A semantic-driven approach toward Industry 4.0

The current manufacturing trend is towards sustainability. Due to the degradation of natural resources and the accumulation of waste with an increase in the world population and in the consumption of goods, many countries attempt to switch from a linear to a circular economy. Accordingly, they legislate strict environmental regulations on resource consumption, so manufacturing companies require the adoption of the circular economy. Meanwhile, Industry 4.0 technologies facilitate efficient monitoring/forecast through big data and analytics, and thus, manufacturing companies can avoid potential risks and save their resources toward sustainable manufacturing. However, in spite of the requirements to achieve sustainable manufacturing toward the circular economy, companies are immature to exploit the advent of new technologies, even though research works have been very active on each application of the newly emphasizing technologies. For this reason, this dissertation is aiming at providing a comprehensive approach in the context of Industry 4.0 for manufacturing companies to achieve sustainable manufacturing. Guided by the technology aggregation issue, this dissertation provides a procedure and related methods consisting of three steps: 1) the comprehensive research in Industry 4.0 era, especially maintenance, 2) design of knowledge representation and 3) a decision-making methodology. Our method will be aligned with the strong commitment from different actors from all over the world for the validation and demonstration.