Image forming system and control program

Abstract

The present invention provides a parameter determination device that can derive the optimal control parameters for each type of paper. [Solution] The parameter determination device 10 has an acquisition unit 111 and a determination unit 112. The acquisition unit 111 acquires data on paper basis weight detected by a sensor. The determination unit 112 determines parameters related to paper processing from the acquired data on paper basis weight based on a program using a machine learning learning function.

Description

Technical Field

[0001] The present invention relates to Image forming system, and a control program.

Background Art

[0002] In recent years, in the color printing industry, image forming devices such as electrophotographic printers have been widely used. In the field of PP (Production Print) corresponding to the color printing industry, adaptation to various papers is required compared to the case of use in an office. And, in order to perform high-quality printing on these various papers, there is an image forming device that sets the paper characteristics stored in the paper feed tray in a plurality of items and performs paper processing such as printing under image forming conditions according to the set items.

[0003] In order to make such various paper settings, there is an image forming device provided with a sensor that automatically detects the characteristics of the paper used for printing (for example, Patent Documents 1 and 2). Furthermore, in recent years, a technique has also been proposed in which a plurality of types of physical property values regarding paper are acquired, the acquired plurality of types of physical property values are applied to a determination table prepared in advance, and control parameters such as a transfer voltage for controlling image forming conditions are determined (for example, Patent Document 3).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, conventional technologies such as those described in the above-mentioned patent document calculate one paper property value (dielectric thickness) related to the control parameter from multiple paper property values ​​(dielectric constant, resistance, paper thickness, etc.) detected from the paper, and then determine one control parameter by applying the calculated value to a pre-prepared table. This technology has the problem that the paper property value for determining the control parameter is secondarily obtained from multiple detection data, so the value is prone to errors. Furthermore, because the above technology determines the control parameter by referring to a pre-prepared table, it determines a control parameter whose value changes stepwise at predetermined intervals (ranges), and therefore has the problem that it is not possible to determine the optimal value of the control parameter.

[0006] The present invention has been made in view of the above circumstances, and aims to provide a parameter determination device, an image forming apparatus, a post-processing device, a paper feeding device, and a method for creating a determination model for deriving optimal control parameters for each type of paper. [Means for solving the problem]

[0007] The above objectives of the present invention are achieved by the following means.

[0008] (1) An acquisition unit that acquires data on paper basis weight detected by a sensor, A determination unit that determines paper processing parameters from acquired paper basis weight data based on a program using machine learning learning capabilities, Equipped with, The aforementioned data relating to paper basis weight is data relating to the amount of light transmitted when light is shone on the paper; this is a parameter determination device.

[0009] (2) The parameter determination device described in (1) above, wherein the learning function is configured by ensemble learning, which fuses multiple learners to generate a single learner.

[0010] (3) The learning function is a parameter determination device as described in (1) or (2) above, which is composed of a neural network.

[0011] (4) The parameter determination device according to any one of (1) to (3) above, wherein the acquisition unit further acquires information regarding the device status of a paper processing device that performs the paper processing, and the determination unit determines parameters related to the paper processing from the data regarding the paper basis weight and the information regarding the device status.

[0012] (5) The parameter determination device according to (4) above, wherein the acquisition unit acquires information regarding the device status of the paper processing device at a predetermined timing, and the determination unit determines parameters related to the paper processing for a plurality of sheets of paper.

[0013] (6) The parameter determination device according to (4) or (5) above, wherein the acquisition unit acquires information regarding the device status of the paper processing device at a predetermined timing, and the determination unit determines parameters related to the paper processing at the initial setup of the preparation for the print, for each pass of paper during the print, or at predetermined intervals between passes of paper.

[0014] (7) The parameter determination device according to any one of (1) to (6) above, wherein the determination unit performs a first process of identifying the paper type from acquired paper basis weight data based on the program, and a second process of determining the parameters for the paper processing without identifying the paper type from acquired paper basis weight data.

[0015] (8) The parameter determination device according to any one of (1) to (7) above, wherein the parameters relating to paper processing include parameters relating to image formation in an image forming apparatus which is the device that performs the paper processing.

[0016] (9) The parameters related to the image formation include at least any one of the parameters related to the fixing process, the charge elimination process, the transfer process, and the conveyance process, and the parameter determination device according to (8) above.

[0017] (10) The parameters related to the paper processing include the parameters related to the post-processing in the post-processing device which is the device for performing the paper processing, or the parameters related to the paper feeding process in the paper feeding device which is the device for performing the paper processing, and the parameter determination device according to any one of (1) to (9) above.

[0018] (11) The parameters related to the post-processing include at least any one of the parameters related to the punching process, the stacking process, the stapling process, the cutting process, the creasing / folding process, the perforation process, and the bookbinding process, and the parameter determination device according to (10) above.

[0019] (12) The parameters related to the paper feeding process include at least any one of the parameters related to the suction air volume and the assist air volume for paper feeding by the suction belt, and the parameters related to the pressing force of the leveling roller and the operating speed of the leveling roller, and the parameter determination device according to (10) above.

[0020] (13) The acquisition unit acquires data related to the paper basis weight from the sensor provided in the parameter determination device, and the parameter determination device according to any one of (1) to (12) above.

[0021] (14) The acquisition unit acquires data related to the paper basis weight from the sensor connected to the parameter determination device, and the parameter determination device according to any one of (1) to (12) above.

[0022] (15) The parameter determination device according to any one of (1) to (14) above, which is connected to the paper processing device for performing the paper processing.

[0023] (16) An image forming apparatus having the parameter determination device according to any one of (1) to (14) above and an image forming unit that forms an image on a sheet.

[0024] (17) A post-processing apparatus having the parameter determination device according to any one of (1) to (14) above and a post-processing unit that performs post-processing on a sheet.

[0025] (18) A paper feeding apparatus having the parameter determination device according to any one of (1) to (14) above and a paper feeding unit that feeds a sheet.

[0026] (19) A method for creating a determination model for parameters related to sheet processing in a sheet processing apparatus, an acquisition step of acquiring data related to the basis weight of the sheet detected by a sensor, a creation step of applying machine learning to the acquired data related to the basis weight of the sheet and creating the determination model by a learning device, and having, The data related to the basis weight of the sheet is data related to the amount of light transmission when light is irradiated on the sheet. A method for creating a determination model.

[0027] (20) The acquisition step further acquires information related to the device state of the sheet processing apparatus, and the creation step applies machine learning to the data related to the basis weight of the sheet and the information related to the device state and creates the determination model by the learning device. The method for creating a determination model according to (21) above.

[0028] (21) An acquisition step of acquiring data related to the basis weight of the sheet detected by a sensor, a determination step of determining parameters related to sheet processing from the acquired data related to the basis weight of the sheet based on a program using a learning function by machine learning, including, The data related to the basis weight of the sheet is data related to the amount of light transmission when light is irradiated on the sheet. A control program for causing a computer to execute processing. [Effects of the Invention]

[0029] The parameter determination device according to the present invention comprises an acquisition unit that acquires data on paper basis weight detected by a sensor, and a determination unit that determines parameters related to paper processing from the acquired data on paper basis weight based on a program using a machine learning learning function. The data on paper basis weight is data on the amount of light transmitted when light is irradiated onto the paper. As a result, control parameters can be determined directly from the detected data without secondarily calculating paper physical properties by adding calculations to the detected data or applying them to a pre-prepared table, thereby enabling the deriving of optimal control parameters for each type of paper. [Brief explanation of the drawing]

[0030] [Figure 1] This figure shows a schematic configuration of the image forming system according to this embodiment. [Figure 2] This is a side view showing the configuration of media sensors placed along the transport path. [Figure 3] This is a block diagram showing the configuration of an image forming apparatus. [Figure 4A] This is a block diagram showing the functional configuration of the control unit of an image forming apparatus. [Figure 4B] This is a block diagram showing the configuration of the memory unit of an image forming apparatus. [Figure 5] This is a schematic diagram illustrating the control parameter determination method. [Figure 6] This diagram illustrates the processing flow of the control parameter determination method. [Figure 7] This diagram illustrates the quality parameters in image formation processing and the paper properties related to each quality parameter. [Figure 8A] This diagram illustrates the quality items in post-processing and the paper properties related to each quality item. [Figure 8B] This is a diagram illustrating the parameters related to post-processing. [Figure 9A]This diagram illustrates the quality parameters in paper feeding and the paper properties related to each quality parameter. [Figure 9B] This is a diagram illustrating the parameters related to paper feeding. [Figure 10A] This is a diagram illustrating the general configuration of the paper feeding process. [Figure 10B] This is a diagram illustrating the general configuration of the paper feeding process. [Figure 10C] This is a diagram illustrating the general configuration of the paper feeding process. [Figure 11] This is a flowchart showing the printing process of an image forming apparatus. [Figure 12] This is a flowchart showing the print preparation process. [Figure 13A] This is a flowchart showing the control parameter determination process. [Figure 13B] This figure follows Figure 13A. [Figure 14] This is a flowchart showing the paper property detection process. [Figure 15] This is a flowchart showing the process for acquiring print condition settings and device status information. [Figure 16] This diagram illustrates the process of determining the initial control parameters when setting the paper size. [Figure 17] This diagram illustrates the process of determining control parameters using paper properties detected for each sheet of paper during the actual printing process. [Figure 18] This diagram illustrates the process of determining control parameters related to post-processing. [Figure 19] This figure shows an example of a database for training data. [Figure 20] This figure shows an example of a coefficient table. [Figure 21] This is a diagram illustrating the process of generating a control parameter determination model algorithm. [Figure 22] This is a diagram illustrating the process of generating the update decision model algorithm. [Figure 23]This is an example of a screen that accepts settings for the execution conditions of updating a decision model algorithm. [Figure 24] This diagram illustrates another example of the process for generating update decision model algorithms. [Figure 25] This is an example of a screen displaying information about the identified paper type. [Figure 26] This is an example of an operation screen that displays the determined control parameters and accepts instructions from the user to change them. [Figure 27] This is a flowchart of the printing process. [Figure 28A] This is a flowchart showing the control parameter determination process. [Figure 28B] This figure follows Figure 28A. [Figure 29A] This is a flowchart showing a modified example of this printing process, part 1. [Figure 29B] This figure follows Figure 29A. [Figure 29C] This figure follows Figure 29B. [Figure 30A] This flowchart shows a modified example of the printing process, part 2. [Figure 30B] This figure follows Figure 30A. [Figure 30C] This figure follows Figure 30B. [Figure 30D] This figure follows Figure 30C. [Figure 31A] This figure shows the schematic configuration of the image forming system according to Modification 3. [Figure 31B] This figure shows the schematic configuration of the image forming system according to Modification 4. [Figure 32] This is a schematic diagram showing the control parameter determination method I for the image forming apparatus according to Comparative Example 1. [Figure 33] This figure shows the control parameter determination method I related to Comparative Example 1. [Figure 34] This is a schematic diagram showing the control parameter determination method II for the image forming apparatus according to Comparative Example 2. [Figure 35] This figure shows the control parameter determination method II related to Comparative Example 2. [Modes for carrying out the invention]

[0031] Embodiments of the present invention will be described below with reference to the attached drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and redundant explanations are omitted. Also, the dimensional ratios in the drawings are exaggerated for illustrative purposes and may differ from the actual ratios. In the drawings, the vertical direction is the Z direction, the front and back directions of the image forming apparatus are the X direction, and the direction perpendicular to these X and Z directions is the Y direction. The X direction is also called the width direction or the rotation axis direction. Furthermore, around the media sensor (media sensor 80 described later), the transport direction of the recording medium parallel to the surface of the transport path (transport path 143 described later) that is inclined with respect to the horizontal plane and perpendicular to the X direction is called the Y' direction, and the direction perpendicular to this is called the Z' direction (see Figure 2, etc.). In this embodiment, the recording medium includes printing paper (hereinafter simply referred to as paper) and various films. In particular, the paper includes those manufactured using plant-derived mechanical pulp and / or chemical pulp. Furthermore, the types of recording media include coated papers such as gloss paper and matte paper (gloss coated paper and matte coated paper), as well as uncoated papers such as plain paper and fine paper.

