Medical imaging equipment, medical imaging systems

Abstract

Even if a defect has been detected multiple times, depending on the component and its cause, it may not necessarily be due to the component's lifespan approaching its end. Determining the failure timing and notifying users of defects that are not nearing the end of their component lifespan would increase the processing load and user burden. [Solution] An image diagnostic device connected to a printing device, comprising: an image reading means for reading a printed material formed by the printing device and generating a read image; a detection means for detecting defects in the image by comparing a reference image with the read image; and a notification means for notifying the user of information, wherein the notification means notifies the user of the predicted failure time of a predetermined component when the defect in the image is a defect based on a change in the lifespan of a predetermined component over time.

Description

Technical Field

[0001] There are some image defects in which the image quality deteriorates as the number of printed sheets increases. Based on this feature, it is possible to detect "minor image defects that are an image quality acceptable to the user" (hereinafter referred to as precursors) and predict the time when it will become "image quality unacceptable to the user" (hereinafter referred to as image defects). As a result, measures such as automatic repair can be taken during the image quality acceptable to the user, and the occurrence of image defects can be reduced.

[0002] In Patent Document 1, what is detected a specified number of times is determined as a precursor. Regarding precursors that are detected multiple times and determined not to be sudden (time-dependent), a technique for predicting the failure time (parts whose life is approaching) is disclosed.

Background Art

[0003] However, even for defects that are detected multiple times, depending on the cause of occurrence such as parts, there are those in which the part life does not approach over time. Determining the failure time and notifying the result of defects where the part life does not approach will increase the processing load and user load.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, even for defects that are detected multiple times, depending on the cause of occurrence such as parts, there are those in which the part life does not approach over time. Determining the failure time and notifying the result of defects where the part life does not approach will increase the processing load and user load.

Means for Solving the Problems

[0006] The present invention relates to an image diagnostic device connected to a printing device, comprising: an image reading means for reading a printed material formed by the printing device and generating a read image; a detection means for detecting defects in the image by comparing a reference image with the read image; and a notification means for notifying the user of information, wherein the notification means notifies the user of the predicted failure time of a predetermined component if the defect in the image is a defect based on a change in the lifespan of the predetermined component over time. It is characterized by the following. [Effects of the Invention]

[0007] According to the present invention, since failure timing is predicted and notified only when there are signs that a component's lifespan is approaching, it is possible to reduce processing load and user burden. [Brief explanation of the drawing]

[0008] [Figure 1] Diagram showing an example of a network configuration including a printing system. [Figure 2] Cross-sectional view showing an example of the hardware configuration of an image forming apparatus. [Figure 3] Block diagram showing the internal configuration of the image forming apparatus, external controller, and client PC. [Figure 4] Flowchart showing the procedure for diagnosing early warning signs. [Figure 5] Diagram showing the level of image defects [Figure 6] This diagram shows an example of setting the diagnostic area for diagnostic items in RIP data. [Figure 7] Flowchart showing the items from which features can be extracted. [Figure 8] Flowchart showing the procedure for performing a premonitory diagnosis. [Figure 9] A flowchart illustrating the procedure for determining the change in component lifespan over time based on the contributing components. [Figure 10] A diagram showing the changes in the size and contrast of the precursors. [Figure 11] Diagram showing failure timing prediction table [Figure 12] Schematic diagram of the diagnostic result notification settings screen. [Figure 13] Schematic diagram of a screen for pop-up display of diagnosis results [Figure 14] Schematic diagram of a screen for graphically displaying diagnosis results [Figure 15] Diagram showing an example where the NG timing fluctuates when the NG level is changed [Figure 16] Diagram showing an example where the NG timing fluctuates after printing progress [Figure 17] Schematic diagram of a screen for displaying notification settings for NG timing fluctuations and fluctuation notifications [Figure 18] Diagram showing an example where the speed of component life change over time varies depending on conditions [Figure 19] Flowchart diagram showing the procedure for determining the change in component life over time based on the transition of component life [Figure 20] Diagram showing an example of the change in component life over time based on the component life curve [Figure 21] Flowchart diagram showing the procedure for determining the change in component life over time based on the factor parts and calculation of the component life curve [Figure 22] Diagram showing an example of the cycle for each part and information on the change in component life over time

Mode for Carrying Out the Invention

[0009] Each embodiment of the present invention will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims, and not all combinations of the features described in each embodiment are essential for the solution means of the present invention. In the present embodiment, an image forming apparatus is used as an example of the information processing apparatus, but it is not limited thereto.

[0010] (First Embodiment) <Configuration of the Entire System>[ The following describes a first embodiment of the present invention. Referring to Figure 1, an example of a network configuration including a printing system (medical imaging system) according to this embodiment will be described. As shown in Figure 1, the printing system 100 includes an image forming apparatus 101 and an external controller 102. The image forming apparatus 101 and the external controller 102 are connected to each other so as to be able to communicate via an internal LAN 105 and a video cable 106. The external controller 102 is connected to a client PC 103 so as to be able to communicate via an external LAN 104. In this embodiment, the description is based on an example in which the image forming apparatus 101 and the external controller 102 are provided separately, but there is no intention to limit the present invention, and for example, the external controller 102 may be provided as an integrated part of the image forming apparatus 101. In that case, the image forming apparatus 101 and the client PC 103 are connected so as to be able to communicate.

[0011] The client PC 103 can issue print commands to the external controller 102 via the external LAN 104. The client PC 103 has a printer driver installed that has the function of converting image data to be printed into a Page Description Language (PDL) that can be processed by the external controller 102. Users who want to print can issue print commands via the printer driver from various applications installed on the client PC 103 by operating the client PC 103. Based on the print command from the user, the printer driver sends PDL data, which is the print data, to the external controller 102. The PDL data is the print data specified by the user, or data generated or selected within the client PC 103. When the external controller 102 receives the PDL data from the client PC 103, it analyzes and interprets the received PDL data. Based on the result of the interpretation, it performs rasterization processing to generate a bitmap image (print image data) with a resolution matched to the image forming apparatus 101, and issues a print command by submitting a print job to the image forming apparatus 101.

[0012] Next, the image forming apparatus 101 will be described. The image forming apparatus 101 is configured to enable complex printing processes such as bookbinding by connecting multiple devices with different functions. The image forming apparatus 101 includes a printing unit 107 (image forming unit), an inserter 108, a precursor diagnosis unit 109, a stacker 110, and a finisher 111. Each module will be described below.

[0013] The printing unit 107 prints an image according to the contents of the print job and discharges the printed recording medium (paper, sheet, etc.). The printed recording medium discharged from the printing unit 107 is transported through the inside of each device in the order of the predictive diagnostic unit 109, the stacker 110, and the finisher 111. The printed recording medium is referred to as a printed material. In this embodiment, the image forming apparatus 101 of the printing system 100 is an example of an image forming apparatus, but the printing unit 107 included in the image forming apparatus 101 may also be referred to as the image forming apparatus. The printing unit 107 forms (prints) an image using toner (colorant), which is the recording medium, on the recording medium that is fed and transported from the paper feeding unit located at the bottom of the printing unit 107.

[0014] The inserter 108 is a device that inserts, for example, a partition recording medium to divide a series of recording media transported from the printing unit 107 at an arbitrary position. The precursor diagnosis unit 109 detects "minor image defects of an image quality acceptable to the user" (hereinafter referred to as precursor candidates) in the image forming apparatus 101 based on the printed recording media on which the image has been printed by the printing unit 107 and transported through the transport path. The precursor diagnosis unit 109 is a device that identifies parts that are precursors to image defects (hereinafter referred to as precursors) whose component lifespan changes over time to "image defects of an image quality level unacceptable to the user" (hereinafter referred to as image defects) and predicts when the image defects will occur. Specifically, the precursor diagnosis unit 109 reads the image printed on the transported printed recording media and performs a diagnosis from the obtained read image.

