter uploaded by the terminal, where the fault parameter includes at least one fault type and a fault number of each fault type and a terminal usage duration.
  • the processor 31 is further configured to calculate, according to the fault parameter, a failure rate of each fault type of each terminal, and an error rate of each fault type of each terminal The ratio of the number of failures of each fault type to the duration of use of the terminal.
  • the processor 31 is specifically configured to:
  • each terminal Determining each of the each terminal by querying a correspondence between a failure rate of each of the failure types stored in the memory and a probability of a back-off according to a failure rate of each failure type of each terminal The probability of a failure corresponding to the failure rate of the fault type.
  • a server obtains a failure rate of each type of failure of each terminal in a terminal set, and determines, by using server statistics, a failure rate corresponding to each failure type of each terminal type. Probability, thereby obtaining the repair probability of each terminal and the number of repairs of the terminal set, and finally obtaining the repair probability of the terminal set, without waiting for the user to actually return the machine, the return probability of the terminal set can be calculated, and the terminal improvement can be performed in advance to reduce the repair probability The cost is greatly reduced.
  • the terminal 4000 includes: a processor 41 and a transmitter 42;
  • the processor 41 is configured to record at least one type of fault that occurs and the number of faults of the type of fault that occurs when the terminal fails.
  • the transmitter 42 is configured to upload a fault parameter to the server, where the fault parameter includes at least one fault type and a fault number of the fault type and a terminal usage duration, so that the server predicts the terminal set according to the fault parameter.
  • the probability of repair is configured to upload a fault parameter to the server, where the fault parameter includes at least one fault type and a fault number of the fault type and a terminal usage duration, so that the server predicts the terminal set according to the fault parameter. The probability of repair.
  • the terminal uploads the fault parameter of the terminal to the server, and the server can learn the failure rate of each fault type of each terminal in the terminal set according to the fault parameter, and can determine each according to the server statistics.
  • the probability of the failure rate corresponding to the failure rate of each fault type of the terminal is obtained, thereby obtaining the repair probability of each terminal and the number of repairs of the terminal set, and finally obtaining the repair probability of the terminal set, and the terminal set cannot be calculated after the user actually returns the machine.
