Computer Vision and Machine Learning to Create an Advanced Pick-and-Place Robotic Operation Using Industry 4.0 Trends

Abstract

This paper explores integrating several Industry 4.0 trends within a Kawasaki Robot and Vanderlande intelligent manufacturing execution system located at Kennesaw State University (KSU) in the United States of America. Several of the key Industry 4.0 trends that will be discussed within this paper include, but are not limited to, the following topics: Machine Learning (ML), Supervisory Control and Data Acquisition (SCADA), Industrial Internet of Things (IIoT), and Cloud Manufacturing (CM). Several researchers explored these Industry 4.0 trends in manufacturing operations, but very few of them researched intelligent robotics grippers using MES and implementing advanced computer vision technologies. This research scopes in this direction. The research novelty contribution relies on exploring advanced intelligent robotic grippers while providing some scenarios to understand the next generation of automation systems according to Industry 4.0 trends by implementing both computer vision (CV) and machine learning (ML) aspects through an MES.