Dynamic Computer-Aided Process Control with Computer Vision for Industry 4.0

Abstract

AbstractBecause of health concerns and factory operational scale backs during the recent COVID-19 pandemic, we now need factory automation more than ever to maintain our productivity. However, most of our factories cannot operate remotely, and none can function without considerable human input and oversight. Trying to automate our factory highlights gaps in our technology, as it seems far behind our expectations, needs, and vision. Thus, this paper aims to fill this gap by showing how we have developed practical methodologies and applied technology to enhance legacy factories and their equipment. Specifically, we present the ORiON Production Interface (OPI) unit to run the factory as a smart networked edge device for virtually any machine or process. We have also implemented various computer vision algorithms in the OPI unit to detect errors autonomously, make decentralized decisions, and even control the quality. Although Industry 4.0 is a known concept to equip our factory to see, understand, and predict, we know that many machines today are closed source and cannot even communicate, let alone join a network. This research provides a workable solution to realize Industry 4.0 truly in existing factories with legacy equipment. Experimental results show that this system has a variety of applications, including process monitoring, part positioning, broken tool detection, etc. This novel intelligent networked system can enable our factories to be more innovative and responsive. It also allows for remote operations that can be unattended or lightly tended—a trend needed for the future.KeywordsSmart manufacturingAutomationComputer vision