Self-adjusting robotic painting system

Purpose - Aims to introduce a self-adjusting robotic painting process for automotive fuel containers, capable of predicting the required correction action to avoid further defect production.Design methodology approach - Presents the development, testing and on-site implementation of a robotic thermal machine vision system designed for evaluating coat thickness and coverage attributes. Computer simulation is used to study the effect of the painting robot's program on the film build-up.Findings - Effective technique for the real-time detection of anti-corrosive coat's pinholes and pop-ups. A systematic study for this paint deposition scheme.Research limitations implications - The presented detection system and the simulation program methodology could be further studied and modified for other painting applications.Practical implications - Provides insights validated with on-site results and systematic study for the automated or the manual adjustments of the robotic painting parameters.Originality value - Introduces a novel application of thermal imaging for evaluating coated surfaces. In addition, a first reported case study of automotive fuel container's painting process. Presents potential application to reduce the defects generation thus, improving quality, and reducing production cost.