Algorithm for the evaluation of imperfections in auto bodywork using profiles from a retroreflective image

Area of Science:

• Automotive manufacturing engineering
• Quality control systems
• Computer vision applications

Background:

• The automotive industry faces increasing quality demands.
• Manual inspection of auto bodywork imperfections is subjective and prone to errors.
• Squeezing processes in auto bodywork production require precise quality assessment.

Purpose of the Study:

• To develop an automated algorithm for evaluating imperfections in auto bodywork sheets post-squeezing.
• To enhance the accuracy and objectivity of quality control in automotive manufacturing.
• To provide a reliable method for characterizing geometrical defect properties.

Main Methods:

• Processing profile signals from retroreflective images.
• Developing a convergence criterion based on maximum gradient lines.
• Automated characterization of imperfection geometry.

Main Results:

• The algorithm successfully processes image data to identify and evaluate imperfections.
• Geometrical characteristics such as maximum gradient, length, width, and area are accurately determined.
• Automated evaluation provides objective and consistent results compared to manual inspection.

Conclusions:

• The proposed algorithm offers an effective solution for automated quality assessment in automotive bodywork production.
• This method significantly improves the reliability and efficiency of detecting squeezing process imperfections.
• Automated defect evaluation contributes to higher overall product quality in the automobile industry.