360° Defect Detection for Starter Switches

Client: A Leading Automotive Technology Supplier

Challenge:

A key player in the automotive technology industry required a solution to identify defects in their starter switches. The specific area of concern was the caulking—a process where the metal parts get blended into the starter switches. This process could lead to defects such as cracks at the edges and knots (corners) of the switches, compromising the integrity and performance of the starters and potentially leading to product recalls and customer complaints.

Solution:

To address these challenges, the company used the SwitchOn DeepInspect system. DeepInspect was integrated into the existing automation system using a PLC to communicate with the robot for picking and placing parts, as well as controlling a rotating motor.

There were two subsystems integrated to identify defects in the edges and corners of the starter switch:

System 1: For Edge Crack Detection
The primary challenge was identifying and disregarding acceptable (good) scratches, which we successfully overcame with our proficiency.

System 2: For Knotch Folding Detection
The main challenge was the lack of contrast, which we successfully overcame with our expertise.

System Hardware Specifications:

• DeepInspect Pro Software

• Basler acA2440-35uc Camera

• Mitsubishi PLC

• TMS industrial machine vision lights

• Controller with i5 and Nvidia GPU

• Integration with existing automation system

Results:

• Utilizing DeepInspect’s advanced vision technology, defects as small as 100-150 microns were detected.

• The entire inspection process was automated with a robotic arm removing the rejected parts, reducing the need for 2 dedicated manpower.

• Inspection completed in less than 11 seconds per part, ensuring high efficiency.

• DeepInspect was able to identify the defects caused by the wear and tear of caulking tools. This enabled the company to address the issue promptly and reduce defects.

• DeepInspect was able to seamlessly inspect two variants of starters, one with 4 knotches and the other with 6 knotches.

• The system ensured that the starter switches met the required quality standards by detecting and rejecting defective parts.

Conclusion:

The implementation of SwitchOn's DeepInspect system at this leading automotive technology supplier significantly improved the defect detection process for starter switches. By automating the inspection process and utilizing advanced vision technology, the company was able to maintain high-quality standards, reduce manpower costs, and increase production efficiency. This case study highlights the effectiveness of integrating automated defect detection systems in the automotive manufacturing process.