IMPROVING THE CAPABILITY OF LEAN ASSEMBLY LINE SIMULATION AT SWISS GERMAN UNIVERSITY INDUSTRIAL ENGINEERING LAB

Abstract

This thesis examines the limitations of the current LEAN assembly line simulation at the Swiss German University (SGU) laboratory by incorporating infrared (IR) sensors and barcode scanners for better data collection and tracking. The existing simulation still relies on manual data gathering, which can lead to errors and lacks the needed flexibility for effective LEAN analysis. The research suggests using IR sensors to automatically detect product movements and barcode scanners to accurately identify components. The goal is to improve data accuracy regarding cycle times and inventory management. The thesis will cover the system's design and implementation, including user-friendly data visualization. Additionally, it will assess the improved simulation's effectiveness compared to manual methods and explore its benefits for teaching LEAN concepts and research.