[0032] (Image Forming System 1) Figure 1 is a diagram showing the schematic configuration of an image forming system 1 comprising an image forming apparatus 10 according to this embodiment. As shown in Figure 1, the image forming system 1 includes an image forming apparatus 10, a paper feeder 20, a post-processing device 30, and an intermediate transport device 35 that are mechanically and electrically connected to each other. The image forming apparatus 10, the paper feeder 20, the post-processing device 30, and the intermediate transport device 35 can each constitute a paper processing apparatus that processes paper S.

[0033] (Image forming apparatus 10) The image forming apparatus 10 includes a control unit 11, a storage unit 12, an image forming unit 13, a paper feeding and transport unit 14, a media sensor 80, an operation panel 15, a communication unit (not shown), etc. These are interconnected via signal lines such as buses for exchanging signals. Figure 2 is a side view showing the configuration of the media sensor 80 arranged on the transport path 143. The media sensor 80 consists of a paper thickness detection unit 40 (paper thickness sensor 40), a basis weight detection unit 50 (basis weight sensor 50), a surface quality detection unit 60 (surface quality sensor 60), and a paper pressing mechanism 70, and measures paper characteristics. The surface quality sensor 60 functions as an optical sensor device and detects paper characteristics, particularly the surface quality of the paper. Details of the media sensor 80, including the surface quality sensor 60, will be described later. In this embodiment, the media sensor 80 functions as a detection unit. The control unit 11 also functions as a parameter determination device.

[0034] (Control Unit 11) The control unit 11 is composed of a CPU, ROM, RAM, etc., and executes various processes by running programs stored in the ROM and the memory unit 12 (described later), and controls each part of the device and performs various calculations according to the program.

[0035] (Storage unit 12) The storage unit 12 consists of auxiliary storage units such as a ROM for pre-storing various programs and data, a RAM for temporarily storing programs and data as a working area, and a hard disk for storing various programs and data. The storage unit 12 also stores information about the paper stored in each paper tray. This paper information includes information such as the paper brand, size (paper width, paper length), basis weight (weight), and paper type (gloss coated paper, matte coated paper, plain paper, fine paper, rough paper, etc.). The storage unit 12 may also store the paper brand, a decision model (decision model algorithm) used to determine control parameters, and a paper profile.

[0036] (Image forming unit 13) The image forming unit 13 forms images, for example, by an electrophotographic method. The image forming unit 13 includes writing units 131 corresponding to each of the basic colors Y (yellow), M (magenta), C (cyan), and K (black), a photosensitive drum 132, and a developer unit 133 that contains a two-component developer consisting of toner and carrier for each color. The image forming unit 13 further includes an intermediate transfer belt 134, a secondary transfer unit 135, and a fixing unit 136. The toner images formed on the photosensitive drum 132 by the developer unit 133 for each color are superimposed on the intermediate transfer belt 134 and transferred to the transported paper S in the secondary transfer unit 135. The toner images on the paper S are fixed to the paper S by heating and pressurizing in the downstream fixing unit 136.

[0037] (Paper feeding and transport section 14) The paper feed transport unit 14 includes a plurality of paper feed trays 141, 142, transport paths 143, 144, etc. Transport paths 143 and 144 include a plurality of transport roller pairs provided along these transport paths, and a drive motor (not shown) that drives these transport roller pairs. A feed roller is provided to feed out the uppermost sheet of paper among the plurality of sheets of paper S loaded and placed in the paper feed trays 141 and 142, and feeds the sheets of paper S in the paper feed trays one by one to the downstream transport path. A media sensor 80 is positioned upstream of the registration roller on the transport path 143. As shown in Figure 2, near the media sensor 80, the transport path 143 includes an upper guide plate 182 and a lower guide plate 181 made of sheet metal, and the paper S passes between these guides which are opposed to each other at a predetermined interval.

[0038] The paper feed transport unit 14 transports the paper S fed from the paper feed tray 141 or the like. After the paper S is transported along the transport path 143, an image is formed on it in the image forming unit 13, and then it is discharged onto the output tray 342 via the subsequent post-processing device 30. When performing double-sided printing, which involves forming an image on both sides of the paper S, the paper S with an image formed on one side is transported to the transport path 144 for double-sided image formation located at the bottom of the device body. The paper S transported to this transport path 144 is flipped over via a switchback path, then rejoins the single-sided transport path 143, and an image is formed on the other side of the paper S again in the image forming unit 13.

[0039] (Control panel 15) The control panel 15 is equipped with a touch panel, numeric keypad, start button, stop button, etc., and displays the status of the image forming apparatus 10 or image forming system 1. It is used by the user to set the type of paper placed in the paper tray 141, etc., and to input instructions. In this embodiment, the control panel 15 functions as a display unit.

[0040] (Paper feeder 20) As shown in Figure 1, the paper feeder 20 includes a paper feed transport unit 24. The paper feed transport unit 24 functions as a paper feeder. In addition to the paper feed transport unit 24, the paper feeder 20 also includes a control unit, a storage unit, and a communication unit (none of which are shown), which are interconnected via signal lines such as buses for exchanging signals. The paper feed transport unit 24 includes a plurality of paper feed trays 241, 242, 243, and a transport path 244. Paper S transported from each paper feed tray is transported to the downstream image forming apparatus 10, where the paper characteristics are measured by a media sensor 80 and images are formed in the image forming unit 13.

[0041] (Post-treatment device 30) As shown in Figure 1, the post-processing device 30 comprises a post-processing unit 31, a transport path 341, and a paper output tray 342. The post-processing unit 31 performs processes such as stapling, cutting, punching, creasing, folding, perforating, and gluing / perfect binding on the paper S transported from the image forming apparatus 10. In addition to these components, the post-processing device 30 also comprises a control unit, a storage unit, and a communication unit (none of which are shown), which are interconnected via signal lines such as buses for exchanging signals.

[0042] As shown in Figure 1, the intermediate transport device 35 is connected between the image forming apparatus 10 and the post-processing device 30, and relays the paper S discharged from the image forming apparatus 10 to the post-processing device 30. A media sensor 80 is provided on the transport path of the intermediate transport device 35 and is configured to detect the paper properties of the paper S after the image fixing process has been performed. In addition to these components, the intermediate transport device 35 also includes a control unit, a storage unit, and a communication unit (none of which are shown), which are interconnected via signal lines such as buses for exchanging signals. The paper property detection data detected by the media sensor 80 is transmitted to the control unit 11 of the image forming apparatus 10.

[0043] (Media Sensor 80) Figure 2 is a side view showing the configuration of a built-in media sensor 80 arranged in the transport path 143. The media sensor 80 is composed of various sensors (sensors 1 to 10, described later) including a paper thickness detection unit 40, a basis weight detection unit 50, a surface quality detection unit 60, and a paper pressing mechanism 70, and measures multiple paper properties. The basis weight detection unit 50 is a transmissive first optical sensor, and the surface quality detection unit 60 is a reflective second optical sensor. The paper pressing mechanism 70 presses down on the paper when the surface quality detection unit 60 detects the paper properties. The media sensor 80 provided in the intermediate transport device 35 has the same configuration as described above.

[0044] As shown in Figure 2, among these components, the paper thickness detection unit 40 is located on the upstream side in the transport direction, while the basis weight detection unit 50, surface quality detection unit 60, and paper pressing mechanism 70 are located on the downstream side. The basis weight detection unit 50 and the surface quality detection unit 60 are located side by side in the width direction (X direction) at the same position in the transport direction. For example, the basis weight detection unit 50 is located on the front side, and the surface quality detection unit 60 is located on the back side. The surface quality detection unit 60 is located above the transport path 143, which is formed between the upper guide plate 182 and the lower guide plate 181, and the paper pressing mechanism 70 is located opposite it below. The transport path 143 has transport roller pairs 41, 186, and 187 arranged in order from the upstream side.

[0045] (Paper thickness detection unit 40) The paper thickness detection unit 40 measures the thickness of the paper S by measuring the height of the displaced axis of the driven roller as the paper S is transported to the nip of the transport roller pair 41. The transport roller pair 41 consists of two rollers: the lower roller is a fixed drive roller (with a fixed axis center), and the upper roller is a driven roller that is biased to move toward and away from the drive roller. The height of the upper roller is detected by a displacement sensor. The displacement sensor consists of an actuator (detection lever) that contacts the axis of the upper roller and an encoder that measures the amount of rotation of this actuator. The paper thickness detection unit 40 outputs, for example, the paper thickness (microns) as the paper thickness measurement result.

[0046] (Basis weight detection unit 50) The basis weight detection unit 50 is a transmissive optical sensor that detects physical properties corresponding to the basis weight of the paper S. It comprises a light-emitting unit positioned below the transport path 143 and a light-receiving unit positioned above it, and measures the attenuation (transmittance) of light passing through the paper S. For example, the transmittance is output from the basis weight detection unit 50 as the basis weight measurement result.

[0047] (Surface texture detection unit 60) The surface detection unit 60 comprises a housing, a light-emitting unit, a collimating lens, and multiple light-receiving units, and optically detects specular and diffuse reflected light from the surface of the paper as described below. An opening (measurement area) is provided in the upper guide plate 182, and this opening becomes the irradiation area of ​​the light-receiving unit. The paper S, transported to the opening, pauses temporarily. In this state, the paper S is pressed from below by the paper pressing mechanism 70 and positioned. The reference surface within the opening is a virtual surface including the lower surface of the upper guide plate 182, and during measurement, the surface of this positioned paper S, which is the object to be measured, is placed on the reference surface. Irradiated light from the light-emitting unit, which is made approximately parallel by the collimating lens, is irradiated to the reference surface at an incident angle of 75°. The wavelength of the irradiated light is, for example, 465 nm. Multiple light-receiving units receive specular and diffuse reflected light. For example, the light receiving units may be placed at three locations with reflection angles of 30 degrees (for diffuse reflection), 60 degrees (for diffuse reflection), and 75 degrees (for specular reflection), or at two locations with reflection angles of 60 degrees and 75 degrees. The surface quality detection unit 60 outputs the signal from this light receiving unit as the measurement result of smoothness (surface quality 1). In this case, the surface quality detection unit 60 functions as a surface quality sensor 1.

[0048] (Paper pressing mechanism 70) The paper pressing mechanism 70 is positioned below the lower guide plate 181. The paper pressing mechanism 70 includes a pressing section, a drive motor, a cam mechanism, etc. The upper surface of the pressing section is a plane parallel to the lower guide plate 181 and moves up and down by the drive motor. During normal paper feeding, it is approximately flush with the lower guide plate 181, but during measurement, it rises and presses the paper S towards the surface detection section 60. When pressed, the transport of the paper S stops.

[0049] (Details of the image forming apparatus 10) Next, the configuration and functions of the image forming apparatus 10 will be described in detail with reference to Figures 3, 4A, and 4B. Figure 3 is a block diagram showing the configuration of the image forming apparatus. Figure 4A is a block diagram showing the functional configuration of the overall control unit of the image forming apparatus. Figure 4B is a block diagram showing the configuration of the storage unit of the image forming apparatus.