  • the probability of repairing can improve the terminal in advance, and the cost of reducing the probability of repair is greatly reduced.
  • the embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium may store a program, and the program includes some or all of the steps of the monitoring method of any one of the service processes described in the foregoing method embodiments.
  • Computer readable storage media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another.
  • a storage medium may be any available media that can be accessed by a computer.
  • the computer readable storage medium may include a random access memory (RAM), a read-only memory (ROM), and an electrically erasable programmable read only memory (Electrically Erasable).
  • EEPROM Electrically Error Read-Only Memory
  • CD-ROM Compact Disc Read-Only Memory
  • Any connection may suitably be a computer readable storage medium.
  • the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, Then coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, wireless and microwave are included in the fixing of the associated medium.
  • DSL Digital Subscriber Line
  • a disk Discs include compact discs (CDs), laser discs, compact discs, digital versatile discs (DVDs), floppy discs, and Blu-ray discs, where the discs are typically magnetically replicated, while discs are optically replicated using lasers. Combinations of the above should also be included within the scope of the computer readable storage medium.

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Abstract

本发明实施例公开了一种返修概率预测方法、装置、服务器、终端及存储介质。通过服务器获取终端集合中每个终端的每种故障类型的故障率，并根据服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。

Description

返修概率预测方法、装置、服务器、终端及存储介质 技术领域
本发明涉及通信技术领域，尤其涉及一种返修概率预测方法、装置、服务器、终端及存储介质。
背景技术
现场失效率(英文：Field Failure Rate，简称：FFR)，用于衡量终端质量的指标，具体指终端故障数占在保量的比例，即通常所说的“返修概率”。终端FFR较高时，会影响终端口碑，增加公司成本，故一款终端终端FFR越低越好。
但目前FFR的值需要得到用户实际的退换机后才能计算出来，时间非常滞后，当发现FFR较高时，往往成本已经产生，降低FFR的成本较高，目前还没有预测FFR的方案。
发明内容
本发明实施例提供了一种返修概率预测方法、装置、服务器、终端及存储介质，以解决目前得到终端的返修概率统计时间滞后的问题。
第一方面，提供了一种返修概率预测方法，所述方法包括：
获取终端集合中每个终端的每种故障类型的故障率；
确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
在该设计中，通过获取终端集合中每个终端的每种故障类型的故障率，并通过服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进 行终端改进，降低返修概率的成本大大减小。
结合第一方面，在一种可能的设计中，所述获取终端集合中每个终端的每种故障类型的故障率，包括：
接收终端上传的故障参数，所述故障参数至少包括一种故障类型以及每种故障类型的故障次数和终端使用时长；
根据所述故障参数，计算每个终端的每种故障类型的故障率，所述每个终端的每种故障类型的故障率为所述每种故障类型的故障次数与所述终端使用时长的比值。
在该设计中，根据终端上传的每种故障类型的故障次数和终端使用时长，可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础，无需等到用户实际退换机后才能计算终端集合的返修概率。
结合第一方面，在另一种可能的设计中，所述确定所述每个终端的所述每种故障类型的故障率对应的退机概率，包括：
根据所述每个终端的每种故障类型的故障率，通过查询每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的每种故障类型的故障率对应的退机概率。
在该设计中，通过服务器统计获得每种故障类型的故障率与退机概率的对应关系，根据每个终端的每种故障类型的故障率，可以查询得到对应的退机概率，计算退机概率简单、快捷。
结合第一方面，在又一种可能的设计中，所述故障类型包括：系统平均故障率、应用平均故障率。
结合第一方面，在又一种可能的设计中，若所述每个终端的每种故障类型的故障率对应的退机概率之和大于1，所述每个终端的返修概率取1，其中，所述每个终端的返修概率小于或等于1。
第二方面，提供了一种故障参数上传方法，应用于具有通信功能的终端，所述方法包括：