[0015] The diagnosis of a precursor involves detecting potential precursors from the difference in reading signal values ​​within the read image, determining whether there is a change in the component lifespan over time for the detected precursor candidates, and predicting image defects according to the determination result. The detailed processing of the precursor diagnosis unit will be described later. Note that the application of the precursor diagnosis unit is not limited to the above example. An inspection system for checking for printing abnormalities in printed recording media and a diagnostic system for diagnosing abnormalities in the image forming apparatus 101 from image defects may also be provided. The stacker 110 is a device capable of stacking a large number of printed recording media. The finisher 111 is a device capable of performing finishing processes such as stapling, punching, and saddle stitching on the transported printed recording media. The recording media after processing by the finisher 111 are discharged into a predetermined output tray.

[0016] In the configuration example shown in Figure 1, an external controller 102 is connected to the image forming apparatus 101, but this embodiment can also be applied to other configurations. For example, the image forming apparatus 101 may be connected to an external LAN 104, and print data may be transmitted from the client PC 103 to the image forming apparatus 101 without going through the external controller 102. In this case, data analysis and rasterization of the print data are performed by the image forming apparatus 101.

[0017] <Hardware configuration of the image forming apparatus 101> Referring to Figure 2, an example of the hardware configuration of the image forming apparatus 101 according to this embodiment will be described. Below, a specific example of the operation of the image forming apparatus 101 will be described with reference to Figure 2. In the printing unit 107, various recording media (paper) are stored in the paper feed deck. During image formation, the topmost recording media among those stored in each paper feed deck are separated one by one and fed to the transport path 303.

[0018] Furthermore, each of the image forming stations 304 to 307 contains a photosensitive drum (photoreceptor) and uses different colored toners to form a toner image on the photosensitive drum. Specifically, each of the image forming stations 304 to 307 uses yellow (Y), magenta (M), cyan (C), and black (K) toners to form a toner image.

[0019] The toner images of each color formed in the image forming stations 304 to 307 are sequentially transferred onto the intermediate transfer belt 308 (primary transfer). The toner images transferred to the intermediate transfer belt 308 are transported to the secondary transfer position 309 as the intermediate transfer belt 308 rotates. At the secondary transfer position 309, the toner images are transferred from the intermediate transfer belt 308 to the recording medium that has been transported along the transport path 303 (secondary transfer). After the secondary transfer, the recording medium is transported to the fixing unit 311. The fixing unit 311 is equipped with a pressure roller and a heating (fixing) roller. Heat and pressure are applied to the recording medium as it passes between these rollers, fixing the toner image onto the recording medium. The recording medium that has passed through the fixing unit 311 is transported through the transport path 312 to the connection point 315 between the printing unit 107 and the predictive diagnostic unit 109. In this way, a color image is formed (printed) on the recording medium.

[0020] If further fixing is required depending on the type of recording medium, the recording medium that has passed through the fixing unit 311 is guided to the transport path 314 where the fixing unit 313 is located. The fixing unit 313 performs further fixing on the recording medium being transported along the transport path 314. The recording medium that has passed through the fixing unit 313 is transported to the connection point 315. Also, if the operation mode for double-sided printing is set, the image is printed on the first side. The recording medium that has been transported along the transport path 312 or transport path 314 is guided to the inversion path 316. The recording medium that has been inverted in the inversion path 316 is guided to the double-sided transport path 317 and transported to the secondary transfer position 309. As a result, at the secondary transfer position 309, the toner image is transferred from the first side of the recording medium to the opposite second side. After that, the recording medium passes through the fixing unit 311 (and fixing unit 313), completing the formation of the color image on the second side of the recording medium. Once the image formation (printing) in the printing unit 107 is complete, the printed recording medium, which has been transported to the connection point 315, is transported into the precursor diagnosis unit 109.

[0021] The pre-diagnosis unit 109 includes image reading units 331 and 332, each equipped with a Contact Image Sensor (CIS), on a transport path 330 through which printed recording media are transported from the printing unit 107. The image reading units 331 and 332 are positioned opposite each other across the transport path 330. The image reading units 331 and 332 are configured to read the top surface (first surface) and bottom surface (second surface) of the recording media, respectively. Note that the image reading units may be configured with, for example, a Charge Coupled Device (CCD) or a line scan camera instead of a CIS.

[0022] The Precursor Diagnosis Unit 109 is operated based on an instruction to execute a Precursor Diagnosis process. Specifically, the instruction to execute a Precursor Diagnosis can be any method that can determine whether or not to execute a Precursor Image Diagnosis, such as linking whether or not to execute a Precursor Diagnosis process to a print job in advance, or pressing the execute button for Precursor Image Diagnosis at the start of the job. Alternatively, an automatic setting method, such as automatically setting the Precursor Image Diagnosis to execute simultaneously with startup, is also acceptable. When an instruction to execute a Precursor Diagnosis process is given, the Precursor Diagnosis Unit 109 uses the read image of the printed recording medium being transported along the transport path 330 to perform an image Precursor Diagnosis process to determine whether or not a precursor has occurred in the image forming apparatus 101. Specifically, the Precursor Diagnosis Unit 109 uses the image reading units 331 and 332 to read the image of the printed recording medium being transported. Then, the Precursor Diagnosis Unit 109 uses the image data acquired through the reading process to perform the image Precursor Diagnosis process described later. The recording media that have passed through the Precursor Diagnosis Unit 109 are transported to the stacker 110 in order. Note that the use of the diagnosis unit is not limited to the above example. A quality control system for inspecting printed recording materials for printing defects may also be provided.

[0023] The stacker 110 includes a stack tray 341, which is a tray on which printed recording media transported from the diagnostic unit 109 located upstream in the transport direction of the printed recording media are stacked. Printed recording media that have passed through the predictive diagnostic unit 109 are transported along the transport path 344 within the stacker 110. Printed recording media transported along the transport path 344 are guided to the transport path 345, whereupon they are stacked on the stack tray 341. Printed recording media that are transported without being stacked or ejected in the stacker 110 are transported to the downstream finisher 111 via the transport path 348.

[0024] The stacker 110 further includes a reversal unit 349 for reversing the orientation of the printed recording media being transported. The reversal unit 349 is used, for example, to make the orientation of the recording media input to the stacker 110 the same as the orientation of the printed recording media when it is loaded onto the stack tray 341 and output from the stacker 110. Note that the reversal operation by the reversal unit 349 is not performed on printed recording media that are transported to the finisher 111 without being loaded into the stacker 110.

[0025] The finisher 111 performs a finishing function specified by the user on the printed recording medium that has been transported from the predictive diagnostic unit 109, which is located upstream in the transport direction of the printed recording medium. In this embodiment, the finisher 111 has finishing functions such as stapling (one or two-point stapling), punching (two or three-hole punching), and saddle-stitch binding. The finisher 111 is equipped with two output trays 351 and 352. If no finishing process is performed by the finisher 111, the printed recording medium that has been transported to the finisher 111 is discharged to the output tray 351 via the transport path 353. If a finishing process such as stapling is performed by the finisher 111, the printed recording medium that has been transported to the finisher 111 is guided to the transport path 354. The finisher 111 uses the finishing processing unit 355 to perform a finishing process specified by the user on the printed recording medium being transported along the transport path 354, and then ejects the finished printed recording medium to the output tray 352.

[0026] <Functional Configuration Diagram> Referring to Figure 3, the functional configuration of the image forming apparatus 101, external controller 102, and client PC 103 according to this embodiment will be described. The printing unit 107 of the image forming apparatus 101 includes a communication interface 201, a network interface 204, a video interface 205, a CPU 206, a memory 207, an HDD unit 208, and a UI display unit 225. The printing unit 107 further includes an image processing unit 202 and a print unit 203. Each of these units is connected to each other via a system bus 209 so that data can be sent and received from each other. The communication interface 201 is connected to the predictive diagnostic unit 109, the stacker 110, and the finisher 111 via a communication cable 260. The CPU 206 communicates via the communication interface 201 for the control of each device. The network interface 204 is connected to the external controller 102 via an internal LAN 105 and is used for communication of control data, etc.

[0027] The video interface 205 is connected to the external controller 102 via the video cable 106 and is used for communicating data such as image data. Alternatively, the printing unit 107 (image forming apparatus 101) and the external controller 102 may be connected only by the video cable 106, provided that the external controller 102 can control the operation of the image forming apparatus 101. The HDD unit 208 stores various programs and data. The CPU 206 controls the operation of the entire printing unit 107 by executing programs stored in the HDD unit 208.

