AI Wire Harness Inspection for Flexible Defect Detection
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Solution Overview
Problem
Conventional visual inspection techniques for quality control in wire harness manufacturing are labor-intensive, unreliable, and require complex setup processes, especially for automated camera systems which need customized software and precise alignment for each wire and terminal combination, limiting their flexibility and applicability.
Innovation Solution
An artificial intelligence program utilizing artificial neural networks for image-based defect detection that identifies objects of interest regardless of alignment or orientation, allowing for flexible operation without the need for customized setup or precise timing, and enabling automatic selection of appropriate image processing steps based on object identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional visual inspection techniques are used, then defect detection capability is provided, but labor intensity and setup complexity increase significantly
Solution Approach 1:
The system automatically identifies objects of interest and selects appropriate image processing steps without requiring manual setup or customization for each wire and terminal combination. The AI program self-configures the inspection process by recognizing object types and autonomously determining the necessary analysis methods, eliminating the need for operator intervention in setup procedures.
Solution Approach 2:
A single unified system handles multiple wire and terminal types through automatic object recognition and adaptive processing. The AI program provides universal defect detection capabilities across different combinations without requiring separate customized software configurations, making one system serve multiple functions and part types.
2Measurement precision
If automated camera systems with customized software are used, then detection accuracy improves, but system flexibility and ease of operation deteriorate
Solution Approach 1:
The system dynamically adapts its processing based on real-time object identification. When a new wire or terminal type is introduced, the AI program automatically recognizes the object and adjusts the image processing parameters and steps accordingly, providing both high detection accuracy and operational flexibility without requiring system reconfiguration.
Solution Approach 2:
The AI program automatically changes processing parameters based on the identified object type. Different wire and terminal combinations trigger automatic adjustments in image analysis methods, thresholds, and processing steps, maintaining detection accuracy while eliminating the need for manual parameter setup and preserving system flexibility.
3Reliability
If precise alignment and customized setup are required, then inspection reliability improves, but productivity and ease of operation decrease
Solution Approach 1:
The system performs self-alignment and selfconfiguration through automatic object recognition. The AI program identifies objects of interest regardless of their precise position or orientation in the field of view, automatically adapting the inspection process to maintain reliability without requiring time-consuming manual alignment procedures, thereby preserving manufacturing throughput.
Data Source
AI summary
An embodiment provides a method of operating wire harness manufacturing equipment, including: adding, using the manufacturing equipment, an element to a wire to form a combination of the element and the wire; capturing, using an imaging device, one or more of an upper image and a lower image of the combination; analyzing, using one or more processors operatively coupled to the imaging device, the one or more of the upper image and the lower image to detect a defect; and thereafter indicating that the defect has been detected. Other embodiments are described and claimed.