Simulation and Optimization of Production Flow

Sammanfattning

This thesis is conducted in the transmission department of Scania, a leading manufacturer of heavy vehicles that provides high-quality transport solutions to their customers. The study addresses the bottlenecks at various lines and aims to optimize the production flow by implementing discrete event simulation modeling. The use of virtual simulation software like Extendsim has become increasingly popular in recent times. It is critical to production optimization as well as to facilitate data-driven decision making to implement production line changes in the factory. This thesis examines the benefits and challenges that come with using software such as Extendsim to create production scenarios that improve the performance of the lines. In Extendsim, a generalized model is created that reflects the various assembly lines present in the shaft and shot peening department. By creating this model, we were able to visualize multiple scenarios to increase operational performance and determine the bottlenecks in the line. The model is created from various input data such as resource utilization, downtimes, and inventory, from which we are able to reduce costs and suggest improvements. This study also highlights the challenges involved in incorporating the software as it depends on model complexity, accuracy of the input data, expertise of the user, and the software limitations. The results demonstrate the successful implementation of the software in optimizing the production flow for soft machining lines, while also recognizing the challenges related to data quality and model configurations. This study provides an overall framework that will help companies determine if simulation tools are valuable for enhanced decision making and optimizing production.