Selfadjusting robotic painting system

Purpose Aims to introduce a selfadjusting robotic painting process for automotive fuel containers, capable of predicting the required correction action to avoid further defect production. Designmethodologyapproach Presents the development, testing and onsite 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 buildup. Findings Effective technique for the realtime detection of anticorrosive coat's pinholes and popups. A systematic study for this paint deposition scheme. Research limitationsimplications 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 onsite results and systematic study for the automated or the manual adjustments of the robotic painting parameters. Originalityvalue 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.