Industrial Defect Detection Solution_Smart Manufacturing Solution_Solution_Xian Xitu Zhiguang Intelligent Technology Co., Lt

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Solution Overview

In the field of industrial manufacturing, product defect detection is a key link for quality assurance and cost reduction, especially in industries including textiles, electronics and automobiles. Traditional manual detection suffers from low efficiency with a missed detection rate ranging from 10% to 50%, inconsistent evaluation standards, and poor data traceability.

This solution adopts AI visual inspection technology and applies a cloud-edge architecture with integrated software and hardware, enabling precise, real-time and automatic defect identification. It targets the unique properties of flexible materials such as fabrics. Combined with deep learning and multimodal imaging technologies, it covers application scenarios across multiple industries ranging from textile fabrics to electronic components.

Core Strengths

Special Optimization for Fabric Detection

In response to the diversity of textile textures, the algorithm adapts to complex backgrounds such as plain weave and twill weave, and supports adaptive learning of defects (such as the "self-evolution" function of AI fabric inspection machines, which enables one-click model updating for new defect samples).

Multi-Industry Compatibility

Expand to electronic solder joints, metal scratches, pharmaceutical packaging and other scenarios on the same platform, so as to reduce duplicate investment.

Balancing Efficiency and Precision

The detection speed reaches 60 meters per minute (fabric) or 30 frames per second (video stream), with a missed detection rate below 10% and an over-detection rate below 4%, far higher than manual inspection level.

Low-Code Rapid Deployment

The AI vision platform supports natural language instructions, and the adaptation cycle for new scenarios has been reduced from several weeks to 2 days.

Data-Driven Decision Making

Generate an American standard 4-point inspection report, associate defect locations, defect types and process parameters to assist quality optimization.

Application Scenarios

Textile Industry

Full inspection of fabric defects, fabric grading, and printing and dyeing quality evaluation.

Electronic Manufacturing

PCB solder joint detection and component placement offset recognition, with an accuracy of ±2μm.

Auto Parts

Measurement of body gap and flush, and monitoring of turbine blade cracks.

Food and Pharmaceuticals

Packaging aluminum foil damage detection and identification of internal bubbles in capsules.

Implementation Case

A State-owned Mining Group

Install AI visual inspection equipment to achieve real-time recognition of faults such as conveyor belt tearing and roller damage.

A Large Textile Enterprise in East China

Introduce the fabric defect inspection system and deploy 12 sets of high-resolution linear camera inspection units in the weaving workshop. The system can automatically identify common fabric defects such as broken warp, broken weft, holes and stains.

A Certain Food Production Enterprise

Deploy a visual inspection system in the outer packaging inspection process to realize automatic detection of packaging bag sealing quality, inkjet code clarity and label position.

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Solution Overview

Core Strengths