Image forming apparatus, information processing method, and program

Abstract

To perform failure prediction with sufficient prediction accuracy even when there is a large variation in data due to the difference in paper thickness.SOLUTION: An image forming apparatus comprises: a sheet detection unit that detects a sheet conveyed by a conveying mechanism at a predetermined position on a conveyance path; a conveyance time information acquisition unit that acquires conveyance time information indicating the conveyance time required for conveying the sheet in a predetermined section on the conveyance path, according to a result of detection performed by the sheet detection unit; a paper thickness detection unit that detects paper thickness information indicating the thickness of the sheet; a detection information storage unit that stores the conveyance time information for every thickness of the sheet; and a prediction unit that predicts the time when the conveying mechanism fails.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an image forming apparatus, an information processing method, and a program. [Background technology]

[0002] 2. Description of the Related Art In recent years, in multifunction machines that can be used as printers, facsimiles, scanners, and copiers, techniques have been used to recognize deterioration over time of mechanisms that transport paper for image formation output, and to predict failures.

[0003] Patent document 1 discloses an image forming device that includes a paper detection unit that detects transported paper at a predetermined position on the transport path, a transport time information acquisition unit that acquires transport time information, which is information about the transport time required to transport the paper in a predetermined section on the transport path, based on the detection result by the paper detection unit, a friction coefficient related information acquisition unit that acquires friction coefficient related information, which is information about the friction coefficient of the transported paper, and a deterioration judgment unit that judges deterioration of the transport mechanism based on the acquired transport time information, and the deterioration judgment unit changes the deterioration judgment result based on the acquired friction coefficient related information. Summary of the Invention [Problem to be solved by the invention]

[0004] However, with conventional technology, failure prediction is performed using the same measured curve for different paper thicknesses, which has the problem that sufficient prediction accuracy cannot be achieved when there is a large variation in data due to differences in paper thickness.

[0005] The present invention has been made in view of the above, and has as its object to perform failure prediction with sufficient prediction accuracy even when data varies greatly due to differences in paper thickness. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the present invention is characterized by comprising a paper detection unit that detects paper transported by a transport mechanism at a predetermined position on the transport path, a transport time information acquisition unit that acquires transport time information indicating the transport time required to transport the paper in a predetermined section on the transport path based on the detection result by the paper detection unit, a paper thickness detection unit that detects paper thickness information indicating the thickness of the paper, a detection information storage unit that stores transport time information for each paper thickness, and a prediction unit that predicts when the transport mechanism will fail. [Effects of the Invention]

[0007] According to the present invention, it is possible to perform failure prediction with sufficient prediction accuracy even when there is a large variation in data due to differences in paper thickness. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing a hardware configuration of an image forming apparatus according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of the image forming apparatus according to the first embodiment. [Figure 3] FIG. 3 is a diagram schematically showing the paper feed table, print engine, paper discharge tray, and paper transport paths between them according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a functional configuration of the engine control unit according to the first embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of information stored in the timing threshold storage unit. [Figure 6] FIG. 6 is a timing chart showing the operating state of the paper transport mechanism and the detection state of the timing sensor during normal operation of the image forming apparatus. [Figure 7] FIG. 7 is a diagram illustrating an example of transport time information stored in the detection information storage unit. [Figure 8] FIG. 8 is a diagram showing an example of predicted failure times for each thickness of paper. [Figure 9A] FIG. 9A is a flowchart illustrating an example of processing according to the first embodiment. [Figure 9B] FIG. 9B is a flowchart illustrating an example of a failure time prediction process according to the first embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a prediction result of the time of failure. [Figure 11] FIG. 11 is a block diagram showing a functional configuration of an image forming apparatus according to the second embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of a functional configuration of an engine control unit according to the second embodiment. [Figure 13] FIG. 13 is a diagram illustrating an example of information stored in the detection information storage unit. [Figure 14] FIG. 14 is a diagram showing an example of a decrease in prediction accuracy when the transport time suddenly increases. [Figure 15] FIG. 15 is a diagram showing an example of a decrease in prediction accuracy when the transport time suddenly becomes shorter. [Figure 16] FIG. 16 is a flowchart illustrating an example of a failure time prediction process according to the third embodiment. [Figure 17] FIG. 17 is a diagram schematically showing a paper feed table, a print engine, a paper discharge tray, and a paper transport path between them according to the fourth embodiment. [Figure 18] FIG. 18 is a flowchart showing an example of a functional configuration of an engine control unit according to the fourth embodiment. [Figure 19] FIG. 19 is a flowchart illustrating an example of a failure time prediction process according to the fourth embodiment. [Figure 20] FIG. 20 is a diagram illustrating a functional configuration of a prediction process using a trained model. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An image forming apparatus, an information processing method, and a program according to embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0010] (First embodiment) FIG. 1 is a block diagram showing the hardware configuration of an image forming apparatus 1 according to this embodiment. As shown in FIG. 1, the image forming apparatus 1 according to this embodiment has a configuration similar to that of an information processing terminal such as a general server or a PC (Personal Computer), and also has an engine that executes image formation. That is, the image forming apparatus 1 according to this embodiment has a central processing unit (CPU) 10, a random access memory (RAM) 20, a read only memory (ROM) 30, an engine 40, a hard disk drive (HDD) 50, and an interface (I / F) 60, all of which are connected via a bus 90. An LCD (Liquid Crystal Display) 70 and an operation unit 80 are also connected to the I / F 60.

[0011] The CPU 10 is a computing means and controls the overall operation of the image forming apparatus 1. The RAM 20 is a volatile storage medium that allows high-speed reading and writing of information, and is used as a work area when the CPU 10 processes information. The ROM 30 is a read-only non-volatile storage medium that stores programs such as firmware. The engine 40 is a mechanism that actually executes image formation in the image forming apparatus 1.

[0012] The HDD 50 is a non-volatile storage medium that can read and write information, and stores an OS (Operating System), various control programs, application programs, etc. The I / F 60 connects and controls the bus 90 with various hardware and networks, etc. The LCD 70 is a visual user interface that allows the user to check the status of the image forming apparatus 1. The operation unit 80 is a user interface that allows the user to input information to the image forming apparatus 1, such as a keyboard or mouse.

[0013] In such a hardware configuration, a software control unit is configured by reading a program stored in a recording medium such as ROM 30, HDD 50, or an optical disk (not shown) into RAM 20 and operating under the control of CPU 10. The combination of the software control unit configured in this way and hardware configures a functional block that realizes the functions of image forming apparatus 1 according to this embodiment.

[0014] Next, the functional configuration of the image forming apparatus 1 according to this embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the functional configuration of the image forming apparatus 1 according to this embodiment. As shown in Fig. 2, the image forming apparatus 1 according to this embodiment includes a controller 100, an ADF (Auto Document Feeder) 101, a scanner unit 102, a paper output tray 103, a display panel 104, a paper feed table 105, a print engine 106, a paper output tray 107, a network I / F 108, and a media sensor 109.

