Information processing system and information processing program

Abstract

To provide an information processing system and an information processing program that predict occurrence of printing failure.SOLUTION: An estimation part 106 outputs failure information corresponding to new input information by inputting the new input information to a trained model learned in advance so as to output failure information related to occurrence of printing failure in a printing job when input information including information on the printing job and information on a printing device that processes the printing job is inputted.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to an information processing system and an information processing program. [Background technology]

[0002] Patent Document 1 discloses a printed matter inspection system that includes a processor that inspects the quality of printed matter and a display unit that displays the results of the inspection. The processor reads and executes a program to compare a scanned image obtained by scanning a printed matter of a page that is the target of inspection among the pages that make up a job with a reference image created using rasterized data of the page that is the target of inspection, inspects a first defect present in the scanned image at a first inspection level that is a preset initial level or a level set by the user, automatically inspects a second defect present in the scanned image at a second inspection level that is different from the first inspection level, and displays the first defect and the second defect on the display unit in a distinguishable manner.

[0003] Printing machines, such as inkjet continuous feed presses, installed in printing factories are equipped with automatic maintenance functions. Automatic maintenance involves the printing machine cleaning its own head box. Without automatic maintenance, clogged or dirty ink nozzles can cause blurred, streaked, and soiled printed materials. While the printing machine is running, a defect during printing can result in the rejection of all subsequent prints. In this case, the defective prints are unusable, resulting in wasted labor and consumable costs. Furthermore, the printing machine cannot be operated during automatic maintenance, and ink is consumed during purging. Therefore, frequent automatic maintenance reduces productivity and increases costs. Therefore, automatic maintenance is preferably performed when printing defects occur. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-136927 Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, an object of the present disclosure is to provide an information processing system and an information processing program that can predict the occurrence of printing defects. [Means for solving the problem]

[0006] In order to achieve the above object, the information processing system of the first aspect includes a processor, and when the processor receives input information including information about a print job and information about a printing device that processes the print job, the processor inputs new input information into a trained model that has been trained in advance to output defect information regarding the occurrence of printing defects in the print job, thereby outputting defect information corresponding to the new input information.

[0007] In an information processing system according to a second aspect, in the information processing system according to the first aspect, the information relating to the printing device includes information relating to maintenance of the printing device, the operating time of the printing device, or the time printing was performed by the printing device.

[0008] An information processing system according to a third aspect is the information processing system according to the second aspect, wherein the information relating to maintenance includes information relating to when the previous maintenance was performed.

[0009] In an information processing system according to a fourth aspect, in the information processing system according to the first aspect, the information relating to the print job includes information relating to the type of paper used for the print job, the type of printed material to be printed by the print job, the printing speed for the print job, or the image to be printed by the print job.

[0010] An information processing system according to a fifth aspect is the information processing system according to the first aspect, wherein the input information further includes scan data obtained by scanning a printed material printed by the print job.

[0011] An information processing system according to a sixth aspect is the information processing system according to the first aspect, wherein the defect information includes information about a printing defect whose occurrence can be suppressed by maintenance.

[0012] An information processing system according to a seventh aspect is the information processing system according to the sixth aspect, wherein the printing device performs printing using a droplet ejection head, and the maintenance is maintenance on the droplet ejection head.

[0013] An information processing system according to an eighth aspect is the information processing system according to the first aspect, wherein the defect information includes a probability that a printing defect will occur in the print job.

[0014] An information processing system according to a ninth aspect is the information processing system according to the eighth aspect, wherein the processor controls the printing device to perform maintenance before the print job if the probability of a printing defect occurring in the output print job is greater than or equal to a predetermined threshold.

[0015] An information processing system according to a tenth aspect is the information processing system according to the eighth aspect, wherein the processor notifies the user to perform maintenance before the print job if the probability of a printing defect occurring in the output print job is greater than or equal to a predetermined threshold.

[0016] The information processing program of the eleventh aspect causes a computer to input input information including information about a print job and information about a printing device that processes the print job, and then output defect information corresponding to the new input information by inputting the new input information into a trained model that has been trained in advance to output defect information regarding the occurrence of printing defects in the print job. [Effects of the Invention]

[0017] According to the first aspect, it is possible to predict the occurrence of printing defects.

