Information processing apparatus, method, program, and information processing system

Abstract

To provide an information processing apparatus for efficiently dealing with a device when a defect phenomenon occurs in the device.SOLUTION: An information processing apparatus includes: an acquisition section for acquiring each value of a plurality of variables related to a device; a deviation degree calculation section for calculating the degree of deviation between each value and each reference value; and a weighting section for weighting the calculated degree of the deviation by using the correlation ratio between a defect phenomenon of the device, a dealing place at the time of occurrence of the defect phenomenon, and the variables.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an information processing device, a method, a program, and an information processing system. [Background technology]

[0002] Conventionally, when a malfunction occurs in a device such as an image forming apparatus, a customer engineer or the like takes measures such as repairing the device at the site where the device is installed. Summary of the Invention [Problem to be solved by the invention]

[0003] However, when a malfunction occurs in a device, it is not easy to determine the cause (i.e., what should be fixed), making it difficult to efficiently fix the device.

[0004] Therefore, an object of the present invention is to efficiently treat a device when a malfunction occurs in the device. [Means for solving the problem]

[0005] An information processing device according to one embodiment of the present invention includes an acquisition unit that acquires the values of multiple variables related to equipment, a deviation calculation unit that calculates the deviation between each of the values and each reference value, and a weighting unit that weights the calculated deviation using a correlation ratio between the variables and a malfunction phenomenon of the equipment and the location of treatment when the malfunction phenomenon occurs. [Effects of the Invention]

[0006] According to the present invention, when a malfunction occurs in a device, the device can be efficiently treated. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a diagram illustrating an overall configuration according to an embodiment of the present invention. [Figure 2] This is a hardware configuration diagram of a server according to an embodiment of the present invention. [Figure 3] This is a hardware configuration diagram of an image forming apparatus (MFP) according to an embodiment of the present invention. [Figure 4] This is a functional block diagram of a server according to an embodiment of the present invention. [Figure 5] This is a diagram for explaining the correlation ratio according to an embodiment of the present invention. [Figure 6] This is a diagram for explaining the calculation of the degree of deviation according to an embodiment of the present invention. [Figure 7] This is an example of weighting the degree of deviation between the value of a variable related to a device and a reference value according to an embodiment of the present invention using the correlation ratio. [Figure 8] This is an example of weighting the degree of deviation between the value of a variable related to a device and a reference value according to an embodiment of the present invention using the correlation ratio. [Figure 9] This is an example of weighting the degree of deviation between the value of a variable related to a device and a reference value according to an embodiment of the present invention using the correlation ratio. [Figure 10] This is a flowchart showing the calculation process of the correlation ratio according to an embodiment of the present invention. [Figure 11] This is a flowchart showing the generation process of the reference value according to an embodiment of the present invention. [Figure 12] This is a flowchart showing the output process of the priority order of the treatment location according to an embodiment of the present invention.

Embodiments for Carrying Out the Invention

[0008] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0009] <Explanation of Terms> · The "variable related to the device" is any variable that can be collected by the device. For example, the variable related to the device includes a variable representing the state of the device, a variable representing the operation of the device, a variable set in the device, and the like. · The "malfunction phenomenon" refers to the state of malfunctions (also referred to as abnormalities or failures) occurring in the device (i.e., what kind of malfunctions are occurring). · The "treatment location" refers to the location to be treated when a malfunction phenomenon occurs in the device (i.e., which part of the device should be treated). Note that treatment includes any arbitrary actions such as repair (e.g., replacement of parts, change of settings), etc.

[0010] <Overall Configuration> Figure 1 is an overall configuration diagram according to an embodiment of the present invention. The information processing system 1 can include a server 10, a device (e.g., an image forming apparatus) 20, and a terminal 30.

[0011] <<Server>> The server 10 (an example of an information processing apparatus) can transmit and receive data to and from one or more devices (e.g., an image forming apparatus) 20 and one or more terminals 30 via an arbitrary network. The server 10 is one or more computers.

[0012] Specifically, the server 10 acquires each value of a plurality of variables related to a device 20 such as an image forming apparatus, calculates the degree of deviation between each value and each reference value, and weights the calculated degree of deviation using the correlation ratio between the malfunction phenomenon of the device and the treatment location at the time of occurrence of the malfunction phenomenon, and the variable. For example, the server 10 can output the priority order of each treatment location to the terminal 30 or the device 20 (it may also be another server). For example, the server 10 can output the necessity of treatment for each treatment location to the terminal 30 or the device 20 (it may also be another server).

