Intelligent and accessible data flow architectures for manufacturing system optimization

Abstract

Many traditional data acquisition (DAQ) systems are expensive and inadaptable – most rely on traditional closed-source platforms – thus limiting their usefulness for machine tool diagnostics, process control and optimization. In this study, three different intelligent data flow architectures are designed and demonstrated based on consumer grade off-the-shelf hardware and software. These architectures allow data flow between both open- and closed-source platforms through multiple wired and wireless communication protocols. The proposed architectures are also evaluated for machine tool diagnostics and monitoring of multiple machine tools in manufacturing systems. To realize cloud-based manufacturing, real time sensor data are collected and displayed on remote interfaces, smart devices and a cloud/global data platform via the Internet. Findings reveal that such cyber physical system (CPS)-based manufacturing systems can effectively be used for real time process control and optimization.