[0050] As shown in Figure 3, the image forming apparatus 10 is connected to the server 90 and other image forming apparatuses 10b and 10c via the network L. In this figure, the components of the image forming apparatus 10 other than the control unit 11 have already been explained in Figure 1, etc., so they are given the same reference numerals and their explanation is omitted.

[0051] The control unit 11 functions as an overall control unit 110, an engine control unit 120, a media sensor control unit 130, a post-processing option control unit 140, a paper feed option control unit 150, and a transport / image forming control unit 160.

[0052] When a print job is input via an instruction sent from the operation panel 15 or an external terminal such as a network-connected PC or printer controller operated by the user, the overall control unit 110 causes the engine control unit 120 to execute the print job based on the print setting information of the input print job.

[0053] The engine control unit 120 performs image formation processing by controlling the post-processing option control unit 140, the paper feed option control unit 150, and the transport / image formation control unit 160. The post-processing option control unit 140 controls the post-processing device 30. Specifically, it transmits information such as the paper transport timing and post-processing settings for the transported paper to the post-processing device 30. The paper feed option control unit 150 controls the paper feed device 20. Specifically, it communicates with the paper feed device 20 to send and receive information such as the paper tray to be used and the paper transport timing.

[0054] The transport and image formation control unit 160 controls the paper feeding and transport of the paper S by controlling the paper feeding and transport unit 14 (including the drive motors for transport paths 143, 144, the fuser unit 136, etc.). It also controls the image formation unit 13 to control the image formation conditions and the image formation timing according to the paper position.

[0055] The media sensor control unit 130 controls various sensors, including the paper thickness sensor 40, basis weight sensor 50, and surface quality sensor 60, in response to execution instruction requests from the engine control unit 120, and performs paper characteristic measurements. The media sensor control unit 130 also controls the operation of the paper pressing mechanism 70.

[0056] As shown in Figure 4A, the control unit 11 functions as an acquisition unit 111, a determination unit 112, and a setting unit 113.

[0057] The acquisition unit 111 acquires values ​​related to multiple types of paper properties.

[0058] The determination unit 112 determines parameters related to paper processing based on values ​​related to paper properties acquired by the acquisition unit 111. For example, the determination unit 112 performs a first process to identify at least one of the paper type and basis weight based on the values ​​related to paper properties acquired by the acquisition unit 111. Based on the identified paper type or basis weight, parameters related to paper processing are determined. At this time, the determination unit 112 functions as a first identification unit 112a. The determination unit 112 also performs a second process to identify parameters related to paper processing from multiple types of paper property values ​​acquired by the acquisition unit 111 without identifying at least one of the paper type and basis weight, based on a program that uses at least one of a learning function including artificial intelligence and statistical methods. At this time, the determination unit 112 functions as a second identification unit 112b. The first identification unit 112a and the second identification unit 112b may function in combination with each other or independently based on instructions from the control unit 11.

[0059] The setting unit 113 accepts a setting regarding whether the determination of parameters related to paper processing is determined by the first specification unit 112a or the second specification unit 112b. This setting is accepted, for example, based on instructions from the user via the operation panel 15.

[0060] The control unit 11 executes parameter determination processing using a parameter determination model (parameter determination model algorithm) stored in the memory unit 12. The parameter determination model is composed of a program that uses a learning function including artificial intelligence or a statistical method, and determines parameters related to paper processing from values ​​related to multiple types of paper properties. The above program is a program based on a dynamically changing algorithm, such as a trained model that is continuously updated through machine learning like artificial intelligence, or a model composed using statistical methods such as a multiple regression model.

[0061] The learning function in the parameter determination engine is comprised of ensemble learning, for example, which fuses multiple learners to generate a single learner. Gradient boosting may be used as a learning method. In machine learning, learning is performed using training data, with the detection output from the media sensor 80 of the paper S as the input value and parameters related to paper processing as the correct labels. The training data may be collected by server 90 from data of other image forming devices 10b, 10c, etc., connected to network L. Furthermore, neural networks, support vector machines (SVMs), Bayesian networks, linear discriminant methods, nonlinear discriminant methods, etc., may be used as learning methods. Additionally, a standalone high-performance computer using CPU and GPU (Graphics Processing Unit) processors, or a cloud computer, may be used as the learning machine for executing machine learning. Details on how to create the parameter determination model will be described later.

[0062] Furthermore, the acquisition unit 111 acquires information regarding the status of the image forming apparatus 10, post-processing apparatus 30, and other devices that perform paper processing. In this case, the determination unit 112 determines the parameters related to paper processing from the values ​​related to multiple types of paper properties and the information regarding the status of the devices. The determination unit 112 may also determine the parameters related to paper processing based on the acquired information regarding the status of the devices and at least one of the identified paper type and basis weight.

[0063] Furthermore, the acquisition unit 111 acquires information regarding the device status at predetermined timings. The determination unit 112 can determine paper processing parameters for multiple sheets of paper. In addition, the determination unit 112 can determine paper processing parameters during the initial setup of the print preparation, for each sheet of paper during the print run, and at predetermined paper feeding intervals.

[0064] Furthermore, each of the multiple types of paper property values ​​used by the determination unit 112 is assigned a priority by weighting or the like, and the determination unit 112 can determine the paper processing parameters based on the assigned priority. Also, the assigned priority may differ between the first process and the second process described above.

[0065] The values ​​relating to multiple types of paper properties include at least two of the following: values ​​relating to the paper surface condition, values ​​relating to the paper basis weight, values ​​relating to the paper thickness, values ​​relating to the paper gloss, values ​​relating to the embossing, values ​​relating to the paper moisture content, values ​​relating to the paper volume resistivity, values ​​relating to the paper bending strength, and values ​​relating to the paper charge.

[0066] The parameters related to paper processing include parameters related to image formation in the image forming apparatus 10. The parameters related to image formation include at least one of the following: parameters related to the fixing process, parameters related to the static elimination process, parameters related to the transfer process, and parameters related to the transport process.

[0067] Furthermore, the parameters related to paper processing include parameters related to post-processing in the post-processing device 30 or parameters related to paper feeding in the paper feed device 20. The parameters related to post-processing include at least one of the following: parameters related to punching, parameters related to stacking, parameters related to stapling when creating handouts, parameters related to cutting when creating borderless brochures and cards, parameters related to folding and creasing when creating spread brochures, parameters related to perforation when creating tickets and coupons, and parameters related to binding. The parameters related to paper feeding include at least one of the following: parameters related to the suction airflow and assist airflow for paper feeding by suction belt, and parameters related to the deflector roller pressure and the operating speed of the deflector roller.

[0068] As shown in Figure 4B, the storage unit 12 has first to sixth storage areas 121 to 126. The first storage area 121 is a control parameter storage area for paper property detection before the actual print. The second storage area 122 is a control parameter storage area with corrections before the actual print. The third storage area 123 is a control parameter storage area for the previous paper property detection during the actual print. The fourth storage area 124 is a control parameter storage area for the current paper property detection during the actual print. The fifth storage area 125 is a storage area for print condition setting information and device status information. The sixth storage area 126 is a storage area for the teacher database. As will be described later, corresponding information is stored and updated in each storage area and read out by the control unit 11 as needed. In addition to the information described above, other necessary information is also stored in the storage unit 12 as appropriate.

[0069] (Control parameter determination method) Figure 5 is a schematic diagram showing the control parameter determination method. Conventional control parameter determination methods first convert the detected data into paper type and basis weight and then classify it before determining the control parameters. However, the control parameter determination method in this embodiment directly determines each control parameter from the detected data of the paper properties. For example, the control unit 11 of the image forming apparatus 10 determines the fixing control parameter from the detected data of paper property sensors i to iii, and determines the transfer control parameter from the detected data of paper property sensors i, iii, and n.

[0070] Figure 6 is a diagram illustrating the processing flow of the control parameter determination method. The control unit 11 of the image forming apparatus 10 performs determination of embossing, paper type, and basis weight classification according to the processing flow shown in Figure 6, and displays the determination results on the operation panel or the like for information provision to the user. That is, the control unit 11 performs a first process to identify the paper type from the acquired paper property values. These determination results for embossing, paper type, and basis weight classification are not basically used for control such as image formation, but are provided to the user in order to correspond with the conventional control parameter determination method. The control unit 11 also directly determines each control parameter from the detected paper property data. That is, the control unit 11 performs a second process to determine the parameters related to the paper processing without identifying the paper type from the acquired paper property values. The control unit 11 may perform the first and second processes described above in combination, or may switch between them and perform them separately as appropriate.

[0071] Figure 7 is a diagram illustrating the quality items in each process of the image forming process and the paper properties related to each quality item.

[0072] Figure 7 shows the relationship between quality items such as fixing quality, secondary transfer quality, transport quality, and paper discharge quality, which exist in each process included in the image formation process, such as the fixing process, transfer process, transport process, and static elimination process, and the paper properties related to each quality item. Examples of paper properties detected by each paper property sensor include smoothness, basis weight, thickness, gloss, indentation depth, moisture content 1, moisture content 2, volume resistivity, bending strength, and charge amount.

[0073] "Smoothness" is obtained by detecting the physical properties corresponding to the smoothness of the paper's surface using a surface sensor 1 (sensor 1). "Smoothness" is obtained by a surface detection unit 60, which will be described later. For example, it is obtained by irradiating the surface of the paper with light at an incident angle of 75 degrees and optically detecting the specularly reflected light and diffusely reflected light from the paper surface using two sensors. "Smoothness" constitutes a value related to the surface condition of the paper.

[0074] "Basis weight" is obtained by detecting the physical properties of the paper according to its basis weight using a basis weight sensor (sensor 2). "Basis weight" is obtained by a basis weight detection unit 50, which will be described later, and is obtained, for example, by measuring the amount of light attenuation (transmittance) transmitted through the paper using transmissive and reflective optical sensors.

[0075] "Paper thickness" is obtained by detecting the physical properties corresponding to the paper thickness using a paper thickness sensor (sensor 3). "Paper thickness" is obtained by a paper thickness detection unit 40, which will be described later, for example by sandwiching the paper between two members and measuring the distance between the two members.

[0076] "Glossiness" is obtained by detecting the physical properties corresponding to the glossiness of the paper's surface using surface property sensor 2 (sensor 4). "Glossiness" is obtained by irradiating the surface of the paper with light at a predetermined incident angle and optically detecting the specularly reflected light from the paper surface.

[0077] The "indentation depth" is obtained by detecting the degree of unevenness of the paper's surface using a surface texture sensor 3 (sensor 5). The "indentation depth" can also be obtained, for example, by irradiating the surface of the paper with light at a large incident angle (80 degrees or more and less than 90 degrees), photographing this state, and processing the obtained image data to measure an index related to the amount of depth corresponding to the unevenness of the surface. The "indentation depth" constitutes a value related to embossing.

[0078] "Moisture content 1" is obtained by detecting the physical properties of the paper according to its moisture content using a moisture content sensor (sensor 6). "Moisture content 1" is obtained, for example, by a moisture content sensor that optically detects the amount of light absorbed by OH groups using a near-infrared method based on the transmitted light of the paper. "Moisture content 1" constitutes a value related to the moisture content of the paper.

[0079] "Moisture content 2" is obtained by detecting the physical properties of the paper according to its moisture content using a moisture content sensor (sensor 7). Sensor 7 is the same type of sensor as sensor 6 used to obtain moisture content 1, but is positioned differently from sensor 6. "Moisture content 1" is obtained by measuring the paper before it passes through the fixing device (a device that heats and pressurizes the paper) of the image forming apparatus 10, and "Moisture content 2" is obtained by measuring the paper after it has passed through the fixing device. "Moisture content 2" constitutes a value related to the amount of moisture in the paper.

