ETD

• cloud computing
• Industry 4.0
• IoT
• performance monitoring
• process management
• production management
• remote monitoring
• visual management

Industry 4.0 is changing the manufacturing landscape towards smart and digital manufacturing. The implementation and integration of various technologies, such as sensors, actuators and robotics, together with devices that allow them to communicate and sense with the surrounding environment, will make manufacturing industry to move towards connected and integrated factories. As a result, manufacturing companies will be capable of improving productivity while reducing lead time and costs. Nevertheless, manufacturers’ scepticism about the benefits provided by Industry 4.0 still represents a barrier to its diffusion. The aim of this project is to demonstrate how Internet of Things and Analytics technologies can bring benefits regarding remote performance monitoring. The intended aim is achieved through the development of a monitoring system concept and its concrete implementation on the Festo Flexible Mechatronics System (MPS 202), a small-scale automated production line. The integration and connection of various sensors allow data collection and communication to a cloud infrastructure, where data are processed and analysed. Data analytics can highlight key performance metrics that are visualised in streaming on a dashboard, facilitating the understanding of process conditions. Furthermore, the system generates alarms on mobile devices in case of anomalies in the Festo system, allowing users to immediately realise whether an undesired event is occurring in the system. The monitoring system enhances process performance awareness, as key performance metrics such as productivity, cycle time and parts produced are displayed. Moreover, the cloud infrastructure enables remote visualisation and monitoring. Additionally, automating data gathering and visualisation, the project addresses the challenge of supporting information flow from the shop floor to the management level. The project demonstrates how the implementation of simple and inexpensive IoT devices represents an efficient way to provide new monitoring capabilities for legacy machines, as a valuable alternative option to the purchase of new and expensive ones.