[0018] According to the second aspect, it is possible to predict the occurrence of a printing defect based on information about the maintenance of the printing device, the operating time of the printing device, or the time during which printing is performed by the printing device.

[0019] According to the third aspect, it is possible to predict the occurrence of a printing defect based on information about the timing of the previous maintenance.

[0020] According to the fourth aspect, it is possible to predict the occurrence of printing defects based on information regarding the type of paper, the type of printed matter, the printing speed, or the image to be printed.

[0021] According to the fifth aspect, it is possible to predict the occurrence of printing defects based on scan data obtained by scanning a printed material.

[0022] According to the sixth aspect, it is possible to predict the occurrence of printing defects that can be suppressed by maintenance.

[0023] According to the seventh aspect, it is possible to predict the occurrence of printing defects that can be suppressed by performing maintenance on the droplet ejection head.

[0024] According to the eighth aspect, the probability of occurrence of a printing defect in a print job can be output.

[0025] According to the ninth aspect, maintenance can be performed before a print job that is highly likely to cause printing defects.

[0026] According to the tenth aspect, it is possible to notify the user to perform maintenance before a print job that is likely to cause a printing defect.

[0027] According to the eleventh aspect, it is possible to predict the occurrence of printing defects. [Brief explanation of the drawings]

[0028] [Figure 1] 1 is a diagram showing a schematic configuration of an information processing system according to an embodiment of the present invention; [Figure 2] FIG. 2 is a block diagram showing the main configuration of an electrical system of a printing device in the information processing system according to the present embodiment. [Figure 3] 2 is a block diagram showing the configuration of the main electrical system of a management device and a client computer in the information processing system according to the present embodiment. FIG. [Figure 4] FIG. 2 is a functional block diagram showing the functional configuration of a client computer in the information processing system according to the present embodiment. [Figure 5] FIG. 10 is a diagram illustrating an example of a trained neural network model. [Figure 6] 10 is a flowchart showing an example of the flow of a learning process performed in a client computer of the information processing system according to the present embodiment. [Figure 7] 10 is a flowchart showing an example of the flow of an estimation process performed in a client computer of the information processing system according to the present embodiment. [Figure 8] FIG. 10 is a diagram illustrating an example of a trained neural network model. DETAILED DESCRIPTION OF THE INVENTION

[0029] [First embodiment] An example of this embodiment will be described in detail below with reference to the drawings. In this embodiment, an information processing system in which a management device, a printing device, a client computer, etc. are connected to each other via communication lines such as various networks will be described as an example. Figure 1 is a diagram showing the schematic configuration of an information processing system 10 according to this embodiment.

[0030] 1, an information processing system 10 according to this embodiment includes a management device 11, a printing device 12, an inspection device 13, and a client computer 14. The management device 11, the printing device 12, the inspection device 13, and the client computer 14 are connected to each other via a communication line 18 such as a local area network (LAN), a wide area network (WAN), the internet, or an intranet. The management device 11, the printing device 12, the inspection device 13, and the client computer 14 are each capable of transmitting and receiving various data to and from each other via the communication line 18. In this embodiment, the client computer 14 issues a printing instruction to the printing device 12 via the management device 11, causing the printing device 12 to form an image in accordance with the print instruction.

[0031] Although FIG. 1 shows one management device 11, one printing device 12, one inspection device 13, and one client computer 14, there may be a plurality of each, or there may be a plurality of any of them.

[0032] The printing device 12 according to this embodiment has multiple functions, such as a printing function for performing print processing, a post-processing function for performing post-processing on paper on which an image has been formed, etc. The multiple functions may include a reading function for reading an original to obtain image information representing the original, a copying function for copying an image recorded on the original onto paper, a facsimile function for sending and receiving various data via a telephone line (not shown), a transfer function for transferring original information such as image information read by the reading function, etc., and a storage function for storing original information such as read image information.

[0033] In the following description, the facsimile function may be referred to as fax, the reading function as scan, the printing function as print, and the copying function as copy.