[0013] The device group described in the embodiments merely represents one of the multiple computing environments for implementing the embodiments disclosed in this specification. In one embodiment, server 10 includes a plurality of computing devices such as a server cluster. The plurality of computing devices are configured to communicate with each other via any type of communication link including a network or shared memory, and implement the processes disclosed in this specification.

[0014] <<Device>> Device 20 is not limited to an image forming apparatus, and may be, for example, an output device such as a PJ (Projector), an IWB (Interactive White Board), a digital signage, a HUD (Head Up Display) device, an industrial machine, an imaging device, a sound collection device, a medical device, a network home appliance, a connected car, a notebook PC (Personal Computer), a mobile phone, a smartphone, a tablet terminal, a game machine, a PDA (Personal Digital Assistant), a digital camera, a wearable PC, or a desktop PC.

[0015] <<Terminal>> Terminal 30 is a terminal operated by a customer engineer or the like who performs treatments such as repair of device 20 such as an image forming apparatus. For example, terminal 30 is a personal computer, a tablet, a smartphone, or the like.

[0016] Specifically, terminal 30 acquires and displays from server 10 the result of weighting (for example, the priority order of each treatment location or the necessity of treatment at each treatment location) using the correlation ratio between the deviation degree of each value of a plurality of variables related to device 20 such as an image forming apparatus and each reference value, the malfunction phenomenon of the device, the treatment location at the time of occurrence of the malfunction phenomenon, and the variable.

[0017] <Hardware Configuration> 2 is a hardware configuration diagram of the server 10 according to an embodiment of the present invention. The same applies to the terminal 30.

[0018] As shown in FIG. 2, the server 10 is constructed by a computer, and as shown in FIG. 2, it is equipped with a CPU 1001, a ROM 1002, a RAM 1003, a HD 1004, an HDD (Hard Disk Drive) controller 1005, a display 1006, an external device connection I / F (Interface) 1007, a network I / F 1008, a data bus 1009, a keyboard 1010, a pointing device 1011, a DVD-RW (Digital Versatile Disk Rewritable) drive 1013, and a media I / F 1015.

[0019] Of these, the CPU 1001 controls the overall operation of the server 10. The ROM 1002 stores programs used to drive the CPU 1001, such as the IPL. The RAM 1003 is used as a work area for the CPU 1001. The HD 1004 stores various data, such as programs. The HDD controller 1005 controls the reading and writing of various data from and to the HD 1004 under the control of the CPU 1001. The display 1006 displays various information, such as a cursor, menu, window, text, or image. The external device connection I / F 1007 is an interface for connecting various external devices. In this case, the external devices are, for example, USB (Universal Serial Bus) memories, printers, etc. The network I / F 1008 is an interface for data communication using a communication network. The bus line 1009 is an address bus, data bus, etc. for electrically connecting the components, such as the CPU 1001, shown in FIG. 2.

[0020] The keyboard 1010 is a type of input means having a plurality of keys for inputting characters, numerical values, various instructions, and the like. The pointing device 1011 is a type of input means for selecting and executing various instructions, selecting a processing target, moving a cursor, and the like. The DVD-RW drive 1013 controls reading or writing of various data with respect to the DVD-RW 1012 as an example of a removable recording medium. Note that it is not limited to DVD-RW, and it may be DVD-R or the like. The media I / F 1015 controls reading or writing (storage) of data with respect to the recording medium 1014 such as a flash memory.

[0021] FIG. 3 is a hardware configuration diagram of an image forming apparatus (MFP) 20 according to an embodiment of the present invention.

[0022] As shown in FIG. 3, the MFP (Multifunction Peripheral / Product / Printer) 20 includes a controller 2010, a short-range communication circuit 2020, an engine control unit 2030, an operation panel 2040, and a network I / F 2050.

[0023] Among these, the controller 2010 has a CPU 2001 which is a main part of a computer, a system memory (MEM-P) 2002, a north bridge (NB) 2003, a south bridge (SB) 2004, an ASIC (Application Specific Integrated Circuit) 2005, a local memory (MEM-C) 2006 which is a storage unit, an HDD controller 2007, and an HD 2008 which is a storage unit, and is configured to connect between the NB 2003 and the ASIC 2005 by an AGP (Accelerated Graphics Port) bus 2021.

