Robert Ian Marr Young

Radio-Frequency Identification (RFID) system technology is a key element for the realization of the Industry 4.0 vision, as it is vital for tasks such as entity tracking, identification and asset management. However, the plethora of RFID systems’ elements in combination with the wide range of factors that need to be taken under consideration along with the interrelations amongst them, make the problem of identification and design of the right RFID system, based on users’ needs particularly complex. The research outlined in this paper seeks to optimize this process by developing an integrating schema that will encapsulate this information in a form that is both human and machine processible. Human readability will allow a shared understanding of the RFID technology domain; machine readability, automated reasoning engines to perform logical deduction techniques returning implicit information. For this purpose, the novel RFID System Configuration Ontology (RFID SCO) is developed. Hence, non-RFID experts are enabled to identify the most suitable RFID system according to their needs and RFID experts to retrieve all the relevant information required for the efficient design of the corresponding RFID system. The RFID SCO is validated and tested successfully against real-world scenarios provided by domain experts.

For many years now, the importance of semantic technologies, that provide a formal, logic-based route to sharing meaning, has been recognised as offering the potential to support interoperability across multiple-related applications and hence, drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems.