Laser Cutting Gap Widths to Prevent Part Wedging in Skeletons
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated removal of workpiece parts from laser-cutting machines is not robust due to interactions with residual skeletons, particularly wedging, which can lead to machine downtimes.
Innovation Solution
A method for determining individual cutting-gap widths based on workpiece part data to prevent interactions with residual skeletons, using AI agents to optimize cutting-gap widths for robustness and productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated removal using passive suction cups and pin shuttles is implemented, then productivity is improved, but reliability deteriorates due to wedging interactions with residual skeleton
Solution Approach 1:
The system performs preliminary analysis of workpiece part geometry and nesting arrangement before removal to identify high-risk parts prone to wedging. Cutting-gap widths are pre-adjusted for these identified parts to prevent wedging interactions during the automated removal process, thereby maintaining both productivity and reliability.
Solution Approach 2:
The system dynamically adjusts cutting-gap width parameters based on individual workpiece part characteristics and nesting configurations. By modifying this physical parameter, the system prevents harmful wedging interactions while maintaining efficient automated removal operations, resolving the contradiction between productivity and reliability.
2Manufacturing precision
If uniform cutting-gap width is used for all workpiece parts, then manufacturing precision is maintained, but productivity deteriorates due to unnecessary wide gaps for low-risk parts
Solution Approach 1:
The system applies different cutting-gap widths to different workpiece parts based on their individual risk parameters. High-risk parts receive wider gaps to prevent wedging, while low-risk parts receive narrower gaps to maximize material utilization. This localized differentiation maintains manufacturing precision where needed while improving overall productivity.
Solution Approach 2:
The system transitions from static uniform cutting-gap widths to dynamic variable cutting-gap widths that adapt to individual workpiece part characteristics. This dynamic adjustment optimizes the balance between manufacturing precision and productivity by applying appropriate gap widths only where necessary.
3Reliability
If individual cutting-gap widths are determined for each workpiece part, then reliability is improved by preventing wedging, but device complexity increases
Solution Approach 1:
The system automatically evaluates workpiece part geometry, determines risk parameters, and calculates optimal cutting-gap widths without requiring complex external intervention. The nesting software and control system self-manage the complexity of individualized parameter determination, maintaining reliability while keeping the operational interface simple.
Solution Approach 2:
The system uses feedback from workpiece part data and nesting arrangements to automatically adjust cutting-gap widths. By implementing closed-loop control where removal risk assessment feeds into cutting parameter optimization, the system manages complexity through systematic feedback mechanisms rather than ad-hoc adjustments.
Data Source
AI summary
A method for determining cutting-gap widths for a laser-cutting method, in which individual workpiece parts are cut out from a workpiece panel. The method includes inputting workpiece part data for the workpiece parts to be cut out. The method further includes establishing individual risk parameters for the workpiece parts to be cut out regarding a risk of workpiece parts interacting at least in part with a residual skeleton remaining from the workpiece panel by becoming wedged, based on the input workpiece part data. The method further includes determining individual cutting-gap widths for the workpiece parts based on the established individual risk parameters.