Ink Jet Nozzle Failure Prediction via Test Chart Analysis
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Solution Overview
Problem
Current methods for detecting and compensating for defective printing nozzles in ink jet printing machines are inefficient, often failing to predict nozzle failures proactively, leading to waste production or premature nozzle switching off, and require additional image data and complex compensation strategies.
Innovation Solution
A method that uses a computer to print nozzle test charts next to the actual print, digitize and evaluate them using an image sensor, calculate failure probabilities for each nozzle based on characteristic values with a statistical prediction model, and switch off nozzles exceeding a defined threshold for proactive compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If printing nozzles are switched off when they fail completely, then print quality is maintained, but productivity decreases due to premature nozzle switching off and waste production
Solution Approach 1:
The patent applies preliminary action by using a prediction model to forecast nozzle failures before they actually occur. The system continuously monitors nozzle characteristics (such as droplet size, velocity, and ink flow) and calculates failure probabilities, allowing proactive switching off of nozzles that are likely to fail soon, rather than reacting after complete failure. This prevents waste production while maintaining print quality.
Solution Approach 2:
The patent implements feedback by continuously monitoring nozzle performance parameters and using this information to update the prediction model. The system evaluates real-time data from the printing process, compares it against established thresholds, and adjusts nozzle operation decisions accordingly. This closed-loop approach ensures that nozzles are switched off based on actual performance trends rather than fixed thresholds, optimizing both quality and productivity.
2Reliability
If printing nozzles are monitored continuously to detect defects, then reliability improves, but device complexity increases due to additional sensors and evaluation systems
Solution Approach 1:
The patent applies universality by using the existing image recording system and evaluation capabilities for dual purposes: both quality control and nozzle failure prediction. The same sensors and processing units that monitor print quality are also utilized to track nozzle performance characteristics over time, eliminating the need for separate dedicated monitoring hardware while improving reliability through comprehensive nozzle surveillance.
Solution Approach 2:
The system performs self-service by using the printing process itself to generate the monitoring data. The nozzles print test patterns during normal operation, and the resulting images are automatically evaluated to extract performance characteristics. This self-testing approach eliminates the need for external diagnostic equipment while continuously monitoring nozzle health, thereby improving reliability without significantly increasing device complexity.
3Measurement precision
If additional test charts are printed to detect nozzle defects, then measurement precision improves, but loss of substance increases due to additional ink consumption and substrate usage
Solution Approach 1:
The patent merges the nozzle testing function with the actual printing process by incorporating test patterns into the normal print job. The test charts are printed alongside the actual product, utilizing the same substrate and ink resources. This integration allows simultaneous production of both the final product and the diagnostic data needed for nozzle performance evaluation, thereby improving measurement precision without proportionally increasing substance loss.
Solution Approach 2:
The system applies partial action by printing test patterns only at critical locations and using selective evaluation of specific nozzle regions. Rather than testing every possible nozzle position exhaustively, the system strategically places test elements where they provide maximum diagnostic value for predicting failures, reducing overall ink consumption and substrate usage while maintaining sufficient measurement precision for reliable nozzle monitoring.
Data Source
AI summary
A method for detecting and compensating for defective printing nozzles in an ink jet printing machine by using a computer includes printing printing nozzle test charts next to an actual print in a production run, subsequently recording and digitizing the printed printing nozzle test charts by using at least one image sensor, evaluating recorded test charts and, based thereon, defining characteristic values for all printing nozzles contributing to the printed printing nozzle test charts by using the computer, calculating a failure probability for every contributing printing nozzle based on the determined characteristic values by applying a statistical prediction model using the computer, and switching off and compensating for all printing nozzles exceeding a first defined threshold for the calculated failure probability. A printing operation is then carried out on the ink jet printing machine with printing nozzle compensation.