This bachelor’s thesis aims to integrate new data into discrete event simulation (DES) models within a powertrain foundry environment at Volvo GTO in Skövde, Sweden. While traditional manufacturing simulations focus on production-related key performance indicators (KPI) such as throughput or lead time, this project integrates energy as a measurable and analysable KPI, supporting sustainability and decision making.
The initial challenge at the line was the lack of energy monitoring in key operations. Combining a case study methodology with simulation modelling, real consumption data from several operations were collected using different methods and tools like ABB’s Signal Analyzer or metering devices. Then, based on this data, energy profiles were created and implemented in two simulation tools: Plant Simulation and the recently launched inFACTS Studio.
A comparison between those two tools was carried out, highlighting the similarities and differences of their results as well as their capabilities and limitations in simulating energy. In addition, both models have been validated with real and theoretical data, confirming their reliability in representing the line’s energy behaviour.
Including energy consumption as a KPI not only provides Volvo with new insights of the process but also opens the door to future optimization approaches or strategies regarding power usage. This thesis closes the gap between sustainability goals and industrial simulation practices, offering a replicable methodology for similar manufacturing environments.