Machine Tool State Diagnosis Using Cut Edge Image Analysis
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Solution Overview
Problem
Current methods for determining and correcting the machine state of machine tools, such as laser cutting machines, are cumbersome and require extensive manual maintenance, leading to significant downtime and costs.
Innovation Solution
A method involving the analysis of surface images from cut edges using a data aggregation routine to ascertain actual machine parameters, compare them with selected parameters, and output maintenance instructions to correct the machine state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If standardized manual maintenance program is performed to identify faulty components, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The patent replaces manual mechanical inspection with optical measurement systems and automated evaluation software. Surface images are captured and analyzed automatically to determine cut edge quality, eliminating the need for manual maintenance checks while maintaining precision assessment accuracy.
Solution Approach 2:
The machine tool performs self-diagnosis by automatically capturing surface images, evaluating cut edge quality through automated routines, and identifying its own faulty components. This self-service capability eliminates dependency on manual inspection and reduces maintenance downtime.
2Manufacturing precision
If standardized manual maintenance program is performed to identify faulty components, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple maintenance steps into a single integrated automated process. Surface image capture, quality evaluation, and component identification are combined into one seamless operation, simplifying the overall maintenance procedure while maintaining precision assessment.
Solution Approach 2:
The system creates digital copies of surface images and uses automated evaluation routines to assess cut edge quality. This virtual copying and analysis replaces complex manual inspection procedures, maintaining accuracy while reducing procedural complexity.
3Manufacturing precision
If standardized manual maintenance program is performed to identify faulty components, then manufacturing precision is improved, but loss of substance increases
Solution Approach 1:
The machine tool autonomously performs quality assessment and component identification without requiring external maintenance resources. This self-service approach reduces maintenance costs by eliminating the need for specialized maintenance personnel and extensive manual intervention.
4Productivity
If automated surface image analysis is used to determine machine state, then productivity is improved, but measurement precision requirements increase
Solution Approach 1:
The system transforms physical surface features into digital image parameters for automated analysis. By converting cut edge characteristics into measurable image data, the system enables rapid automated diagnosis while maintaining measurement precision through digital processing and evaluation routines.
Data Source
AI summary
A method for ascertaining and correcting the defective machine state and/or at least one defective component state of a machine tool includes ascertaining the state using imaging and analysis of a cut edge produced and comparing with selected machine parameters and making the correction by way of a maintenance instruction based on the machine state for maintaining the machine tool.