Industry 4.0: Digital platform for grinding machines

Abstract

In the manufacturing industry, and for a company like SKF with facilities worldwide, it is challenging to monitor machining processes in real-time from remote locations. One method involves monitoring and visualizing machine output on a digital dashboard, updated manually at various locations. Both methods present certain challenges. For security reasons, new CNC machines do not support data transfer via USB sticks and can only store data for about a week. Additionally, when any external sensor is connected to the machine, monitoring this data becomes even more complicated, requiring manual intervention to record, document, and store the data digitally. This makes it difficult for SKF to conduct real-time machining studies with multiple sensors connected to the machine. To address these issues, the Manufacturing Development division at SKF is conducting extensive studies and projects. This thesis, proposed in collaboration with Chalmers, aims to demonstrate the project's potential, which is to setup up a digital platform for grinding machines to capture sensor data and send it to the cloud. Through discussions with SKF team members and several brainstorming sessions, we identified and refined possible outcomes based on SKF's feedback and expectations. We focused on data collection, storage, and real-time monitoring on the SKF Cloud platform. This was to be implemented to push machine data and any external sensors to the SKF cloud platform, which is Microsoft Azure. The thesis project successfully demonstrated the capability and possibilities of capturing and monitoring data in real time. The project utilized hardware and software that may or may not be implemented later in the SKF MD lab. SKF is currently engaged in collaborative work with different partners who supply advanced edge devices that can be connected to machines. Currently, the thesis project serves as a demonstrator, integrating hardware components (selected by the customer) with software (to capture data from sensors). This integration is demonstrated on the Chalmers grinding machine.