Data and Knowledge in IIoT-Based Maintenance Application

Along with increased digitalization, virtualization of processes and automation in industry, Industrial Internet of Things opens for new possible scenarios and business models. The opportunities of this technology rely, among the others, on new way for data and knowledge management. Knowledge Based Engineering (KBE) is greatly considered to support design activities related to digital technologies. The paper aims at analyzing the role of Industrial Internet of Things for supporting maintenance operations and evaluating whether the adoption of data structure and the integration with the KBE system can face the actual gaps and needs. After a brief overview of different technologies for knowledge management, a possible scenario has been identified. It represents the framework within IIoT technologies can be applied. This conceptual environment considers a multilevel structure: local facilities, the whole company, suppliers, retailers and global network have been involved into the analysis. Upon that scenario, how data and knowledge can be mapped and managed for each level have been investigated. Moreover, these data can be used to improve the predictive maintenance model as well as to enhance the design of new products through the acquisition and monitoring of an effective set of parameters. Finally, in order to demonstrate the feasibility of the proposed approach with the use of simulation as well as physical devices, a prototypical application related to the maintenance of refrigerated display cabinets has been developed.