Optimizing Correction Factors on Color Differences for Automotive Painting Services

Area of Science:

• Materials Science
• Color Science
• Automotive Engineering

Background:

• Automotive painting demands high quality and speed, facing challenges with color consistency across different areas.
• Discrepancies in car color arise from varied color formulas, leading to inefficiencies and increased repair costs.

Purpose of the Study:

• To optimize correction factors for automotive painting to minimize color differences.
• To streamline the color identification process with minimal tolerances by adjusting correction factors.
• To identify factors influencing color reading and identification in automotive applications.

Main Methods:

• Utilized a BYK Gardner spectrophotometer for 135 measurements.
• Employed two datasets (DS1: 85 pairs, DS2: 53 pairs) for visual experiments.
• Investigated visual perception of painted cars regarding brightness, chroma, and hue differences.

Main Results:

• Optimized correction factor values to minimize color differences in automotive painting.
• Demonstrated improved efficiency in the color identification process.
• Successfully estimated the closest color variant to the objective color, reducing discrepancies.

Conclusions:

• Optimized correction factors significantly reduce color differences in automotive painting.
• The study enhances the efficiency and accuracy of the color identification and painting process.
• Findings contribute to improved quality control and cost reduction in specialized automotive painting services.