当所述终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数；
向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故 障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
在该设计中，根据终端上传的故障参数，服务器可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
第三方面，提供了一种返修概率预测装置，所述装置包括：
第一获取单元，用于获取终端集合中每个终端的每种故障类型的故障率；
确定单元，用于确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
所述第一获取单元还用于获取所述每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
所述第一获取单元还用于获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
所述第一获取单元还用于获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
基于同一发明构思，由于该装置解决问题的原理以及有益效果可以参见上述第一方面和第一方面的各可能的实施方式以及所带来的有益效果，因此该装置的实施可以参见方法的实施，重复之处不再赘述。
第四方面，提供了一种故障参数上传装置，所述装置包括：
记录单元，用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数；
上传单元，用于向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
第五方面，提供了一种服务器，所述服务器包括：处理器，存储器；
其中，
所述存储器用于存储指令和数据，所述数据包括每种故障类型的故障率与退机概率的对应关系；
所述处理器用于执行所述指令以实现：
获取终端集合中每个终端的每种故障类型的故障率；
确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
获取所述每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
所述处理器调用存储在所述存储器中的指令以实现上述第一方面的方法设计中的方案，由于该服务器解决问题的实施方式以及有益效果可以参见上述第一方面和第一方面的各可能的实施方式以及有益效果，因此该服务器的实施可以参见方法的实施，重复之处不再赘述。
第六方面，提供了一种终端，所述终端包括处理器和发送器；
所述处理器用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数；
所述发送器用于向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
第七方面，提供了一种存储一个或多个程序的非易失性计算机可读存储介质，所述一个或多个程序包括指令，所述非易失性计算机可读存储介质应用于具有处理器的服务器，所述指令当被所述服务器执行时使所述服务器执行本发明第一方面和第一方面的各可能的实施方式，因此该非易失性计算机可读存储介质的实施可以参见本发明第一方面和第一方面的实施，重复之处不再赘述。
第八方面，提供了一种存储一个或多个程序的非易失性计算机可读存储介 质，所述一个或多个程序包括指令，所述非易失性计算机可读存储介质应用于具有处理器的终端，所述指令当被所述终端执行时使所述终端执行以下事件：当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数终端；向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数预测终端集合的返修概率。
实施本发明实施例提供的一种返修概率预测方法、装置、服务器、终端及存储介质，通过获取终端集合中每个终端的每种故障类型的故障率，并根据服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的一种返修概率预测方法的流程示意图；
图2a为根据理论计算得到的某种故障类型的退机概率示意图；
图2b为根据质量等级要求人为设定故障率门限后得到的该终端的退机概率示意图；
图3为本发明实施例提供的一种故障参数上传方法的流程示意图；
图4为本发明实施例提供的一种返修概率预测装置的结构示意图；
图5为本发明实施例提供的一种故障参数上传装置的结构示意图；
图6为本发明实施例提供的一种服务器与终端的结构示意图。
具体实施方式
本发明实施例提供一种返修概率预测方法、装置、服务器、终端及存储介 质，通过获取终端集合中每个终端的每种故障类型的故障率，并通过服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
下面通过具体的实施例进行详细描述：
本领域技术人员可以理解地，本发明实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，简称为“GSM”)系统、码分多址(Code Division Multiple Access，简称为“CDMA”)系统、宽带码分多址(Wideband Code Division Multiple Access，简称为“WCDMA”)系统、通用分组无线业务(General Packet Radio Service，简称为“GPRS”)、长期演进(Long Term Evolution，简称为“LTE”)系统、LTE频分双工(Frequency Division Duplex，简称为“FDD”)系统、LTE时分双工(Time Division Duplex，简称为“TDD”)、通用移动通信系统(Universal Mobile Telecommunication System，简称为“UMTS”)或全球互联微波接入(Worldwide Interoperability for Microwave Access，简称为“WiMAX”)通信系统等。
本领域技术人员可以理解地，在本发明实施例中，终端可称之为用户设备(User Equipment，简称为“UE”)、移动台(Mobile Station，简称为“MS”)、移动终端(Mobile Terminal)，计算机，微机，冰箱，空调等。该终端可以经无线接入网(Radio Access Network，简称为“RAN”)与一个或多个核心网进行通信，例如，终端可以是移动电话(或称为“蜂窝”电话)、具有移动终端的计算机等，例如，终端还可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置，它们与无线接入网交换语音和/或数据。本发明对此并不限定，例如终端还包括具有多承载特征的有线接入的终端。