[0080] "Paper resistance" is obtained by using sensor 8 to detect physical properties corresponding to the electrical resistance inside or on the surface of the paper. "Paper resistance" can also be obtained, for example, by measuring the voltage and current flowing when a high voltage is applied to the paper. "Paper resistance" constitutes a value related to the volume resistance of the paper.

[0081] "Rigidity" is obtained by detecting the physical properties corresponding to the rigidity of the paper using sensor 9. "Rigidity" is obtained, for example, by mechanically measuring the force or displacement exerted by the paper on one of the outer guide plates constituting the curved transport path when the paper is transported along the curved transport path. "Rigidity" constitutes a value related to the paper bending strength.

[0082] The "charge amount" is obtained by the sensor 10 detecting physical properties corresponding to the charge characteristics of the paper surface. The "charge amount" can be obtained, for example, by using a non-contact potential sensor as the sensor 10.

[0083] The paper properties related to each quality item are indicated by circles in Figure 7. Therefore, for example, various control parameters in the fixing process are directly determined from the detection data of the paper S's smoothness, basis weight, thickness, gloss, indentation depth, moisture content 1, moisture content 2, bending strength, and charge amount. Similarly, various control parameters in other processes are directly determined from the detection data of the relevant paper properties.

[0084] Figure 8A is a diagram illustrating the quality items in post-processing and the paper properties related to each quality item. Figure 8B is a diagram illustrating the parameters related to post-processing.

[0085] Figure 8A shows the relationship between quality items present in the post-processing process, such as punch defects, stapling defects, stacking defects, cutting defects, folding defects, perforation defects, and adhesive application defects in perfect binding, and the paper properties related to each quality item. The paper properties related to each quality item are indicated by circles in Figure 8A. Figure 8B shows the relationship between each quality item and various control parameters related to post-processing. For example, the paper properties related to the quality item of punch defects are the basis weight, thickness, and bending strength of the paper S, as shown in Figure 8A. Also, the control parameters related to the quality item of punch defects are the number of sheets punched and the punch pressure, as shown in Figure 8B. Therefore, the control parameters for the number of sheets punched and the punch pressure in the post-processing process are directly determined from the detected data of the basis weight, thickness, and bending strength of the paper S. Similarly, other control parameters are directly determined from the detected data of the paper properties corresponding to the relevant quality items.

[0086] Figure 9A is a diagram illustrating the quality items in the paper feeding process and the paper properties related to each quality item. Figure 9B is a diagram illustrating the parameters related to the air-fed paper feeding process. Figures 10A to 10C are diagrams illustrating the schematic configuration of the paper feeding device.

[0087] Figure 9A shows the relationship between paper feeding quality in the paper feeding process and the paper properties related to paper feeding quality. The paper properties related to paper feeding quality are indicated by circles in Figure 9A. Figure 9B shows the relationship between paper feeding failures and belt suction failures, which are quality items of paper feeding quality, and various control parameters related to the paper feeding process by the air paper feeding mechanism.

[0088] As shown in Figures 10A to 10C, the paper feeder 20 includes a front-end restricting member 211, a side-end restricting member 212, and a rear-end restricting member 213 for loading and storing the paper S in predetermined positions, and an air suction belt (suction belt) 214 for suctioning the paper S and feeding it in the transport direction. The front-end restricting member 211 sends front air toward the front end of the paper S loaded on top in the transport direction (Y direction). The side-end restricting member 212 sends side air toward both ends of the paper S loaded on top in the transport direction (Y direction). The air suction belt (suction belt) 214 sends suction air to suck the paper S loaded on top in the loading direction (Z direction). Hereinafter, the airflow rate of the front air, the airflow rate of the side air, and the airflow rate of the suction air will be referred to as the handling airflow rate, side airflow rate, and suction airflow rate, respectively. The main airflow and side airflow are also referred to as assist airflow.

[0089] For example, the paper properties related to paper feeding quality are the smoothness, basis weight, thickness, gloss, and bending strength of the paper S, as shown in Figure 9A. Furthermore, the control parameters related to quality items of paper feeding defects are the sieve airflow and side airflow, as shown in Figure 9B. Therefore, the control parameters for sieve airflow and side airflow in the paper feeding process are directly determined from the detection data of the smoothness, basis weight, thickness, gloss, and bending strength of the paper S. Similarly, other control parameters are directly determined from the detection data of the paper properties corresponding to the relevant quality items. In addition, parameters related to paper feeding may also be used, such as the pressure of the sieve roller (sieve roller pressure), which contacts the paper S stacked on top and transports it, and parameters related to the operating speed of the sieve roller.

[0090] <Overview of processing in image forming apparatus> Figure 11 is a flowchart showing the printing process of an image forming apparatus. The processes of the image forming apparatus 10 shown in the flowchart of Figure 11 are stored as a program in the storage unit 12 and executed by the control unit 11 controlling each part. The same applies to each process shown in the following flowcharts.

[0091] (Step S50) The control unit 11 executes the print preparation process in response to user instructions, etc. This print preparation process involves setting various control parameters necessary for printing, performing a test print, and checking the print quality. Details of this print preparation process will be described later.

[0092] (Step S60) The control unit 11 uses the control parameters set in this print preparation process to execute the print process, which is, for example, the process of printing a large number of documents, and then terminates the process. Details of this print process will be described later.

[0093] <Preparation process for final printing> Figure 12 is a flowchart showing the print preparation process.

[0094] (Step S201) The control unit 11 obtains provisional control parameters related to the paper feeding process from the storage unit 12.

[0095] (Step S202) The control unit 11 controls the paper feed transport unit 14 and the paper feed device 20 to execute a paper feeding process for feeding paper S from the tray.

[0096] (Step S203) The control unit 11 transports the paper S to the media sensor 80 by executing the paper feeding process.

[0097] (Step S204) The control unit 11 executes the control parameter determination process 1 using the media sensor 80. The control parameter determination process 1 is a process that determines the initial control parameters for the paper S to be used during the paper setting operation in the preparation stage before actual printing. Details of the control parameter determination process 1 will be described later.

[0098] (Step S205) The control unit 11 controls each part using the control parameters determined in step S204 and performs a test print on the paper S. The test print is an operation to check the quality of the final printed material before the actual print, including the front and back positions of the paper S, the image position on the paper, etc., in addition to the control parameters of the determined image conditions.

[0099] (Step S206) The control unit 11 receives input from the user regarding whether the print quality was achieved as expected by the user. If it is as expected (step S206: YES), the control unit 11 terminates the print preparation process. If it is not as expected (step S206: NO), the control unit 11 proceeds to step S207. In other words, the process in step S206 is to correct the values ​​of the control parameters if the test print result is unsatisfactory.

[0100] (Step S207) The control unit 11 accepts instructions for fine-tuning (correction) each control parameter.

[0101] (Step S208) The control unit 11 controls each part using the control parameters corrected in step S207, and performs a test print on the paper S again.

[0102] (Step S209) The control unit 11 again receives input from the user regarding whether the print quality was achieved as expected by the user. If it is not as expected (step S209: NO), the control unit 11 returns to the process in step S207. If it is as expected (step S209: YES), the control unit 11 proceeds to the process in step S210.

[0103] (Step S210) The control unit 11 stores all control parameters, including the control parameters corrected in step S207, in the second storage area 122 of the storage unit 12.

[0104] (Step S211) The control unit 11 associates each control parameter, detection data, and print condition information with each other and registers them in the update teacher database of the sixth storage area 126 of the storage unit 12, and then terminates this print preparation process.

[0105] <Control parameter determination process 1> Figures 13A and 13B are flowcharts showing the control parameter determination process 1.

[0106] (Step S301) When the paper tray to be used for printing is selected, the paper S loaded in the paper tray is transported. If the paper sensor for starting the paper property detection process is OFF (step S301: NO), the control unit 11 waits until the paper sensor turns ON. If the paper sensor turns ON (step S301: YES), the control unit 11 proceeds to step S302.

[0107] (Step S302) The control unit 11 detects the paper properties of the paper S using each paper property sensor along the paper feeding and transport path. Details of the process in step S302 will be described later.

[0108] (Step S303) The control unit 11 acquires print condition setting information (double-sided / single-sided printing, color printing / monochrome printing, paper width, etc.) and device status information (machine environment information including temperature, humidity, standby time, etc.). Details of the processing in step S303 will be described later.

[0109] (Step S304) The control unit 11 stores the paper physical properties detection data acquired in step S302 and the various information acquired in step S303 in the storage unit 12.

[0110] (Step S305) The control unit 11 determines various control parameters for each process of paper feeding / transportation, transfer, and fixing of the paper S. Details of the process in step S305 will be described later.

[0111] (Step S306) The control unit 11 stores the various control parameters determined in step S305 in the first storage area 121 of the storage unit 12.

[0112] (Step S307) The control unit 11 determines whether or not the post-processing device 30 is connected to the image forming apparatus 10. If it is connected (step S307: YES), the control unit 11 proceeds to step S308. If it is not connected (step S307: NO), the control unit 11 terminates the process in step S204 and proceeds to step S205 in Figure 12.

[0113] (Step S308) The control unit 11 checks the type of post-processing device 30 that is connected.

[0114] (Step S309) The control unit 11 reads and acquires relevant paper property detection data from the storage unit 12, depending on the type (function) of the connected post-processing device 30.

[0115] (Step S310) The control unit 11 performs control parameter determination processing according to the function of the connected post-processing device 30. Details of the processing in step S310 will be described later.

[0116] (Step S311) The control unit 11 stores the control parameters of the post-processing device determined in step S310 in the first storage area 121 of the storage unit 12, and terminates the control parameter determination process 1.

[0117] <Paper property detection process> Figure 14 is a flowchart showing the paper property detection process.

[0118] (Step S401) The control unit 11 controls the media sensor 80 to measure the paper thickness of the paper S and acquires the measurement result as detection data.

[0119] (Step S402) The control unit 11 controls the media sensor 80 to measure the basis weight of the paper S and acquires the measurement result as detection data.

[0120] (Step S403) The control unit 11 controls the media sensor 80 to measure the surface properties 1 (smoothness) of the paper S and acquires the measurement result as detection data.

[0121] (Step S404) The control unit 11 controls the media sensor 80 to measure the surface properties 2 (glossiness) of the paper S and acquires the measurement result as detection data.

[0122] (Step S405) The control unit 11 controls the media sensor 80 to measure the surface quality 3 (depth of indentation) of the paper S and acquires the measurement result as detection data.

[0123] (Step S406) The control unit 11 controls the media sensor 80 to measure the moisture content 1 of the paper S and acquires the measurement result as detection data.

[0124] (Step S407) The control unit 11 controls the media sensor 80 to measure the resistance value of the paper S and acquires the measurement result as detection data.

[0125] (Step S408) The control unit 11 controls the media sensor 80 to measure the stiffness of the paper S and acquires the measurement result as detection data.

[0126] (Step S409) The control unit 11 controls the media sensor 80 to measure the amount of charge on the paper S and acquires the measurement result as detection data.

[0127] <Print condition setting information and device status information acquisition process> Figure 15 is a flowchart showing the process for acquiring print condition setting information and device status information.

[0128] (Step S411) The control unit 11 reads and obtains print condition setting information such as print mode and paper width from the fifth storage area 125 of the storage unit 12.

[0129] (Step S412) The control unit 11 acquires device status information such as internal temperature, internal humidity, total number of printed pages (durability information), and standby time from temperature sensors, humidity sensors, timers, etc.