[0034] FIG. 2 is a block diagram showing the main configuration of the electrical system of the printing device 12 in the information processing system 10 according to this embodiment.

[0035] 2, the printing device 12 according to this embodiment includes a control unit 20. The control unit 20 may include a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory).

[0036] Meanwhile, the printing device 12 according to this embodiment includes a hard disk drive (HDD) 26 that stores various data, application programs, and the like. The printing device 12 is also connected to a user interface 22 and includes a display control unit 28 that controls the display of various operation screens and the like on the display of the user interface 22. The printing device 12 is also connected to the user interface 22 and includes an operation input detection unit 30 that detects operation instructions input via the user interface 22. In the printing device 12, the HDD 26, the display control unit 28, and the operation input detection unit 30 are electrically connected to a system bus 42. While the printing device 12 according to this embodiment uses the HDD 26 as a storage unit, this is not a limitation and a non-volatile storage unit such as a flash memory may also be used. Furthermore, while this embodiment uses a touch panel capable of displaying and inputting operations as the user interface 22, this is not a limitation and a user interface having a display and an operation unit that are separate may also be used.

[0037] The printing device 12 according to this embodiment also includes a print control unit 34 that controls the printing process performed by the printing unit 24, the transport of paper to the printing unit 24 by the transport unit 25, the post-processing performed by the post-processing unit 46, the reading process of the printed material performed by the inspection unit 47, and maintenance performed by the maintenance unit 48. The printing unit 24 performs printing using a droplet ejection head. The maintenance unit 48 performs maintenance on the droplet ejection head. The printing device 12 may also include a read control unit that controls the optical image reading operation performed by the document reading unit and the document feeding operation performed by the document transport unit. The printing device 12 also includes a communication line I / F (interface) unit 36 ​​that is connected to a communication line 18 and transmits and receives communication data to and from other external devices, such as a client computer 14, connected to the communication line 18. The printing device 12 may also include a facsimile I / F (interface) that is connected to a telephone line (not shown) and transmits and receives facsimile data to and from a facsimile device connected to the telephone line. The printing device 12 may also include a transmission / reception control unit that controls the transmission and reception of facsimile data via the facsimile I / F unit 38. In the printing device 12, the print control unit 34 and the communication line I / F unit 36 ​​are electrically connected to the system bus 42.

[0038] With the above configuration, the printing device 12 according to this embodiment uses the control unit 20 to control the display of information such as operation screens and various messages on the display of the user interface 22 via the display control unit 28. The printing device 12 also uses the control unit 20 to control the operation of the printing unit 24, conveying unit 25, post-processing unit 46, inspection unit 47, and maintenance unit 48 via the print control unit 34, and to control the sending and receiving of communication data via the communication line I / F unit 36. Furthermore, the printing device 12 uses the control unit 20 to grasp the operation content of the user interface 22 based on the operation information detected by the operation input detection unit 30, and executes various controls based on the operation content.

[0039] In this embodiment, an example of an application stored in the HDD 26 includes an application that executes a function such as printing.

[0040] When the printing device 12 prints based on the printing information, the inspection device 13 inspects the printed matter by comparing the rasterized image represented by the printing information with the scanned image of the printed matter obtained by the inspection unit 47.

[0041] Next, the configuration of the main electrical parts of the management device 11 and the client computer 14 according to this embodiment will be described. Fig. 3 is a block diagram showing the configuration of the main electrical parts of the management device 11 and the client computer 14 in the information processing system 10 according to this embodiment. Note that the management device 11 and the client computer 14 have general computer configurations, and therefore, the following description will be given using the management device 11 as a representative.

[0042] As shown in FIG. 3 , the management device 11 according to this embodiment includes a CPU 11A as an example of a processor, a ROM 11B, a RAM 11C, a storage 11D, an operation unit 11E, a display unit 11F, and a communication line I / F (interface) unit 11G. The CPU 11A controls the overall operation of the management device 11. The ROM 11B stores various control programs and parameters in advance. The RAM 11C is used as a work area when the CPU 11A executes various programs. The storage 11D stores various data and application programs. The operation unit 11E is used to input various information. The display unit 11F is used to display various information. The communication line I / F unit 11G is connected to a communication line 18 and transmits and receives various data to and from other devices connected to the communication line 18. The communication line I / F unit 11G may also be configured to be capable of directly communicating with each device using various well-known wireless communications. The above-described components of the management device 11 are electrically connected to one another via a system bus 111. In the management device 11 according to this embodiment, the storage 11D is used as a storage unit, and examples of storage include non-volatile storage units such as HDDs (Hard Disk Drives) and flash memories.