[0024] Among these, the CPU 2001 is a control unit that performs overall control of the MFP 20. The NB 2003 is a bridge for connecting the CPU 2001 to the MEM-P 2002, the SB 2004, and the AGP bus 2021, and has a memory controller that controls reading and writing to the MEM-P 2002, and a PCI (Peripheral Component Interconnect) master and an AGP target.

[0025] The MEM-P 2002 consists of a ROM 2002a which is a memory for storing programs and data for realizing each function of the controller 2010, and a RAM 2002b which is used as a memory for developing programs and data, and for drawing during memory printing. Note that the programs stored in the RAM 2002b may be provided by being recorded on a computer-readable recording medium such as a CD-ROM, a CD-R, or a DVD in an installable or executable file format.

[0026] The SB 2004 is a bridge for connecting the NB 2003 to PCI devices and peripheral devices. The ASIC 2005 is an IC (Integrated Circuit) for image processing applications having hardware elements for image processing, and has the role of a bridge for connecting the AGP bus 2021, the PCI bus 2022, the HDD 2007, and the MEM-C 2006 respectively. This ASIC 2005 includes a PCI target and an AGP master, an arbiter (ARB) forming the core of the ASIC 2005, a memory controller for controlling the MEM-C 2006, a plurality of DMACs (Direct Memory Access Controllers) for performing operations such as rotation of image data by means of hardware logic, etc., and a PCI unit for performing data transfer via the PCI bus 2022 between the scanner unit 2031 and the printer unit 2032. Note that a USB (Universal Serial Bus) interface or an IEEE1394 (Institute of Electrical and Electronics Engineers 1394) interface may be connected to the ASIC 2005.

[0027] MEM-C2006 is the local memory used as a copy image buffer and a code buffer. HD2008 is the storage for accumulating image data, font data used at the time of printing, and forms. HD2008 controls the reading or writing of data to HD2008 according to the control of CPU2001. The AGP bus 2021 is a bus interface for a graphics accelerator card proposed to speed up graphic processing. By directly accessing MEM-P2002 with high throughput, the graphics accelerator card can be made faster.

[0028] In addition, the short-distance communication circuit 2020 is provided with a short-distance communication circuit 2020a. The short-distance communication circuit 2020 is a communication circuit such as NFC or Bluetooth.

[0029] Furthermore, the engine control unit 2030 is composed of a scanner unit 2031 and a printer unit 2032. Also, the operation panel 2040 includes a panel display unit 2040a such as a touch panel that displays current setting values, selection screens, etc. and receives inputs from the operator, and an operation panel 2040b composed of a numeric keypad that receives setting values of conditions related to image formation such as density setting conditions and a start key that receives a copy start instruction. The controller 2010 controls the entire MFP20, for example, controls drawing, communication, inputs from the operation panel 2040, etc. The scanner unit 2031 or the printer unit 2032 includes an image processing part such as error diffusion or gamma conversion.

[0030] Note that the MFP 20 can sequentially switch and select the document box function, copy function, printer function, and facsimile function by operating the application switching key on the operation panel 2040. When the document box function is selected, the document box mode is entered; when the copy function is selected, the copy mode is entered; when the printer function is selected, the printer mode is entered; and when the facsimile mode is selected, the facsimile mode is entered.

[0031] Also, the network I / F 2050 is an interface for data communication using a communication network. The short-range communication circuit 2020 and the network I / F 2050 are electrically connected to the ASIC 2005 via the PCI bus 2022.

[0032] <Functional Configuration> FIG. 4 is a functional block diagram of the server 10 according to an embodiment of the present invention.

[0033] The server 10 can include an acquisition unit 101, a divergence calculation unit 102, a weighting unit 103, a normalization processing unit 104, an output unit 105, a correlation ratio calculation unit 106, a correlation ratio storage unit 107, a reference value generation unit 108, and a reference value storage unit 109. Note that the terminal 30 may include at least a part of these functions. The server 10 can function as the acquisition unit 101, the divergence calculation unit 102, the weighting unit 103, the normalization processing unit 104, the output unit 105, the correlation ratio calculation unit 106, and the reference value generation unit 108 by executing a program.