图1为本发明实施例提供的一种返修概率预测方法的流程示意图，该方法包括以下步骤：
S101，获取终端集合中每个终端的每种故障类型的故障率。
本实施例中，终端集合指销售给用户、且用户正在使用或已经使用的多个终端的集合。各个终端如果发生故障，可能存在一种或多种类型的故障。故障率是指每单位时间发生多少次某种故障，即每种故障类型的故障率为故障次数 与终端使用时长的比值。
本实施例中，可由用户将所使用终端的故障参数上传至服务器，或还可以是当终端发生故障时自动向服务器上传故障参数，或者终端侧统计每一种故障类型的故障次数和发生故障时终端使用时长，并将统计的信息保存在终端的存储器中，在设定时间间隔内将存储器中保存的故障参数自动上传至服务器。所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和发生故障时终端使用时长，终端使用时长是终端用户初次启动终端至发生故障时所经历的时长。
具体地，当由服务器侧统计故障参数时，当服务器收到终端发送的故障类型时，可以自动统计该类故障类型的故障发生次数，使用时长则可以通过以下方式统计：终端初次启动时，向服务器发送消息，消息中可包含时间信息，当服务器收到终端发送的故障类型时，获取终端发生故障的时间，计算终端初次启动时间和终端发生故障时的时间差，计算发生故障时终端的使用时长。当由终端侧统计故障参数时，终端自动统计每一个故障类型的故障发生次数，以及记录终端初次启动时间，并分别记录发生某类故障时终端的使用时长，从而得到每一个故障类型的终端使用时长。
服务器获取到终端集合中每个终端的故障参数后，可获取得到终端集合中每个终端的每种故障类型的故障率，该服务器可以是故障采集服务器。
具体地，获取终端集合中每个终端的每种故障类型的故障率，包括：接收终端上传的故障参数，所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和终端使用时长；根据所述故障参数，计算每个终端的每种故障类型的故障率，每个终端的每种故障类型的故障率为每种故障类型的故障次数与终端使用时长的比值。从而，得到的每个终端的每种故障类型的故障次数和终端使用时长，可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础。
例如，某用户用某件终端j在某个使用过程中，使用时长为T，发生的故障有(1,2..n)类，故障次数分别为(C1，C2，…,Cn)，则(1,2..n)类故障的故障率分别为：C1/T，C2/T，…，Cn/T。
S102，确定所述每个终端的所述每种故障类型的故障率对应的退机概率。
一定的故障率对应有一定的退机概率，通常故障率越高，该终端的退机概 率越高。
在本实施例中，服务器中存储有每种故障类型的故障率与退机概率的对应关系，因此，根据所述每个终端的每种故障类型的故障率，通过查询该对应关系，便可得知每个终端的每种故障类型的故障率对应的退机概率。
可选的，该故障类型可包括：系统故障率或应用故障率。一个终端的故障可能只包括系统故障率或应用故障率，也可能两种类型的故障率都包括。
该对应关系可通过服务器统计获得，例如经过多个或多代终端的性能、价格、品牌的故障率与退机概率的对应关系的统计，统计得到的故障率与退机概率的对应关系基本是动态稳定的。具体地，例如，对于整个终端集合，当服务器统计得到N种故障类型；以第一种故障类型为例，服务器统计得到n种故障率(a1、a2、a3……an)；对于第一种故障类型，当故障率为a1时，服务器统计得到实际退机数为x，且故障率为a1但并没有退机的数量为y(可以理解地，这部分用户对第一种故障类型的容忍度较高)，则对于第一种故障类型，当故障率为a1时的退机概率为x/(x+y)；可以理解地，本发明实施例中，故障率可以是具体的故障率值，也可以是故障率区间。
示例性地，本发明实施例以故障类型为系统故障为例，服务器按以上方法统计得到系统故障的故障率与退机概率之间的对应关系，其中，系统故障率可以是具体的故障率值，故障率也可以是故障率区间，本发明实施例以区间形式表示系统故障率；如下表1所示：
表1系统故障率与退机概率的对应关系表
系统故障率(次/小时) 退机概率
>20 1
10-20 0.8
5-10 0.6
2-5 0.4
0.7-2 0.2
∠0.7 0
当服务器获取到终端上传的系统故障率时，通过查询系统故障率与退机概率的对应关系表，确定该系统故障率对应的退机概率。例如，当服务器获取到 终端上传的系统故障率为15时，通过查询系统故障率与退机概率的对应关系表，确定该系统故障率对应10-20的故障率区间，该区间对应的退机概率为0.8，因此确定系统故障率为15时，对应的退机概率为0.8。
S103，获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和。
要评估用户投诉退机的可能性即终端的返修概率，用返修概率P(user，fault-type，fualt-cout，time)来表示(简写Pj)，即返修概率与用户(user)、故障类型(fault-type)、故障次数(fualt-cout)和使用时长(time)相关，根据上面的举例和依据公式(1)计算得到每个终端的返修概率Pj为：
Figure PCTCN2016080841-appb-000001
即，每个终端的返修概率为所述每个终端的每种故障类型的故障率对应的退机概率之和。
其中，每个终端的返修概率小于或等于1，因此，若某个终端的每种故障类型的故障率对应的退机概率之和大于1，则该终端的退机概率取1。
S104，获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和。
假定有一个终端集合，终端编号为(1,2,3,…j..,m)，则该终端集合可能的投诉/退机个数即该终端集合的返修个数定义为Cr，依据公式(2)计算得到Cr为：
Figure PCTCN2016080841-appb-000002
即，终端集合的返修个数为所述终端集合中每个终端的返修概率之和。
S105，获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据以上计算得到的终端集合的返修个数与终端集合的终端总个数，即可依据公式(3)计算得到终端集合的返修概率FFR为：
FFR＝Cr/m   ....公式(3)
即，终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据上面实施例的描述，通过获取终端集合中每个终端的每种故障类型的故障率，并通过根据服务器统计确定每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的 返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
