3D Print Part Quality Prediction With Real-Time Sensor Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D printing technologies lack real-time quality assurance and predictive capabilities to ensure the quality of parts being formed, leading to potential defects and suboptimal printing outcomes.
Innovation Solution
A computing apparatus and method that predicts the quality of 3D objects by accessing information from sensing devices, allowing for real-time adjustments to the printing process, such as modifying the application of fusing agents or radiation, to improve part quality and notify users of potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If real-time sensing and prediction systems are implemented in 3D printing, then manufacturing precision and quality control are improved, but device complexity increases
Solution Approach 1:
The system performs preliminary quality prediction by accessing information from sensing devices before the printing process completes, allowing potential quality issues to be identified and addressed in advance. The processing device predicts part quality based on sensed information and can notify users or trigger adjustments before defects manifest in the final product.
Solution Approach 2:
The system implements a feedback loop where sensing devices continuously monitor the printing process, the processing device analyzes the information to predict quality outcomes, and this prediction feeds back to allow real-time adjustments to printing parameters or user intervention to maintain quality standards.
2Manufacturing precision
If real-time quality prediction and adjustment mechanisms are added, then manufacturing precision is improved, but productivity decreases
Solution Approach 1:
The system applies partial action by selectively triggering adjustments only when quality predictions indicate potential issues, rather than continuously modifying printing parameters. This approach maintains productivity by avoiding unnecessary interventions while still ensuring quality when needed.
Solution Approach 2:
The system enables self-service quality control where the processing device automatically analyzes sensing information and determines quality outcomes without requiring constant human intervention. Users are notified of predicted quality issues and can decide whether to intervene, allowing the system to maintain quality standards while minimizing disruptions to the printing process.
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
According to an example, a computing apparatus may include a processing device and a machine readable storage medium on which is stored instructions that when executed by the processing device, cause the processing device to access, from a sensing device, information pertaining to formation of a part of a 3D object in a layer of build materials upon which fusing agent droplets have been or are to be selectively deposited. The instructions may also cause the processing device to predict, based upon the accessed information, a quality of the part and output an indication of the predicted quality of the part.