[0130] <Details of the control parameter determination process> Figure 16 is a diagram illustrating the process of determining the initial control parameters when setting the paper size (parameter determination process 1).

[0131] As shown in Figure 16, the control unit 11, as the selection unit, selects information related to each process from paper property detection data, print condition setting information, and device status information. Each piece of information is newly detected or updated when this process is executed.

[0132] The control unit 11, acting as a paper feeding and transport process control parameter determination processing unit, uses the selected information and determination models 1 and 2 to determine various parameters related to the paper feeding and transport process, such as the paper handling airflow value and the paper feed resist loop amount.

[0133] The control unit 11, acting as a transfer process control parameter determination processing unit, uses the selected information and determination models 10, 11, etc., to determine various parameters related to the transfer process, such as the secondary transfer current value and the tip microvoltage start timing value.

[0134] The control unit 11, acting as a fixing process control parameter determination unit, uses the selected information and the determination models 20, 21, etc., to determine various parameters related to the fixing process, such as the fixing temperature value and fixing speed value.

[0135] The control unit 11, acting as a static elimination process control parameter determination unit, uses the selected information and determination models 30, 31, etc., to determine various parameters related to the static elimination process, such as the static elimination output current value and the static elimination output frequency.

[0136] Next, for the sake of clarity, we will explain the control parameter determination process (parameter determination processes 2 and 3) during actual printing, which will be described later.

[0137] Figure 17 illustrates the process of determining control parameters using paper properties detected for each sheet of paper during actual printing.

[0138] As shown in Figure 17, the control unit 11 selects information related to each process from paper property detection data, print condition setting information, and device status information as the selection unit. Here, the information enclosed by the dashed line is newly detected or updated information when this process is executed, while the other information may be information that has already been acquired and stored in the storage unit 12. Information that changes before and after the fixing process or due to the internal temperature of the machine is newly detected or updated, while information that does not change may use the information from when the paper was set.

[0139] The control unit 11, similar to the process shown in Figure 16, uses the selected information and the corresponding decision model to determine the control parameters for each process, such as the paper feeding and transporting process, the transfer process, the fixing process, and the static elimination process.

[0140] Next, we will explain the process for determining the control parameters of the post-processing device.

[0141] Figure 18 is a diagram illustrating the process of determining control parameters related to post-processing.

[0142] As shown in Figure 18, the control unit 11 selects information related to each process from paper property detection data, print condition setting information, and device status information as the selection unit. Here, the information enclosed by the dashed line is newly detected or updated information when this process is executed, while the other information may be information that has already been acquired and stored in the storage unit 12.

[0143] The control unit 11, acting as a post-processing 1 control parameter determination processing unit, uses the selected information and determination models 40, 41, etc., to determine various parameters related to post-processing 1, such as the punch limit and the staple limit.

[0144] The control unit 11, acting as a post-processing 2 control parameter determination processing unit, uses the selected information and determination models 50, 51, etc., to determine various parameters related to post-processing 2, such as the punch limit and the paper ejection speed fine adjustment value.

[0145] The control unit 11, acting as a post-processing 3 control parameter determination processing unit, uses the selected information and determination models 60, 61, etc., to determine various parameters related to post-processing 3, such as the static elimination high-voltage output current value and the static elimination high-voltage output frequency.

[0146] <Creating a decision model> The method for creating the decision model described above will be explained in detail below. The following explanation will use the example of using an algorithm obtained through machine learning as the decision model.

[0147] In this embodiment, in order to determine the control parameters, a model that determines (predicts) the control parameters is created using machine learning with training data. In this embodiment, the algorithm for the decision model (prediction model) is created using Gradient Boosting Modeling (GBM), one of the machine learning techniques.

[0148] The GBM described above is a model creation method that further improves prediction accuracy by performing weak learning on the error output as a result of model creation. Therefore, it is possible to further improve the accuracy of the control parameter values ​​obtained as predictions by the model.

[0149] Specifically, a database (DB) to be used as training data is prepared, and a decision model algorithm file using GBM is created in advance (default decision model algorithm). The file format is binary. However, the file format may be other formats; for example, it may be created in PMML format, which is commonly used to convert decision models to decision model algorithms.

[0150] Figure 19 shows an example of a training data database. Figure 20 shows an example of a coefficient table.

[0151] As shown in Figure 19, a database for training data is created for each control parameter. Therefore, a database is created for each control parameter to be determined. Each database records the name of the paper, the detected values ​​(detection data) from sensors that read the physical properties of each paper, or the physical property values ​​calculated from the detected values, and the appropriate control parameter values ​​obtained through experiments, etc.

[0152] Here, when creating a decision model, by determining the contribution of the input factors (detected values ​​or calculated values ​​from each sensor) and removing input factors that have little impact on prediction accuracy, the file size of the decision model algorithm can be reduced and processing time minimized. Furthermore, by appropriately weighting the values ​​of the input factors, the predicted values ​​can be appropriately corrected.

[0153] Therefore, for example, a coefficient table like the one shown in Figure 20 is provided, and each input factor is multiplied by a weighting coefficient such as 0 to 2. For example, "0" indicates that the input factor is deleted. "1" indicates that the value of the input factor is used as is. Values ​​greater than 1, such as "2", indicate that the weighting is applied so that the influence of the value of the input factor becomes greater. Values ​​less than 1, such as "0.5", indicate that the weighting is applied so that the influence of the value of the input factor becomes smaller. By applying weighting in this way, a priority can be assigned to each of the multiple types of paper property values, and the control unit 11 can determine various control parameters based on the priority. Note that different weighting values ​​can be set and used for the process of determining various parameters (second process) and the process of identifying the paper type (first process).

[0154] Figure 21 is a diagram illustrating the process of creating a control parameter determination model algorithm.

[0155] The process shown in Figure 21 is for creating the default decision model algorithm described above, and can be executed, for example, by running R on a CPU with the Linux® OS installed. Alternatively, various processes may be executed using Python instead of R.

[0156] As shown in Figure 21, training data is registered in the database, data handling and data analysis are performed, and then each data point is multiplied by a weighting coefficient. Subsequently, a random forest discrimination model generation process is performed using R, and a decision model algorithm is created. Depending on the type of control parameters, if they can be calculated using statistical methods such as multiple regression equations, the control parameters may be determined using statistical methods such as multiple regression equations. Thus, decision methods using machine learning and decision methods using statistical methods may be used in combination.

[0157] Figure 22 is a diagram illustrating the process of creating the update decision model algorithm.

[0158] The process shown in Figure 22 involves establishing a training database within the image forming apparatus 10. When the user (operator) corrects the control parameters, the corrected information is added to the training database, and the decision model algorithm file is continuously updated. This allows the control parameters to be determined that better suit the user's preferred output quality. It is also possible to revert the updated decision model algorithm file to a previous version or to the default state.

[0159] As shown in Figure 22, control parameter correction information, which is information about the corrected control parameters based on user input to the operation panel 15, is acquired. The control parameter correction information is registered in the update training database, and after data missing data processing and data analysis processing are performed, a multiplication process of weighting coefficients is performed on each data point. Subsequently, a decision model generation process using GBM is performed, and the update decision model algorithm is created.

[0160] Figure 23 shows an example of a screen that accepts settings for the execution conditions of updating the decision model algorithm.

[0161] The image forming apparatus 10 displays a screen, for example, as shown in Figure 23, on the operation panel 15 to accept settings from the user for the execution conditions for updating the decision model algorithm.

[0162] In the screen shown in Figure 23, the user can select either "standby" or "specified time" for the update timing (update period), which is an execution condition, by operating the touch panel buttons. If "specified time" is selected as the update timing, the user can specify the update time (the time when the update will be performed) by pressing the up and down buttons "△" and "▽" on the touch panel, or by using a numeric keypad or soft keys not shown in the diagram. In addition to time, the update time may also be set to the day of the week or date. Alternatively, the update time may be set to the elapsed time since the previous update. Furthermore, the user can set the number of processing steps related to the number of training data updates N1, which is an execution condition, in the same way as setting the update time. In the example in Figure 23, the predetermined number of steps is set to 10, and the execution condition related to the number of training data updates is met when 10 new sets of training data are added. In addition, the user can specify whether or not to update the decision model algorithm, or to select a previous version such as the default decision model algorithm, by selecting a button in the decision model column on the screen shown in Figure 23.

[0163] Furthermore, the process of creating the above decision model algorithm may be performed using machine learning methods that utilize neural networks, such as deep learning.

[0164] Figure 24 illustrates another example of the process for creating an update decision model algorithm.

[0165] As shown in Figure 24, control parameter correction information, which is information about the control parameters corrected by user input to the operation panel 15, is obtained. The control parameter correction information is registered in the update training database, and after data missing data processing and data analysis processing are performed, a multiplication process of weight coefficients is performed on each data point. Subsequently, a deep learning decision model generation process is performed, and the update decision model algorithm is created.

[0166] <Display to the user> The information determined by the control parameter determination process described above can be provided to the user, for example, by being displayed on the screen.

[0167] Figure 25 is an example of a screen showing information about the identified paper type.

[0168] As shown in Figure 25, information regarding the identified paper type is displayed on the control panel 15, for example, as an automatic paper setting screen. The screen in Figure 25 displays the identified paper type, basis weight, paper thickness, and the prediction accuracy, in accordance with conventional display methods. This allows the user to confirm the results of the control parameter determination process as a familiar paper type and accuracy, giving them confidence in the automatic determination process.

[0169] Figure 26 shows an example of an operation screen that displays the determined control parameters and accepts instructions from the user to change them.

[0170] As shown in Figure 26, the values ​​of the control parameters automatically determined by the control parameter determination process are displayed on the operation panel 15, for example, on the expert adjustment screen for paper settings. The screen in Figure 26 displays the values ​​of various control parameters automatically determined by the control parameter determination process, allowing the user to check the determined control parameters and change them as needed. In the example in Figure 26, the control parameters of the transfer process and their values ​​before correction are displayed. The user can change the control parameters by entering a correction value of a predetermined step, such as "+2". In addition, by pressing up / down keys, for example, the control parameters of other processes other than the transfer process, such as the paper feeding process, can be displayed and changed by the user.

[0171] <Main Printing Process> Figure 27 is a flowchart of this printing process.

[0172] (Step S501) The control unit 11 obtains control parameters related to the paper feeding process from the storage unit 12. Except for the control parameters related to the paper feeding process, the values ​​of the control parameters determined each time a print operation is performed are used. The control parameters related to the paper feeding process use the values ​​determined in the previous print operation. When feeding the same type of paper from the tray, the values ​​of the control parameters do not change significantly, so there are no problems with paper feeding quality.

[0173] (Step S502) The control unit 11 controls the paper feed transport unit 14 and the paper feed device 20 to execute a paper feeding process for feeding paper S from the tray.

[0174] (Step S503) The control unit 11 transports the paper S to the media sensor 80 by executing the paper feeding process.

[0175] (Step S504) The control unit 11 executes the control parameter determination process 2 using the media sensor 80. Details of the control parameter determination process 2 will be described later.

[0176] (Step S505) The control unit 11 temporarily stops the transport of the paper S and has it wait at the registered paper feed position.

[0177] (Step S506) The control unit 11 controls the image forming unit 13 to start image creation (toner image creation).

[0178] (Step S507) The control unit 11 restarts the transport of the paper S and starts the registered paper feeding.

[0179] (Step S508) The control unit 11 controls the image forming unit 13 to transfer the toner image onto the paper S.

[0180] (Step S509) The control unit 11 controls the image forming unit 13 to heat and fix the toner image onto the paper S.

[0181] (Step S510) The control unit 11 executes the control parameter determination process 3 using the media sensor 80. Details of the control parameter determination process 3 will be described later.