[0034] The acquisition unit 101 acquires each value of a plurality of variables related to the device. For example, the acquisition unit 101 acquires each value of a plurality of variables related to the device (specifically, the device in which a malfunction occurs and some treatment should be taken) from the device.

[0035] The deviation calculation unit 102 calculates the deviation between each value of a plurality of variables related to the device acquired by the acquisition unit 101 and each reference value of the variable (for example, the value of the variable related to the device when the device is normal). For example, the deviation calculation unit 102 can represent the deviation in points, where it is 0 points when the value of the variable related to the device acquired by the acquisition unit 101 is a normal value, 0.5 points when it is a quasi-normal value, and 1 point when it is an abnormal value.

[0036] The weighting unit 103 weights the deviation calculated by the deviation calculation unit 102 using the correlation ratio between the malfunction phenomenon of the device and the location of treatment when the malfunction phenomenon occurs, and the variable related to the device.

[0037] The normalization processing unit 104 normalizes the deviation weighted by the weighting unit 103.

[0038] The output unit 105 outputs various information to the terminal 30 or the device 20 (it may also be another server).

[0039] [Output of the priority order of each treatment location] For example, the output unit 105 outputs the priority order of each treatment location (for example, the greater the deviation, the higher the priority order). For example, the output unit 105 outputs the priority order of each treatment location using the normalized deviation.

[0040] [Output of the necessity of treatment at each treatment location] For example, the output unit 105 outputs the necessity of treatment at each treatment location. For example, the output unit 105 compares the weighted deviation (for example, the total value of the deviations at all treatment locations) with a threshold value and outputs the necessity of treatment at each treatment location. The threshold value is determined based on the weighted deviation when the device is normal and the weighted deviation when a malfunction has occurred in the device, using the maintenance history of a plurality of devices.

[0041] The correlation ratio calculation unit 106 calculates the correlation ratio between the malfunction phenomenon of the device and the location of treatment when the malfunction phenomenon occurs, and the variable related to the device.

[0042] The correlation ratio storage unit 107 stores the correlation ratio calculated by the correlation ratio calculation unit 106.

[0043] The reference value generating unit 108 generates reference values of variables related to the device.

[0044] The reference value storage unit 109 stores the reference value generated by the reference value generation unit .

[0045] [Problem and solution location] Here, we will explain the malfunction phenomenon and the treatment location. The malfunction phenomenon of the device and the treatment location when the malfunction phenomenon occurs may be any combination. For example, it may be a combination of malfunction phenomenon: A1 and treatment location: B1, or a combination of malfunction phenomenon: A1 and treatment location: B2 (note that B1 and B2 are different treatment locations), or a combination of malfunction phenomenon: A2 (note that A1 and A2 are different malfunction phenomena) and treatment location: B1.

[0046] [Device-related variables] Here, we will explain the variables related to the equipment. It is assumed that multiple variables related to the equipment are defined for each combination of the malfunction phenomenon and the treatment location. Note that the variables related to the equipment may be processed data collected by the equipment (for example, changes over the past x days, etc.).

[0047] [Correlation ratio] 5 is a diagram illustrating a correlation ratio according to one embodiment of the present invention. The correlation ratio storage unit 107 stores "variables related to equipment ("explanatory variable content" in FIG. 5)," "fault phenomena of equipment and treatment locations at the time of occurrence of said fault phenomena ("objective variable content (phenomenon name_treatment location)" in FIG. 5), and "correlation ratios between said equipment variables and said fault phenomena and treatment locations ("correlation ratio" in FIG. 5)." The correlation ratio indicates the degree of correlation between two variables when one is a quantitative variable (variable related to equipment) and the other is a nominal scale (fault phenomenon and treatment location). The correlation ratio value is between 0 and 1, with a larger value indicating a stronger correlation.

[0048] [Reference value] The reference value is a value that serves as a reference for a variable related to the device, determined for each variable related to the device (for example, the value of the variable related to the device when the device is normal). Hereinafter, three examples of calculating the degree of deviation (degree of deviation) between the value of the variable related to the device and the reference value will be described.