[0015] The controller 100 also has a main control unit 111, an engine control unit 112, an input / output control unit 113, an image processing unit 114, and an operation display control unit 115. As shown in Fig. 2, the image forming apparatus 1 according to this embodiment is configured as a multifunction peripheral having a scanner unit 102 and a print engine 106. In Fig. 2, electrical connections are indicated by solid arrows, and paper flow is indicated by dashed arrows.

[0016] The display panel 104 is an output interface that visually displays the status of the image forming apparatus 1, and also serves as an input interface (operation unit) that functions as a touch panel when the user directly operates the image forming apparatus 1 or inputs information to the image forming apparatus 1. The network I / F 108 is an interface that enables the image forming apparatus 1 to communicate with other devices via a network, and an Ethernet (registered trademark) or USB (Universal Serial Bus) interface is used.

[0017] The controller 100 is configured by a combination of software and hardware. Specifically, a control program such as firmware stored in a nonvolatile recording medium such as the ROM 30, a nonvolatile memory, and the HDD 50 or an optical disk is loaded into a volatile memory (hereinafter referred to as memory) such as the RAM 20, and the controller 100 is configured by a software control unit configured under the control of the CPU 10 and hardware such as an integrated circuit. The controller 100 functions as a control unit that controls the entire image forming apparatus 1. The controller 100 is also an example of a computer.

[0018] The main control unit 111 controls the various units included in the controller 100 and issues commands to the various units of the controller 100. The engine control unit 112 controls or functions as a driving unit that drives the print engine 106, scanner unit 102, etc. The engine control unit 112 also has a function related to the gist of this embodiment, which is to recognize deterioration of the paper feed table 105 and the transport mechanism included in the print engine 106 and to predict when they will fail. Details of the functions of the engine control unit 112 will be described later.

[0019] The input / output control unit 113 inputs signals and commands input via the network I / F 108 to the main control unit 111. The main control unit 111 also controls the input / output control unit 113 and accesses other devices via the network I / F 108.

[0020] Image processing unit 114 generates drawing information based on print information included in the input print job under the control of main control unit 111. This drawing information is information used by print engine 106, which is an image forming unit, to draw an image to be formed in an image forming operation. Furthermore, the print information included in the print job is image information converted into a format recognizable by image forming device 1 by a printer driver installed in an information processing device such as a PC.

[0021] Furthermore, the image processing unit 114 processes the image data input from the scanner unit 102 to generate image data. This image data is information stored in the image forming apparatus 1 as a result of the scanner operation or saved in a file server or the like connected via a network. The operation display control unit 115 displays information on the display panel 104 or notifies the main control unit 111 of information input via the display panel 104.

[0022] When the image forming apparatus 1 operates as a printer, first, the input / output control unit 113 receives a print job via the network I / F 108. The input / output control unit 113 transfers the received print job to the main control unit 111. Upon receiving the print job, the main control unit 111 controls the image processing unit 114 to generate drawing information based on the print information included in the print job.

[0023] When the image processing unit 114 generates drawing information, the engine control unit 112 executes image formation on paper conveyed from the paper feed table 105 based on the generated drawing information. That is, the print engine 106 functions as the image forming unit. Specific embodiments of the print engine 106 include an inkjet image forming mechanism and an electrophotographic image forming mechanism. The document on which the image has been formed by the print engine 106 is discharged to a paper discharge tray 107.

[0024] When the image forming apparatus 1 operates as a scanner, in response to a scan execution instruction input from an external client terminal or the like via a user's operation on the display panel 104 or a network I / F 108, the operation display control unit 115 or the input / output control unit 113 transfers a scan execution signal to the main control unit 111. The main control unit 111 controls the engine control unit 112 based on the received scan execution signal.

[0025] The engine control unit 112 drives the ADF 101 to transport an image-capture target document set in the ADF 101 to the scanner unit 102. The engine control unit 112 also drives the scanner unit 102 to capture an image of the document transported from the ADF 101. When an original document is not set in the ADF 101 but is set directly in the scanner unit 102, the scanner unit 102 captures an image of the set original document under the control of the engine control unit 112. That is, the scanner unit 102 operates as an imaging unit.

[0026] In the imaging operation, an imaging element such as a CCD included in the scanner unit 102 optically scans an original, and imaging information is generated based on the optical information. The engine control unit 112 transfers the imaging information generated by the scanner unit 102 to the image processing unit 114. The image processing unit 114 generates image information based on the imaging information received from the engine control unit 112 under the control of the main control unit 111. The image information generated by the image processing unit 114 is stored in a storage medium attached to the image forming apparatus 1 in the HDD 50.

[0027] The image information generated by the image processing unit 114 is stored directly in the HDD 50 or the like in response to a user instruction, or is transmitted to an external device via the input / output control unit 113 and the network I / F 108. That is, the ADF 101 and the engine control unit 112 function as an image input unit.

[0028] Furthermore, when the image forming apparatus 1 operates as a copier, the image processing unit 114 generates drawing information based on the imaging information received by the engine control unit 112 from the scanner unit 102 or the image information generated by the image processing unit 114. Based on the drawing information, the engine control unit 112 drives the print engine 106, just as in the case of printer operation.

[0029] When the image forming apparatus 1 operates as a printer or copier, the media sensor 109 detects information about the paper conveyed from the paper feed table 105 to the print engine 106. Information that the media sensor 109 can detect includes the thickness of the paper, the material of the paper, the paper quality, and the coefficient of friction of the paper surface. The media sensor 109 according to this embodiment functions as a paper thickness detection unit that detects paper thickness information that indicates the thickness of the paper. The detection output by the media sensor 109 is input to the engine control unit 112. The control program that constitutes the controller 100 causes the engine control unit 112 to function as paper thickness detection means that detects paper thickness information using the media sensor 109.

[0030] Next, the paper feed table 105, the print engine 106, the paper discharge tray 107, and the paper transport path between them according to this embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram schematically showing the paper feed table 105, the print engine 106, the paper discharge tray 107, and the paper transport path between them according to this embodiment. In Fig. 3, the transport path along which paper is transported is indicated by a dashed line.

[0031] 3, the paper feed table 105 according to this embodiment includes a paper feed tray 151, a paper feed roller 152, and a paper feed sensor 153. The paper feed tray 151 is a tray on which paper sheets are stacked. The paper feed roller 152 pulls out the paper sheets stacked in the paper feed tray 151 and feeds them to the transport path. The paper feed sensor 153 is a timing sensor that detects the paper sheets fed to the transport path by the paper feed roller 152.

[0032] 3, in addition to the media sensor 109, an intermediate feed roller 154 and an intermediate feed sensor 155 are provided on the transport path between the paper feed table 105 and the print engine 106 according to this embodiment. The intermediate feed roller 154 transports the paper transported from the paper feed table 105 to the print engine 106. The intermediate feed sensor 155 is a timing sensor that detects the paper transported by the intermediate feed roller 154.