事实上，也可基于故障容忍度模型理论计算得到终端集合的返修概率：
终端发生一次或多次某种故障时，用户对此的容忍程度，称为此终端上该类故障的故障容忍度(英文：Fault-Tolerance，简称：FT)。用户如果不能容忍此类故障，就可能抱怨，投诉甚至退机。
如何来衡量故障的容忍度？我们使用故障容忍度系数(英文：Fault-Tolerance-Measurement，简称FTM)来描述，故障容忍度越高，系数越大，FTM值越大，故障越不严重；故障容忍度越低，系数越小，FTM值越小，故障越严重。
对给定的终端而言，FTM的大小跟哪些因素有关？因素比较多，这里我们挑选最具普遍意义的因素：用户，故障类型，故障次数，使用时长；为了建立FTM与这些因素之间的关系，我们使用一个过程来考察某个用户容忍度与发生的故障之间的关系(简称考察过程)：从终端开始使用开始，到用户无法容忍投诉退机结束。
一般地，对给定的用户和给定的某类故障，考察过程中故障次数越多，说明故障越不严重，FTM值越大；反之，故障次数越少，说明故障越严重，FTM越小。因此FTM与故障次数FC是正比例关系。另一方面，考察过程中需要的时间越长，说明故障越严重，FTM值越小；反之，时间越短，说明故障越不严重，FTM值越大。因此，FTM与使用时长T的关系是反比例关系。
对于一个给定的终端，假定其可能发生的故障类型有n种，编号为(1,2,....i,…n)，第i种故障的容忍度系数为FTM(i)，考察过程中发生的故障次数为nc，考察时长为tc，则有：
FTM(i)＝nc/tc  ....公式(4)
FTM的量纲为“次/小时”，FTM值越小，故障容忍度越低；FTM值越大，故障容忍度越高，可见FTM描述的是不容忍的故障率门限。
接下来，统计给定的某个故障率下，返修的用户数，经过归一化处理后，即可得到此故障率下的返修概率密度P’(x)：
P’(x)＝在故障率x下的返修数/此类故障总返修数  ....公式(5)
其中，故障率x＝故障次数/使用时长
从而得到给定的某个终端第i类故障的故障率达到该终端的某个故障率门限FTM(对于每一种终端或所有终端，可以设置多个故障率区间，每个故障率区间有一个故障率门限)时，该终端的退机概率P(i,FTM)为：
Figure PCTCN2016080841-appb-000003
根据前面的步骤S104-S105，由某个终端的退机概率P(i,FTM)，最终可计算得到终端集合的返修率。
然而，实际计算过程中，不会去计算一个积分算式来获得终端的退机概率，这样不太直观，而通过服务器统计得到的故障率区间与退机概率的对应关系，得到某种故障类型的故障率对应的退机概率，这样更方便、直观。
图2a为根据理论计算得到的某种故障类型的退机概率示意图，其中，阴影部分面积即为计算出的该终端的退机概率P(i,FTM)，图2b为根据质量等级要求人为设定故障率门限后得到的该终端的退机概率示意图，由图2a和图2b可知，图2b预测的退机概率显然高于图2a预测的退机概率，即，图2b的阴影部分面积要大于图2a的阴影部分面积，因此，根据人为设定的故障率门限最终获得的终端的退机概率明显要高于根据理论计算得到的终端的退机概率，因此其对终端质量要求更高。
实际上，根据服务器统计得到的故障率区间与退机概率的对应关系就是对终端质量要求更高而得到的对应关系，其故障率区间的门限对应的退机概率更大。
根据本发明实施例提供的一种返修概率预测方法，通过获取终端集合中每个终端的每种故障类型的故障率，并通过服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
图3为本发明实施例提供的一种故障参数上传方法的流程示意图，应用于具有通信功能的终端，该方法包括以下步骤：
S201，当所述终端发生故障时，记录所发生的至少一种故障类型以及所发 生的故障类型的故障次数。
当终端发生故障时，终端侧统计所发生的故障类型和所发生的故障类型的故障次数，并将统计的信息保存在终端的存储器中。
S202，向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
用户将所使用终端的故障参数上传至服务器，或当终端发生故障时自动向服务器上传故障参数，或者终端侧统计每一种故障类型的故障次数和发生故障时终端使用时长，并将统计的信息保存在终端的存储器中，在设定时间间隔内将存储器中保存的故障参数自动上传至服务器。所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和发生故障时终端使用时长，终端使用时长是终端用户初次启动终端至发生故障时所经历的时长。
服务器获取到终端集合中每个终端的故障参数后，可获取得到终端集合中每个终端的每种故障类型的故障率。每个终端的每种故障类型的故障率为故障次数与终端使用时长的比值。从而，服务器根据得到的每个终端的每种故障类型的故障次数和终端使用时长，可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础。
然后，服务器确定所述每个终端的每种故障类型的故障率对应的退机概率，获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的每种故障类型的故障率对应的退机概率之和，获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和，获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据本发明实施例提供的一种故障参数上传方法，通过将终端的故障参数上传服务器，服务器根据故障参数可以获知终端集合中每个终端的每种故障类型的故障率，并根据服务器统计可以确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
需要说明的是，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为根据本发明，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定是本发明所必须的。
图4为本发明实施例提供的一种返修概率预测装置的结构示意图，该装置1000包括：第一获取单元11和确定单元12；
第一获取单元11，用于获取终端集合中每个终端的每种故障类型的故障率。
本实施例中，终端集合指销售给用户、且用户正在使用或已经使用的多个终端的集合。各个终端如果发生故障，可能存在一种或多种类型的故障。故障率是指每单位时间发生多少次某种故障，即每种故障类型的故障率为故障次数与终端使用时长的比值。
本实施例中，可由用户将所使用终端的故障参数上传至服务器，或还可以是当终端发生故障时自动向服务器上传故障参数，或者终端侧统计每一种故障类型的故障次数和发生故障时终端使用时长，并将统计的信息保存在终端的存储器中，在设定时间间隔内将存储器中保存的故障参数自动上传至服务器。所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和发生故障时终端使用时长，终端使用时长是终端用户初次启动终端至发生故障时所经历的时长。
