As an important component of vehicles, the assembly quality of car sunroofs directly affects sealing, safety, and user experience. Traditional manual inspection has problems such as low efficiency, high missed detection rate, and strong subjectivity, while industrial visual sensing technology can achieve automated detection of screws and glue points through high-precision imaging and intelligent algorithms, significantly improving production efficiency and quality control level.

This case successfully applied a high-precision machine vision inspection system to achieve 100% automated online detection of multiple key defects in the car sunroof assembly. All inspection items were completed within 500 milliseconds, greatly improving the automation level and product quality of the production line.

The customer needs a fast and non-destructive visual inspection system for four key items at the assembly line offline station of the sunroof assembly line:

1. Screw inspection: Ensure that all screws at designated positions are installed to prevent abnormal noise or component loosening caused by missing installation.

Check for glue points: Confirm that the sealant or fixing glue has been applied according to the process requirements. The absence of glue points will directly affect the sealing and waterproof performance of the sunroof.

2. Sunroof sealant defect detection: Check whether the sealant strip has any unqualified phenomena such as breakage, missed application, uneven thickness or depression.

The core challenge lies in:

High speed requirement: It must match the production line rhythm, and the total time for a single inspection must be controlled within 500ms.

The accuracy requirement is moderate but stable: the detection accuracy is ± 1mm, and it is necessary to be able to stably identify all defects that exceed this tolerance range.

The tested objects are diverse: from highly reflective metal screws to low contrast transparent/black colloids, the imaging difficulty varies.