[0033] As shown in FIG. 3, the print engine 106 according to this embodiment includes a registration sensor 161, registration rollers 162, an image forming unit 163, a transfer / separation unit 164, a fixing unit 165, a front discharge sensor 166, and a front discharge roller 167.

[0034] Registration sensor 161 is a timing sensor that detects paper transported into print engine 106. Registration rollers 162 transport paper detected by registration sensor 161 toward transfer / separation unit 164. Registration rollers 162 transport the paper in synchronization with image creation unit 163. Image creation unit 163 includes a photosensitive member, a charging device, and a developing device, and forms a toner image to be transferred onto the transported paper.

[0035] The transfer / separation unit 164 transfers the toner image formed in the image forming unit 163 onto the transported paper. The fixing unit 165 fixes the toner image transferred onto the paper. The front paper discharge sensor 166 is a timing sensor that detects paper that has passed through the fixing unit 165. The front paper discharge rollers 167 transport the paper detected by the front paper discharge sensor 166 out of the print engine 106.

[0036] 3, a rear discharge sensor 168 and a rear discharge roller 169 are provided on the transport path between the print engine 106 and the discharge tray 107 according to this embodiment. The rear discharge sensor 168 is a timing sensor that detects paper discharged from the print engine 106. The rear discharge roller 169 discharges the paper detected by the rear discharge sensor 168 to the discharge tray 107.

[0037] As described above, the conveyance mechanism of the image forming apparatus 1 according to this embodiment is made up of the paper feed roller 152, the intermediate feed roller 154, the registration roller 162, the front discharge roller 167, and the rear discharge roller 169. Furthermore, the timing sensors shown in FIG. 3, namely, the paper feed sensor 153, the intermediate feed sensor 155, the registration sensor 161, the front discharge sensor 166, and the rear discharge sensor 168, are controlled by the engine control unit 112. Each timing sensor shown in FIG. 3 functions as a paper detection unit that detects a paper sheet conveyed at a predetermined position on the paper conveyance path. The control program constituting the controller 100 causes the engine control unit 112 to function as a paper detection unit that detects a paper sheet using each timing sensor.

[0038] The engine control unit 112 has a function of recognizing the deterioration of the above-mentioned conveying mechanism and predicting when the conveying mechanism will fail, based on the outputs of the timing sensors and media sensor 109 shown in Fig. 3 and environmental information of the image forming apparatus 1. Next, the functional configuration of the engine control unit 112 will be described with reference to Fig. 4.

[0039] FIG. 4 is a diagram showing an example of the functional configuration of the engine control unit 112 according to this embodiment. As shown in FIG. 4, the engine control unit 112 includes a timing sensor control unit 121, a media sensor control unit 122, a detection information storage unit 124, a timing threshold storage unit 125, and a prediction unit 126. The timing sensor control unit 121 controls each timing sensor shown in FIG. 3 to acquire sheet detection signals from the respective timing sensors, and acquires information about the transport time, which is the time required for each transport mechanism shown in FIG. 3 to transport the sheet along a predetermined section on the transport path. In other words, the timing sensor control unit 121 functions as a transport time information acquisition unit. The control program constituting the controller 100 causes the timing sensor control unit 121 to function as transport time information acquisition means for acquiring the above-mentioned transport time information.

[0040] The media sensor control unit 122 controls the media sensor 109 to acquire its detection signal and obtains information about the paper being conveyed. As described above, the media sensor 109 according to this embodiment detects the thickness of the paper, so the media sensor control unit 122 according to this embodiment obtains information about the thickness of the paper (hereinafter referred to as paper thickness information).

[0041] The detection information storage unit 124 stores the information acquired by the timing sensor control unit 121 and the media sensor control unit 122 based on the output signals of the sensors in a recording medium such as the HDD 50. The information stored in the detection information storage unit 124 will be described in detail later.

[0042] The timing threshold storage unit 125 stores thresholds for predicting when the transport mechanism will malfunction, based on the arrival times of sheets detected by the respective timing sensors, in a storage medium such as the HDD 50. FIG. 5 is a diagram showing an example of information stored in the timing threshold storage unit 125. As shown in FIG. 5, the timing threshold storage unit 125 stores information on the sheet feed timing threshold (TK), the intermediate feed timing threshold (TM), the registration timing threshold (TR), the front ejection timing threshold (TH1), and the rear ejection timing threshold (TH2). That is, the above TK, TM, TR, TH1, and TH2 are used as prediction thresholds for when the malfunction will occur. Therefore, the timing threshold storage unit 125 functions as a prediction threshold storage unit.

[0043] The paper feed timing threshold TK is a reference value for predicting when a failure will occur with respect to the detection timing by the paper feed sensor 153. As shown in Fig. 3, the paper feed sensor 153 detects the leading edge of the paper being conveyed by the paper feed roller 152, and therefore the paper feed timing threshold TK is used as a threshold for predicting when the paper feed roller 152 will fail.

[0044] The intermediate feed timing threshold TM is a reference value for predicting when a failure will occur with respect to the detection timing by the intermediate feed sensor 155. As shown in Fig. 3, the intermediate feed sensor 155 detects the leading edge of the paper conveyed by the intermediate feed roller 154, and therefore the intermediate feed timing threshold TM is used as a threshold for predicting when the intermediate feed roller 154 will fail.

[0045] The registration timing threshold TR is a reference value for predicting when a malfunction will occur with respect to the detection timing by the registration sensor 161. The pre-discharge timing threshold TH1 is a reference value for predicting when a malfunction will occur with respect to the detection timing by the pre-discharge sensor 166. As shown in FIG. 3, the pre-discharge sensor 166 detects the leading edge of a sheet of paper being transported by the image creation system from the registration rollers 162 to the fixing unit 165, and therefore the pre-discharge timing threshold TH1 is used as a threshold for predicting when a malfunction will occur with respect to the image creation system.

[0046] The rear discharge timing threshold value TH2 is a reference value for predicting when a failure will occur with respect to the detection timing by the rear discharge sensor 168. As shown in Fig. 3, the rear discharge sensor 168 detects the leading edge of the paper being conveyed by the front discharge rollers 167, and therefore the rear discharge timing threshold value TH2 is used as a threshold value for predicting when the front discharge rollers 167 will fail.

[0047] The prediction unit 126 predicts when a failure will occur in the transport mechanism of the image forming apparatus 1, based on the information acquired by the timing sensor control unit 121 and the media sensor control unit 122 and stored in the detection information storage unit 124, and the information stored in the timing threshold storage unit 125. The function of the prediction unit 126 will be described in detail later. Note that the control program constituting the controller 100 causes the prediction unit 126 to function as a prediction means for predicting when a failure will occur in the transport mechanism.