[0182] (Step S511) The control unit 11 determines whether or not the printing is in duplex mode. If it is not in duplex mode (step S511: NO), the control unit 11 proceeds to step S514. If it is in duplex mode (step S511: YES), the control unit 11 proceeds to step S512.

[0183] (Step S512) The control unit 11 determines whether or not printing on the first side (front surface) is complete. If printing on the first side is not complete, i.e., printing on up to the second side is complete (step S512: NO), the control unit 11 proceeds to step S514. If printing on the first side is complete (step S512: YES), the control unit 11 proceeds to step S513.

[0184] (Step S513) The control unit 11 controls the paper reversal mechanism of the paper feed transport unit 14 to transport the paper S to the transport path 144 for double-sided image formation, reverses the paper S via the switchback path, and returns to the process of step S505.

[0185] (Step S514) The control unit 11 ejects the paper S on which image formation is complete and transports it to the post-processing device 30.

[0186] (Step S515) The control unit 11 determines whether a predetermined number of pages have been printed. If not, it returns to the process in step S501. If completed, it terminates the printing process.

[0187] Furthermore, in the above process, if the control parameters are corrected during the print preparation process before the actual print, the print process may be executed using the corrected control parameter values ​​instead of the control parameter values ​​determined during printing. This allows for print quality that better suits the user's preferences. In addition, to reduce processing time, the automatic control parameter determination operation during printing may be stopped, and pre-determined control parameters may be used as fixed values. Furthermore, during printing, the print process may be executed using the control parameter values ​​that were automatically determined during printing, except for the corrected control parameter values. This allows for print quality that suits the user's preferences while using appropriate control parameter values ​​for the paper. Details of these processes will be described later as Modifications 1 and 2 of this print process.

[0188] <Control parameter determination process 2, 3> Figures 28A and 28B are flowcharts showing the control parameter determination processes 2 and 3.

[0189] (Step S601) If the paper sensor for starting the paper property detection process is OFF (step S601: NO), the control unit 11 waits until the paper sensor turns ON. If the paper sensor turns ON (step S601: YES), it proceeds to step S602.

[0190] (Step S602) The control unit 11 detects the paper properties of the paper S using each paper property sensor along the paper feeding and transport path. The process in step S602 is the same as the process in step S302 shown in Figure 13A.

[0191] (Step S603) The control unit 11 acquires print condition setting information (double-sided / single-sided printing, color printing / monochrome printing, paper width, etc.) and device status information (machine environment information including temperature, humidity, standby time, etc.). The process in step S603 is the same as the process in step S303 shown in Figure 13A.

[0192] (Step S604) The control unit 11 stores the paper physical properties detection data acquired in step S602 and the various information acquired in step S603 in the storage unit 12.

[0193] (Step S605) The control unit 11 determines various control parameters for each process of paper feeding / transportation, transfer, and fixing of the paper S. The process in step S605 is the process described above using Figure 17.

[0194] (Step S606) The control unit 11 moves the various control parameters for the paper feeding / transporting, transfer, and fixing processes, which are stored in the fourth storage area 124 of the storage unit 12 as control parameters for the current paper property detection during printing, to the third storage area 123 of the storage unit 12, and stores them as control parameters for the previous paper property detection during printing.

[0195] (Step S607) The control unit 11 stores the various control parameters for the paper feeding / transporting, transfer, and fixing processes determined in step S605 in the fourth storage area 124 of the storage unit 12 as control parameters for detecting the current paper properties during printing.

[0196] (Step S608) The control unit 11 determines whether or not the post-processing device 30 is connected to the image forming apparatus 10. If it is connected (step S608: YES), the control unit 11 proceeds to step S609; if it is not connected (step S608: NO), the control unit 11 returns to the flow shown in Figure 27.

[0197] (Step S609) The control unit 11 checks the type of post-processing device 30 that is connected.

[0198] (Step S610) The control unit 11 reads and acquires relevant paper property detection data from the storage unit 12, depending on the type (function) of the connected post-processing device 30.

[0199] (Step S611) The control unit 11 performs control parameter determination processing according to the function of the connected post-processing device 30. The processing in step S611 is the processing described above using Figure 18.

[0200] (Step S612) The control unit 11 moves the various control parameters of the post-processing device 30, which are stored in the fourth storage area 124 of the storage unit 12 as control parameters for the current paper property detection during printing, to the third storage area 123 of the storage unit 12, and stores them as control parameters for the previous paper property detection during printing.

[0201] (Step S613) The control unit 11 stores the various control parameters of the post-processing device 30 determined in step S611 in the fourth storage area 124 of the storage unit 12 as control parameters for current paper property detection during printing.

[0202] <Modification 1 of this printing process> As a modification of this printing process, we will describe an example in which, if the control parameters are corrected during the print preparation process before the actual printing, the printing process is executed using the corrected control parameter values, rather than using the control parameter values ​​obtained during printing.

[0203] Figures 29A, 29B, and 29C are flowcharts showing a modified example 1 of this printing process.

[0204] (Step S701) The control unit 11 determines whether the control parameters determined by the decision model have been corrected. If they have not been corrected (step S701: NO), the control unit 11 proceeds to step S702. If they have been corrected (step S701: YES), the control unit 11 proceeds to step S703.

[0205] (Step S702) The control unit 11 obtains the current control parameters related to the paper feeding process during the print run from the fourth storage area 124 of the storage unit 12.

[0206] (Step S703) The control unit 11 obtains control parameters with pre-print corrections related to the paper feeding process from the second storage area 122 of the storage unit 12.

[0207] (Step S704) The control unit 11 controls the paper feed transport unit 14 and the paper feed device 20 to execute a paper feeding process for feeding paper S from the tray.

[0208] (Step S705) If the paper sensor for starting the paper property detection process is OFF (step S705: NO), the control unit 11 waits until the paper sensor turns ON. If the paper sensor turns ON (step S705: YES), it proceeds to the process in step S706.

[0209] (Step S706) The control unit 11 detects the paper properties of the paper S using each paper property sensor along the paper feeding and transport path. The process in step S706 is the same as the process in step S302 shown in Figure 13A.

[0210] (Step S707) The control unit 11 acquires print condition setting information (double-sided / single-sided printing, color printing / monochrome printing, paper width, etc.) and device status information (machine environment information including temperature, humidity, standby time, etc.). The process in step S707 is the same as the process in step S303 shown in Figure 13A.

[0211] (Step S708) The control unit 11 stores the paper physical properties detection data acquired in step S706 and the various information acquired in step S707 in the storage unit 12.

[0212] (Step S709) The control unit 11 determines various control parameters for each process of paper feeding / transportation, transfer, and fixing of the paper S. The process in step S709 is the process described above using Figure 17.

[0213] (Step S710) The control unit 11 moves the various control parameters for the paper feeding / transporting, transfer, and fixing processes, which are stored in the fourth storage area 124 of the storage unit 12 as control parameters for the current paper property detection during printing, to the third storage area 123 of the storage unit 12, and stores them as control parameters for the previous paper property detection during printing.

[0214] (Step S711) The control unit 11 stores the various control parameters for the paper feeding / transporting, transfer, and fixing processes determined in step S709 in the fourth storage area 124 of the storage unit 12 as control parameters for detecting the current paper properties during printing.

[0215] (Step S712) The control unit 11 determines whether the control parameters determined by the decision model have been corrected. If they have not been corrected (step S712: NO), the control unit 11 proceeds to step S713. If they have been corrected (step S712: YES), the control unit 11 proceeds to step S714.

[0216] (Step S713) The control unit 11 obtains the current control parameters during the print run related to the transport, transfer, and fixing processes from the fourth storage area 124 of the storage unit 12.

[0217] (Step S714) The control unit 11 acquires the control parameters with pre-print correction related to the conveyance, transfer, and fixing processes from the second storage area 122 of the storage unit 12.

[0218] (Step S715) The control unit 11 executes a conveyance process for conveying the sheet S.

[0219] (Step S716) The control unit 11 executes a transfer process for transferring the toner image onto the sheet S.

[0220] (Step S717) The control unit 11 executes a fixing process for fixing the toner image onto the sheet S.

[0221] [[ID=2)) (Step S718) The control unit 11 determines whether it is double-sided printing. If it is double-sided printing (Step S718: YES), the control unit 11 proceeds to Step S719. If it is not double-sided printing (Step S718: NO), the control unit 11 proceeds to Step S720.

[0222] (Step S719) The control unit 11 determines whether the printing on the first side (front side) is completed. If the printing on the first side is not completed, that is, if the printing up to the second side is completed (Step S719: NO), the control unit 11 proceeds to the process of Step S720. If the printing on the first side is completed (Step S719: YES), the control unit 11 proceeds to the process of Step S721.

[0223] (Step S720) The control unit 11 executes a main body paper discharge process for discharging the sheet S on which the image formation is completed from the main body of the image forming apparatus 10.

[0224] (Step S721) The control unit 11 controls the paper reversal mechanism of the paper feed transport unit 14 to transport the paper S to the transport path 144 for double-sided image formation, reverses the paper S via the switchback path, and returns to the process of step S705.

[0225] (Step S722) The control unit 11 determines whether or not the post-processing device 30 is connected to the image forming apparatus 10. If it is connected (step S722: YES), the control unit 11 proceeds to step S723; if it is not connected (step S722: NO), the control unit 11 terminates the printing process.

[0226] (Step S723) The control unit 11 checks the type of post-processing device 30 that is connected.

[0227] (Step S724) The control unit 11 determines whether or not a device for detecting the physical properties of the paper is provided. If it is provided (step S724: YES), the control unit 11 proceeds to step S725; if it is not provided (step S724: NO), the control unit 11 proceeds to step S728.

[0228] (Step S725) The control unit 11 performs control parameter determination processing according to the function of the connected post-processing device 30. The processing in step S725 is the same as the processing shown in steps S601 to S604 and steps S610 to S611 in Figures 28A and B.

[0229] (Step S726) The control unit 11 moves the various control parameters of the post-processing device 30, which are stored in the fourth storage area 124 of the storage unit 12 as control parameters for the current paper property detection during printing, to the third storage area 123 of the storage unit 12, and stores them as control parameters for the previous paper property detection during printing.

[0230] (Step S727) The control unit 11 stores the various control parameters of the post-processing device 30 determined in step S725 in the fourth storage area 124 of the storage unit 12 as control parameters for current paper property detection during printing.

[0231] (Step S728) The control unit 11 determines whether the control parameters determined by the decision model have been corrected. If they have not been corrected (step S728: NO), the control unit 11 proceeds to step S729. If they have been corrected (step S728: YES), the control unit 11 proceeds to step S730.

[0232] (Step S729) The control unit 11 obtains the current control parameters related to post-processing during the main print run from the fourth storage area 124 of the storage unit 12.

[0233] (Step S730) The control unit 11 obtains control parameters with corrections applied before the main print for post-processing from the second storage area 122 of the storage unit 12.

[0234] (Step S731) The control unit 11 executes a post-processing process that applies post-processing to the paper S.

[0235] (Step S732) The control unit 11 executes a post-processing and paper ejection process to eject the paper S that has undergone post-processing, and then terminates the printing process.

[0236] The above process allows for print quality that better suits the user's preferences. To reduce processing time, the automatic control parameter determination process during printing may be stopped, and pre-determined control parameters may be used as fixed values.

[0237] <Modification 2 of this printing process> As a second modification example of this printing process, an example in which, during printing, the printing process is executed using the control parameter values automatically determined during printing, except for the values of the corrected control parameters, will be described.

[0238] FIGS. 30A, 30B, 30C, and 30D are flowcharts showing a second modification example of this printing process.

