Predicting Nozzle Failure in 3D Printing Printheads

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Solution Overview

Problem

Nozzle failures in 3D printing printheads can significantly impact the quality of printed objects, with existing technologies lacking effective predictive methods to identify and mitigate potential failures before printing begins.

Innovation Solution

A method is implemented to predict nozzle failure likelihood based on historical and current test data, using drop detection results to determine if nozzle failures will affect print quality, allowing for corrective actions such as relocating the print object or performing maintenance before printing, thereby ensuring the use of nozzles with lower failure probabilities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If printhead is used continuously for printing, then productivity is improved, but nozzle failure risk increases

Engineering Contradiction:

Improvecontinuous productionVSAvoidnozzle failure likelihood

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary testing of nozzles before printing to identify potential failures. Drop detection tests are conducted in advance to detect nozzles that may fail during printing, allowing the system to proactively address issues before they impact production.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback through drop detection testing that monitors nozzle performance. Test results are fed back to update failure likelihood predictions, enabling the system to adapt and adjust printing assignments based on real-time nozzle conditions.

Inventive Principle:

Principle #23Feedback

2Reliability

If nozzles are tested frequently to predict failures, then reliability is improved, but loss of time increases

Engineering Contradiction:

Improvenozzle failure prediction accuracyVSAvoidtesting time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Instead of testing all nozzles equally frequently, the system applies testing selectively based on predicted failure likelihood. Nozzles with higher risk profiles undergo more frequent testing, while lower-risk nozzles are tested less frequently, optimizing the balance between reliability and time investment.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system dynamically adjusts testing parameters including frequency and depth of tests based on nozzle history and conditions. Testing intensity is modified according to individual nozzle risk profiles, allowing the system to maintain high prediction accuracy while minimizing overall testing time.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If printing is delayed to perform maintenance, then reliability is improved, but productivity decreases

Engineering Contradiction:

Improveprint qualityVSAvoidproduction continuity

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

Maintenance and nozzle replacements are performed in advance based on predicted failure likelihoods. The system proactively schedules maintenance during planned downtime rather than waiting for failures to occur, ensuring high reliability without unplanned production interruptions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts printing assignments in real-time based on current nozzle conditions. When nozzles are identified as at-risk, the system automatically reassigns printing tasks to healthier nozzles, maintaining production continuity while managing reliability risks.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20240326132A1Nozzle failure prediction and object quality determination

Publication Date: 2024.10.03 PERIDOT PRINT LLC

AI summary

Example implementations relate to determining and correcting for nozzle failure in printheads used for printing objects. One example implementation receives object data for printing an object and predicts a nozzle failure of a nozzle in the printhead which corresponds with a print location of the object. A print quality parameter of the object to be printed without using the nozzle is determined.