Descripción
Role Summary Are you passionate about optimization and smart manufacturing? At Scania, you'll have the opportunity to contribute to the next generation of digital factory planning by developing innovative optimization solutions that improve material flow, workplace efficiency, and factory layout design. In this master's thesis, you will explore how Plan for Every Part (PFEP) data can be leveraged to jointly optimize line-side material presentation and factory layouts within a virtual production environment. Working on a real industrial challenge, you will develop and evaluate advanced optimization methods that support data-driven decision making across production and logistics operations. This thesis offers an excellent opportunity to gain hands-on experience in a global manufacturing company while building valuable connections for your future career. Job Responsibilities As part of this thesis project, you will: Review existing PFEP-based rack generation solutions and layout optimization frameworks. Formulate a station- or area-level multi-objective optimization problem. Design, implement, and evaluate suitable optimization algorithms and methodologies. Optimize the configuration and positioning of line-side resources, including racks, shelves, and material presentation solutions. Consider real-world constraints such as geometry, package fit, accessibility, and material flow requirements. Assess objectives including: Worker well-being and ergonomics, Material flow efficiency, Walking distance reduction, Logistics handling performance, Area utilization, Reconfiguration effort Compare optimized solutions against a PFEP baseline using industrial case studies. Evaluate solution quality, robustness, and computational performance. Develop structured and traceable PFEP change proposals for resource relocation, rack reconfiguration, and article reassignment. Who You Are We are looking for one or two highly motivated Master's students who are eager to apply analytical think