[0043] With the above configuration, the management device 11 according to this embodiment uses the CPU 11A to access the ROM 11B, RAM 11C, and storage 11D, to obtain various data via the operation unit 11E, and to display various information on the display unit 11F. In addition, the management device 11 uses the CPU 11A to control the transmission and reception of communication data via the communication line I / F unit 11G.

[0044] In the information processing system 10 configured as above, the management device 11 manages a series of manufacturing processes. The series of manufacturing processes includes, for example, a production process, a prepress process, a plate making process, a printing process, a processing process, and a delivery process.

[0045] Next, a description will be given of the functional configuration of the client computer 14. Fig. 4 is a block diagram showing an example of the functional configuration of the client computer 14.

[0046] As shown in FIG. 4, the client computer 14 is functionally configured to include a collection unit 101, a learning data storage unit 102, a learning unit 103, a model storage unit 104, a reception unit 105, an estimation unit 106, and an output unit 107.

[0047] The collection unit 101 collects learning data including pairs of input information related to past print jobs and defect information related to the occurrence of printing defects in the print jobs.

[0048] The input information may include information about the printing device 12 that processes the print job. The information about the printing device 12 may include information about maintenance of the printing device 12, the number of hours the printing device 12 has been running, the number of hours the printing device 12 has printed, or the number of hours the droplet ejection heads have been in use.

[0049] Specifically, the information regarding maintenance of the printing device 12 may include information regarding when the previous maintenance was performed. More specifically, the information regarding when the previous maintenance was performed may include, for example, the date and time when the previous maintenance was performed, or the time elapsed since the previous maintenance was performed.

[0050] The operating time of the printing device 12 includes, for example, the cumulative operating time of the printing device 12 since the previous maintenance was performed.

[0051] The time during which printing has been performed by the printing device 12 includes, for example, the cumulative time during which printing processing has been performed by the printing device 12 since the previous maintenance was performed.

[0052] The usage time of the droplet ejection head includes, for example, the cumulative usage time of the droplet ejection head since the droplet ejection head was attached.

[0053] The management device 11 has history information for managing information relating to orders for printed materials, manufacturing information, and information relating to the status of the printing device 12.

[0054] The collection unit 101 collects information related to the printing device 12 in past print jobs from the history information held by the management device 11.

[0055] The input information may include information about the print job, which may include information about the paper type, the type of print, the printing speed, or the image to be printed.

[0056] Specifically, paper types include, for example, coated, matte, 90kg fine paper, 110kg fine paper, long 3 envelopes (long size 3), long 4 envelopes (long size 4), Western long 3 envelopes (Western long size 3), square 3 envelopes (square size 3), square 4 envelopes (square size 4), bank transfer forms, slip paper, regular postcards, reply postcards, New Year's postcards, etc.

[0057] The types of printed matter include, for example, photo books, posters, magazines, flyers, envelopes, business cards, catalogs, newspapers, and the like.

[0058] Information about the image to be printed includes, for example, the proportion of the area to be printed on the paper, or the type of object to be printed.

[0059] The collection unit 101 acquires information about past print jobs from the history information held by the management device 11.

[0060] The results of inspections by the inspection device 13 corresponding to past print jobs are managed as historical information in the management device 11, and the collection unit 101 acquires the inspection results from the management device 11 and acquires defect information regarding printing defects whose occurrence can be suppressed by maintenance by the maintenance unit 48.

[0061] Specifically, the results of inspection by the inspection device 13 for past print jobs, whether they are OK or NG, and the causes of printing defects if they are NG, are managed as history information in the management device 11. The collection unit 101 acquires the results of inspection by the inspection device 13 and the causes of printing defects if they are NG from the management device 11, and acquires defect information regarding printing defects that can be suppressed by maintenance by the maintenance unit 48. Printing defects that can be suppressed by maintenance by the maintenance unit 48 include, for example, blurred marks, streaks, and soiling. The defect information may include the causes of printing defects.

