Development and implementation of an architecture for cloud-based monitoring in machining, focusing on high performance applications

Abstract

The digitalization of machining processes has sensorization and monitoring as one of its key pillars. There are several technologies demonstrated at an academic and industrial level for monitoring applications in machining related to process stability, tool wear and product quality monitoring. Nevertheless, industrial adoption is still limited considering the technological maturity of specific solutions and the number of years that research on such topics is active. A significant barrier lies on the digital maturity of the end users themselves, as well as the complexity of integration, maintenance and operation of such monitoring technologies. From a software perspective, the Software as a Service (SaaS) model could be beneficial to reduce that barrier, as has been proven in other applications (e.g. simulation). A SaaS approach on machining monitoring could reduce the investment cost from the end user side (i.e. investment in costly, high-performance edge computing systems) and ease the intellectual property preservation and software maintenance and improvement from the technology provider side. However, for high performance applications, such as stability monitoring, a SaaS approach should in parallel be robust and reliable. This paper proposes such an approach for cloud-based monitoring of machining stability, based on low cost digitalization components (sensor and edge gateway), utilizing the 5G network and standardized protocols to ensure a robust and transferrable architecture. The approach is implemented and demonstrated in a real, industrial milling environment.