Improved Automatic Quality Inspections Through the Integration of State-of-the-Art Machine Vision and Collaborative Robots

Abstract

In this paper, we discuss the concepts of a flexible and high-performing solution for automatic quality control that integrates state-of-the-art machine learning algorithms with collaborative robots. The overall aim of the paper is to take the first steps towards improved automatic quality inspections in the manufacturing industry, leading to reduced quality defects and reduced costs in the manufacturing process. For developing and evaluating a first version of a solution that integrates state-of-the-art machine vision and collaborative robots we use a real-world case study focusing on improved quality inspection. Results from the case study shows that it is possible to realize automatic quality inspections through the use of a collaborative robot as intended, but also that there are some challenges that need to be further addressed in order to achieve a top-performing system.