[0062] The learning data storage unit 102 stores a plurality of pieces of learning data collected by the collection unit 101.

[0063] The learning unit 103 receives input information based on a plurality of learning data and constructs a neural network model for outputting defect information relating to printing defects that can be suppressed by maintenance and correspond to the input information.

[0064] Specifically, the trained neural network model receives input information including at least one of information regarding maintenance, the operating time of the printing device 12, the time printing has been performed by the printing device 12, the usage time of the droplet ejection head, the type of paper, the type of printed material, the printing speed, and information regarding the image to be printed, and estimates defect information regarding the occurrence of a printing defect that can be suppressed by maintenance, which corresponds to the input information (see FIG. 5). The estimated defect information regarding the occurrence of a printing defect includes the probability that a printing defect that can be suppressed by maintenance will occur. Deep learning can be used as an example of a learning algorithm, and the neural network model may be constructed so that when input information of training data is input, defect information of the training data is output.

[0065] More specifically, the input information of the learning data is used as input, and the probability of a printing defect occurring is estimated as the output of the model. The estimated probability of a printing defect occurring is compared with the defect information of the learning data to calculate the error in the defect information, and the parameters of the model may be updated so as to minimize the value of the error.

[0066] Here, the correlation between the various information included in the input information and the probability of occurrence of a printing defect included in the defect information will be described.

[0067] First, the longer the time since the last maintenance, the higher the likelihood that dirt has accumulated on the droplet ejection head, and the higher the probability that printing defects will occur. In this way, there is a correlation between information about maintenance and information about defects.

[0068] Furthermore, the longer the droplet ejection head is used continuously, the greater the likelihood of dirt accumulating on the droplet ejection head, increasing the probability of print defects. The droplet ejection head can dry out and cause nozzle clogging not only during printing but also when in standby mode. Thus, there is a correlation between the length of time the droplet ejection head is used and defect information.

[0069] Furthermore, the longer the printer 12 operates and the longer it prints, the greater the likelihood that dirt will accumulate on the droplet ejection head, increasing the probability of print defects. Thus, there is a correlation between the operating time of the printer 12, the time the printer 12 has printed, and the defect information.

[0070] Furthermore, from the print job information, it is possible to infer whether a printing defect may occur if printing is continued. For example, it is possible to determine whether a nozzle of a droplet ejection head that may cause blurring is being used for printing, or whether an image that may cause unevenness is being printed. In this way, there is a correlation between information about the print job and defect information.

[0071] The model storage unit 104 stores a trained neural network model.

[0072] The receiving unit 105 receives input information related to a new print job to be estimated.

[0073] The input information includes information about the printing device 12. For example, the information received from the management device 11 includes the time elapsed since the last maintenance was performed ("150 hours"), the operating time of the printing device 12 ("1000 hours"), the time printing has been performed by the printing device 12 ("800 hours"), and the usage time of the droplet ejection head ("200 hours").

[0074] The input information may also include information about the print job. For example, the input information may include the paper type "90 kg high-quality paper," the type of print "photo album," the print speed "10 ppm," the percentage of the area to be printed on the paper "30%," and the type of object to be printed "image," all of which are acquired from the management device 11.

[0075] The estimation unit 106 uses the trained neural network model stored in the model storage unit 104 to estimate defect information corresponding to the received input information.

[0076] Specifically, various pieces of information contained in the received input information are converted into data structures (e.g., scalar values, vectors, etc.) that can be input into a trained neural network model, and then input into the trained neural network model, and defect information is estimated from the output of the trained model.

[0077] The output unit 107 controls the printing device 12 to issue a notification according to the estimated defect information. Specifically, if the probability of occurrence of a printing defect included in the estimated defect information is equal to or greater than a threshold, the output unit 107 notifies the user to perform maintenance before the print job. For example, the output unit 107 controls the printing device 12 to display a message recommending maintenance on the user interface 22 of the printing device 12 or to turn on a lamp provided on the printing device 12 recommending maintenance. If the defect information includes the cause of the printing defect, a message according to the cause of the printing defect included in the estimated defect information may be used as the message recommending maintenance.