[0028] Furthermore, the HDD unit 208 stores the total number of printed pages, which is used to determine whether to execute automatic repair. The memory 207 stores programs and data necessary for the CPU 206 to perform various processes. The memory 207 operates as the work area for the CPU 206. The UI display unit 225 receives input and operation instructions from the user for various settings and is used to display various information such as setting information and the processing status of print jobs. For example, it receives various instructions from the user, such as instructions and settings for executing a pre-diagnosis image and setting paper information.

[0029] The pre-diagnosis unit 109 comprises a communication interface 211, a CPU 214, a memory 215, an HDD unit 216, image reading units 331 and 332, and a UI display unit 241. These devices are connected to each other via a system bus 219, enabling them to send and receive data. The communication interface 211 is connected to the printing unit 107 via a communication cable 260. The CPU 214 performs the necessary communication for controlling the pre-diagnosis unit 109 via the communication interface 211.

[0030] The CPU 214 controls the operation of the precursor diagnosis unit 109 by executing a control program stored in the memory 215. The memory 215 stores the control program for the precursor diagnosis unit 109. The image reading units 331 and 332 read images from the transported recording medium according to the instructions of the CPU 214. Based on the images read for precursor diagnosis read by the image reading units 331 and 332, the CPU 214 diagnoses whether or not a precursor has occurred in the image forming apparatus 101. The UI display unit 241 is used to display the precursor diagnosis results and setting screens, etc. The operation unit is shared with the UI display unit 241 and is operated by the user, receiving various instructions from the user, such as changing the settings of the precursor diagnosis unit 109, issuing and setting instructions for executing precursor image diagnosis, and issuing and setting instructions for notification of precursor diagnosis results. The HDD unit 216 stores various setting information and image data necessary for image precursor diagnosis. The various setting information and image data stored in the HDD unit 216 can be reused.

[0031] The stacker 110 controls whether the printed recording medium that has been transported along the transport path is ejected to the stack tray, ejected to the escape tray, or transported to the finisher 111 which is connected downstream in the transport direction of the printed recording medium.

[0032] The finisher 111 controls the transport and ejection of the printed recording medium and performs finishing processes such as stapling, punching, or saddle stitching.

[0033] The external controller 102 comprises a CPU 251, memory 252, HDD unit 253, keyboard 256, display unit 254, network I / F 255, 257, and video I / F 258. These devices are connected to each other via a system bus 259, enabling them to send and receive data. The CPU 251 controls the overall operation of the external controller 102 by executing programs stored in the HDD unit 253, such as receiving print data from a client PC 103, performing RIP processing, and sending print data to the image forming apparatus 101. The memory 252 stores programs and data necessary for the CPU 251 to perform various processes. The memory 252 operates as the work area for the CPU 251.

[0034] Various programs and data are stored in the HDD unit 253. The keyboard 256 is used to input operation instructions from the user to the external controller 102. The display unit 254 is, for example, a display and is used to display information about the application running on the external controller 102 and the operation screen. The network interface 255 is connected to the client PC 103 via the external LAN 104 and is used for data communication such as print instructions. The network interface 257 is connected to the printing unit 107 via the internal LAN 105 and is used for data communication such as print instructions. The external controller 102 is configured to communicate with the printing unit 107, the predictive diagnostic unit 109, the stacker 110, and the finisher 111 via the internal LAN 105 and the communication cable 260. The video interface 258 is connected to the printing unit 107 via the video cable 106 and is used for data communication such as image data (print data).

[0035] The client PC 103 comprises a CPU 261, memory 262, HDD unit 263, display unit 264, keyboard 265, and network interface 266. These devices are connected to each other via a system bus 269, enabling them to send and receive data. The CPU 261 controls the operation of each device via the system bus 269 by executing programs stored in the HDD unit 263. This enables various processes to be performed by the client PC 103. For example, the CPU 261 generates print data and issues print commands by executing a document processing program stored in the HDD unit 263. The memory 262 stores programs and data necessary for the CPU 261 to perform various processes. The memory 262 operates as the work area of ​​the CPU 261.

[0036] The HDD unit 263 stores various applications such as document processing programs, printer drivers and other programs, and various data. The display unit 264 is, for example, a display and is used to display information about applications running on the client PC 103 and the operation screen. The keyboard 265 is used to input operation instructions from the user to the client PC 103. The network interface 266 is connected to the external controller 102 via the external LAN 104 so as to be able to communicate. The CPU 261 communicates with the external controller 102 via the network interface 266.

[0037] <Precursor Diagnosis Process> The predictive diagnostic process according to this embodiment will be explained with reference to a diagram. Figure 4 is a flowchart showing the steps of the printing operation performed by the printing unit 107 and the predictive diagnostic process performed by the predictive diagnostic unit 109. Figure 4 shows the overall flow from the work before the start of predictive diagnostics to the execution of predictive diagnostics and automatic repair execution. In the explanation of the flowchart, the symbol "S" represents a step. The same applies to the explanation of the flowchart below. The processing of each step in Figure 4 is executed by the CPU 206 of the printing unit 107 and the CPU 214 of the predictive diagnostic unit 109.

[0038] In S401, the printing system 100 receives instructions for predictive diagnostics from users and service personnel via the UI display unit 241, which also serves as the operation unit, and confirms the settings for the predictive diagnostic process. In this embodiment, a screen for receiving instructions to start predictive diagnostics is displayed on the UI display unit 241, and upon receiving the instruction to start, settings for the image defect level and notification of the diagnostic results are made as the settings for predictive diagnostics.

[0039] Furthermore, the start instruction is not limited to the example above; it is sufficient to know that a predictive diagnostic test will be performed. For example, a job and the execution of a predictive diagnostic test may be linked in advance, and when a job for execution of a predictive diagnostic test is received, a start instruction for the predictive diagnostic test may be issued. Regarding the setting of the image defect level, in this embodiment, the level at which an image defect is judged is classified into nine stages based on the size and contrast of the image defect, and the case in which the user selects the level at which an image defect is judged will be described.

[0040] Figure 5 shows an example of an image defect level. The image defect level 501 selected by the user has different settings: lower levels result in larger image defect size 502 and higher contrast 503, while higher levels result in smaller image defect size 502 and lower contrast 503. Note that the image defect level setting is not limited to the above. Any level that indicates an image defect is acceptable; it may be set by size only, contrast only, or by selecting from the image defect category. Alternatively, a numerical value or a sample image can be selected instead of a level. Details regarding notification of the diagnostic results will be described later in the diagnostic result notification section.

[0041] After confirming the settings for the pre-announcement diagnosis and saving to the HDD unit 216, the process proceeds to print the print job. S402 receives print commands from the client PC 103 and the external controller 102 and starts the printing operation. In other words, the print job is started. Specifically, the CPU 251 of the external controller 102 interprets the PDF print job received by S401, interpreting the PDL (Personal Data Listing) from the text in the PDF file to determine the font type, size, and paper position of the characters. Next, the CPU 251 creates RIP data by rasterizing it into a bitmap according to the resolution settings interpreted by S402's PDL interpretation. The CPU 251 associates feature extractable items with the RIP data. Details of the feature extractable items will be described later.

[0042] The CPU 251 uses the created RIP data as a reference image, links it to the diagnostic items, and temporarily stores it in the HDD unit 253 of the external controller 102. The reference image stored in the HDD unit 253 is then sent to the precursor diagnosis unit 109 and stored in the HDD unit 216 of the precursor diagnosis unit 109. Subsequently, the CPU 251 transmits the RIP data from the video I / F 258 through the video cable 106 to the video I / F 205 of the printing unit 107. The CPU 206 of the printing unit 107 performs halftone processing on the RIP data received by the video I / F 205, and the print unit 203 prints the image data after halftone processing.