[0048] In such an image forming apparatus 1, the gist of this embodiment is that the engine control unit 112 predicts when the paper transport mechanism will fail. The operation of the image forming apparatus 1 according to this embodiment will be described below.

[0049] First, the operating state of the paper transport mechanism and the detection state of the timing sensor during normal operation of the image forming apparatus 1 according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a timing chart showing the operating state of the paper transport mechanism and the detection state of the timing sensor during normal operation of the image forming apparatus 1 according to this embodiment.

[0050] 6, first, in response to the output of a paper feed start signal by engine control unit 112 (timing t0 in the figure), paper feed roller 152 and intermediate feed roller 154 start rotating, and the paper stacked in paper feed tray 151 is separated and transported toward intermediate feed roller 154. During this process, paper feed sensor 153 detects the leading edge of the paper and switches its output from "0" to "1" (timing t1 in the figure). Timing sensor control unit 121 recognizes the period from the output timing of the paper feed start signal to the timing when the output of paper feed sensor 153 switches to "1", that is, from t0 to t1, as paper feed arrival period tK.

[0051] The paper conveyed by intermediate feed rollers 154 is conveyed toward registration rollers 162. During this process, intermediate feed sensor 155 detects the leading edge of the paper and switches its output from "0" to "1" (timing t2 in the figure). Furthermore, registration sensor 161 detects the leading edge of the paper and switches its output from "0" to "1" (timing t3 in the figure).

[0052] As a result, the timing sensor control unit 121 recognizes the period from the output timing of the paper feed start signal to the timing when the output of the intermediate feed sensor 155 switches to "1", i.e., from t0 to t2, as the intermediate feed arrival period tM. Also, the timing sensor control unit 121 recognizes the period from the output timing of the paper feed start signal to the timing when the output of the registration sensor 161 switches to "1", i.e., from t0 to t3, as the registration arrival period tR.

[0053] Then, engine control unit 112 stops the rotation of intermediate feed rollers 154 in response to the timing when the output of registration sensor 161 switches to "1." Also, as the paper conveyed by intermediate feed rollers 154 reaches registration rollers 162, media sensor 109 detects the thickness of the paper. Media sensor control unit 122 acquires the detection output of media sensor 109 and recognizes the thickness of the paper being conveyed.

[0054] In response to the timing when the output of the registration sensor 161 switches to "1", the engine control unit 112 switches the registration roller rotation signal for rotating the registration roller 162 from "0" to "1" (timing t3' in the figure). This causes the registration roller 162 to start rotating, and transports the paper toward the image creating unit 163 and the transfer / separation unit 164. At the same time that the registration roller 162 starts rotating, the front paper ejection roller 167 and the rear paper ejection roller 169 also start rotating. The paper, on which the toner image has been transferred by the transfer / separation unit 164, is further transported and reaches the fixing unit 165. The toner image transferred on the paper surface is fixed by the fixing unit 165.

[0055] After the fixing process by fixing unit 165 is completed, the paper is further conveyed and reaches pre-ejection rollers 167. During this process, pre-ejection sensor 166 detects the leading edge of the paper and switches its output from "0" to "1" (timing t4 in the figure). Timing sensor control unit 121 recognizes the period from the output timing of the paper feed start signal to the timing when the output of paper feed sensor 153 switches to "1", that is, from t0 to t4, as pre-ejection arrival period tH1.

[0056] The paper that has reached the front discharge rollers 167 is further transported by the front discharge rollers 167 and reaches the rear discharge rollers 169. During this process, the rear discharge sensor 168 detects the leading edge of the paper and switches its output from "0" to "1" (timing t5 in the figure). The timing sensor control unit 121 recognizes the period from the output timing of the paper feed start signal to the timing when the output of the paper feed sensor 153 switches to "1", that is, from t0 to t5, as the rear discharge arrival period tH2. The paper that has reached the rear discharge rollers 169 is discharged outside the apparatus by the rear discharge rollers 169, and the transport of the paper inside the image forming apparatus 1 is completed.

[0057] The periods tK, tM, tR, tH1, and tH2 acquired as described above are the transport times required to transport a sheet at a predetermined position on the transport path. Hereinafter, the positions on the transport path near the sheet feed sensor 153, the intermediate feed sensor 155, the registration sensor 161, the front sheet discharge sensor 166, and the rear sheet discharge sensor 168 will be referred to as the first to fifth positions, respectively. Furthermore, since the transport times described above correspond to the mth position (m=0, 1, ..., 5), they will be represented using the symbol tm, such as t0 for tK, t1 for tM, .... Similarly, the timing thresholds TK, TM, TR, TH1, and TH2 will be represented using the symbol Tm (m=0, 1, ..., 5).

[0058] The prediction unit 126 uses information on the transport time (transport time information tm), a predetermined threshold Tm, and the detection result of the media sensor 109 (paper thickness = K) to predict the time of failure (JmK) of the transport mechanism at a predetermined position (position m) for each paper thickness.

[0059] FIG. 7 is a diagram showing an example of transport time information stored in the detection information storage unit 124. In FIG. 7, transport time information tm at the mth position is shown in table format. Here, the horizontal direction of the table represents the cumulative number of transported sheets, and the vertical direction of the table represents the thickness of the sheets. Also, "xxx" indicates the detected and stored value of tm, and "-" indicates that tm for that paper thickness has not been detected. In this way, paper thickness information and transport time information tm are stored in association with information on the cumulative number of sheets. In this example, for paper with thickness A, tm is detected and stored when the cumulative number of sheets is 100, 103, 104, and 200. For paper with thickness B, tm is detected and stored when the cumulative number of sheets is 101 and 102. Note that there may be three or more types of paper thickness. The control program constituting the controller 100 causes the detection information storage unit 124 to function as a detection information storage unit that stores transport time information tm for each paper thickness.

[0060] Figure 8 shows an example of predicted failure times for each paper thickness. In Figure 8, the horizontal axis of the graph represents the cumulative number of transported sheets, and the vertical axis represents the transport time tm. The vertical axis is positively downward, indicating that the transport time increases as the vertical axis moves downward. The two curves are predicted transport time curves corresponding to each paper thickness (A, B). Both curves predict that the transport time increases (the transport mechanism deteriorates) as the cumulative number of sheets increases. The predicted curves can be calculated using known methods, such as fitting using actual measured transport time values, as shown in Figure 7. For example, they can be calculated using linear approximation using a linear function or curve approximation using a quadratic or higher function. To calculate the predicted curve with appropriate accuracy, the number of samples of actual measurements should be, for example, 50 or more for each paper thickness. However, the number of samples may be less than 50 if appropriate accuracy is ensured.