[0078] Next, specific processing performed in the information processing system 10 according to this embodiment configured as described above will be described.

[0079] First, in the client computer 14, the CPU 14A reads out the learning program from the ROM 14B or the storage 14D, loads it into the RAM 14C, and executes it, thereby performing the learning process shown in FIG.

[0080] In step S100, the CPU 14A functions as the collection unit 101 to collect learning data including pairs of input information related to a print job and defect information corresponding to the input information, and stores the collected learning data in the learning data storage unit 102.

[0081] In step S102, the CPU 14A, as the learning unit 103, takes input information as input based on a plurality of learning data, learns a neural network model for estimating defect information corresponding to the input information, stores the model in the model storage unit 104, and terminates the learning process.

[0082] Next, in the client computer 14, the CPU 14A reads out the estimation program from the ROM 14B or the storage 14D, loads it into the RAM 14C, and executes it, thereby performing the estimation process shown in Fig. 7 before processing the new print job to be estimated. At this time, it is assumed that various information included in the input information regarding the new print job to be estimated has been input.

[0083] In step S110, CPU 14A functions as reception unit 105 to receive input information related to a new print job to be estimated.

[0084] In step S112, the CPU 14A functions as the estimation unit 106 and uses the trained neural network model stored in the model storage unit 104 to estimate defect information corresponding to the received input information.

[0085] In step S114, the CPU 14A as the output unit 107 determines whether the probability of occurrence of a printing defect included in the estimated defect information is equal to or greater than a threshold. If the probability of occurrence of a printing defect is less than the threshold, the estimation process ends. On the other hand, if the probability of occurrence of a printing defect is equal to or greater than the threshold, the process proceeds to step S116.

[0086] In step S116, CPU 14A controls output unit 107 to display a message recommending maintenance on user interface 22 of printing device 12, and then ends the estimation process. This allows the user to understand the need for maintenance before processing the print job.

[0087] By performing the process in this manner, it is possible to predict the occurrence of a printing defect before processing a print job.

[0088] [Second embodiment] Next, an information processing system 10 according to a second embodiment will be described. Note that the information processing system 10 according to the second embodiment has the same configuration as the information processing system 10 according to the first embodiment, and therefore the same reference numerals are used and the description thereof will be omitted.

[0089] In the first embodiment, the case where defect information is estimated before a print job is processed has been described as an example, but in the second embodiment, defect information is estimated while a print job is being processed, which is a difference.

[0090] The collection unit 101 collects learning data including pairs of input information related to past print jobs and defect information related to the occurrence of printing defects that corresponds to the input information.

[0091] The input information may further include scan data obtained by scanning a printed material printed by the print job.

[0092] Specifically, the scan data includes, for example, a scan image obtained by the inspection unit 47, or a result of analyzing the scan image by the inspection device 13, or the like.

[0093] The scanned images obtained by the inspection unit 47 and the results of analyzing the scanned images by the inspection device 13 for past print jobs are managed as history information in the management device 11. The collection unit 101 acquires the scanned images obtained by the inspection unit 47 and the results of analyzing the scanned images by the inspection device 13 from the management device 11.

[0094] The learning unit 103 receives input information based on a plurality of learning data and constructs a neural network model for outputting defect information relating to printing defects that can be suppressed by maintenance and correspond to the input information.

[0095] Specifically, the trained neural network model accepts input information including at least one of information regarding maintenance, the operating time of the printing device 12, the time printing has been performed by the printing device 12, the usage time of the droplet ejection head, the type of paper, the type of printed material, the printing speed, information regarding the image to be printed, and scan data, and estimates defect information regarding the occurrence of printing defects that can be suppressed by maintenance and correspond to the input information (see Figure 8).

[0096] Here, the correlation between the scan data included in the input information and the defect information will be described.

