DYNAMIC CO2 EMISSION EVALUATION - Application of Discrete Event Simulation (DES) for emission evaluation in a pump production line

Abstract

As companies across the globe are transitioning towards net-zero manufacturing practices, applying smart data-driven solutions to the complex production systems is paramount. This thesis presents a Discrete Event Simulation (DES) based approach to quantify and reduce the CO2 emissions for a process within the pump manufacturing line at Grundfos. Utilising DES, the study replicates the manufacturing line to study real-world operations needed for a complete product, capturing production specifications like resource utilisation, idle times and energy usage. This data is also used to calculate the CO2 emissions from the line dynamically. The model was developed using the DES software, FlexSim. The data used was validated against one day of previously recorded factory data and from the feedback from experts at Grundfos. Multiple scenarios were contemplated to evaluate their effects on CO2 emission reduction. Results highlight the key inefficiencies of the current manufacturing setup and showcase how data-driven improvements can allow for a significant reduction in energy usage and emissions with consistent output. Finally, the study supports Grundfos’s sustainability goals and also facilitates a framework for integration of DES with sustainable manufacturing. The findings from the thesis lay the foundation of a shift towards smart production systems, committing to low carbon emissions, and demonstrating the power of DES.