[0061] In FIG. 8, the cumulative number of sheets (JmA, JmB) at which each prediction curve reaches the timing threshold Tm indicates the predicted value of the failure time for each paper thickness (A, B). In this example, B is larger than A, and it is predicted that the thinner paper with a paper thickness of A has an earlier failure time than the thicker paper with a paper thickness of B (JmA < JmB). This is because the measured value of the conveyance time varies depending on the paper thickness. Thus, since the measured value of the conveyance time is larger for thinner paper than for thicker paper, when the predicted value of the failure time is obtained from data for different paper thicknesses, the prediction accuracy deteriorates due to the variation in the measured values. On the other hand, by obtaining the predicted value of the failure time for each paper thickness as in the present embodiment, the prediction accuracy can be improved.

[0062] FIG. 9A is a flowchart showing an example of the process according to the present embodiment. First, each timing sensor detects a sheet conveyed at a predetermined position on the conveyance path (step S1), and the timing sensor control unit 121 acquires conveyance time information according to the detection result (step S2).

[0063] Next, the media sensor 109 detects paper thickness information indicating the thickness of the paper (step S3), and the detection information storage unit 124 stores the conveyance time information for each paper thickness (step S4).

[0064] Then, the prediction unit 126 predicts the failure time of the conveyance mechanism (step S5) and stores the prediction result (step S6).

[0065] FIG. 9B is a flowchart showing an example of the failure time prediction process according to the present embodiment. This flowchart shows the details of the processes in steps S4 to S6 in FIG. 9A. Here, at the m-th position, after the number of samples of the measured value has been sufficiently accumulated, the process when the conveyance time tm of a single sheet (with a paper thickness of K) is detected is shown.

[0066] First, the detection information storage unit 124 stores the transport time tm detected by the timing sensor control unit 121 at the mth position (step S10). Next, the prediction unit 126 predicts the failure time JmK at the mth position for the paper thickness (K) acquired by the media sensor control unit 122 (step S11). Here, the prediction unit 126 obtains a prediction curve as described above from the actual measured values ​​of the transport time for the paper thickness (K), and sets the cumulative number of sheets at which the predicted transport time reaches the timing threshold Tm as the predicted value JmK of the failure time.

[0067] Next, the prediction unit 126 stores the predicted value JmK, which is the prediction result, in a recording medium such as the HDD 50 (step S12). FIG. 10 is a diagram showing an example of the prediction result of the failure time. Here, the predicted value for paper thickness (A) is shown in the row "JmA", and the predicted value for paper thickness (B) is shown in the row "JmB". In this way, the prediction unit 126 stores the prediction result of the failure time at the mth position for each paper thickness.

[0068] Thus, according to this embodiment, the time of failure of the transport mechanism at a specified position is predicted for each paper thickness, making it possible to predict failure with sufficient accuracy even when there is a large variation in data due to differences in paper thickness.

[0069] The prediction unit 126 may be configured to predict the time to failure for a paper thickness for which there is no (or insufficient) number of actual measurement sample values, using predicted values ​​of the time to failure obtained for a plurality of paper thicknesses for which a sufficient number of actual measurement sample values ​​have been accumulated. For example, if a sufficient number of actual measurement sample values ​​have been accumulated for paper with thicknesses A and B, but not for paper with thickness C, the predicted value JmC for paper with thickness C can be obtained by the following equation (1) using the predicted values ​​JmA and JmB.

[0070] JmC=(α A ×JmA+α B ×JmB) / (α A +α B ) ···(1)

[0071] where α A and α B is a predetermined coefficient, which is a value previously set through experiments or the like. This coefficient may be set for each paper thickness, or may be dynamically changed depending on the usage status of the image forming apparatus 1. A =α B In this case, JmC is calculated by averaging JmA and JmB.

[0072] Furthermore, even if the image forming apparatus 1 does not accumulate a sufficient number of actual measurement value samples, it is possible to predict the time of failure by aggregating data on actual measurement values ​​accumulated in other apparatuses having the same or similar specifications as the image forming apparatus 1. In this case, the prediction unit 126 can predict the time of failure using data on performance values ​​accumulated in other apparatuses, which data has been acquired via the network I / F 108 and stored in a recording medium such as the HDD 50. Note that the prediction unit 126 may be configured to predict the time of failure using both the actual measurement values ​​being accumulated in the image forming apparatus 1 and the actual measurement values ​​of other apparatuses acquired via the network I / F 108. This allows the time of failure to be predicted using more actual measurement values ​​than those in the image forming apparatus 1, thereby improving the accuracy of the prediction.

[0073] (Second embodiment) The above-mentioned transport time varies depending on the coefficient of friction between the paper being transported inside the image forming apparatus 1 and the transport mechanism that transports the paper. The coefficient of friction also varies depending on the environmental conditions (temperature, humidity, etc.) inside the apparatus. In this embodiment, information (environmental information) indicating the environmental conditions such as temperature and humidity is used to correct parameters (timing thresholds and detected transport time) used to predict when the transport mechanism will fail.

[0074] Fig. 11 is a block diagram showing the functional configuration of an image forming apparatus 1 according to this embodiment. Fig. 12 is a diagram showing an example of the functional configuration of an engine control unit 112 according to this embodiment. The differences from the first embodiment are that the image forming apparatus 1 includes an environmental sensor 110, the engine control unit 112 has an environmental sensor control unit 123, and the detection information storage unit 124 and the prediction unit 126 perform processing related to environmental information. The other functional configurations and operations are the same as those of the first embodiment, so detailed description will be omitted.

[0075] The environmental sensor 110 detects temperature, humidity, and the like as environmental conditions in which the image forming apparatus 1 operates. That is, the environmental sensor 110 functions as a temperature detection unit, a humidity detection unit, and the like. The environmental conditions detected by the environmental sensor 110 are used to determine the coefficient of friction between paper and the transport mechanism inside the image forming apparatus 1, so it is preferable to set up the environmental sensor 110 so that it can detect environmental conditions inside the apparatus. Note that it may be possible to detect other information other than temperature and humidity as long as it is an environmental condition related to the friction of paper transported inside the apparatus. It may also be possible to detect environmental conditions outside the apparatus.

[0076] The environment sensor control unit 123 controls the environment sensor 110 and acquires its detection signal. As described above, the environment sensor 110 detects temperature and humidity, so the environment sensor control unit 123 according to this embodiment acquires information about the environment inside the image forming apparatus 1.

[0077] The environmental information acquired by the environmental sensor control unit 123 is used as information relating to the coefficient of friction between the transport path information and the rollers serving as the transport mechanism, and the parameters used to predict when a malfunction will occur can be corrected based on this information relating to the friction coefficient. That is, the above-mentioned environmental information is used as friction coefficient-related information, and the environmental sensor control unit 123 functions as a friction coefficient-related information acquisition unit.

[0078] The detection information storage unit 124 stores information acquired by the timing sensor control unit 121, the media sensor control unit 122, and the environment sensor control unit 123 based on the output signals of the respective sensors in a recording medium such as the HDD 50.

[0079] The prediction unit 126 predicts the time of failure of the conveying mechanism of the image forming device 1 based on the information acquired by the timing sensor control unit 121, media sensor control unit 122, and environmental sensor control unit 123 and stored in the detection information memory unit 124 and the information stored in the timing threshold memory unit 125.

