Cognitive Digital Twins for Production of Sustainable Modular Wooden Houses: A Knowledge Graph-based Solution

Cognitive Digital Twins (CDT) are introduced as the next level of Semantic Digital Twins in Construction 4.0, where efficient and sustainable processes are simulated and optimized. Cognitive Modular Production (CMP) is an emerging approach to manufacturing that combines the benefits of Cyber Physical Systems (CPPS) and CDT to create a more intelligent and automated manufacturing system.

By using CDT, CMP allows for virtual testing and the simulation of the modular components before they are deployed, while the CPPS enables the monitoring and control of the physical production process in real time. Knowledge Graphs (KG) as structured representations of knowledge that capture relationships between entities, are incorporated into CDTs as a way of organizing and representing the data that are used to create the virtual model.

There is lack of empirical evidence on the effectiveness of integrating KG into CMP and the potential benefits that this fusion could bring to the production of modular wooden houses in industrialized building industry. The purpose of this research is to adapt the CDT applications to support the production line in the CMP process, integrate KG into CDT and structure and represent data in the real-time view of the CMP process, and investigate the opportunities that KG can provide for production optimization, allowing proactive decision making in the CMP process.

The preliminary results show that a KG can improve the accuracy and reliability of predictions made by the CDT during production of modular units. CDT with KG can act as a decision support tool for manufacturers, allowing them to anticipate and mitigate potential problems, reduce downtime, and optimize their production processes.