Digital Twins for Sustainable Production: Modelling and Simulation of a Production System Towards a Digital Twin - Annepanavar, Arpita; Gopalakrishnan, Dhanush Krishnan (My University, 2021)
This master thesis is a part of a pilot study of a larger EU-funded Industrial project "Twin Goals" by European Institute of Innovation and Technology (EIT) in collaboration with Chalmers University of Technology. The primary purpose of this study was to investigate the possibility of using a Digital Twin for ensuring production sustainability. Previous research has indicated the potential of using Cyber-physical system (CPS) based Digital Twins for remotely monitoring and controlling the production processes by establishing a bi-directional flow of information between the virtual entities and the physical assets. This project attempts to use this information exchange to perform a real-time optimization of the production processes and increase the sustainability of the production system. The project was carried out in a test-facility for manufacturing drones at the Stena Industry Innovation Lab (SII-Lab), Lindholmen, Gothenburg. This thesis followed a methodology that combines triangulation research methodology and banks methodology. The literature study was carried out to identify suitable Key Performance Indicators (KPIs) for measuring Triple Bottom Line (TBL) aspects of sustainability namely economical, ecological and social aspects. Qualitative and quantitative studies were performed during model building and the analysis phases. The DES model of the Drone factory was built on Siemens Plant Simulation platform with four scenarios that included, the current state (AS-IS scenario), an additional product variant (base scenario), a parallel station (experimental scenario 1), and a potential “operative digital twin” scenario with the dynamically re-balanced station (experimental scenario 2). The scenarios were evaluated by conducting experiments for varying customer demands and pallet sizes. Among the four scenarios, the results of experimental scenario 2 showed a positive impact both in the economic and environmental aspects of TBL. The operative scenario exhibited an ability to autonomously utilize the production resources ensuring that the production load on the system was evenly distributed among all the processing stations. This scenario decreased the waste and non-value adding activities in the process thereby contributing towards a higher throughput, decreased lead times and improved material and energy efficiencies. Enabling a data exchange between this operative scenario and the physical assets we can create a potential Digital Twin for production sustainability.
Keywords: Digital Twin, Discrete Event Simulation, Triple Bottom Line; Sustainability, Key Performance Indicators.