[0080] FIG. 13 is a diagram showing an example of information stored in the detection information storage unit 124. In FIG. 13, the temperature, humidity, and transport time information tm at the mth position are shown in a table format. Note that "yyy" indicates the detected and stored temperature and humidity values. In this way, environmental information such as temperature and humidity is stored in association with information on the cumulative number of sheets, along with paper thickness information and transport time information tm.

[0081] The prediction unit 126 corrects the timing threshold Tm using the following equation (2), and predicts the failure time using the corrected timing threshold Tm.

[0082] Tm=Tm+f(environmental information)...(2)

[0083] Here, f is a function for correcting the timing threshold Tm according to the value of the environmental information. Note that the prediction unit 126 may be configured to correct the detected transportation time tm using the following equation (3) instead of correcting the timing threshold Tm, and predict the failure time using the corrected transportation time tm.

[0084] tm=tm-f(environmental information)...(3)

[0085] The coefficient of friction between the roller and the paper changes not only due to wear and tear on the roller over time, but also due to environmental conditions such as temperature and humidity during transport. However, if the paper transport speed is determined uniformly without taking these conditions into account, the roller may be judged to be deteriorated even when it is not, or deterioration may not be detected even when it is. In response to this problem, the above-mentioned problem can be solved by correcting the timing threshold Tm by taking into account the environmental conditions during paper transport, as shown in equations (2) and (3). For example, the lower the temperature, the lower the coefficient of friction between the paper and the roller. As a result, even when the roller is not worn, the probability of slippage increases. Therefore, the function f included in equation (2) is set to increase the value of Tm as the temperature decreases. In other words, f in equation (2) or (3) is set to a positive value.

[0086] Furthermore, the higher the humidity, the higher the coefficient of friction between the paper and rollers tends to be. As a result, even if the roller is worn, the probability of slippage decreases. Therefore, the function f included in equation (2) is set so that the value of Tm decreases as the humidity increases. In other words, the function f in equation (2) or (3) is set to a negative value.

[0087] Thus, according to this embodiment, by correcting the parameters according to the environmental information, it is possible to predict failures with sufficient accuracy for each paper thickness even when the environmental information changes significantly.

[0088] (Third embodiment) In the image forming apparatus 1, slippage can occur due to the adhesion of paper dust or other particles to the paper, resulting in a sudden increase in transport time. Furthermore, a "multiple feed" (i.e., two or more sheets of paper overlap) can eliminate slippage and suddenly reduce transport time. For example, if a slippage occurs with thin paper due to deterioration of the transport mechanism, and then a double feed occurs, the transport pressure on the rollers increases, reducing slippage. In this case, the device may temporarily appear to have recovered from the degradation, but in reality, the transport has simply stabilized due to the multiple feed, and not recovered at all. Therefore, using such detection results to predict when a malfunction will occur can result in a prediction that the malfunction will occur later than it actually is. This embodiment prevents a decrease in the accuracy of malfunction predictions due to such sudden abnormal transport time values.

[0089] FIG. 14 shows an example of a drop in prediction accuracy when the transport time suddenly increases. In FIG. 14, cumulative 199 indicates the predicted transport time for a specific paper thickness (K) calculated when the cumulative number of sheets reached 199, while cumulative 200 indicates the predicted transport time calculated when paper of the same thickness (K) was transported when the cumulative number of sheets reached 200. In this example, when the cumulative number of sheets reached 200, long transport time information indicated by an "abnormal value" was detected, and the predicted curve (cumulative 200) calculated including the abnormal value significantly differed from the previous predicted curve (cumulative 199). As a result, the failure time JmK200 predicted from cumulative 200 was significantly lower than the failure time JmK199 predicted from cumulative 199, resulting in a drop in the prediction accuracy of the failure time.

[0090] Figure 15 shows an example of a drop in prediction accuracy when the transport time suddenly decreases. In this example, when the cumulative number of sheets reaches 200, data on a short transport time indicated by an "abnormal value" is detected, and the prediction curve (cumulative 200) calculated including the abnormal value changes significantly from the previous prediction curve (cumulative 199). As a result, the failure time JmK200 predicted from cumulative 200 increases significantly from the failure time JmK199 predicted from cumulative 199, resulting in a drop in the prediction accuracy of the failure time.

[0091] In this manner, when the predicted value of the failure time fluctuates significantly, in this embodiment, the latest detected transport time information is regarded as an abnormal value, and the failure time calculated including the abnormal value is not stored as a prediction result (excluded from the prediction result), and the latest transport time information is not used for prediction. FIG. 16 is a flowchart showing an example of a failure time prediction process according to this embodiment. The difference from the first embodiment is that the fluctuation rate of the predicted failure time is determined in step S22, and if the fluctuation rate exceeds a threshold, the transport time stored in step S24 is excluded from the storage target. The other functional configurations and operations are the same as those of the first embodiment, and therefore detailed description will be omitted.

[0092] The prediction unit 126 monitors fluctuations in the predicted value JmK of the failure time for paper thickness (K), and if the fluctuation rate of JmK is equal to or less than a predetermined threshold (step S22: Yes), it stores the predicted value JmK calculated in step S21 as a prediction result in a recording medium such as the HDD 50 (step S23). On the other hand, if the fluctuation rate of JmK exceeds the predetermined threshold (step S22: No), it does not store the calculated predicted value JmK as a prediction result (excludes it from the prediction result). In addition, the prediction unit 126 excludes the latest transport time tm stored by the detection information storage unit 124 in step S20 from the storage targets, and does not use this transport time information for future predictions (step S24).

[0093] Here, the predetermined threshold is a predetermined percentage for determining whether the latest transport time is an abnormal value, and may be, for example, 10 to 20%. The predetermined percentage is a value set in advance through experiments, etc. This coefficient may also be set for each paper thickness, or may be dynamically changed depending on the usage status of the image forming apparatus 1, etc.

[0094] In this way, according to this embodiment, by not using the latest transport time information for prediction when the fluctuation rate of the predicted value exceeds a predetermined rate, it is possible to prevent a decrease in the accuracy of prediction of the time of failure due to abnormal values ​​of transport time that occur.

[0095] (Fourth embodiment) When an abnormal value of the transport time occurs due to the double feeding of fed sheets, the load torque on the roller increases. In this embodiment, the load torque on the roller is detected at a predetermined position (position m) to prevent a decrease in the accuracy of prediction of the time of failure due to the abnormal value.

[0096] 17 is a diagram schematically illustrating the paper feed table 105, print engine 106, and paper discharge tray 107 according to this embodiment, and the paper transport path between them. The difference from the first embodiment is that the paper feed roller 152, intermediate feed roller 154, registration roller 162, front discharge roller 167, and rear discharge roller 169 are each provided with load torque sensors 152t, 154t, 162t, 167t, and 169t that detect the load torque on each roller. Here, each load torque sensor functions as a load torque detection unit that detects the load torque at a predetermined position.