[0097] From the scan data obtained by scanning the printed material printed by the print job, it is possible to measure the type of output that can be obtained from the currently operating droplet ejection head and printing device 12, and to predict whether printing defects may occur if printing continues. In this way, there is a correlation between the scan data and defect information.

[0098] 7 is performed while a new print job to be estimated is being processed. At this time, the scan data obtained by the inspection unit 47 for the print job is also input as input information.

[0099] This allows the user to know when maintenance needs to be performed while a print job is being processed.

[0100] The other configurations and operations of the information processing system 10 are the same as those of the first embodiment, and therefore will not be described again.

[0101] <Modification> The present invention is not limited to the above-described embodiment, and various modifications and applications are possible without departing from the spirit and scope of the present invention.

[0102] For example, if the estimated defect information indicates a probability of occurrence of a printing defect equal to or greater than a threshold, control may be performed to perform maintenance on the printing device 12. Specifically, if the probability of occurrence of a printing defect equals or exceeds a threshold, control may be performed to perform maintenance on the printing device 12 before a print job.

[0103] Furthermore, in the above embodiment, the trained neural network model estimates defect information related to a printing defect that can be prevented by maintenance. However, this is not limiting. The trained neural network model may estimate defect information related to a printing defect regardless of whether the printing defect can be prevented by maintenance. In this case, the defect information includes the probability of the printing defect occurring and the cause of the printing defect. If the probability of the printing defect occurring is equal to or greater than a threshold and the cause of the printing defect is a printing defect that can be prevented by maintenance, the output unit 107 may control the printing device 12 to perform maintenance before the print job or may notify the user to perform maintenance before the print job.

[0104] In addition, although an example has been described in which various types of input information are accepted and defect information is estimated, it is also possible to accept only a portion of the various types of input information rather than accepting all of the various types of input information and estimate defect information.

[0105] Furthermore, although the client computer 14 has been described as learning a model and estimating defect information, it may be configured as a learning device that learns a model and an estimation device that estimates defect information.

[0106] Furthermore, in the above embodiments, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPUs, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

[0107] Furthermore, the operations of the processors in the above embodiments may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. Furthermore, the order of the operations of the processors is not limited to the order described in the above embodiments, and may be changed as appropriate.

[0108] Furthermore, although the "system" in this embodiment is described as being composed of multiple devices as an example, it may also be composed of a single device that has some of the functions of the multiple devices.

[0109] The processing performed by the printing device 12 according to the above embodiment may be software-based, hardware-based, or a combination of both. The processing performed by the printing device 12 may also be stored as a program on a storage medium and distributed.

[0110] Furthermore, the present disclosure is not limited to the above, and it goes without saying that various modifications can be made without departing from the spirit of the present disclosure.

[0111] The following additional notes are provided regarding the above-described embodiments. (((1))) a processor, the processor comprising: When input information including information about a print job and information about a printing device that processes the print job is input, new input information is input to a trained model that has been trained in advance to output defect information related to the occurrence of printing defects in the print job, and defect information corresponding to the new input information is output. Information processing system.

[0112] (((2))) The information about the printing device includes information about the maintenance of the printing device, the operating time of the printing device, or the time when printing was performed by the printing device. The information processing system according to (((1))).

[0113] (((3))) The information processing system according to (((2))), wherein the information relating to maintenance includes information on when the previous maintenance was carried out.

[0114] (((4))) The information processing system described in any one of (((1))) to (((3))) wherein the information about the print job includes information about the type of paper used for the print job, the type of printed material to be printed by the print job, the printing speed for the print job, or the image to be printed by the print job.

[0115] (((5))) The information processing system according to any one of ((1))) to ((4))), wherein the input information further includes scan data obtained by scanning a printed material printed by the print job.

[0116] (((6))) The information processing system according to any one of ((1))) to ((5))), wherein the defect information includes information relating to a printing defect whose occurrence can be suppressed by maintenance.

[0117] (((7))) the printing device performs printing using a droplet ejection head, The information processing system according to (((6))), wherein the maintenance is maintenance for the droplet ejection head.

[0118] (((8))) The defect information includes a probability that a printing defect will occur in the print job. The information processing system according to any one of (((1))) to (((7))).