[0043] In S403, the CPU 214 of the predictive diagnostic unit 109 performs a predictive diagnostic, as described later, in the predictive diagnostic execution process, and saves the execution result to the HDD unit 216. In S404, the CPU 214 notifies the diagnostic result according to the notification content saved in the HDD unit 216. In this embodiment, the case where the notification is displayed on the UI display unit 241 is described. The method of notifying the result is not limited to displaying it on the UI display unit 241. It may also be done by displaying it on the display unit 264 of the client PC, the display unit 254 of the external controller, the UI display unit 225 of the printing unit, printing the result, or sending the result to an external cloud or external PC via the network. Details of the content to be notified will be described later in the diagnostic result notification section.

[0044] In S405, the CPU 214 of the pre-diagnosis unit 109 performs an automatic repair execution determination. In this embodiment, the timing for automatic repair execution is set to the number of pages predicted by the pre-diagnosis. The number of printed pages stored in the HDD unit 208 is read, and automatic repair is executed when the number of printed pages reaches the set number. If the number of printed pages is not the number required for automatic repair (No), the process proceeds to S407.

[0045] If the number of discs to be automatically repaired is set to Yes, the process will proceed to S406 and the automatic repair will be executed. The timing of the automatic repair may also be determined according to the user's instructions. In that case, the process will proceed to S407 after the completion of process S404.

[0046] In S406, the CPU 214 performs automatic repair according to the diagnostic results stored in the HDD unit 216. After the automatic repair is performed, the process moves to S407. In S407, it is determined whether the job has finished. If the job is still ongoing (No in S407), the process moves to S402. If the job has finished (Yes in S407), this flow ends. Automatic repair includes, for example, cleaning the wires and grid of the corona charger, which is a means of charging the photoreceptor drum.

[0047] <Features that can be extracted> Figure 6 is a schematic diagram showing the setting of feature extractable items. Figure 7 is a diagram showing an example of feature extractable items to be saved in association with RIP data. In this embodiment, eight feature extractable items are set as combinations of four types of colors: cyan, magenta, yellow, and black, and two types of defects in contrast. Defects in contrast refer to whether the defect occurs in the darker direction (positive contrast direction) or the lighter direction (negative contrast direction). Furthermore, each feature extractable item is represented by a feature extractable map (701-708) in which pixels from which features can be extracted are set to 1 and pixels from which features cannot be extracted are set to 0.

[0048] For example, suppose an image defect occurs in image 605 printed from RIP data 601, which includes areas with high black density 602, areas with low black density 603, and white areas 604 for monochrome (black and white printing). If vertical streaks 612 in the negative contrast direction occur at the main scanning position X1, the image defect will be apparent in areas with high black density 606, but not in white areas 608 or areas with low black density 607. For the feature of negative black contrast, areas with black density above a certain density can be feature extracted.

[0049] Therefore, the map 708 of extractable features in the negative contrast direction of black is saved by setting a 1 for pixels with a black density exceeding 40% (615) to indicate a detectable feature, and setting 0 for other pixels as locations where feature extraction is not possible (616, 617). Also, if a vertical streak 613 in the positive contrast direction of black occurs at the main scan position X2, the vertical streak will be visible in the white area 611 and in areas with low black density 610, but it will not be visible in areas with high black density 609. For the feature of positive contrast in black, feature extraction is possible in areas where the black density is below a certain density.

[0050] Therefore, in the map 707 of extractable features in the positive contrast direction of black, pixels with a black density of 60% or less are marked with a diagnosable 1 (620, 621), and all other pixels are marked with a 0 (619) as undiagnosable locations.

[0051] Furthermore, it is impossible to extract features of cyan, magenta, and yellow in the negative (paper white) direction from the monochrome (black and white printing) RIP data 601. Therefore, in the case of monochrome RIP data, feature extraction maps 702, 704, and 706 are saved as items for which feature extraction is impossible for cyan, magenta, and yellow in the negative contrast direction. On the other hand, feature extraction of cyan, magenta, and yellow in the positive direction is possible only from the white background area 602 without black, and feature extraction maps 701, 703, and 705 are saved as such.

[0052] Furthermore, the diagnostic items are not limited to the color and contrast direction mentioned above; they can also include area and flatness. In addition, any method that identifies locations where feature extraction is possible is acceptable, regardless of the map shape. For example, instead of judging each pixel, the RIP data could be divided into multiple blocks, and the diagnostic criteria could be set for each block.

[0053] <Precursor diagnosis execution process> The S403 precursor diagnosis process according to this embodiment will be explained in detail with reference to the figures. Figure 8 is a flowchart showing the procedure of the image precursor diagnosis process performed by the precursor diagnosis unit 109. Figure 8 shows the flow of the precursor diagnosis process. Each step in Figure 8 is performed by the CPU 214 of the precursor diagnosis unit 109.

[0054] In S801, the CPU 214 executes the process of reading the recording medium using the image reading units 331 and 332. The read image of the recording medium to be judged is saved as a precursor diagnosis target image in the HDD unit 216 of the diagnostic unit 109. Once the precursor diagnosis target image is saved, the process proceeds to S802.

[0055] In S802, the CPU 214 compares a reference image with a target image for early detection of defects in the printing section to detect potential defects. In this embodiment, the reference image and the target image for early detection are compared, and a difference value is calculated to detect potential defects. Alternatively, a correction unit may be provided to correct the nonlinear relationship between the signal value and brightness of the target image for early detection acquired by the image reading unit 311, and the signal value of the early detection image may be corrected before calculating the difference image data. If the calculated difference value exceeds a threshold, a difference is detected, and 1 is set in the difference image data. Conversely, if it falls below the threshold, 0 is set in the difference image data.

[0056] In this embodiment, the threshold value is set to a value with an even smaller size and lower contrast than the level set in S401. For example, if level 7 (510) (size 400 μm, contrast 30%) is set as an image defect in S401, then level 9 (504) (size 200 μm, contrast 10%) is set as the detection threshold. The difference image data, which is binary data indicating the presence or absence of a difference, is saved in the HDD unit 216, and the process proceeds to S803.

[0057] Once the creation of the differential image data is complete, in S803, the CPU 214 determines whether or not a potential precursor has occurred. This determination is made by checking whether or not there is data containing the number 1 in the differential image data. If the CPU 214 determines that no potential precursor has occurred (No in S803), this flow terminates. On the other hand, if the CPU 214 determines that a potential precursor has occurred (the differential image data contains the number 1) (Yes in S803), the process moves on to S804.

[0058] In S804, the CPU 214 extracts features from the image data to be diagnosed, the differential image data, and the diagnostic items linked to the reference image, in order to identify the part where a potential defect in the printing unit 107 is occurring and to predict the timing of the failure. From the image data to be diagnosed and the diagnostic items corresponding to the differential region determined to have a "difference" in S802, feature extraction of the difference is performed. In this feature extraction process, for example, colorant information and contrast information are obtained according to the diagnostic items. The colorant information is information on which color (yellow, magenta, cyan, or black) is occurring in the differential image. The contrast information is information that expresses whether the contrast of the potential defect is in the positive or negative contrast direction as a positive or negative numerical value. At this time, colors and contrast directions (positive or negative contrast) that are not set in the diagnostic items determined from the RIP data are not extracted as features.

[0059] Furthermore, size information such as the width (size in the main scanning direction) and height (size in the sub-scanning direction) of the precursor candidate, as well as shape information such as dot shape, vertical streak shape, and horizontal streak shape, are acquired. In this embodiment, an example is described in which the acquisition of shape information is determined from the aspect ratio of the width and height of the acquired size information. Specifically, if the aspect ratio obtained by width ÷ height exceeds a predetermined threshold, the shape is determined to be a horizontal streak. If the aspect ratio is less than or equal to the threshold, the shape is determined to be a vertical streak, and anything that does not fit either is determined to be a dot. Note that the acquisition of shape information is not limited to the above example; any method that can determine the shape of the precursor, such as whether it is a dot, horizontal streak, or vertical streak, is acceptable. For example, if the width is greater than or equal to the threshold, it may be determined to be a horizontal streak, if the height is greater than or equal to the threshold, it may be determined to be a vertical streak, and everything else may be determined to be a dot. Another feature is the coordinate information indicating the position in a direction perpendicular to the transport direction of the recording medium within the printing unit 107.