[0097] FIG. 18 is a diagram showing an example of the functional configuration of the engine control unit 112 according to this embodiment. The difference from the first embodiment is that the engine control unit 112 has a torque sensor control unit 127, and the detection information storage unit 124 and the prediction unit 126 perform processing related to the load torque value. The torque sensor control unit 127 controls the load torque sensors 152t, 154t, 162t, 167t, and 169t and acquires their detection signals. The other functional configurations and operations are the same as those of the first embodiment, so detailed description will be omitted.

[0098] 19 is a flowchart showing an example of a failure time prediction process according to the present embodiment. The difference from the first embodiment is that in step S32, the prediction unit 126 monitors the load torque value acquired by the torque sensor control unit 127 and determines the load torque value, and in that if the load torque value exceeds a threshold value, the transport time stored in step S34 is excluded from the storage targets. The other functional configurations and operations are the same as those of the first embodiment, and therefore detailed description thereof will be omitted.

[0099] The prediction unit 126 monitors the load torque value at the mth position for the paper thickness (K), and if the load torque value is equal to or less than a predetermined threshold (step S32: Yes), it stores the predicted value JmK calculated in step S31 as a prediction result in a recording medium such as the HDD 50 (step S33). On the other hand, if the load torque value exceeds the predetermined threshold (step S32: No), it does not store the calculated predicted value JmK as a prediction result (excludes it from the prediction result). In addition, the prediction unit 126 excludes the latest transport time tm stored by the detection information storage unit 124 in step S30 from the storage targets, and does not use this transport time information for future predictions (step S34).

[0100] Here, the predetermined threshold is a predetermined value for determining whether the latest transport time is an abnormal value, and is a value that is set in advance through experiments, etc. Furthermore, this coefficient may be set for each paper thickness, or may be dynamically changed depending on the usage status of the image forming apparatus 1, etc.

[0101] In this way, according to this embodiment, by not using the latest transport time information for prediction when the load torque value exceeds a predetermined value, it is possible to prevent a decrease in the accuracy of prediction of the time of failure due to abnormal values ​​of the transport time that occur.

[0102] Although the embodiments of the present invention have been described above, the above-described embodiments are presented as examples and are not intended to limit the scope of the invention.

[0103] For example, the algorithm used by the prediction unit 126 in the first to fourth embodiments to predict the time of failure may be an algorithm generated by the learning effect of machine learning. Specifically, a model (trained model) may be generated by machine learning using the input and output values ​​for each sheet thickness stored in the detection information storage unit 124 as training data, and the prediction unit 126 may use this model to predict the time of failure of the conveyance mechanism at the m-th position for each sheet thickness. Here, the input values ​​include conveyance time information, cumulative sheet count information, environmental information, and load torque detection information, and the output values ​​include information on the actual time of failure (cumulative sheet count) measured for each sheet thickness. Furthermore, the environmental sensor 110 that detects environmental information and the load torque sensors 152t, 154t, 162t, 167t, and 169t that detect load torque function as auxiliary information detection units that detect at least one of the environmental temperature, humidity, and load torque at a predetermined position.

[0104] Machine learning is a technology that allows a computer to acquire human-like learning capabilities, in which the computer autonomously generates algorithms necessary for judgments such as data identification from training data that is input in advance, and applies these to new data to make predictions. The learning method for machine learning may be any of the above-mentioned learning methods using teacher data, unsupervised learning, semi-supervised learning, reinforcement learning, and deep learning, or may be a combination of these learning methods; any learning method for machine learning is acceptable.

[0105] Fig. 20 is a diagram schematically illustrating the functional configuration of a prediction process using a trained model. As shown in Fig. 20, the auxiliary information detection unit 500 has an environment sensor 110 and a load torque sensor Xt. Here, the load torque sensor Xt refers to all or some of the above-mentioned load torque sensors 152t, 154t, 162t, 167t, and 169t. The auxiliary information detection unit 500 is assumed to have at least one of the environment sensor 110 and the load torque sensor Xt.

[0106] The prediction unit 126 has a trained model 600. The trained model 600 is a model that has undergone machine learning as described above. The prediction unit 126 inputs into the trained model 600 the transport time information and cumulative sheet count information stored by the detection information storage unit 124 in a recording medium such as the HDD 50, and at least one of the environmental temperature, humidity, or load torque at a predetermined position detected by the auxiliary information detection unit 500, and predicts the time of failure of the transport mechanism at a predetermined position for each sheet thickness. In this way, by making predictions using the trained model 600, the accuracy of the prediction of the time of failure can be improved.

[0107] Furthermore, each function of the above-described embodiments can be realized by one or more processing circuits. Here, the term "processing circuit" in this specification includes a processor programmed to execute each function by software, such as a processor implemented by an electronic circuit, as well as devices such as an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and conventional circuit modules designed to execute each of the above-described functions.

