Solution

Smart Energy Solutions

Smart Manufacturing Solution

Core Strengths

In the field of industrial manufacturing, product defect detection is a key link to ensure quality and reduce costs, especially in industries such as textiles, electronics, and automobiles. Traditional manual detection has pain points such as low efficiency (missed detection rate up to 10% -50%), inconsistent standards, and difficult data traceability. This solution is based on AI visual inspection technology and utilizes a cloud edge architecture that integrates software and hardware to achieve precise, real-time, and automated defect identification. The plan focuses on the special characteristics of flexible materials such as fabrics, combined with deep learning and multimodal imaging technology, covering multiple industry scenarios from textile fabrics to electronic components.

Industrial Defect Detection Solution

Core Strengths

Special optimization for fabric testing

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

Multi industry compatibility

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

Balance efficiency and accuracy

The detection speed reaches 60 meters per minute (fabric) or 30 frames per second (video stream), with a missed detection rate of less than 10% and an over detection rate of less than 4%, far higher than manual 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 location, type, and process parameters to assist in quality optimization.

Application Scenarios

textile industry

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

electronics manufacturing

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

auto parts

Measurement of body gap surface difference and monitoring of turbine blade cracks.

Food and Medicine

Packaging aluminum foil damage detection, 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 a fabric defect detection system and deploy 12 sets of high-resolution linear array camera detection units in the weaving workshop. The system can automatically identify common fabric defects such as broken warp, broken weft, holes, stains, etc.

A certain food production enterprise

Deploy a visual inspection system in the external packaging inspection process to achieve automated inspection of packaging bag sealing quality, coding clarity, and label position.

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