Fully Automated Car Component Checking Machine with Vision System

System parameters

Inspection principle

The automotive industry uses machine vision technology to automate inspection to reduce cost and waste, automotive parts vision inspection system data acquisition, including robotic guidance, part traceability, measurement of critical dimensions, tack weld nuts, the presence of springs and fasteners, sealants Weld bead tracking, inspection verification, and more, which are then analyzed and acted upon by machine learning algorithms and extract real-time and customized reports.

As today's industrial technology becomes more and more developed, visual inspection equipment is also widely used, and now such equipment can be seen in various industries, especially in automotive parts, visual inspection equipment can detect their defect size and appearance. Defects, etc.

Inspection details

The visual inspection equipment for electronic components developed and produced by KEYE TECH uses machine vision to replace the human eye, converts the captured target into an image signal through a CCD industrial camera, and transmits it to a dedicated image processing system. Digitized signals; the image system performs various operations on these signals to extract the characteristics of the target, and then controls the on-site equipment actions according to the results of the discrimination. The equipment realizes the automatic process of component size measurement and appearance defect detection, automatic feeding, automatic detection, automatic sorting, automatic unloading, and automatic rejection of defective products.

• 1. Dimensional measurement of auto parts: At the same time, analyze and judge according to the product outline provided by the enterprise.
• 2. Appearance defect detection: such as obvious scratches, scratches, and missing phenomena on the product. Based on the image, it can be judged whether the product is defective or not. However, this also depends on the pixel level of the industrial camera. Generally, the higher the pixel, the more obvious the defects will be.
• 3. Surface contamination detection: If the product surface is contaminated, it can be identified.
• 4. Detect the integrity of technical products: no matter whether there are cracks or leakage in the product design of the enterprise.
• 5. Sunroof glue detection: For the visual inspection solution after gluing the front and rear windshields of the car, detect the glue height (uniformity) and glue width data of the glue, and detect whether there is any defect such as broken glue.

• 6. Wheel hub size inspection: The automotive hub size verification system uses 3D laser profiling technology to evaluate key measurements of refurbished rims to indicate overall rim stability while driving.
• Once the wheel is loaded into the system, two cameras create a 3D height map of the top and bottom of the lug area, and when the scan is complete, the custom software locates the serialized wheel 1D/2D barcode, two air bars, backplane plane degrees, lug hole surface defects, and other critical dimension measurements. All measurement data is stored in a database and associated with a serialized barcode number for each wheel. A robotic cell downstream of the production line sorts the wheels according to the tolerance of these measurements.
• 7. Tire flatness inspection: A combination of two different machine vision applications, used individually or in sequence, to ensure tire assembly quality is free from the more common non-compliance issues.
• The auto parts visual inspection system is one of the equipments used earlier in the machine vision industry. Due to the very high inspection requirements for auto parts, general manual inspection cannot meet the current needs. Only through the use of automated visual inspection technology can the quality of the car be truly improved. At the same time, it also plays a role in escorting the quality of my country's auto parts.

Our advantages

About Us

Development History

The technology center is composed of algorithm department, software department, optics department, hardware department and mechanical department. The algorithm team currently has 7 PhDs, ensuring that the AI algorithm has the ability to continuously update.

Organization Structure

Visual Inspection Solution

Vision Applications

Cooperation Partners