[0108] For example, aspects of the present invention are as follows. <1> The image forming device comprises a paper detection unit that detects paper transported by a transport mechanism at a predetermined position on the transport path, a transport time information acquisition unit that acquires transport time information indicating the transport time required to transport the paper in a predetermined section on the transport path based on the detection result by the paper detection unit, a paper thickness detection unit that detects paper thickness information indicating the thickness of the paper, a detection information storage unit that stores transport time information for each paper thickness, and a prediction unit that predicts when the transport mechanism will fail, wherein the prediction unit predicts when the transport mechanism will fail at the predetermined position for each paper thickness using the transport time information stored in the detection information storage unit and the cumulative number of transported sheets. <2> the prediction unit uses a first failure time when the paper has a first thickness and a second failure time when the paper has a second thickness to calculate a failure time for paper having a thickness between the first thickness and the second thickness; <1> 2. The image forming apparatus according to claim 1, wherein: <3> a temperature detection unit that detects a temperature of an environment in which the image forming apparatus is operating, wherein the prediction unit predicts a time when the conveying mechanism at the predetermined position will fail for each thickness of the paper using the conveying time information, the cumulative number of sheets, and the temperature of the environment; <1> or <2> 2. The image forming apparatus according to claim 1, wherein: <4> the image forming apparatus further includes a humidity detection unit that detects humidity in an environment in which the image forming apparatus is operating, and the prediction unit predicts a time when the conveying mechanism at the predetermined position will fail for each thickness of the paper using the conveying time information, the cumulative number of sheets, and the humidity of the environment; <1> or <2> 2. The image forming apparatus according to claim 1, wherein: <5> the prediction unit monitors the fluctuation of the failure time, which is the predicted result, for each thickness of the paper, and when the rate of fluctuation of the failure time exceeds a predetermined rate, excludes the failure time from the prediction result, and does not use the latest transport time information stored in the detection information storage unit for prediction; <1> ~ <4> 10. The image forming apparatus according to claim 9, wherein the first and second electrodes are arranged parallel to each other. <6> The apparatus further includes a load torque detection unit that detects a load torque at the predetermined position, and the prediction unit monitors the value of the load torque detected by the load torque detection unit, and when the load torque at the predetermined position exceeds a predetermined value, the prediction unit excludes the failure time from the prediction result and does not use the latest transport time information stored in the detection information storage unit for the prediction. <1> ~ <4> 10. The image forming apparatus according to claim 9, wherein the first and second electrodes are arranged parallel to each other. <7> the image forming apparatus further includes an auxiliary information detection unit that detects at least one of a temperature, a humidity, or a load torque at the predetermined position in an environment in which the image forming apparatus is operating, and the prediction unit predicts the time when the transport mechanism at the predetermined position will fail for each thickness of the paper using a machine-learned model that uses as training data the relationship between the transport time information, the cumulative number of sheets, and the information detected by the auxiliary information detection unit, and the actual time when a failure will occur measured for each thickness of the paper; <1> ~ <6> 10. The image forming apparatus according to claim 9, wherein the first and second electrodes are arranged parallel to each other. <8> This information processing method includes a paper detection step for detecting paper transported by a transport mechanism at a predetermined position on the transport path; a transport time information acquisition step for acquiring transport time information indicating the transport time required to transport the paper in a predetermined section on the transport path based on the detection result of the paper detection step; a paper thickness detection step for detecting paper thickness information indicating the thickness of the paper; a detection information storage step for storing transport time information for each paper thickness; and a prediction step for predicting when the transport mechanism will fail, wherein the prediction step predicts when the transport mechanism will fail at the predetermined position for each paper thickness using the transport time information stored in the detection information storage step and the cumulative number of transported sheets. <9> This program causes a computer to function as a paper detection means for detecting paper transported by a transport mechanism at a predetermined position on the transport path, a transport time information acquisition means for acquiring transport time information indicating the transport time required to transport the paper in a predetermined section on the transport path based on the detection result by the paper detection means, a paper thickness detection means for detecting paper thickness information indicating the thickness of the paper, a detection information storage means for storing transport time information for each paper thickness, and a prediction means for predicting when the transport mechanism will fail, wherein the prediction means uses the transport time information stored in the detection information storage means and the cumulative number of transported sheets to predict when the transport mechanism will fail at the predetermined position for each paper thickness. [Explanation of symbols]

[0109] 1. Image forming device 10 CPU 121 Timing sensor control unit 122 Media sensor control unit 124 Detection information storage unit 125 Timing threshold memory 126 Prediction Department 153 Paper feed sensor 155 Intermediate feed sensor 161 Resist Sensor 166 Front paper discharge sensor 168 Rear paper ejection sensor [Prior art documents] [Patent documents]

[0110] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-210801

Claims

1. a sheet detection unit that detects the sheet transported by the transport mechanism at a predetermined position on the transport path; a conveyance time information acquisition unit that acquires conveyance time information indicating a conveyance time required to convey the sheet in a predetermined section on the conveyance path in accordance with a detection result by the sheet detection unit; a paper thickness detection unit that detects paper thickness information indicating the thickness of the paper; a detection information storage unit that stores conveyance time information for each thickness of the sheet; a prediction unit that predicts a time when the transport mechanism will fail; Equipped with the prediction unit predicts a time when the transport mechanism at the predetermined position will fail for each thickness of the paper sheets, using the transport time information stored in the detection information storage unit and the cumulative number of transported paper sheets. Image forming device.

2. the prediction unit calculates a failure time for paper having a thickness between the first thickness and the second thickness, using a first failure time when the paper has a first thickness and a second failure time when the paper has a second thickness; The image forming apparatus according to claim 1 .

3. a temperature detection unit that detects the temperature of an environment in which the image forming apparatus is operating; the prediction unit predicts a time when the transport mechanism at the predetermined position will fail for each thickness of the sheets, using the transport time information, the cumulative number of sheets, and the environmental temperature.

3. The image forming apparatus according to claim 1.

4. a humidity detection unit that detects the humidity of an environment in which the image forming apparatus is operating; the prediction unit predicts a time when the transport mechanism at the predetermined position will fail for each thickness of the paper sheets using the transport time information, the cumulative number of sheets, and the environmental humidity.

3. The image forming apparatus according to claim 1.

5. the prediction unit monitors fluctuations in the predicted failure time for each thickness of the paper, and when the rate of fluctuation in the failure time exceeds a predetermined rate, excludes the failure time from the prediction result and does not use the latest transport time information stored in the detection information storage unit for the prediction.

3. The image forming apparatus according to claim 1.

6. a load torque detection unit that detects a load torque at the predetermined position, the prediction unit monitors the value of the load torque detected by the load torque detection unit, and when the load torque at the predetermined position exceeds a predetermined value, excludes the failure time from the prediction result, and does not use the latest transport time information stored in the detection information storage unit for the prediction.

3. The image forming apparatus according to claim 1.

7. further comprising an auxiliary information detection unit that detects at least one of a temperature, a humidity, or a load torque at the predetermined position in an environment in which the image forming apparatus is operating; the prediction unit predicts the time when the transport mechanism at the predetermined position will fail for each thickness of the paper using a machine-learned model that uses as training data the relationship between the transport time information, the cumulative number of sheets, and the information detected by the auxiliary information detection unit, and the actual time when the failure will occur measured for each thickness of the paper.

3. The image forming apparatus according to claim 1.

8. a paper detection step of detecting the paper conveyed by the conveyance mechanism at a predetermined position on the conveyance path; a conveyance time information acquisition step of acquiring conveyance time information indicating a conveyance time required to convey the sheet in a predetermined section on the conveyance path in accordance with a detection result in the sheet detection step; a paper thickness detection step of detecting paper thickness information indicating the thickness of the paper; a detection information storage step of storing transport time information for each thickness of the sheet; a prediction step of predicting a time when the transport mechanism will fail; and the prediction step predicts a time when the transport mechanism at the predetermined position will fail for each thickness of the paper sheets, using the transport time information stored in the detection information storage step and the cumulative number of transported paper sheets. Information processing methods.

9. Computer, a sheet detection means for detecting the sheet conveyed by the conveyance mechanism at a predetermined position on the conveyance path; a conveyance time information acquiring means for acquiring conveyance time information indicating a conveyance time required to convey the sheet in a predetermined section on the conveyance path in accordance with a detection result by the sheet detecting means; a paper thickness detection means for detecting paper thickness information indicating the thickness of the paper; a detection information storage means for storing transport time information for each thickness of the sheet; a prediction means for predicting a time when the transport mechanism will fail; It functions as the prediction means predicts a time when the transport mechanism at the predetermined position will fail for each thickness of the paper sheets, using the transport time information stored in the detection information storage means and the cumulative number of transported paper sheets. program.

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