[0049] [Example 1 of calculating the degree of deviation] FIG. 6 is a diagram for explaining the calculation of the degree of deviation according to an embodiment of the present invention. The degree of deviation may be calculated based on whether the value of the variable related to the device is a normal value, a sub-normal value, or an abnormal value. For example, when the value of the variable related to the device is a normal value, it is 0 points, when it is a sub-normal value, it is 0.5 points, and when it is an abnormal value, it is 1 point, and the degree of deviation is represented by points. (1) The normal value is in the range from the first quartile number to the third quartile number of the values of the variable related to the device of a plurality of normal devices. (2) The sub-normal value is in the range from a value that is k times the quartile width smaller than the first quartile number to the first quartile number, and in the range from the third quartile number to a value that is k times the quartile width larger than the third quartile number (where k is an arbitrary coefficient). (3) The abnormal value is other than the normal value and other than the sub-normal value.

[0050] [Example 2 of calculating the degree of deviation] Similar to Example 1, the degree of deviation may be calculated based on whether the value of the variable related to the device is a normal value, a sub-normal value, or an abnormal value. For example, when the value of the variable related to the device is a normal value, it is 0 points, when it is a sub-normal value, it is 0.5 points, and when it is an abnormal value, it is 1 point, and the degree of deviation is represented by points. (1) The normal value is the average value of the values of the variable related to the device of a plurality of normal devices ± mσ (where m is an arbitrary coefficient and σ is the standard deviation). (2) The sub-normal value is the average value ± nσ (where n is an arbitrary coefficient (however, n > m) and σ is the standard deviation). (3) The abnormal value is other than the normal value and other than the sub-normal value.

[0051] [Example 3 of calculating the degree of deviation] The degree of deviation may be calculated based on the deviation rate of the value of a variable related to the device from a predetermined reference value. For example, the degree of deviation is represented by a score corresponding to the deviation rate.

[0052] Hereinafter, with reference to FIGS. 7 to 9, an example of weighting the degree of deviation between the value of a variable related to the device and the reference value using a correlation ratio will be described. The "explanatory variable" in FIGS. 7 to 9 indicates a variable related to the device. The "correlation ratio" in FIGS. 7 to 9 indicates the correlation ratio between the variable related to the device, the malfunction phenomenon, and the treatment location. The "temporary point conversion from reference value deviation" in FIGS. 7 to 9 indicates the degree of deviation (temporary score) between the value of the variable related to the device and the reference value. The "score after weighting" in FIGS. 7 to 9 indicates the degree of deviation after weighting (score after weighting).

[0053] FIG. 7 is an example of weighting the degree of deviation between the value of a variable related to the device and the reference value using a correlation ratio according to an embodiment of the present invention. FIG. 7 shows a case where the malfunction phenomenon is "streak (sub-scanning)" and the treatment location is the "intermediate transfer unit". When the variable related to the device is "detected paper size", the correlation ratio is 0.38, and it is assumed that the degree of deviation (the degree of deviation expressed as a score) between the value of the variable related to the device (that is, the value of "detected paper size") and the reference value is 2. Then, from the degree of deviation "2" and the correlation ratio "0.38", a weighted value of 2.8 is calculated (note that it is obtained by multiplying the degree of deviation by "1 + correlation ratio"). The same applies when the variables related to the device are "paper type", "set paper thickness", "paper remaining amount", and "paper feed line speed". The total value of the weighted values of all variables is used (in the example of FIG. 7, the larger the total value, the higher the possibility that the intermediate transfer unit should be the treatment location when the malfunction phenomenon (streak (sub-scanning)) occurs).

[0054] FIG. 8 is an example of weighting the degree of deviation between the value of a variable related to a device according to an embodiment of the present invention and a reference value using a correlation ratio. FIG. 8 shows a case where the defect phenomenon is "streak (sub-scanning)" and the treatment location is the "photoconductor unit section". When the variable related to the device is "AC power supply voltage", the correlation ratio is 0.00, and it is assumed that the degree of deviation (the degree of deviation expressed as a score) between the value of the variable related to the device (that is, the value of "AC power supply voltage") and the reference value is 0. Then, from the deviation degree "0" and the correlation ratio "0.00", 0 which is the weighted value is calculated (note that the deviation degree is multiplied by "1 + correlation ratio"). The same applies when the variables related to the device are "printing quantity_K", "printing quantity_C", "printing quantity_M", and "printing quantity_Y". The total value of the weighted values of all variables is used ((in the example of FIG. 8, the larger the total value, the higher the possibility that the photoconductor unit section is the location to be treated when the defect phenomenon (streak (sub-scanning)) occurs)).