[0060] In S805, the CPU 214 identifies the parts that are the cause of the precursor candidate within the printing unit 107 and the image reading unit 331, based on the characteristic information of the difference region obtained in S804. In the case of dots or horizontal streaks, it selects combinations with the same color and high similarity within the difference region, and identifies which part is causing the precursor based on the cycle of the selected combination.

[0061] This embodiment describes a method for determining highly similar combinations using a known template matching technique. Images of potential precursors are compared using template matching, and the highest value is taken as the similarity between the two precursors. Precursors whose calculated similarity is above a predetermined threshold are determined to be highly similar combinations. Note that the similarity determination method is not limited to the above; any method that determines whether or not potential precursors are similar is acceptable. For example, a method that uses machine learning to determine the similarity between images, or a method that calculates similarity by comparing the features or feature points of the potential precursor images, may also be used.

[0062] Next, the distance in the sub-scan direction between similar precursor candidates is calculated, and if that distance is a multiple of the period of a certain part, that part is identified. Periodic precursors are characterized by occurring periodically at the same main scan position and with the same color as the precursor-generating part. For example, suppose a period correspondence table is prepared in advance where parts and period information correspond. Figure 22 shows an example of a period correspondence table. When the period distance is a multiple of the period information 2102, the corresponding part 2101 is identified as the causative part. Specifically, when the distance in the sub-scan direction between similar precursor candidates is a multiple of 96 mm (2102), such as 96 mm or 198 mm, the photoreceptor drum 2101 is determined to be the causative part. The multiple of the period distance and the distance in the sub-scan direction between similar precursor candidates do not need to be exactly the same; a margin may be allowed. Furthermore, if identification using period information is difficult, or for vertical streaks that continue to occur at the same main scan position, characteristic information such as size and contrast is used to identify the part. The LS unit 2113 is one example, and it is a part in which vertical streaks occur when the periodic information 2114 is set to "none".

[0063] Furthermore, the method for identifying parts is not limited to the above. Any method that can identify the cause is acceptable, including machine learning-based determination or identification by matching with past databases. Also, if there is insufficient feature information and the cause cannot be identified, it is not necessary to narrow it down to a single cause, and multiple candidate causes may be sought. After identifying the cause, the current number of printed pages stored in the HDD unit 208 is read, the extracted features are linked to the affected part and stored in the HDD unit 216, and the process proceeds to S806.

[0064] In S806, the CPU 214 performs a process to determine whether a potential precursor is a component that undergoes a change in lifespan over time (whether it is a precursor or a defect that does not undergo a change in lifespan over time). Details of the process for determining the change in lifespan over time will be described later in the section on the process for determining the change in lifespan over time. The CPU 214 stores the determination result in the HDD unit 216. For example, if the lifespan of the component changes over time, 1 should be stored, and if it does not change over time, 0 should be stored. This method is not limited to any method that indicates whether or not the lifespan of the component changes over time.

[0065] In S807, the CPU 214 determines whether the component lifespan has changed over time based on the data stored in the HDD section 216 in S806. If the component lifespan does not change over time (No in S807), the process terminates this flow. If the component lifespan does change over time (Yes in S807), the process proceeds to S808.

[0066] In S808, the CPU 214 predicts the number of prints that will reach an image quality defect level based on the component identified in S805, the size and contrast of the precursors, and the characteristic information of past precursors stored in the HDD unit 216, as well as the failure timing prediction table for each component. Details of the prediction method will be described later in the failure timing prediction section. The predicted number of prints is stored in the HDD unit 216, and the process proceeds to S809.

[0067] Next, the CPU 214 determines in S809 whether automatic repair is possible. Examples of cases that cannot be automatically repaired include those requiring user action, such as cleaning dirt from the reading glass surfaces of the image reading units 331 and 332 of the diagnostic unit 109, or adjusting the recording medium being used, as well as those requiring service technician action, such as replacing parts. Cases that cannot be automatically repaired also include reading errors in the image reading unit and issues with fibers or foreign objects present in the recording medium before image formation. If automatic repair is not possible, the process moves to S811.

[0068] Items that can be automatically repaired are those that can be automatically restored in the printing unit 107, such as cleaning the wires and grids of the corona charger, which is the means for charging the photoreceptor drums provided in the image forming stations 304-307 of the printing unit 107, by a charger cleaning mechanism (not shown). If an item can be automatically repaired, the process proceeds to S810.

[0069] In S810, the CPU 214 stores the details of the automatic repair in the HDD 216, linked to the number of images up to the level of image defect stored in the HDD 216. For example, if a precursory event occurred in the corona charger, which is the charging means for the photoreceptor drum, cleaning the wires of the corona charger is saved as the content of the automatic repair. After saving is complete, the process moves on to S811.

[0070] In S811, the CPU 214 saves the notified diagnostic result to the HDD unit 216. If there are no potential warning signs, it saves that there is no problem. If there are potential warning signs, it saves the predicted number of discs and characteristic information. After saving is complete, this flow ends. In the case of No in S803 as described above, the flow shown in Figure 8 ends when either S808 or S809 is completed.

[0071] <Processing for determining changes in component lifespan over time> This section describes the details of the process for determining the change in component lifespan over time in S806. Precursors occur due to scratches, dirt, or deterioration of parts, and over time (as printing progresses), the component lifespan changes to printing defects. Therefore, these precursors appear repeatedly, and the component lifespan gradually approaches its end. However, depending on the material of the component causing the printing defect and the cause of the defect, some parts may not change their lifespan over time even as the number of printed sheets increases, or sudden defects may occur. Therefore, it is necessary to determine whether the detected candidate precursors are actually precursors and then process accordingly. This embodiment describes an example of determining whether a component's lifespan changes over time on a part-by-part basis.

[0072] Figure 9 is a flowchart showing the procedure for determining the change in component lifespan over time. Each step in Figure 9 is executed by the CPU 214 of the predictive diagnostic unit 109. In S901, the CPU 214 determines whether the issue has been detected more than a specified number of times in the past. This is to determine whether the suspected issue is sudden or not. Since suspects tend to appear repeatedly, sudden failures are judged not to be suspects. The number of occurrences can be one that has been stored in the HDD unit 216 in advance, or it can be input from an external source. In addition, different numbers of occurrences may be set for each part. If the issue has occurred more than a specified number of times (Yes in S901), the process moves to S902. If the issue is a sudden failure (No in S901), the process moves to S903.

[0073] In S902, the CPU 214 determines whether the component lifespan changes over time according to the factor part stored in the HDD unit 216 by the part identification process in S805. It compares the factor part with the list of parts previously stored in the HDD unit 216. Figure 22 shows an example of a correspondence list between factor parts and the possibility of component lifespan changes over time. If the possibility 2103 of component lifespan changes over time for the suspected factor is "none", it is determined that the defect is one in which the component lifespan does not change over time.

[0074] For example, the fixing roller 2110, LS unit 2114, developing sleeve 2116, and secondary transfer belt 2119 have "no" possibility of changes in component lifespan over time (2112, 2115, 2118, 2121). Therefore, the fixing roller 2110, LS unit 2114, developing sleeve 2116, and secondary transfer belt 2119 are judged to be defective as their component lifespan does not change over time.

[0075] If it is determined that the component lifespan will not change over time, the process proceeds to S904. If the possibility of component lifespan change over time 2103, a candidate for a precursor, is "yes", it is determined that the component lifespan will change over time. Since the possibility of component lifespan change over time 2106 for the photoreceptor drum 2104 and the possibility of component lifespan change over time for the charging roller 2107 are both "yes", it is determined that the component lifespan will change over time, and the process proceeds to S907.

[0076] In S903, CPU214 saves a notification of a sudden malfunction to HDD216 stating that there are no problems. Since this is a sudden malfunction that the user did not identify as a printing error, it is unlikely to occur again and no action is required. Therefore, a notification of "no problems" is issued.