具体地，当由服务器侧统计故障参数时，当服务器收到终端发送的故障类型时，自动统计该类故障类型的故障发生次数，使用时长则可以通过以下方式统计：终端初次启动时，向服务器发送消息，消息中可包含时间信息，当服务器收到终端发送的故障类型时，获取终端发生故障的时间，计算终端初次启动时间和终端发生故障时的时间差，计算发生故障时终端的使用时长。当由终端侧统计故障参数时，终端自动统计每一个故障类型的故障发生次数，以及记录终端初次启动时间，并分别记录发生某类故障时终端的使用时长，从而得到每一个故障类型的终端使用时长。
服务器获取到终端集合中每个终端的故障参数后，可获取得到终端集合中每个终端的每种故障类型的故障率，该服务器可以是故障采集服务器。
具体地，第一获取单元11包括：接收单元，用于接收终端上传的故障参数，所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和终端使用时长；计算单元，用于根据所述故障参数，计算每个终端的每种故障类型的故障率，每个终端的每种故障类型的故障率为每种故障类型的故障次数与终端使用时长的比值。从而，得到的每个终端的每种故障类型的故障次数和终端使用时长，可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础。
例如，某用户用某件终端j在某个使用过程中，使用时长为T，发生的故障有(1,2..n)类，故障次数分别为(C1，C2，…,Cn)，则(1,2..n)类故障的故障率分别为：C1/T，C2/T，…，Cn/T。
确定单元12，用于确定所述每个终端的所述每种故障类型的故障率对应的退机概率。
一定的故障率对应有一定的退机概率，通常故障率越高，该终端的退机概率越高。
在本实施例中，服务器中存储有每种故障类型的故障率与退机概率的对应关系，因此，所述确定单元12具体用于：根据所述每个终端的每种故障类型的故障率，通过查询每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的每种故障类型的故障率对应的退机概率。
可选的，该故障类型可包括：系统故障率或应用故障率。一个终端的故障可能只包括系统故障率或应用故障率，也可能两种类型的故障率都包括。
该对应关系可通过服务器统计获得，例如经过多个或多代终端的性能、价格、品牌的故障率与退机概率的对应关系的统计，统计得到的故障率与退机概率的对应关系基本是动态稳定的。具体地，例如，对于整个终端集合，当服务器统计得到N种故障类型；以第一种故障类型为例，服务器统计得到n种故障率(a1、a2、a3……an)；对于第一种故障类型，当故障率为a1时，服务器统计得到实际退机数为x，且故障率为a1但用户并没有退机的数量为y(可以理解地，这部分用户对第一种故障类型的容忍度较高)，则对于第一种故障类 型，当故障率为a1时的退机概率为x/(x+y)；可以理解地，本发明实施例中，故障率可以是具体的故障率值，也可以是故障率区间。
示例性地，本发明实施例以故障类型为系统故障为例，服务器按以上方法统计得到系统故障的故障率与退机概率之间的对应关系，其中，系统故障率可以是具体的故障率值，与可以是故障率区间，本发明实施例以区间形式表示系统故障率；如表1所示。
当服务器获取到终端上传的系统故障率时，通过查询系统故障率与退机概率的对应关系表，确定该系统故障率对应的退机概率。例如，当服务器获取到终端上传的系统故障率为15时，通过查询系统故障率与退机概率的对应关系表，确定该系统故障率对应10-20的故障率区间，该区间对应的退机概率为0.8，因此确定系统故障率为15时，对应的退机概率为0.8。
所述第一获取单元11还用于获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和。
要评估用户投诉退机的可能性即终端的返修概率，用返修概率P(user，fault-type，fualt-cout，time)来表示(简写Pj)，即返修概率与用户(user)、故障类型(fault-type)、故障次数(fualt-cout)和使用时长(time)相关，根据上面的举例和依据公式(1)可计算得到每个终端的返修概率Pj。
即，每个终端的返修概率为所述每个终端的每种故障类型的故障率对应的退机概率之和。
其中，每个终端的返修概率小于或等于1，因此，若某个终端的每种故障类型的故障率对应的退机概率之和大于1，则该终端的退机概率取1。
所述第一获取单元11还用于获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和。
假定有一个终端集合，终端编号为(1,2,3,…j..,m)，则该终端集合可能的投诉/退机个数即该终端集合的返修个数定义为Cr，依据公式(2)可计算得到Cr。
即，终端集合的返修个数为所述终端集合中每个终端的返修概率之和。
所述第一获取单元11还用于获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据以上计算得到的终端集合的返修个数与终端集合的终端总个数，即可依据公式(3)可计算得到终端集合的返修概率FFR。
即，终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据本发明实施例提供的一种返修概率预测装置，通过获取终端集合中每个终端的每种故障类型的故障率，并通过根据服务器统计确定每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
图5为本发明实施例提供的一种故障参数上传装置的结构示意图，该装置可以为具有通信功能的终端，该装置2000包括：
记录单元21，用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数。
当终端发生故障时，记录单元21统计所发生的故障类型和所发生的故障类型的故障次数，并将统计的信息保存在终端的存储器中。
上传单元22，用于向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
用户将所使用终端的故障参数上传至服务器，或当终端发生故障时自动向服务器上传故障参数，或者终端侧统计每一种故障类型的故障次数和发生故障时终端使用时长，并将统计的信息保存在终端的存储器中，在设定时间间隔内将存储器中保存的故障参数自动上传至服务器。所述故障参数至少包括一种故障类型，可选地，故障参数还可以包括每种故障类型的故障次数和发生故障时终端使用时长，终端使用时长是终端用户初次启动终端至发生故障时所经历的时长。
