Self‐adjusting robotic painting system

Abstract

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.