[0077] In S904, the CPU 214 stores notification information about recurring defects in the HDD unit 216, even though the component lifespan does not change over time. If the component lifespan of a potential defect does not change over time, it will not result in a failure at the currently set level. However, since raising the setting level may result in a failure, the inspection level at which a failure occurs is saved as a notification. In this embodiment, the case where a failure inspection level is notified is described. The level at which an image defect is judged is calculated from the size and contrast of the feature information. If the level is changed to that level, the fact that an image defect will occur is saved as a notification. Once saving is complete, the process moves to S905.

[0078] CPU214 deletes the factor and characteristic information in S905. It deletes the factor parts and characteristic information that were stored in HDD216. After the deletion is complete, processing is transferred to S906.

[0079] In the S906, the CPU 214 stores the result of the component lifespan change determination over time, which is "component lifespan does not change over time," in the HDD unit 216. For example, it stores whether or not component lifespan changes over time as a binary value. If component lifespan changes over time, it sets the component lifespan change determination result to "1," and if component lifespan does not change over time, it sets it to "0." In other words, it stores the component lifespan change determination result of "0."

[0080] In S907, the CPU 214 saves the result of the component lifespan change over time, which is "component lifespan changes over time," to the HDD unit 216. The result of the component lifespan change over time judgment, "1," is saved. When the processing in S906 or S907 described above is completed, the flow shown in Figure 9 is terminated.

[0081] <Failure timing prediction> This section describes how to predict the timing of failures leading to image defects in the S806. In this embodiment, the number of prints that will result in image defects is predicted based on the size and contrast information of the same part stored in the HDD unit 216 during past pre-diagnosis. The method for predicting the number of prints that will result in image defects from the changes in the size and contrast of the occurring pre-diagnoses will be explained with reference to Figure 10.

[0082] For example, suppose the current precursor diagnosis results, after printing 300 pages, indicate that precursor B has occurred in the black drum, with a size of 275 μm and a contrast of 20%. In a past precursor diagnosis, after printing 100 pages, information about precursor A, with a black drum size of 270 μm and a contrast of 19%, was stored. After printing 200 pages, the size has decreased by 5 μm and the contrast by 1%.

[0083] Let's consider the case where the lifespan of the components approaches in proportion to the number of images. If the image defect level set in S401 is level 7 (506), then an image defect value of 400 μm in size and 30% in contrast is considered an image defect. From the perspective of size, it can be predicted that the image will progress to defect level C after another 5000 images, and from the perspective of contrast, it can be predicted that the image will progress to defect level D after another 2000 images.

[0084] If either the size or contrast exceeds the image quality level, and the image quality level has reached that point, then printing another 2000 pages will cause the contrast to reach the image quality level. Therefore, the predicted number of pages until image quality deteriorates is 2000. Thus, since the current number of printed pages is 300, it can be predicted that the image quality may deteriorate after 2300 pages (2000 pages). Note that predictions can be made not only from a single past print run, but also by drawing an approximation curve based on the trends over multiple past print runs.

[0085] The CPU 214 saves the predicted number of prints that will result in image defects to the HDD unit 216 and proceeds to S807. Alternatively, the number of prints and the rate of change for each part's size and contrast may be stored in advance and referenced. The case where a failure timing prediction table for each part is stored in advance is described below. Figure 11 is an example of a prediction table.

[0086] As shown in Figure 11, the changes in size 1102 and contrast 1103 per 100 images for part 1101 are stored. For example, consider the case where a black drum shows signs of size 275 μm and contrast 20%, and level 7 (506) is set as the image defect level.

[0087] When the image quality drops to a level of 400 μm in size and 30% in contrast, the size changes by 400 μm - 275 μm = 125 μm, and the contrast changes by 30% - 20% = 10%. The photosensitive drum changes size by 2.5 μm and contrast by 0.5% per 100 sheets. Therefore, the number of sheets required to reach the point of image defects is 125 μm ÷ 2.5 μm × 100 sheets = 5000 sheets in terms of size, and 10% ÷ 0.5% × 100 sheets = 2000 sheets in terms of contrast.

[0088] If we assume that an image is considered defective when either size or contrast reaches a defective level, then it will reach that level in 2000 more prints. If the current number of printed pages is 300, then we can predict that the image will reach a defective level at 2300 prints (2000 prints later). Alternatively, if a specific part cannot be identified and there are multiple possible parts, the part can be identified by comparing the changes in size and contrast of the precursors with the changes in each part. The calculated changes are then compared with the pre-recorded rate of change for each part to identify the precursor that most closely matches the changes in that part.

[0089] Furthermore, the prediction method only needs to be able to predict how many more images will be needed after detecting a precursor to a defective image. A machine learning method that uses the precursor images, features, and the current image defect level as input to predict how many more images will be needed to reach a defective image level is also acceptable.

[0090] <Diagnosis Result Notification> This section describes the settings for diagnostic result notifications in S401 and the details of result notifications in S404. CPU 214 configures the result notification settings in S401 and saves them to HDD unit 216. This section details how S806 notifies the results stored in HDD unit 216 according to the settings saved in HDD unit 216 in S401.

[0091] The settings for result notifications in S401 will be explained based on Figure 12. Displays 1201, 1202, 1203, and 1204 in Figure 12 are schematic diagrams of the setting screens displayed on the UI display unit 241. Display 1201 is the result notification setting screen. In this embodiment, there are two methods for displaying notifications: popup display and graph display, and the case where the display content of each can be set will be described. The user can set each display by pressing the popup display setting button 1205 and the graph display setting button 1206 on display 1201. Pressing button 1205 transitions to the popup display selection screen of display 1202. Pressing button 1206 transitions to the graph display selection screen of display 1203. Depending on the cause of the warning, the response may be automatic repair or the user may perform cleaning. For each response, it is possible to select whether to display a graph display or a popup display. In the settings screens for displays 1202 and 1203, you can toggle the display of cleaning items 1207 and 1210 by checking the on and off checkboxes. Similarly, you can toggle the display of automatic repair items 1208 and 1211 by checking the on and off checkboxes.

[0092] Buttons 1209 and 1212 are advanced settings buttons. Pressing them transitions to display 1204, where you can configure the display details. In display 1204 of the advanced settings, you can configure item 1213. You can set which unit to display for the number of items 1216, the time item 1217, and the job item 1218 by checking the corresponding checkbox. Additionally, in the display timing item 1214, you can set the numerical value 1219 using the plus / minus buttons to trigger a notification when the NG timing falls below the set number of items, according to the unit of the display unit item 1213. In the repetition item 1215, you can set the timing for repeated notifications according to the unit of the display unit item 1213 by setting the repetition timing item 1220 using the plus / minus buttons.

[0093] The values ​​1219 and 1220 can be entered as numerical values, not just based on the plus / minus button settings. Furthermore, these values ​​have preset values ​​for each unit selected in the display unit item 1213, and the preset values ​​can be set according to the units checked in the display unit item 1213. Additionally, each unit can have upper and lower limits, making it impossible to set values ​​exceeding these limits. The settings configured in these ways are saved to the HDD unit 216.

[0094] In S404, the CPU 214 issues notifications according to the settings and notification content stored in the HDD unit 216. Except when a precursor is detected, the notification content is displayed on the UI display unit 241 according to the notification content. If a precursor is detected, the notification content is displayed according to the notification settings in S401. Figures 13 and 14 show examples of notification displays. The display timing is determined based on the value in the display timing item 1214, and if the predicted number of discs stored in the HDD unit 216 is less than or equal to the number displayed in the display timing item 1214, the precursor detection result is displayed. If the predicted number of discs is greater than the set number displayed in the display timing item 1214, no notification regarding that precursor is issued, and no precursor is detected. In addition, if multiple precursors are detected, or if a defect is detected that does not change the component life over time along with the precursor, they may be displayed side by side. Alternatively, only the one with the earliest NG timing may be displayed as a representative, and other diagnostic results may be switchable after pressing the details button.

[0095] Figure 13 shows an example of a pop-up display. When the checkboxes for items 1207 and 1208 in Display 1202 are checked to enable display settings, the precursor results are displayed as in Display 1301 and Display 1302. If the automatic repair item 1208 in Display 1202 is turned on and the number item 1216 in Display 1204 is checked, the number of images will be displayed in message 1303, which indicates when the image defect occurs, and the countermeasures will be displayed. The countermeasures may include, for example, that automatic repair must be performed. Also, if the cleaning item 1207 in Display 1202 is turned on and the time item 1217 in Display 1204 of the settings screen is checked, the time will be displayed in message 1305, which indicates when the image defect occurs, and the parts that need cleaning will be displayed.

