Neural-Network Inspection Time Prediction for Print Jobs
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Solution Overview
Problem
Existing printing systems face inefficiencies in estimating inspection time for printed materials, leading to reduced productivity and potential delays due to sheet-disposable paths and reprinting processes.
Innovation Solution
An information processing system utilizing a neural network model to estimate inspection time based on input information about print jobs, printers, and inspection apparatuses, allowing for optimized printing speed settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If printing speed is increased to improve productivity, then output per unit time increases, but inspection time may be insufficient leading to faults in the sheet-disposable path portion
Solution Approach 1:
The system performs preliminary estimation of inspection time using a learned model before actual printing begins. This allows the printing speed to be pre-adjusted based on predicted inspection requirements, ensuring that inspection can be completed within the sheet-disposable path portion while maintaining high productivity.
2Measurement precision
If inspection is performed thoroughly to improve quality, then defect detection accuracy increases, but printing speed must be reduced leading to lower productivity
Solution Approach 1:
The system dynamically adjusts printing speed based on real-time inspection results and learned patterns. When defects are detected, the system can slow down for reinspection of specific areas while maintaining normal speed for defect-free sections, thus preserving both high detection accuracy and overall productivity.
3Reliability
If reprinting is performed when faults are detected, then quality is maintained, but productivity is substantially reduced due to sheet disposal and reprocessing
Solution Approach 1:
The system implements continuous feedback from inspection results to control printing operations. When potential defects are detected, the system provides feedback to adjust printing parameters in real-time or identify specific sheets for targeted reinspection, reducing the need for complete reprinting and minimizing productivity loss while maintaining quality standards.
Data Source
AI summary
An information processing system includes a processor configured to: when new input information including information on a new print job, information on a printer including an inspection apparatus performing an inspection on a printed material or information on the inspection performed by the inspection apparatus is input to a model, output inspection time of a printed material to be printed in the new print job, in which the model has been learned such that inspection time of a printed material to be printed in a print job is output when input information including information on the print job, information on the printer or information on the inspection is input to the model.