Laser Processing Inspection Control for Defect Localization
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Solution Overview
Problem
Laser micromachining processes face challenges in achieving consistent feature quality due to non-uniformities in workpieces and degradation of laser sources and optical components, leading to variations in feature quality and increased risk of missed defects during post-processing inspection.
Innovation Solution
A laser-processing apparatus that includes a laser source, scan lens, beam positioners, and sensors to generate process control data, which is processed by a controller to estimate defective features and identify their location, facilitating targeted inspection and improving quality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If real-time controls are used to adjust laser parameters, then feature quality consistency is improved, but device complexity increases
Solution Approach 1:
The patent implements real-time feedback control by monitoring laser power with a photodetector during the micromachining process. The system continuously measures the actual laser power delivered to the workpiece and uses this feedback to dynamically adjust laser parameters, compensating for degradation and maintaining consistent feature quality across the entire workpiece and over time.
Solution Approach 2:
The system performs self-diagnosis and self-adjustment by automatically detecting laser power deviations and correcting them without external intervention. The photodetector monitors the laser source performance, and the control system autonomously modifies operating parameters to maintain optimal feature quality, enabling the system to compensate for its own aging and degradation.
2Measurement precision
If comprehensive post-processing inspection is performed, then defect detection accuracy is improved, but inspection time increases
Solution Approach 1:
The system performs preliminary action by recording process data during laser micromachining that indicates potential defect conditions. By analyzing this process data in real-time or near-real-time, the system can predict which features are likely to be defective before post-processing inspection occurs, enabling targeted inspection of only those high-risk areas rather than comprehensive inspection of all features.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the consistency of feature quality by adjusting laser parameters in real-time and reduces the likelihood of missed defects by focusing inspections on high-risk areas, thereby improving the overall efficiency and accuracy of the laser processing and inspection processes.
Implementation Method 1
a laser source operative to generate a beam of laser energy
Implementation Method 2
a scan lens arranged operative to focus the beam of laser energy such that the focused beam of laser energy is deliverable to the workpiece
Implementation Method 3
at least one beam positioner arranged between the laser source and the scan lens, the at least one beam positioner operative to scan the focused beam of laser energy relative to the workpiece
Implementation Method 4
a photodetector is used to monitor the laser power as the workpiece is being processed
Data Source
AI summary
A laser-processing apparatus for forming features in a workpiece includes at least one sensor for generating process control data representing a) at least one characteristic of the apparatus either before, during or after the workpiece is processed to form a set of features, b) at least one characteristic of the workpiece either before, during or after the workpiece is processed to form a set of features, and/or c) at least one characteristic of an ambient environment in which the apparatus is located either before, during or after the workpiece is processed to form a set of features. A controller executes, or facilitate execution of, a candidate feature selection process whereby process control data is processed to estimate whether any of the features formed in the workpiece are defective and the location of any feature estimated to be defective is identified.