[0119] (((9))) The processor: When the probability of occurrence of a printing defect in the output print job is equal to or greater than a predetermined threshold, the printing device is controlled to perform maintenance before the print job is output. The information processing system according to (((8))).

[0120] (((10))) The processor: If the probability of occurrence of a printing defect in the output print job is equal to or greater than a predetermined threshold, a user is notified to perform maintenance before the print job is output. The information processing system according to (((8))).

[0121] (((11))) When input information including information about a print job and information about a printing device that processes the print job is input, new input information is input to a trained model that has been trained in advance to output defect information related to the occurrence of printing defects in the print job, and defect information corresponding to the new input information is output. An information processing program that causes a computer to perform certain tasks.

[0122] According to (((1))), it is possible to predict the occurrence of printing defects.

[0123] According to (((2))), it is possible to predict the occurrence of printing defects based on information about the maintenance of the printing device, the operating time of the printing device, or the time during which printing is performed by the printing device.

[0124] According to (((3))), it is possible to predict the occurrence of printing defects based on information about the timing of the previous maintenance.

[0125] According to (((4))), it is possible to predict the occurrence of printing defects based on information about the type of paper, the type of printed matter, the printing speed, or the image to be printed.

[0126] According to (((5))), it is possible to predict the occurrence of printing defects based on scan data obtained by scanning printed matter.

[0127] According to (((6))), it is possible to predict the occurrence of printing defects that can be suppressed by maintenance.

[0128] According to ((7)), it is possible to predict the occurrence of printing defects that can be suppressed by maintenance of the droplet ejection head.

[0129] According to (((8))), it is possible to output the probability of occurrence of a printing defect in a print job.

[0130] According to (((9))), maintenance can be performed before a print job that is likely to cause printing defects.

[0131] According to (((10))), it is possible to notify the user to perform maintenance before a print job that is likely to cause printing defects.

[0132] According to (((11))), it is possible to predict the occurrence of printing defects. [Explanation of symbols]

[0133] 10 Information Processing Systems 11 Management device 12 Printing device 13 Inspection equipment 14 client computers 24 Printing Department 46 Post-processing section 47 Inspection Department 48 Maintenance Department 101 Collection Department 102 Learning data storage unit 103 Learning Department 104 Model Memory Unit 105 Reception 106 Estimation part 107 Output section

Claims

1. a processor, the processor comprising: When input information including information about a print job and information about a printing device that processes the print job is input, new input information is input to a trained model that has been trained in advance to output defect information related to the occurrence of printing defects in the print job, and defect information corresponding to the new input information is output. Information processing system.

2. The information about the printing device includes information about the maintenance of the printing device, the operating time of the printing device, or the time when printing was performed by the printing device. The information processing system according to claim 1 .

3. 3. The information processing system according to claim 2, wherein the information relating to the maintenance includes information relating to when the previous maintenance was performed.

4. 2. An information processing system according to claim 1, wherein the information about the print job includes information about the type of paper used for the print job, the type of printed material printed by the print job, the printing speed for the print job, or the image printed by the print job.

5. The information processing system according to claim 1 , wherein the input information further includes scan data obtained by scanning a printed material printed by the print job.

6. The information processing system according to claim 1 , wherein the defect information includes information about printing defects whose occurrence can be prevented by maintenance.

7. the printing device performs printing using a droplet ejection head, 7. The information processing system according to claim 6, wherein the maintenance is performed on the droplet ejection head.

8. The defect information includes a probability that a printing defect will occur in the print job. The information processing system according to claim 1 .

9. The processor: When the probability of occurrence of a printing defect in the output print job is equal to or greater than a predetermined threshold, the printing device is controlled to perform maintenance before the print job is output. The information processing system according to claim 8 .

10. The processor: If the probability of occurrence of a printing defect in the output print job is equal to or greater than a predetermined threshold, a user is notified to perform maintenance before the print job is output. The information processing system according to claim 8 .

11. When input information including information about a print job and information about a printing device that processes the print job is input, new input information is input to a trained model that has been trained in advance to output defect information related to the occurrence of printing defects in the print job, and defect information corresponding to the new input information is output. An information processing program that causes a computer to perform certain tasks.

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