Industry 4.0 refers to the 4th Industrial revolution – the recent trend of automation and data exchange in manufacturing technologies. To fully realize the Industry 4.0 vision, manufacturers need to unlock several capabilities: vertical integration through connected and smart manufacturing assets of a factory; horizontal integration through connecting discrete operational systems of a factory; end-to-end integration through the entire supply chain. In recent technology advancements in Web of Things (WoT) and Semantic Web (Jointly referred as Semantic Web of Things) have a promising role to play to address Industry 4.0 vision. Integration of Semantic Web with WoT technologies enables communications among heterogeneous Industrial assets. Semantic Web can be also used to represent manufacturing knowledge in machine-interpretable way. The semantic modeling of industrial assets and their service produces unambiguous and machine-interpretable descriptions and creates interoperability among assets and their services across domains. Semantic Web is indeed a good fit for a plethora of complex problems related to automated, flexible, and self-configurable systems like Industry 4.0 systems.
Several of such novel systems based on Semantic Web of Things are are already being proposed. However, the efforts have not been consolidated to link together, and capitalize on experience in, the major issues related to computational underpinning, multidisciplinary technologies involved, and application domain demands. Time is ripe to bring together the different disciplines related to use of Semantic Web of Things for Industry 4.0 and form an international community to identify the major challenges and research directions. The workshop is intended to make the first step in shaping such community and providing a forum that enables:
- Sharing techniques and experience
- Develop better underlying of the foundation principles of building Industry 4.0 systems using Semantic Web
- Identifying potential domains and application areas
- Identifying future research directions