[0239] (Steps S801 to S811) The processes of steps S801 to S811 are the same as the processes of steps S701 to S711 in FIG. 29A, and thus the description thereof will be omitted.

[0240] (Step S812) The control unit 11 determines whether the control parameter related to the conveyance process determined by the determination model has been corrected. If not corrected (step S812: NO), the control unit 11 proceeds to the process of step S813. If corrected (step S812: YES), the control unit 11 proceeds to the process of step S814.

[0241] (Step S813) The control unit 11 acquires the current control parameter during this printing related to the conveyance process from the fourth storage area 124 of the storage unit 12.

[0242] (Step S814) The control unit 11 acquires the corrected control parameter before this printing related to the conveyance process from the second storage area 122 of the storage unit 12.

[0243] (Step S815) The control unit 11 executes a conveyance process for conveying the sheet S.

[0244] (Step S816) The control unit 11 determines whether the control parameters for the transcription process determined by the decision model have been corrected. If they have not been corrected (step S816: NO), the control unit 11 proceeds to step S817. If they have been corrected (step S816: YES), the control unit 11 proceeds to step S818.

[0245] (Step S817) The control unit 11 obtains the current control parameters for the transfer process during the print run from the fourth storage area 124 of the storage unit 12.

[0246] (Step S818) The control unit 11 acquires the control parameters with correction applied before the main print for the transfer process from the second storage area 122 of the storage unit 12.

[0247] (Step S819) The control unit 11 executes a transfer process to transfer the toner image onto the paper S.

[0248] (Step S820) The control unit 11 determines whether the control parameters related to the fixing process determined by the determination model have been corrected. If they have not been corrected (step S820: NO), the control unit 11 proceeds to step S821. If they have been corrected (step S820: YES), the control unit 11 proceeds to step S822.

[0249] (Step S821) The control unit 11 obtains the current control parameters for the fixing process during the print run from the fourth storage area 124 of the storage unit 12.

[0250] (Step S822) The control unit 11 obtains control parameters with corrections applied before the actual print for the fixing process from the second storage area 122 of the storage unit 12.

[0251] (Step S823) The control unit 11 executes a fixing process to fix the toner image onto the paper S.

[0252] (Step S824) The control unit 11 determines whether or not it is double-sided printing. If it is double-sided printing (step S824: YES), the control unit 11 proceeds to step S825. If it is not double-sided printing (step S824: NO), the control unit 11 proceeds to step S826.

[0253] (Step S825) The control unit 11 determines whether or not printing on the first side (front surface) is complete. If printing on the first side is not complete, i.e., printing on up to the second side is complete (step S825: NO), the control unit 11 proceeds to step S826. If printing on the first side is complete (step S825: YES), the control unit 11 proceeds to step S830.

[0254] (Step S826) The control unit 11 determines whether the control parameters related to the paper ejection process (paper ejection process from the main body of the image forming apparatus 10) determined by the determination model have been corrected. If they have not been corrected (step S826: NO), the control unit 11 proceeds to step S827; if they have been corrected (step S826: YES), the control unit 11 proceeds to step S828.

[0255] (Step S827) The control unit 11 obtains the current control parameters related to paper ejection during the print run from the fourth storage area 124 of the storage unit 12.

[0256] (Step S828) The control unit 11 obtains control parameters with pre-print corrections related to paper ejection processing from the second storage area 122 of the storage unit 12.

[0257] (Step S829) The control unit 11 executes a paper ejection process to eject the paper S on which image formation is complete from the main body of the image forming apparatus 10, and then proceeds to step S834.

[0258] (Step S830) The control unit 11 determines whether the control parameters related to the double-sided transport process (the reverse transport process of paper S using the reverse transport mechanism of the image forming apparatus 10) determined by the determination model have been corrected. If they have not been corrected (step S830: NO), the control unit 11 proceeds to step S831; if they have been corrected (step S830: YES), the control unit 11 proceeds to step S832.

[0259] (Step S831) The control unit 11 obtains the current control parameters for the double-sided transport process during the main print run from the fourth storage area 124 of the storage unit 12.

[0260] (Step S832) The control unit 11 obtains the pre-print correction control parameters related to the double-sided transport process from the second storage area 122 of the storage unit 12.

[0261] (Step S833) The control unit 11 controls the paper reversal mechanism of the paper feed transport unit 14 to transport the paper S to the transport path 144 for double-sided image formation, reverses the paper S via the switchback path, and returns to the process of step S805.

[0262] (Steps S834 to S844) The processing in steps S834 to S844 is the same as the processing in steps S722 to S732 in Figure 29C, so the explanation is omitted.

[0263] Through the above process, it is possible to obtain print quality that suits the user's preferences while using appropriate control parameter values ​​for the paper.

[0264] <Modification of the image forming system> In the above embodiment, the case in which a media sensor 80 is provided inside the image forming apparatus 10 was described as an example, but the system configuration of the image forming system 1 of this embodiment is not limited to this. Hereinafter, modified examples of the image forming system 1 will be described.

[0265] Figure 31A is a diagram showing the schematic configuration of the image forming system according to the modified example 3.

[0266] As shown in Figure 31A, in the image forming system 1 according to modified example 3, an intermediate transport device 25 is connected between the image forming apparatus 10 and the paper feeding device 20, and a media sensor 80 is provided on the intermediate transport device 25.

[0267] This makes it possible to implement the processing of this embodiment without adding a media sensor 80 inside the main body of the image forming apparatus 10.

[0268] Figure 31B is a diagram showing the schematic configuration of the image forming system according to the modified example 4.

[0269] As shown in Figure 31B, in the image forming system 1 according to the modified example 4, a media sensor 80 is provided in the transport path 144 for double-sided image forming of the image forming apparatus 10.

[0270] This allows for the detection of the paper properties of the paper S after the image has been fixed to one side of the paper S during double-sided printing, and enables the determination of control parameters.

[0271] In the image forming system 1, the number of media sensors 80 and the locations where the media sensors 80 are provided are not limited to the above example, and any number of media sensors 80 can be provided at any location. For example, the media sensors 80 may be provided in the paper feeder 20 or the post-processing device 30. Alternatively, the media sensors 80 may be provided as standalone outside the image forming system 1. In this case, the detection data from the media sensors 80 is input to the decision model algorithm of the image forming apparatus 10 by any method such as a network, storage medium, or user input.

[0272] Furthermore, although Figure 1 and other figures show the image forming system 1 as an image forming apparatus 10 with optional devices such as a paper feeder 20, a post-processing device 30, and an intermediate transport device 35 connected to it, it may also be configured as a standalone image forming apparatus 10 without these options. In addition, each process described in the above embodiments as being performed by the control unit 11 of the image forming apparatus 10 may be performed by a control unit of another component connected to the image forming apparatus 10, such as a paper feeder 20, a post-processing device 30, an intermediate transport device 35, a server 90, a printer controller, or a PC.

[0273] <Comparative Example> Below, as a comparative example, we will describe a control parameter determination method in a conventional image forming apparatus.

[0274] (Conventional control parameter determination method I) Figure 32 is a schematic diagram showing the control parameter determination method I for the image forming apparatus according to Comparative Example 1. Figure 33 is a diagram showing the control parameter determination method I for Comparative Example 1.

[0275] In the conventional determination method I, the user inputs the paper type and basis weight (weight) of the paper to be used from the operation panel of the image forming apparatus 10m. The control unit of the image forming apparatus 10m determines the control parameters for the fixing process, transfer process, and transport / feed process by referring to the respective control parameter tables pre-stored in the memory unit, based on the combination of paper type and basis weight. Here, the control parameters for the transport / feed process are the timing of paper feeding from the paper tray, the rotation speed of the rollers during transport, or the restart timing of the registration rollers positioned immediately before the transfer position, depending on the paper type / basis weight. The control parameters for the transfer process are the voltage and current output when transferring toner on the secondary transfer belt to the paper in the electrophotographic method. The control parameters for the fixing process are the settings for the control temperature and pressure of the fixing member, or the paper transport speed, when fixing the toner to the paper by heating and pressurizing the fixing device.

[0276] In the example shown in Figure 33, embossed paper information is input separately from the paper type and basis weight. The control unit of the image forming apparatus 10m controls the functional components within the image forming apparatus 10m, namely the fixing unit, transfer unit, and paper feed and transport unit, using control parameter values ​​determined based on the embossed paper information, paper type information, and basis weight information input by the user.

[0277] (Conventional control parameter determination method II) Figure 34 is a schematic diagram showing the control parameter determination method II for the image forming apparatus according to Comparative Example 2. Figure 35 is a diagram showing the control parameter determination method II according to Comparative Example 2.

[0278] In the conventional determination method II, the control unit of the image forming apparatus 10n performs a paper type and basis weight discrimination process based on detection data (first detection data or second detection data) obtained from each internal sensor of the media sensor 80. Based on the paper type and basis weight classified by the discrimination process, the control unit performs a control parameter determination process and determines each control parameter. The control parameter determination process is basically the same as in determination method I, except that the number of paper type and basis weight classifications is different.

[0279] In the example shown in Figure 35, embossed paper information is input separately from the paper type and basis weight determined based on the detection data. The control unit of the image forming apparatus 10n controls the functional components within the image forming apparatus 10n, namely the fixing unit, transfer unit, and paper feed transport unit, using control parameter values ​​determined based on the embossed paper information, paper type information, and basis weight information input by the user.

[0280] <Effects realized by the image forming system of this embodiment> As shown in the comparative example above, in conventional systems, control parameters are determined by secondarily calculating values ​​for determining control parameters from detected paper physical properties through calculations, or by applying the calculated values ​​to a pre-prepared table. In such systems, for example, there are problems such as the fact that errors are easily introduced into the values ​​because the values ​​are calculated secondarily, and that because the values ​​are determined by referring to a pre-prepared table, the control parameters must be determined as discretely fluctuating values ​​for each predetermined interval (range), making it impossible to determine the optimal control parameter values.

[0281] In contrast, the image forming system 1 of this embodiment acquires values ​​related to multiple types of paper properties and determines paper processing parameters from the acquired values ​​related to multiple types of paper properties based on a program that uses at least one of a learning function including artificial intelligence and statistical methods. This makes it possible to automatically determine control parameters directly from the detection data without secondarily calculating paper property values ​​by adding calculations to the detection data or applying them to a pre-prepared table. Therefore, the optimal control parameters for each type of paper can be derived regardless of the user's level of knowledge or skill.

[0282] Furthermore, since the system can identify and display at least one of the paper type and basis weight, users can easily and reliably understand the results of the automatic detection using a method they are already familiar with, allowing them to recognize if the wrong paper has been loaded and to take appropriate action such as correcting settings.

[0283] Furthermore, since it is possible to set whether the parameters related to paper processing are identified by the first or second identification unit, it is possible to accommodate various requests, such as users who want to set and adjust control parameters based on their own expertise, or users who lack expertise and want to use automatic settings.

[0284] Furthermore, the above program is composed of a program based on a dynamically changing algorithm. This allows for the deriving of more appropriate control parameters depending on the situation.

[0285] Furthermore, the learning function described above is comprised of ensemble learning, which fuses multiple learners to generate a single learner. This allows for the more accurate and appropriate deriving of control parameters.

[0286] Furthermore, the learning function described above is comprised of a neural network. This allows for easier deriving of appropriate control parameters.

[0287] Furthermore, the image forming system 1 acquires information regarding the state of the paper processing apparatus that performs paper processing, and determines paper processing parameters from values ​​related to multiple types of paper properties and information regarding the apparatus state. This allows control parameters to be determined considering not only multiple types of paper properties but also the apparatus state, thus enabling the derivation of more appropriate control parameters.