[0096] Figure 14 shows an example of a graph display. When the checkbox is checked in Display 1210 or Display 1211 of Display 1203 in the popup display settings, the precursor results are displayed as in Display 1301 and 1302. In this embodiment, we describe the case where a change prediction curve 1402 is calculated from the size changes of precursors detected in the past, and the timing of prediction point A, where the image defect size of 500 μm is reached, is displayed. Note that the indicator for determining an image defect is not limited to size, but can be anything that shows how much the component life has changed, and a rank that ranks contrast or degree may also be used.

[0097] If you check the number of pages 1216 in display 1204, the horizontal axis will represent the number of printed pages, and the point at which an image defect will occur (NG) is 5000 pages after the current number of pages (1403) reaches the predicted point A.

[0098] Furthermore, the notification of the diagnosis results is not limited to the methods described above. Any method of notifying the results is acceptable; for example, the results may be displayed when the "Precursor Diagnosis Results" button is pressed. In addition to graphs and pop-up displays, the results may also be displayed in a time-series format or as a list or table for each component. Selecting a precursor or component item from the list may transition to a detailed information or graph screen, and different colors may be used to display them for easier identification.

[0099] (Variation 1) Example 1 described an example of notifying diagnostic results according to the diagnostic result notification settings. However, when the print level is changed or as the number of printed pages increases, the NG timing that was notified may change significantly if the speed of change in component life changes. Figures 15 and 16 are used to explain the change in NG timing. Figure 15 is a diagram that explains the NG timing when the NG level is changed. At time 1403, the predicted NG timing point A predicted by the component life curve 1402 with an NG level of 500 μm is 5000 pages. However, when the NG level is changed to 300 μm, the NG timing changes to predicted point A', which is 3000 pages.

[0100] Figure 16 shows a case where the predicted point changes as the number of printed pages increases. At time 1602, the predicted NG timing in the component life curve 1601 is 5000 pages after predicted point B. However, at time 1604, 500 pages later, the component life change in the component life curve 1603 has progressed faster than predicted, and the NG timing has shifted to predicted point B'. In the transition to predicted point B, the predicted NG timing would occur 4500 pages later (5000 pages - 500 pages), but with the shift to predicted point B', the NG timing becomes 3000 pages later. In this way, when the predicted NG timing differs significantly from the timing previously notified, it may mislead the user. Therefore, an example of implementing a change notification when a change occurs is described.

[0101] Figure 17 is a schematic diagram of the fluctuation notification settings and fluctuation content notification. The CPU 214 sets the notification to be issued when a fluctuation occurs in the S401 predictive diagnostic settings and saves it to the HDD unit 216. Then, the CPU 214 notifies of the fluctuation in S404 according to the settings saved in the HDD unit 216.

[0102] Change notification settings are configured on the change notification settings screen 1702. You can enable or disable change notifications for each item, such as cleaning (1702) and automatic repair (1703), by checking the corresponding checkbox.

[0103] The notification fluctuation amount 1704 allows you to set how much fluctuation triggers a notification. In this embodiment, we describe the case where the number can be set using plus or minus. Note that the fluctuation amount may be set in the display unit 1213 of the detailed setting 1204 of S401 and displayed based on that unit, or the unit and amount may be selectable or inputtable.

[0104] This section describes how to display change notifications as pop-ups in the change display 1705. By displaying the change in NG timing in the same way as the timing change in 1706, the user is notified that the NG timing has changed. Note that the notification only needs to convey that a change has occurred, and it is also acceptable to display a message indicating that a change has occurred on the graph display. Alternatively, the timing before and after the change may be displayed together.

[0105] (Modification 2) Example 1 described a case where the NG timing was predicted from the component life cycle progression of previously detected warning signs. However, the speed of component life change in warning signs also varies depending on the job content and environment. Figure 18 shows an example where the component life change speed differs depending on the printing conditions.

[0106] This section describes the case where a warning sign is occurring in the magenta drum. While component life curve 1803 estimates the progression from the detection history of warning signs detected between the past detection time 1806 and the present time 1805, component life curves 1802 and 1804 represent the fluctuations in the speed of component life change when the amount of magenta toner used differs from the past.

[0107] Component life curve 1802 represents a scenario where magenta toner usage increases significantly, resulting in a faster rate of component life change compared to component life curve 1803. Therefore, the failure timing shifts earlier, from 7,000 pages at predicted point Y to 5,000 pages at predicted point X. Conversely, if toner usage is low, the predicted component life curve 1804 shows a slower rate of component life change compared to component life curve 1803.

[0108] Therefore, the NG timing will be 9500 pages at the predicted point Z. In this way, there are factors that cause the rate of change in component lifespan to differ depending on printing conditions such as toner usage and environmental conditions such as humidity information. In such cases, predicting the failure time under the same conditions as in the past will reduce the accuracy of the NG timing prediction. Therefore, by displaying the component life curves 1802, 1803, and 1804 for multiple conditions side by side, as in condition 1807, it becomes possible to notify the NG timing when the conditions change.

[0109] Additionally, checkboxes can be added to each condition in 1807 to switch the display of component life curves 1802-1804. Furthermore, it is not necessary to display the component life curves side by side; after predicting the failure time for multiple conditions, only component life curve 1802 with the earliest NG timing, or only the 5000 NG timings at predicted point X, can be displayed.

[0110] Furthermore, the method for predicting failure timing based on different conditions is not limited to the method described above. Alternatively, the printing conditions may be obtained by analyzing previously scheduled print jobs before calculating the component life curve. For example, scheduled print job information can be obtained via an external LAN 105 or communication cable 260. Another method involves comparing future printing conditions related to the precursory factor with past printing conditions, such as magenta toner usage, to predict the failure timing. Another method involves obtaining humidity information via an external input or sensor and predicting the failure timing based on the humidity conditions. Moreover, the conditions considered in failure timing prediction may differ for each condition or factor. A list of conditions to be considered for each factor is stored in advance in the HDD unit 216, and the conditions to be considered are determined according to the detected precursory factor to perform the prediction. By performing failure prediction while considering conditions that affect the speed of component life change, prediction accuracy is improved, and the user can be accurately notified of the timing for automatic repair or cleaning.

[0111] The above describes a predictive image diagnostic system that detects potential precursors, determines whether the component lifespan changes over time, and issues notifications according to the determination result. This eliminates the need to predict failure timing other than foreshadowing, thereby reducing processing load and user burden.

[0112] (Second example) In this embodiment, the first embodiment described an example of determining the change in component lifespan over time based on the type of part, but the method for determining the change in component lifespan over time is not limited to the above. An example of determining the change in component lifespan over time based on the progression of component lifespan will be described. Whether or not a component lifespan changes is determined by the part, but in some cases, the component lifespan may not change over time depending on the cause of the part's failure. In the above case, a defect that does not cause a change in component lifespan over time is judged as a precursor, and its characteristic information is continuously stored, resulting in a notification that there is a precursor, which increases processing and user burden.

[0113] Therefore, we will describe a method for determining whether or not there is a change in component lifespan over time based on the changes in characteristic information of size and contrast over time. Figure 19 shows the detailed procedure for determining the change in component lifespan over time in S806 in this embodiment. The configuration of the printing system and the flow of the predictive diagnostic processing according to this embodiment are the same as in the first embodiment, so their explanation will be omitted. We will explain the processes S1901 to S1905 that differ from the first embodiment.

[0114] CPU214 determines in S901 whether it has detected multiple precursors to the same cause in the past. If it has not been detected more than the predetermined number of times (No in S901), the process proceeds to S1903. If it has been detected more than the predetermined number of times (Yes in S901), the process proceeds to S1901.

