AI Inspection Control for Workpiece Defect Verification
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Solution Overview
Problem
Conventional inspection methods for manufacturing defects in workpieces, such as vehicle bodies, do not provide a meaningful and/or 100% reliable conclusion regarding systematic production errors, limiting the efficiency and quality of workpiece inspection and production processes.
Innovation Solution
An inspection method utilizing artificial intelligence (AI) to suggest and/or automatically implement process optimizations, material optimizations, and production optimizations through control and/or regulation interventions in a plant control system, involving the determination and compilation of workpiece and system parameters to create optimized databases for improved verification of workpiece quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional inspection methods are used to check workpieces, then inspection can be performed, but the reliability and meaningfulness of conclusions regarding systematic production errors is insufficient
Solution Approach 1:
The inspection process is segmented into multiple independent measurement steps (rough measurement, intermediate measurement, fine measurement) with different precision levels. Each segment serves a specific purpose: rough measurement for quick screening, intermediate for detailed analysis, and fine for precise verification. This segmentation allows the system to achieve high overall reliability without requiring every measurement to be maximally precise.
Solution Approach 2:
Rough measurement is performed as a preliminary action before detailed inspection. This initial low-precision measurement identifies potential defect areas, allowing subsequent high-precision measurements to focus only on relevant regions. This preliminary screening improves the efficiency and reliability of the overall inspection process by preventing false positives from consuming excessive resources.
2Manufacturing precision
If detailed and comprehensive inspection is performed on all workpieces, then inspection quality improves, but inspection time and production efficiency decrease
Solution Approach 1:
The inspection system applies different measurement qualities to different regions of the workpiece based on defect probability and criticality. High-precision measurements are concentrated on areas identified as high-risk or critical zones, while low-risk areas receive simpler inspection. This local differentiation maintains high inspection quality for critical defects while reducing overall inspection time.
Solution Approach 2:
The system performs partial detailed inspection rather than exhaustive examination of every workpiece. By using rough measurement to identify suspicious areas and then applying detailed measurement only where needed, the system achieves sufficient inspection quality without the time cost of complete detailed inspection on all items.
3Reliability
If multiple measurement steps with different precision levels are implemented, then inspection reliability improves, but device complexity increases
Solution Approach 1:
The measurement device is designed with multi-functionality, capable of performing rough measurement, intermediate measurement, and fine measurement using the same physical hardware. The system achieves different measurement precision levels through software control and measurement strategy rather than requiring separate dedicated devices for each precision level, thereby reducing overall system complexity.
Solution Approach 2:
The measurement system dynamically adjusts its precision and measurement strategy based on the inspection context. The same device can switch between different measurement modes (rough, intermediate, fine) depending on the workpiece characteristics and defect suspicion levels. This dynamic adaptability allows a single device to replace what would traditionally require multiple fixed-precision devices.
Data Source
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AI summary
In order to provide a control system for checking workpieces and a treatment system for treating workpieces, which enable efficient and reliable quality optimization, it is proposed that, for example, workpiece parameters are recorded by means of an automatic control station and a workpiece-specific data set is created from this and/or from system parameters.