Abstract: A failure time estimation device includes: a memory configured to store a machine-learned model obtained by performing machine learning using teaching data associating printer information including at least one of operation history of a printer, state information indicating a current state, and a print result image indicating a print result with failure time of the printer; and a controller configured to obtain the printer information and estimate the failure time of the printer using the obtained printer information and the machine-learned model.

Abstract: A printing abnormality detection system includes a printer that prints an image on a printing medium based on image data, a reader that reads the image printed on the printing medium, a processing unit that detects an abnormal printed portion based on read image data from the reader, a storage unit that stores information of a display necessity determination criterion, and a display unit. The processing unit determines, based on the image data, the read image data, and the display necessity determination criterion, whether the abnormal printed portion is to be displayed on the display unit. When the processing unit determines that the abnormal printed portion is to be displayed, the processing unit executes a process of displaying, on the display unit, abnormal printed portion information including an image of the abnormal printed portion.

Abstract: A printer includes: a memory configured to store a machine-learned model obtained by machine learning using teaching data associating at least one of reflectance of a print medium, transmittance of the print medium, and image data obtained by capturing an image of a surface of the print medium with a type of the print medium; and a print controller configured to determine a type of a print medium using at least one of reflectance of the print medium, transmittance of the print medium, and image data obtained by capturing an image of a surface of the print medium and the machine-learned model.

Abstract: A method for determining a working gap includes a first recording step for ejecting ink from a recording head onto a first recording medium to record a test pattern, a first imaging step for capturing the test pattern recorded on the first recording medium in each of a state where a distance between the recording head and the first recording medium is a first distance, and a state where a distance between the recording head and the first recording medium is a second distance, a function calculating step, a second recording step for recording the test pattern on a second recording medium, a second imaging step for capturing the test pattern recorded on the second recording medium, and a working gap determining step for determining, based on the number of pixels of the captured test pattern and a function, a distance between the recording head and the second recording medium.

Abstract: A printing abnormality detection system includes a printer that prints an image on a printing medium based on image data, a reader that reads the image printed on the printing medium, a processing unit that detects an abnormal printed portion based on read image data from the reader, a storage unit that stores information of a display necessity determination criterion, and a display unit. The processing unit determines, based on the image data, the read image data, and the display necessity determination criterion, whether the abnormal printed portion is to be displayed on the display unit. When the processing unit determines that the abnormal printed portion is to be displayed, the processing unit executes a process of displaying, on the display unit, abnormal printed portion information including an image of the abnormal printed portion.

Abstract: A printer including a motor for transporting an object to be transported, the printer includes: a memory storing a machine-learned model configured to output a control parameter of the motor that brings a transport position of the object to be transported close to a reference based on one or more state variables including at least one of a speed of the object to be transported, an acceleration of the object to be transported, a movement amount of the object to be transported, a start position of movement of the object to be transported, an ambient environment of the printer, a value of a current flowing through the motor, a type of a print medium onto which printing is to be performed by the printer, and an accumulated movement amount of the object to be transported; and a controller configured to control the motor to perform printing by using the control parameter obtained based on the machine-learned model.

Abstract: A printer includes: a carriage which moves with a print head mounted thereon, the print head being configured to eject ink; a camera attached to the carriage and configured to capture an image printed on a print medium by the print head; a movement mechanism configured to move the carriage along a main scan direction; a transportation mechanism configured to transport the print medium along a sub-scan direction; a processor configured to control printing of the image onto the print medium; and a storage configured to store a correction value of a movement amount of the movement mechanism as a first correction value for a location adjustment of a capture area of the camera and store a correction value of a transportation amount of the transportation mechanism as a second correction value for the location adjustment of the capture area.

Abstract: Provided is technology enabling detecting cockling in a print medium without printing a cockling detection pattern on the print medium. An image processing device has: a light source configured to illuminate a print medium; a sensor configured to scan the print medium; and a controller configured to control the light source and sensor. The controller determines if there is cockling in an evaluation area of the print medium based on change in the detection values of the sensor in the evaluation area.

Abstract: A printer includes: a carriage which moves with a print head mounted thereon, the print head being configured to eject ink; a camera attached to the carriage and configured to capture an image printed on a print medium by the print head; a movement mechanism configured to move the carriage along a main scan direction; a transportation mechanism configured to transport the print medium along a sub-scan direction; a processor configured to control printing of the image onto the print medium; and a storage configured to store a correction value of a movement amount of the movement mechanism as a first correction value for a location adjustment of a capture area of the camera and store a correction value of a transportation amount of the transportation mechanism as a second correction value for the location adjustment of the capture area.

Abstract: An information processing apparatus includes a storage that stores a machine-learned model, an accepting section, and a processor. In the machine-learned model, according to a data set in which an association is made between discharge failure factor information related to the factor of a discharge failure and printed image information that represents an image formed on a print medium, a prediction condition has been machine-learned for the discharge failure. The accepting section accepts the discharge failure factor information from a printing apparatus. The processor predicts the discharge failure in the print head according to the accepted discharge failure factor information and the machine-learned model.

