Abstract: A raster image processor and a convolutional neural network or other artificial intelligence module operate in parallel. Image data for printing is passed to the raster image processor and the convolutional neural network. The raster image processor translates computer vector files and/or rasterizes bitmaps having higher or lower resolution than the output device to a raster image that includes a matrix of dots a printer can process. The raster image processor generates layers for process inks. The convolutional neural network generates a mask layer, based on the image, that is used by the raster image processor to generate an additional layer for spot colors, object colors, or specialty ink. The mask layer transmitted to the raster image processor generates a spot color layer. The layers generated by the raster image processor and the additional layer for the spot colors and/or specialty inks are combined into a print data file.

Abstract: The systems and methods presented here completely separate a non-user pattern from the user jobs being printed. In fact, depending on the number of images in the job and the number of patterns provided by the manufacturer or press operator, the patterns may appear on different images of the job each time the job is printed. This is because the image marks are generated and processed according to the configuration of ROUS, independent of the user jobs being printed.

Abstract: The systems and methods presented here completely separate a non-user pattern from the user jobs being printed. In fact, depending on the number of images in the job and the number of patterns provided by the manufacturer or press operator, the patterns may appear on different images of the job each time the job is printed. This is because the image marks are generated and processed according to the configuration of ROUS, independent of the user jobs being printed.

Abstract: The systems and methods presented here completely separate a non-user pattern from the user jobs being printed. In fact, depending on the number of images in the job and the number of patterns provided by the manufacturer or press operator, the patterns may appear on different images of the job each time the job is printed. This is because the image marks are generated and processed according to the configuration of ROUS, independent of the user jobs being printed.

Abstract: The systems and methods presented here completely separate a non-user pattern from the user jobs being printed. In fact, depending on the number of images in the job and the number of patterns provided by the manufacturer or press operator, the patterns may appear on different images of the job each time the job is printed. This is because the image marks are generated and processed according to the configuration of ROUS, independent of the user jobs being printed.

Abstract: Techniques described herein automatically discover the IP address of a first network device such as but not limited to a multifunction printer. Such techniques use a unique identifier of the first network device, such as for example a multifunction printer serial number. Such unique number is used in the configuration of a second network device, such as for example a Digital Front End/External Print Controller that may need the IP address of the first network device. The unique number may be entered once into the second network device or may be received from the first network device through a data interface by the second network device. Techniques then may use any available broadcast technology such as but not limited to Simple Network Management Protocol (SNMP) to determine from available network devices which network device therefrom has the same unique number, thereby obtaining the IP address of the first network device.

Abstract: Techniques described herein automatically discover the IP address of a first network device such as but not limited to a multifunction printer. Such techniques use a unique identifier of the first network device, such as for example a multifunction printer serial number. Such unique number is used in the configuration of a second network device, such as for example a Digital Front End/External Print Controller that may need the IP address of the first network device. The unique number may be entered once into the second network device or may be received from the first network device through a data interface by the second network device. Techniques then may use any available broadcast technology such as but not limited to Simple Network Management Protocol (SNMP) to determine from available network devices which network device therefrom has the same unique number, thereby obtaining the IP address of the first network device.

Abstract: Techniques described herein automatically discover the IP address of a first network device such as but not limited to a multifunction printer. Such techniques use a unique identifier of the first network device, such as for example a multifunction printer serial number. Such unique number is used in the configuration of a second network device, such as for example a Digital Front End/External Print Controller that may need the IP address of the first network device. The unique number may be entered once into the second network device or may be received from the first network device through a data interface by the second network device. Techniques then may use any available broadcast technology such as but not limited to Simple Network Management Protocol (SNMP) to determine from available network devices which network device therefrom has the same unique number, thereby obtaining the IP address of the first network device.

Abstract: Techniques are provided for generating and using automated production and performance dashboards. For example, an automated production dashboard is generated and used that includes, but is not limited to, defining production performance metrics, job stats, trends, red/green/yellow with health check, and risks. As well, an automated upkeep dashboard is generated and used that includes, but is not limited to, defining supplies, maintenance, trends, next service appointments, red/green/yellow with health check, and risks. Such techniques may include a remote view of such dashboards, e.g. via native mobile applications in addition to web/client, etc.

Abstract: Techniques are provided for generating and using automated production and performance dashboards. For example, an automated production dashboard is generated and used that includes, but is not limited to, defining production performance metrics, job stats, trends, red/green/yellow with health check, and risks. As well, an automated upkeep dashboard is generated and used that includes, but is not limited to, defining supplies, maintenance, trends, next service appointments, red/green/yellow with health check, and risks. Such techniques may include a remote view of such dashboards, e.g. via native mobile applications in addition to web/client, etc.

Abstract: Techniques described herein automatically discover the IP address of a first network device such as but not limited to a multifunction printer. Such techniques use a unique identifier of the first network device, such as for example a multifunction printer serial number. Such unique number is used in the configuration of a second network device, such as for example a Digital Front End/External Print Controller that may need the IP address of the first network device. The unique number may be entered once into the second network device or may be received from the first network device through a data interface by the second network device. Techniques then may use any available broadcast technology such as but not limited to Simple Network Management Protocol (SNMP) to determine from available network devices which network device therefrom has the same unique number, thereby obtaining the IP address of the first network device.