[0055] FIG. 9 is an example of weighting the degree of deviation between the value of a variable related to a device according to an embodiment of the present invention and a reference value using a correlation ratio. FIG. 9 shows a case where the defect phenomenon is "streak (sub-scanning)" and the treatment location is the "intermediate transfer cleaning section". When the variable related to the device is "printing quantity (pressure roller)", the correlation ratio is 0.53, and it is assumed that the degree of deviation (the degree of deviation expressed as a score) between the value of the variable related to the device (that is, the value of "printing quantity (pressure roller)") and the reference value is 2. Then, from the deviation degree "2" and the correlation ratio "0.53", 3.1 which is the weighted value is calculated (note that the deviation degree is multiplied by "1 + correlation ratio"). The same applies when the variables related to the device are "travel distance (developing unit) BK", "travel distance (developing unit) C", "travel distance (developing unit) M", and "travel distance (developing unit) Y". The total value of the weighted values of all variables is used ((in the example of FIG. 8, the larger the total value, the higher the possibility that the intermediate transfer cleaning section is the location to be treated when the defect phenomenon (streak (sub-scanning)) occurs)).

[0056] [Standardization] When there are multiple candidate treatment locations for a single defect phenomenon, a standardization process is performed so that they can be compared using the same criteria. For example, when the defect phenomenon (streaks (sub-scanning)) shown in FIGS. 7 to 9 occurs, a standardization process is performed to compare three candidate treatment locations (i.e., the intermediate transfer unit in FIG. 7, the photoreceptor unit in FIG. 8, and the intermediate transfer cleaning unit in FIG. 9) using the same criteria.

[0057] For example, in the intermediate transfer unit of FIG. 7, assume that the average value of the total values of the weighted values in a plurality of devices (e.g., all devices) (in the example of FIG. 7, the total value of the weighted values of "detected paper size", "paper type", "set paper thickness", "remaining paper amount", and "paper feed line speed") is 5, and the standard deviation is 2. Also, in the photoreceptor unit of FIG. 8, assume that the average value of the total values of the weighted values in a plurality of devices (e.g., all devices) (in the example of FIG. 8, the total value of the weighted values of "AC power supply voltage", "number of printed sheets_K", "number of printed sheets_C", "number of printed sheets_M", and "number of printed sheets_Y") is 10, and the standard deviation is 3. Also, in the intermediate transfer cleaning unit of FIG. 9, assume that the average value of the total values of the weighted values in a plurality of devices (e.g., all devices) (in the example of FIG. 9, the total value of the weighted values of "number of printed sheets (pressure roller)", "travel distance (developing unit) BK", "travel distance (developing unit) C", "travel distance (developing unit) M", and "travel distance (developing unit) Y") is 7, and the standard deviation is 2. Then, after standardization, the values for FIG. 7 are 0.67, for FIG. 8 are -0.29, and for FIG. 9 are 0.26. The priority order of the treatment locations is that FIG. 7 (i.e., the intermediate transfer unit) is the highest, followed by FIG. 9 (i.e., the intermediate transfer cleaning unit), and then FIG. 8 (i.e., the photoreceptor unit). Note that the average value and standard deviation of the day may be used (i.e., updated), or the pre-determined average value and standard deviation may be used.

[0058] <Method> Figure 10 is a flowchart showing the correlation ratio calculation process according to an embodiment of the present invention. The correlation ratio calculation unit 106 calculates in advance the correlation ratio between each variable related to the device, the variable related to the device, the malfunction phenomenon, and the treatment location, from the past maintenance history and the values of the variables related to the device at that time.

[0059] In step 101 (S101), the correlation ratio calculation unit 106 acquires the target variable. Specifically, the correlation ratio calculation unit 106 acquires the maintenance history of a certain past period as the target variable, and extracts the combination of the target malfunction phenomenon and the treatment location at the time of occurrence of the malfunction phenomenon (that is, the location where the malfunction phenomenon was actually treated at the time of occurrence of the malfunction phenomenon) (for example, set the flag = 1). Further, the correlation ratio calculation unit 106 identifies the devices that were normal during the same period (that is, the same period as the certain period in which the malfunction phenomenon was extracted) (for example, set the flag = 0).