Abstract: A failure time estimation device includes: a memory configured to store a machine-learned model obtained by performing machine learning using teaching data associating printer information including at least one of operation history of a printer, state information indicating a current state, and a print result image indicating a print result with failure time of the printer; and a controller configured to obtain the printer information and estimate the failure time of the printer using the obtained printer information and the machine-learned model.

Abstract: There is provided a printing apparatus including: an ink jet head that prints on a print medium; a camera that captures an image on the print medium; a carriage that mounts the ink jet head and the camera; and a processor that generates image data based on a captured image obtained by capturing a chart by the camera, the chart being printed on the print medium by the ink jet head, in which the processor generates at least one of image data representing an image of an image range smaller than a capturing range of the camera and image data representing an image of a resolution lower than a resolution of the captured image, for an adjustment item.

Abstract: A printer includes: a memory configured to store a machine-learned model obtained by machine learning using teaching data associating at least one of reflectance of a print medium, transmittance of the print medium, and image data obtained by capturing an image of a surface of the print medium with a type of the print medium; and a print controller configured to determine a type of a print medium using at least one of reflectance of the print medium, transmittance of the print medium, and image data obtained by capturing an image of a surface of the print medium and the machine-learned model.

Abstract: A method for determining a working gap includes a first recording step for ejecting ink from a recording head onto a first recording medium to record a test pattern, a first imaging step for capturing the test pattern recorded on the first recording medium in each of a state where a distance between the recording head and the first recording medium is a first distance, and a state where a distance between the recording head and the first recording medium is a second distance, a function calculating step, a second recording step for recording the test pattern on a second recording medium, a second imaging step for capturing the test pattern recorded on the second recording medium, and a working gap determining step for determining, based on the number of pixels of the captured test pattern and a function, a distance between the recording head and the second recording medium.

Abstract: An image quality inspection camera system includes: N (integer of N?2) light sources that emit light on a medium; a camera for photographing the medium; and a control section, in which the control section executes setting processing when an i-th light source (integer of i=1 to N) is lit with a reference driving signal, for setting an image quality inspection time driving signal of the i-th light source, and the setting processing includes calculating an i-th representative luminance value by performing a predetermined representative luminance value calculation processing based on a luminance value of each pixel photographed by the camera when the i-th light source is lit with the reference driving signal, and determining the image quality inspection time driving signal of the i-th light source by adjusting the reference driving signal such that the i-th representative luminance value satisfies a predetermined target luminance value condition.

Abstract: A printer including a motor for transporting an object to be transported, the printer includes: a memory storing a machine-learned model configured to output a control parameter of the motor that brings a transport position of the object to be transported close to a reference based on one or more state variables including at least one of a speed of the object to be transported, an acceleration of the object to be transported, a movement amount of the object to be transported, a start position of movement of the object to be transported, an ambient environment of the printer, a value of a current flowing through the motor, a type of a print medium onto which printing is to be performed by the printer, and an accumulated movement amount of the object to be transported; and a controller configured to control the motor to perform printing by using the control parameter obtained based on the machine-learned model.

Abstract: A printing apparatus includes a spectrometer that emits light to detect reflected light and outputs a signal corresponding to an intensity of the light, a white board that reflects the light, a carriage that holds the spectrometer, and a second adjustment mechanism that adjusts a posture of the spectrometer with respect to the carriage.

Abstract: Provided is technology enabling detecting cockling in a print medium without printing a cockling detection pattern on the print medium. An image processing device has: a light source configured to illuminate a print medium; a sensor configured to scan the print medium; and a controller configured to control the light source and sensor. The controller determines if there is cockling in an evaluation area of the print medium based on change in the detection values of the sensor in the evaluation area.

Abstract: A measuring apparatus includes a carriage on which an imaging control section that controls imaging of an object is mounted, a movement control section that moves the carriage relative to the object, an image processing section that acquires image information, a first signal line that connects the imaging control section and the movement control section to each other, and a second signal line that connects the imaging control section and the image processing section to each other. A control signal is transmitted over the first signal line, and a data signal is transmitted over the second signal line.

Abstract: An image quality inspection camera system includes: N (integer of N?2) light sources that emit light on a medium; a camera for photographing the medium; and a control section, in which the control section executes setting processing when an i-th light source (integer of i=1 to N) is lit with a reference driving signal, for setting an image quality inspection time driving signal of the i-th light source, and the setting processing includes calculating an i-th representative luminance value by performing a predetermined representative luminance value calculation processing based on a luminance value of each pixel photographed by the camera when the i-th light source is lit with the reference driving signal, and determining the image quality inspection time driving signal of the i-th light source by adjusting the reference driving signal such that the i-th representative luminance value satisfies a predetermined target luminance value condition.