Description

Problem: Smart manufacturing systems require advanced monitoring solutions to optimize energy consumption effectively. Traditional modeling and simulation techniques fail to adequately capture the complex energy behaviors in smart manufacturing systems, particularly in adapting quickly to changes within the system. This limitation significantly affects operational efficiency and sustainability.

Goal: This thesis aims to develop a digital twin that enhances the monitoring and understanding of energy consumption within smart manufacturing systems. The thesis will focus on conducting an extensive literature review to evaluate the current state of Energy-oriented Digital Twins (EODT) and develop a methodology for smart manufacturing systems. The project may explore the feasibility of implementing the EODT methodology in a case study with LEGO to demonstrate its practical application.