[0060] In step 102 (S102), the correlation ratio calculation unit 106 acquires the explanatory variable. Specifically, the correlation ratio calculation unit 106 acquires, as the explanatory variable, the values of the variables related to the device on the same day as the maintenance date selected in the target variable (specifically, the values of the variables related to the devices where the malfunction phenomenon occurred (flag = 1) and the devices that were normal (flag = 0)). Note that the correlation ratio calculation unit 106 may use, as the explanatory variable, the difference from m days before the value of the variable related to the device on the maintenance date selected in the target variable, the difference from before printing n sheets, etc.

[0061] In step 103 (S103), the correlation ratio calculation unit 106 calculates the correlation ratio between the target variable (nominal scale) acquired in S101 and the explanatory variable (quantitative variable) acquired in S102.

[0062] Figure 11 is a flowchart showing the reference value generation process according to an embodiment of the present invention.

[0063] In step 201 (S201), the reference value generation unit 108 acquires the values of the variables related to normal devices (that is, devices in which no malfunction event has occurred).

[0064] In step 202 (S202), the reference value generation unit 108 determines a normal value for each variable related to the device. For example, the reference value generation unit 108 determines, as the normal value, the range from the first quartile number to the third quartile number of the values of the variables related to the device for a plurality of normal devices.

[0065] In step 203 (S203), the reference value generation unit 108 determines a quasi-normal value for the variable related to the device for which the normal value was determined in S201. For example, the reference value generation unit 108 determines, as the quasi-normal value, the range from a value that is quartile width × k smaller than the first quartile number to the first quartile number, and the range from the third quartile number to a value that is quartile width × k larger than the third quartile number (where k is an arbitrary coefficient).

[0066] In step 204 (S204), the reference value generation unit 108 determines, as the abnormal value, the range that is outside the normal value in S202 and also outside the quasi-normal value in S203.

[0067] FIG. 12 is a flowchart showing the output process of the priority order of the treatment locations according to an embodiment of the present invention.

[0068] In step 301 (S301), the deviation calculation unit 102 calculates the deviation between each value of a plurality of variables related to the device and each reference value of the variable (for example, represents the deviation as a score based on whether each value of the variable related to the device is a normal value, a quasi-normal value, or an abnormal value).

[0069] In step 302 (S302), the weighting unit 103 weights the deviation calculated in S301 (for example, the deviation represented as a score) using a correlation ratio (specifically, the correlation ratio between the malfunction phenomenon of the device and the treatment location at the time of occurrence of the malfunction phenomenon, and the variable related to the device).

[0070] In step 303 (S303), the normalization processing unit 104 normalizes the value weighted in S302.

[0071] In step 304 (S304), the output unit 105 outputs the value standardized in S303. For example, the output unit 105 outputs the priority of each treatment location. Note that the output unit 105 may acquire and display the necessity of treatment at each treatment location after S302.

[0072] <Effect> As described above, in one embodiment of the present invention, when a malfunction occurs in a device such as an image forming apparatus, a customer engineer or the like can grasp the priority of the treatment location where the device should be repaired or the necessity of repair or the like at each treatment location of the device. Therefore, the time for performing treatments such as on-site repair can be shortened.

[0073] Each function of the embodiment described above can be realized by one or a plurality of processing circuits. Here, the "processing circuit" in this specification refers to a processor programmed to execute each function by software like a processor implemented by an electronic circuit, an ASIC (Application Specific Integrated Circuit) designed to execute each function described above, a DSP (digital signal processor), an FPGA (field programmable gate array), and devices such as conventional circuit modules.

Description of Reference Numerals

[0074] 1 Information processing system 10 Server 20 Device (image forming apparatus) 30 Terminal 101 Acquisition unit 102 Deviation degree calculation unit 103 Weighting unit 104 Standardization processing unit 105 Output unit 106 Correlation ratio calculation unit 107 Correlation ratio storage unit 108 Reference value generation unit 109 Reference value storage unit

Prior Art Documents

Patent Document

[0075]

Patent Document 1

Claims

1. An acquisition unit that acquires each value of a plurality of variables related to a machine; A deviation degree calculation unit that calculates the degree of deviation between each of the values and each reference value; A weighting unit that weights the calculated degree of deviation using the correlation ratio between the malfunction phenomenon of the machine, the location of treatment when the malfunction phenomenon occurs, and the variable; An information processing apparatus comprising the above.