[0115] Next, the CPU 214 calculates the component lifespan trend in S1901. It reads the size and contrast of previously detected precursor candidates from the HDD unit 216 and plots them. In this embodiment, the case of plotting the component lifespan curve is described. Figure 20 is an example of a component lifespan curve. Graph 2001 shows the case where the component lifespan curve is calculated for size. The detected precursors are plotted at detection points 1, 2, 3, and 4 to obtain component lifespan curve 2002. Graph 2003 is the component lifespan curve with contrast as the axis. The detected precursors are plotted at detection points 1, 2, 3, and 4 to obtain component lifespan curve 2004. The axis for calculating the component lifespan curve is not limited to size or contrast; any axis that can determine the change in component lifespan over time is acceptable, and may include the number of occurrences per unit area or a rank determined by image or machine learning. The post-processing after calculating the component lifespan curve proceeds to S1902.

[0116] Furthermore, in S1902, the CPU 214 determines whether the component lifespan is changing over time based on the component lifespan curve obtained in S1901. In this embodiment, we describe an example of evaluating component lifespan curves 2002 and 2004 to determine whether or not there is a change in component lifespan over time. Specifically, one method is to find the minimum and maximum values ​​of the curve and determine that the component lifespan is changing over time if the difference between them is greater than or equal to a threshold, or to find an approximate curve and determine that the curve is changing over time if the slope of its tangent line is greater than or equal to a threshold. Alternatively, it may be determined that there is a change if either the size or the contrast changes, or only when both conditions change. In addition, thresholds and axes for determining the change in component lifespan over time may be defined for each factor. If the component lifespan is changing over time (Yes in S1902), the process moves to S1904. If the component lifespan is not changing over time (No in S1902), the process moves to S907.

[0117] Next, the CPU 214 stores in the HDD unit 216 the information that the component lifespan changes over time in the S907.

[0118] In S1903, the CPU 214 stores information on detected precursors and potential precursors in the HDD unit 216's past database. By saving the detected potential precursors and precursors for each contributing part and location, this information is used when calculating the component life curve.

[0119] Next, in S1904, the CPU 214 deletes from the past database any candidate components whose lifespan does not change over time. Furthermore, continuously storing past data may strain memory. Therefore, data older than a predetermined threshold may also be deleted, or older data may be deleted and overwritten if the number of data items stored in the database exceeds the upper limit. The subsequent processes S902 to S1904 are the same as in the first embodiment, so their explanation is omitted.

[0120] As explained above, we have described a method for determining changes in component lifespan over time based on the trends of previously detected precursor candidates. By making determinations based on the trends in component lifespan, it becomes possible to identify defects where the component lifespan does not change over time.

[0121] (Third example) This embodiment describes a case in which the change in component life over time is determined using parts and component life curves. The effects of the present invention are not limited to the examples in the first and second embodiments, and the change in component life over time may be determined using both the type of part and the component life curve. In the case of parts whose component life does not change over time, it is not necessary to calculate the component life curve, so the change in component life over time is determined by the type of part. By determining the change in component life, the processing load can be reduced and the accuracy can be improved by obtaining the component life curve for parts whose component life may change over time. Figure 21 shows the detailed procedure of the predictive diagnostic process in the third embodiment. The configuration of the printing system and the flow of the predictive diagnostic process in this embodiment are the same as in the first and second embodiments, so their explanation is omitted.

[0122] CPU214 first determines in S902 whether the lifespan of a component changes over time depending on the type of component. If the component's lifespan changes over time (Yes in S902), the process moves to S901. If the component's lifespan does not change over time (No in S902), the process moves to S904.

[0123] Next, CPU214 determines in S901 whether it has been detected multiple times in the past. If it has been detected in the past (Yes in S901), the process moves to S1901; if it has not been detected in the past (No in S901), the process moves to S1903.

[0124] The subsequent processes are the same as in the first embodiment S904-907 and the second embodiment S1903-1904, so the explanation will be omitted.

[0125] As explained above, by using the type of part and the progression of part lifespan to determine changes in part lifespan over time, it is possible to reduce processing load and improve the accuracy of the determination.

[0126] (Other examples) Although various examples and embodiments of the present invention have been described above, the spirit and scope of the present invention are not limited to the specific descriptions herein.

[0127] The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions. [Explanation of Symbols]

[0128] 101 Image forming apparatus 107 Printing Department 109 Precursor Diagnosis Department 206 CPU 214 CPU

Claims

1. A diagnostic imaging device connected to a printing device, An image reading means that reads a printed material formed by a printing device and generates a read image, A detection means for detecting image defects by comparing a reference image with the read image, It has a notification means for notifying the user of information, The notification means notifies the predicted failure time of a predetermined component if the defect in the image is due to a change in the lifespan of that predetermined component over time. A diagnostic imaging device characterized by the following features.

2. The image diagnostic apparatus according to claim 1, characterized in that the notification means does not notify the predicted failure time of the different component if the defect in the image is a defect not based on a change in the lifespan of a different component over time.

3. The image diagnostic apparatus according to claim 1, characterized in that the defect in the image is a defect that occurred before the predetermined component reached its lifespan.

4. The image diagnostic apparatus according to claim 1, further comprising a determination means for determining whether or not the defect in the image detected by the detection means is a defect based on a change in the lifespan of a component over time.

5. The image diagnostic apparatus according to claim 1, characterized in that when the notification means detects an image defect in a predetermined component, it changes the content of the notification indicating countermeasures for the image defect and the notification of the predicted failure time depending on the type of image defect.

6. The image diagnostic apparatus according to claim 5, characterized in that the notification indicating countermeasures for the aforementioned image defect contains instructions for the automatic repair of the predetermined part or instructions for cleaning the predetermined part.

7. The diagnostic imaging apparatus according to claim 1, characterized in that the prediction result includes at least one of the remaining number of prints for which failure of the predetermined component is predicted and a notification to clean the printing device for which failure of the predetermined component is predicted.

8. The notification means is characterized by making notifications according to pre-set settings, The aforementioned settings include at least one of the following: whether or not to send notifications, the timing of notifications, the method of notifications, recurrence settings, and notifications for changes in failure timing. The image diagnostic apparatus according to claim 1, characterized by the following:

9. The image diagnostic apparatus according to claim 1, characterized in that the prediction result is calculated based on a predetermined value corresponding to the type of predetermined component.

10. The image diagnostic apparatus according to claim 9, characterized in that the predetermined values ​​are size and contrast information.

11. The image diagnostic apparatus according to claim 1, characterized in that the predetermined component is at least one of a photosensitive drum and a charging roller.

12. The diagnostic imaging apparatus according to claim 2, characterized in that the different component is at least one of a fixing roller, an LS unit, a developing sleeve, and a secondary transfer belt.

13. A diagnostic imaging system having a printing device and a diagnostic imaging device, An image reading means that reads a printed material formed by a printing device and generates a read image, A detection means for detecting image defects by comparing a reference image with the read image, It has a notification means for notifying the user of information, The notification means notifies the predicted failure time of a predetermined component if the defect in the image is due to a change in the lifespan of that predetermined component over time. A diagnostic imaging system characterized by the following features.

14. The image diagnostic system according to claim 13, characterized in that the notification means does not notify the predicted failure time of the different component if the defect in the image is a defect not based on a change in the lifespan of a different component over time.

15. The image diagnostic system according to claim 13, characterized in that the defect in the image is a defect that occurred before the predetermined component reached its lifespan.

16. The image diagnostic system according to claim 13, further comprising a determination means for determining whether or not the defect in the image detected by the detection means is a defect based on a change in the lifespan of the component over time.

17. The image diagnostic system according to claim 13, characterized in that when the notification means detects a defect in the image in the predetermined component, it changes the content of the notification, which includes information indicating how to address the defect in the image and the predicted result of the failure time, depending on the type of defect in the image.

18. The notification means is characterized by making notifications according to pre-set settings, The aforementioned settings include at least one of the following: whether or not to send notifications, the timing of notifications, the method of notifications, recurrence settings, and notifications for changes in failure timing. The image diagnostic system according to claim 13, characterized by the following:

19. The image diagnostic system according to claim 13, characterized in that the predetermined component is at least one of a photosensitive drum and a charging roller.

Images