Digital tvilling inom sophantering

Sammanfattning

In connection with increasing urbanization and growing demands for sustainable resource utilization,higher requirements are being placed on the optimization of systems in urban environments.A central aspect of all urban environments is waste management, and this study investigates howdigital twins can be used to improve waste management in Gothenburg Municipality. The projectwas carried out on behalf of Volvo Group Trucks and aims to analyze how data integration betweenstakeholders can enable improved route planning and create new business opportunities.The study is based on a design science approach with an iterative working method, where interviewswith employees from Volvo Group Trucks, Renova, and the City of Gothenburg were conducted.The information from these interviews is combined with literature studies, service blueprints, andthe development of a simplified simulation model. The simulation compares the current state witha demand-driven model based on the fill levels of bins, which could potentially be measured usingsensors.The results demonstrate that there is room for efficiency improvements through increased datasharing and dynamic route optimization. The simulation model shows how demand-driven collectioncan reduce unnecessary emptying operations and help prevent overflowing bins. The economicanalysis also indicates potential cost savings, although assumptions have been made and the resultsshould therefore be interpreted with some caution.Furthermore, the recommendations suggest a phased implementation in which the initial focusshould be on utilizing existing data and establishing simpler forms of data-driven route planningbefore more advanced functions are implemented. In the longer term, a solution integrating realtimedata, sensors, and optimization algorithms can be developed. However, the results also showthat successful implementation requires not only technical solutions but also collaboration betweenstakeholders and access to relevant shareable data.