[0288] Furthermore, the image forming system 1 acquires information regarding the status of the paper processing device at predetermined timings and determines paper processing parameters for multiple sheets of paper. This allows for the continuous deriving of appropriate control parameters and the assurance of print quality, even during long printing processes or printing large quantities of sheets.

[0289] Furthermore, the image forming system 1 acquires information regarding the status of the paper processing device at predetermined timings and determines paper processing parameters during the initial setup of the print preparation, for each sheet of paper passed during the print run, or at predetermined paper passing intervals. This allows control parameters to be determined at appropriate timings according to the user's or print processing needs, or the required print quality.

[0290] Furthermore, the image forming system 1 performs a first process to identify the paper type from the acquired paper property values, and a second process to determine paper processing parameters from the acquired paper property values ​​without identifying the paper type. This allows the control parameters to be determined directly from the paper property values ​​in the second process, while the paper type is identified and presented to the user in the first process. Therefore, appropriate control parameters can be automatically determined, and the results of the automatic processing can be presented to the user in an easily understandable form such as the paper type, giving the user a sense of security and satisfaction.

[0291] Furthermore, each of the multiple types of paper properties is assigned a priority, and the image forming system 1 determines the paper processing parameters based on the assigned priority. This allows for prioritization of paper property values ​​that have a high contribution to the impact on print quality, and enables the derivation of more appropriate control parameters.

[0292] Furthermore, the assigned priorities are set to differ between the first and second processes described above. This allows for assigning appropriate priorities to the values ​​of each paper property in each process, thereby deriving appropriate control parameters and appropriate paper properties.

[0293] Furthermore, the values ​​related to multiple types of paper properties include at least one of the following: values ​​related to the paper surface condition, paper basis weight, paper thickness, paper gloss, embossing, paper moisture content, paper volume resistivity, paper bending strength, and paper charge. This allows for the derivation of appropriate control parameters by considering multiple types of paper properties that may affect the execution quality of each process.

[0294] Furthermore, the parameters related to paper processing include parameters related to image formation in the image forming apparatus 10. This allows for the setting of appropriate control parameters related to image formation, enabling high-quality image formation processing.

[0295] Furthermore, the parameters related to image formation include at least one of the following: parameters related to the fixing process, parameters related to the static elimination process, parameters related to the transfer process, and parameters related to the transport process. This allows for the setting of appropriate control parameters for each process required for image formation, enabling each process to be executed with high quality.

[0296] Furthermore, the parameters related to paper processing include parameters related to post-processing in the post-processing device 30, or parameters related to paper feeding in the paper feed device 20. This allows for the setting of appropriate control parameters for post-processing and paper feeding, enabling high-quality execution of post-processing and paper feeding.

[0297] Furthermore, the parameters related to post-processing include at least one of the following: parameters related to punching, parameters related to stacking, and parameters related to binding. This allows for the setting of appropriate control parameters for each function according to the post-processing function, enabling high-quality execution of each post-processing step.

[0298] Furthermore, the parameters related to the paper feeding process include at least one of the following: parameters related to the suction airflow and assist airflow for paper feeding by the suction belt, and parameters related to the shuffling roller pressure and the operating speed of the shuffling roller. This allows for the setting of appropriate control parameters for each process required for paper feeding, enabling high-quality paper feeding.

[0299] Furthermore, in the image forming system 1, the parameter determination device may acquire values ​​related to multiple types of paper properties from sensors installed in the machine. This makes it possible to derive appropriate control parameters from values ​​related to multiple types of paper properties with a simple configuration of only one device.

[0300] Furthermore, in the image forming system 1, the parameter determination device may acquire values ​​related to multiple types of paper properties from sensors connected to the machine. This allows the parameter determination device to connect sensors as external devices and derive appropriate control parameters from values ​​related to multiple types of paper properties.

[0301] Furthermore, in the image forming system 1, the parameter determination device may be connected to a paper processing device that processes paper. This allows the device that determines the control parameters and the device that uses the control parameters to be configured separately, thereby increasing the degree of freedom in the design of the device configuration in the image forming system 1.

[0302] Furthermore, in the image forming system 1, the parameter determination device can be provided in any of the other components, such as the image forming apparatus 10, the paper feeder 20, the post-processing device 30, the intermediate transport device 35, and the server 90. This increases the degree of freedom in the design of the apparatus configuration in the image forming system 1.

[0303] The configuration of the image forming system 1 described above is intended to illustrate the main features of the above embodiment, and is not limited to the above configuration. Various modifications can be made within the scope of the claims. Furthermore, it does not preclude configurations that are generally found in image forming systems.

[0304] For example, the image forming system 1 may include components other than the image forming apparatus 10, paper feeder 20, post-processing device 30, and intermediate transport device 35, or it may not include some of these components. Furthermore, each of the image forming apparatus 10, paper feeder 20, post-processing device 30, and intermediate transport device 35 may include components other than those mentioned above, or it may not include some of the components mentioned above.

[0305] Furthermore, the image forming apparatus 10, paper feeder 20, post-processing device 30, and intermediate transport device 35 may each be composed of multiple devices or a single device. Also, the functions of each component may be realized by other components.

[0306] Furthermore, the processing units in the flowcharts of the above embodiments are divided according to the main processing content in order to facilitate understanding of each process. The present invention is not limited by the way the processing steps are classified. Each process can be further divided into more processing steps. Also, one processing step may perform even more processes.

[0307] The means and methods for performing various processing tasks in the system according to the above embodiment can be implemented by either a dedicated hardware circuit or a programmed computer. The program may be provided, for example, on a computer-readable recording medium such as a flexible disk or CD-ROM, or it may be provided online via a network such as the Internet. In this case, the program recorded on the computer-readable recording medium is usually transferred to and stored in a storage unit such as a hard disk. Furthermore, the program may be provided as a standalone application software, or it may be incorporated into the software of the device as a function of the system. [Explanation of Symbols]

[0308] 1. Image forming system 10 Image forming apparatus 11 Control Unit 110 Overall Control Unit 14 Conveying section 141, 142 Paper feed tray 143, 144 Conveyor paths 15. Control Panel 40 Paper thickness sensor 50 basis weight sensor 60 Surface Sensors 70 Paper pressing section 80 Media Sensors 20 Paper feeder 30 Post-processing equipment 35 Intermediate transport device 90 servers

Claims

1. An image forming unit that forms an image on a sheet of paper, An acquisition unit that acquires values ​​related to multiple types of paper physical properties detected by a sensor, A determination unit that determines paper processing parameters from acquired values ​​related to multiple types of paper properties based on a program using machine learning learning capabilities, Equipped with, The values ​​relating to the physical properties of the aforementioned multiple types of paper are, It includes at least two values ​​relating to the basis weight of the paper, the moisture content of the paper, the bending strength of the paper, and the electrostatic charge of the paper, Multiple sensors corresponding to each of the aforementioned multiple types of paper properties are arranged on the transport path that carries the paper. An image forming system characterized by the following features.

2. The image forming system according to claim 1, wherein the plurality of values ​​relating to paper properties include a value relating to the basis weight of the paper.

3. The image forming system according to claim 1, wherein the plurality of values ​​relating to paper properties include a value relating to the paper moisture content.

4. The image forming system according to claim 1, wherein the plurality of values ​​relating to the physical properties of the paper include a value relating to the bending strength of the paper.

5. The image forming system according to claim 1, wherein the plurality of values ​​relating to the paper properties include a value relating to the basis weight of the paper and a value relating to the moisture content of the paper.

6. The image forming system according to claim 1, wherein the plurality of values ​​relating to paper properties include a value relating to the basis weight of the paper and a value relating to the bending strength of the paper.

7. The image forming system according to claim 1, wherein the plurality of values ​​relating to paper properties include a value relating to the paper moisture content and a value relating to the paper bending strength.

8. The image forming system according to claim 1, wherein the plurality of values ​​relating to the paper properties include a value relating to the basis weight of the paper, a value relating to the moisture content of the paper, and a value relating to the bending strength of the paper.

9. The image forming system according to any one of claims 1 to 8, wherein the learning function is configured by ensemble learning, which fuses multiple learners to generate a single learner.

10. The image forming system according to any one of claims 1 to 9, wherein the learning function is configured by a neural network.

11. The image forming system according to any one of claims 1 to 10, wherein the determination unit performs a second process based on the program to determine parameters related to paper processing without specifying the type of paper from the acquired values ​​related to paper physical properties.

12. The image forming system according to claim 11, wherein the determination unit further performs a first process to identify the type of paper from the acquired values ​​relating to the physical properties of the paper, based on the program.

13. The image forming system according to any one of claims 1 to 12, wherein the parameters relating to paper processing include parameters relating to image forming in an image forming apparatus which is the device that performs the paper processing.

14. The parameters relating to image formation include, at a minimum, parameters relating to the fixing process. The image forming system according to claim 13, comprising any one of the following: parameters relating to the static elimination process, parameters relating to the transfer process, and parameters relating to the transport process.

15. The image forming system according to any one of claims 1 to 14, wherein the parameters relating to paper processing include parameters relating to post-processing in a post-processing device which is a device that processes the paper, or parameters relating to paper feeding in a paper feed device which is a device that processes the paper.

16. The image forming system according to claim 15, wherein the post-processing parameters include at least one of the following: punching parameters, stacking parameters, stapling parameters, cutting parameters, crease / folding parameters, perforation parameters, and binding parameters.

17. The image forming system according to claim 15, wherein the parameters relating to the paper feeding process include at least one of the parameters relating to the suction airflow and assist airflow for paper feeding by the suction belt, and the parameters relating to the sorting roller pressure and the operating speed of the sorting roller.

18. The image forming system according to claim 1, further comprising a post-processing unit for performing post-processing on paper.

19. The paper feed section for feeding paper, The image forming system according to claim 1, having the following features.

20. The acquisition unit further acquires information regarding the device status of the paper processing device that performs the paper processing, The image forming system according to any one of claims 1 to 19, wherein the determination unit determines parameters related to the paper processing from values ​​relating to the multiple types of paper properties and information relating to the state of the apparatus.

21. The acquisition unit acquires information regarding the device status of the paper processing device at a predetermined timing. The image forming system according to claim 20, wherein the determination unit determines parameters related to the paper processing for a plurality of sheets of paper.

22. The acquisition unit acquires information regarding the device status of the paper processing device at a predetermined timing. The image forming system according to claim 20 or 21, wherein the determination unit determines the parameters related to paper processing during the initial setup of the print preparation, for each sheet of paper passed during the print, or at predetermined intervals between sheets of paper passed.

23. Each of the aforementioned multiple types of paper properties is assigned a priority level. The image forming system according to any one of claims 1 to 22, wherein the determination unit determines the parameters related to the paper processing based on the assigned priority.

24. Each of the aforementioned multiple types of paper properties is assigned a priority level. The image forming system according to claim 12, wherein the determination unit determines parameters related to the paper processing based on the assigned priority, and the assigned priority differs between the first processing and the second processing.

25. An image forming system including an image forming unit that forms an image on a sheet of paper, comprising an acquisition step of acquiring values ​​related to multiple types of paper properties detected by multiple sensors that are placed on a transport path for transporting the paper and measure each of multiple types of paper properties, A decision step in which parameters related to paper processing are determined from acquired values ​​related to multiple types of paper properties based on a program using machine learning learning capabilities, A control program that causes a computer to perform a process including the following: A control program for an image forming system, wherein the aforementioned multiple types of paper properties include at least two values ​​relating to paper basis weight, paper moisture content, paper bending strength, and paper charge amount.

Images