服务器获取到终端集合中每个终端的故障参数后，可获取得到终端集合中每个终端的每种故障类型的故障率。每个终端的每种故障类型的故障率为故障次数与终端使用时长的比值。从而，服务器根据得到的每个终端的每种故障类 型的故障次数和终端使用时长，可以方便地获得每个终端的每种故障类型的故障率，作为计算终端集合的返修概率的基础。
然后，服务器确定所述每个终端的每种故障类型的故障率对应的退机概率，获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的每种故障类型的故障率对应的退机概率之和，获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和，获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
根据本发明实施例提供的一种故障参数上传装置，通过将终端的故障参数上传服务器，服务器根据故障参数可以获知终端集合中每个终端的每种故障类型的故障率，并根据服务器统计可以确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
图6为本发明实施例提供的一种服务器3000与终端4000的结构示意图，如图6所示，该服务器3000可包括：处理器31，存储器32；
其中，所述存储器32用于存储指令和数据，所述数据包括每种故障类型的故障率与退机概率的对应关系；
所述处理器31用于执行存储在存储器32中的指令以实现：
获取终端集合中每个终端的每种故障类型的故障率；
确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
获取所述每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
在一种可能的设计中，所述服务器3000还可包括接收器33(图中以虚线连 接)；
所述接收器33用于接收终端上传的故障参数，所述故障参数至少包括一种故障类型以及每种故障类型的故障次数和终端使用时长。
在另一种可能的设计中，所述处理器31还用于根据所述故障参数，计算每个终端的每种故障类型的故障率，所述每个终端的每种故障类型的故障率为所述每种故障类型的故障次数与所述终端使用时长的比值。
在又一种可能的设计中，所述处理器31具体用于：
根据所述每个终端的每种故障类型的故障率，通过查询存储在所述存储器中的所述每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的每种故障类型的故障率对应的退机概率。
根据本发明实施例提供的一种服务器，该服务器通过获取终端集合中每个终端的每种故障类型的故障率，并通过服务器统计确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
请继续参阅图6，该终端4000包括：处理器41和发送器42；
所述处理器41用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数。
所述发送器42用于向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
根据本发明实施例提供的一种终端，该终端将终端的故障参数上传服务器，服务器根据故障参数可以获知终端集合中每个终端的每种故障类型的故障率，并根据服务器统计可以确定每个终端的每种故障类型的故障率对应的退机概率，从而获取每个终端的返修概率以及终端集合的返修个数，最终获取终端集合的返修概率，无需等到用户实际退换机后才能计算终端集合的返修概率，能够提前进行终端改进，降低返修概率的成本大大减小。
本发明实施例还提供一种计算机存储介质，其中，该计算机存储介质可存储有程序，该程序执行时包括上述方法实施例中记载的任何一种服务进程的监控方法的部分或全部步骤。
在上述实施例中，基于同一发明构思，本发明实施例中的服务器、终端及对应装置所解决的技术问题、实施方式以及有益效果可以参见对应方法的实施，重复之处不再赘述。
本发明实施例方法中的步骤可以根据实际需要进行顺序调整、合并和删减。
本发明实施例装置中的单元可以根据实际需要进行合并、划分和删减。本领域的技术人员可以将本说明书中描述的不同实施例以及不同实施例的特征进行结合或组合。
通过以上的实施方式的描述，所属领域的技术人员可以清楚地了解到本发明可以用硬件实现，或固件实现，或它们的组合方式来实现。当使用软件实现时，可以将上述功能存储在非易失性计算机可读存储介质中或作为计算机可读存储介质上的一个或多个指令或代码进行传输。计算机可读存储介质包括计算机存储介质和通信介质，其中通信介质包括便于从一个地方向另一个地方传送计算机程序的任何介质。存储介质可以是计算机能够存取的任何可用介质。以此为例但不限于：计算机可读存储介质可以包括随机存取存储器(Random Access Memory，RAM)、只读存储器(Read-Only Memory，ROM)、电可擦可编程只读存储器(Electrically Erasable Programmable Read-Only Memory，EEPROM)、只读光盘(Compact Disc Read-Only Memory，CD-ROM)或其他光盘存储、磁盘存储介质或者其他磁存储设备、或者能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质。此外。任何连接可以适当的成为计算机可读存储介质。例如，如果软件是使用同轴电缆、光纤光缆、双绞线、数字用户线(Digital Subscriber Line，DSL)或者诸如红外线、无线电和微波之类的无线技术从网站、服务器或者其他远程源传输的，那么同轴电缆、光纤光缆、双绞线、DSL或者诸如红外线、无线和微波之类的无线技术包括在所属介质的定影中。如本发明所使用的，盘(Disk) 和碟(disc)包括压缩光碟(CD)、激光碟、光碟、数字通用光碟(DVD)、软盘和蓝光光碟，其中盘通常磁性的复制数据，而碟则用激光来光学的复制数据。上面的组合也应当包括在计算机可读存储介质的保护范围之内。
总之，以上所述仅为本发明技术方案的较佳实施例而已，并非用于限定本发明的保护范围。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (15)

  1. 一种返修概率预测方法，其特征在于，所述方法包括：
    获取终端集合中每个终端的每种故障类型的故障率；
    确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
    获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
    获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
    获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