2. An output unit that outputs the priority order of each treatment location The information processing apparatus according to claim 1, further comprising the above.

3. An output unit that outputs the necessity of treatment for each treatment location The information processing apparatus according to claim 1, further comprising the above.

4. The information processing apparatus according to claim 1, wherein the machine is an image forming apparatus.

5. The degree of deviation is calculated based on whether each of the values is a normal value, a quasi-normal value, or an abnormal value. The normal value is in the range from the first quartile number to the third quartile number of the values of the variables related to the machine of a plurality of normal machines. The quasi-normal value is in the range from a value that is smaller than the first quartile number by a quartile width × k to the first quartile number, and in the range from the third quartile number to a value that is larger than the third quartile number by a quartile width × k (where k is an arbitrary coefficient). The abnormal value is outside the normal value and the quasi-normal value. The information processing apparatus according to claim 1. The normal value is in the range from the first quartile number to the third quartile number of the values of the variables related to the machine of a plurality of normal machines. The quasi-normal value is in the range from a value that is smaller than the first quartile number by a quartile width × k to the first quartile number, and in the range from the third quartile number to a value that is larger than the third quartile number by a quartile width × k (where k is an arbitrary coefficient). The abnormal value is outside the normal value and the quasi-normal value. The information processing apparatus according to claim 1.

6. The degree of deviation is calculated based on whether each of the values is a normal value, a quasi-normal value, or an abnormal value. The normal value is the average value ± mσ of the values of the variables related to the machine of a plurality of normal machines (where m is an arbitrary coefficient and σ is the standard deviation). The quasi-normal value is the average value ± nσ (where n is an arbitrary coefficient (however, n > m) and σ is the standard deviation). The abnormal value is outside the normal value and the quasi-normal value. The information processing apparatus according to claim 1. The normal value is the average value ± mσ of the values of the variables related to the machine of a plurality of normal machines (where m is an arbitrary coefficient and σ is the standard deviation). The quasi-normal value is the average value ± nσ (where n is an arbitrary coefficient (however, n > m) and σ is the standard deviation). The abnormal value is outside the normal value and the quasi-normal value. The information processing apparatus according to claim 1.

7. Further comprising a normalization processing unit that normalizes the weighted degree of deviation using the average value and standard deviation of the day or the average value and standard deviation determined in advance. The output unit outputs the priority order of each treatment location using the normalized degree of deviation. The information processing apparatus according to claim 2. The output unit outputs the priority order of each treatment location using the normalized degree of deviation. The information processing apparatus according to claim 2.

8. The output unit compares the weighted degree of deviation with a threshold value and outputs the necessity of treatment for each treatment location. The information processing apparatus according to claim 3, wherein the threshold value is determined based on a weighted degree of deviation when the device is normal and a weighted degree of deviation when a malfunction occurs in the device, using the maintenance history of a plurality of devices.

9. A method executed by an information processing apparatus, comprising: acquiring each value of a plurality of variables related to a device; calculating a degree of deviation between each value and each reference value; weighting the calculated degree of deviation using a correlation ratio between a malfunction phenomenon of the device and a location for treatment when the malfunction phenomenon occurs, and the variable; A method including the above steps.

10. A program for causing an information processing apparatus to function as: an acquisition unit that acquires each value of a plurality of variables related to a device; a degree-of-deviation calculation unit that calculates a degree of deviation between each value and each reference value; a weighting unit that weights the calculated degree of deviation using a correlation ratio between a malfunction phenomenon of the device and a location for treatment when the malfunction phenomenon occurs, and the variable;

11. An information processing system including a server, wherein: the server includes: an acquisition unit that acquires each value of a plurality of variables related to a device; a calculation unit that calculates a degree of deviation between each value and each reference value; a weighting unit that weights the calculated degree of deviation using a correlation ratio between a malfunction phenomenon of the device and a location for treatment when the malfunction phenomenon occurs, and the variable; an output unit that outputs a priority order of each treatment location or a necessity of treatment at each treatment location to a terminal or the device; and the terminal or the device acquires and displays the priority order of each treatment location or the necessity of treatment at each treatment location output by the server.

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