  2. 如权利要求1所述的方法，其特征在于，所述获取终端集合中每个终端的每种故障类型的故障率，包括：
    接收终端上传的故障参数，所述故障参数至少包括一种故障类型以及每种故障类型的故障次数和终端使用时长；
    根据所述故障参数，计算每个终端的每种故障类型的故障率，所述每个终端的每种故障类型的故障率为所述每种故障类型的故障次数与所述终端使用时长的比值。
  3. 如权利要求1或2所述的方法，其特征在于，所述确定所述每个终端的所述每种故障类型的故障率对应的退机概率，包括：
    根据所述每个终端的每种故障类型的故障率，通过查询每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的每种故障类型的故障率对应的退机概率。
  4. 一种故障参数上传方法，应用于具有通信功能的终端，其特征在于，所述方法包括：
    当所述终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数终端；
    向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故 障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
  5. 一种返修概率预测装置，其特征在于，所述装置包括：
    第一获取单元，用于获取终端集合中每个终端的每种故障类型的故障率；
    确定单元，用于确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
    所述第一获取单元还用于获取所述每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
    所述第一获取单元还用于获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
    所述第一获取单元还用于获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
  6. 如权利要求5所述的装置，其特征在于，所述第一获取单元包括：
    接收单元，用于接收终端上传的故障参数，所述故障参数至少包括一种故障类型以及每种故障类型的故障次数和终端使用时长；
    计算单元，用于根据所述故障参数，计算每个终端的每种故障类型的故障率，所述每个终端的每种故障类型的故障率为所述每种故障类型的故障次数与所述终端使用时长的比值。
  7. 如权利要求5或6所述的装置，其特征在于，所述确定单元具体用于：
    根据所述每个终端的每种故障类型的故障率，通过查询每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的每种故障类型的故障率对应的退机概率。
  8. 一种故障参数上传装置，其特征在于，所述装置包括：
    记录单元，用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数；
    上传单元，用于向服务器上传故障参数，所述故障参数至少包括一种故障 类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数预测终端集合的返修概率。
  9. 一种服务器，其特征在于，所述服务器包括：处理器，存储器；
    其中，
    所述存储器用于存储指令和数据，所述数据包括每种故障类型的故障率与退机概率的对应关系；
    所述处理器用于执行所述指令以实现：
    获取终端集合中每个终端的每种故障类型的故障率；
    确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
    获取所述每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
    获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
    获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
  10. 如权利要求9所述的服务器，其特征在于，所述服务器还包括接收器；
    所述接收器用于接收终端上传的故障参数，所述故障参数至少包括一种故障类型以及每种故障类型的故障次数和终端使用时长。
  11. 如权利要求10所述的服务器，其特征在于，
    所述处理器还用于根据所述故障参数，计算每个终端的每种故障类型的故障率，所述每个终端的每种故障类型的故障率为所述每种故障类型的故障次数与所述终端使用时长的比值。
  12. 如权利要求9-11任意一项所述的服务器，其特征在于，所述处理器具体用于：
    根据所述每个终端的每种故障类型的故障率，通过查询存储在所述存储器中的所述每种故障类型的故障率与退机概率的对应关系，确定所述每个终端的 每种故障类型的故障率对应的退机概率。
  13. 一种终端，其特征在于，所述终端包括处理器和发送器；
    所述处理器用于当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数；
    所述发送器用于向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数，预测终端集合的返修概率。
  14. 一种存储一个或多个程序的非易失性计算机可读存储介质，所述一个或多个程序包括指令，所述非易失性计算机可读存储介质应用于具有处理器的服务器，所述指令当被所述服务器执行时使所述服务器执行以下事件：
    获取终端集合中每个终端的每种故障类型的故障率；
    确定所述每个终端的所述每种故障类型的故障率对应的退机概率；
    获取每个终端的返修概率，所述每个终端的返修概率为所述每个终端的所述每种故障类型的故障率对应的退机概率之和；
    获取所述终端集合的返修个数，所述终端集合的返修个数为所述终端集合中每个终端的返修概率之和；
    获取所述终端集合的返修概率，所述终端集合的返修概率为所述终端集合的返修个数与所述终端集合的终端总个数的比值。
  15. 一种存储一个或多个程序的非易失性计算机可读存储介质，所述一个或多个程序包括指令，所述非易失性计算机可读存储介质应用于具有处理器的终端，所述指令当被所述终端执行时使所述终端执行以下事件：
    当终端发生故障时，记录所发生的至少一种故障类型以及所发生的故障类型的故障次数终端；
    向服务器上传故障参数，所述故障参数至少包括一种故障类型以及所述故障类型的故障次数和终端使用时长，以使所述服务器根据所述故障参数预测终端集合的返修概率。
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