Thesis Work - Digital Factory (layout planning)

30 hp – Plan for Every Part-driven multi-objective optimization of line-side material presentation and factory layout 

Introduction

Thesis work is an excellent way to get closer to Scania and build relationships for the future. Many of today's employees began their Scania career with their degree project. 

Background 

Digital factory planning requires continuity between material planning, resource configuration and factory layout. PFEP datasets describes article-level needs such as point of use, packaging, quantity, weight, and more. Ongoing Scania work uses PFEP datasets to generate line-side racks and pallets configurations in a virtual factory environment as part of a broader concept in production-and-logistics (P&L) data backbone. The next step is to utilize these PFEP generated configurations in virtual environment of station- or area-level multi-objective optimizations. 

Objective 

Develop and evaluate a multi-objective approach for jointly reconfiguring and positioning PFEP-generated line-side resources. Decision variables may include rack pose, rack and shelf configuration, article or package reassignment and within-shelf placement. Preserve PFEP traceability and return accepted results as structured PFEP change proposals. 

Job description 

Review the PFEP rack generator and previous layout optimization framework; formulate the station- or area-level problem; and implement suitable optimization methods. Constraints may include geometry, package fit, access and material-flow rules. Objectives may include worker well-being, material flow or walking, logistics handling, area use and reconfiguration effort. Compare optimized solutions with a PFEP baseline in an industrial case and evaluate quality, robustness and computational performance. Define a traceable, user-approved PFEP change set for article reassignment, rack reconfiguration and resource relocation. 

Education/program/focus 

Master's in Applied Mathematics, Industrial Engineering, Computer Science/AI, Production Engineering or similar, with focus on optimization/OR, algorithms or simulation. 

Number of students: 1-2 

Start date for the thesis work: January 2027, or as agreed 

Estimated time required: 20 weeks 

Contact persons and supervisors 

Scania CV AB, Global Industrial Development, Södertälje.

Andreas Lind, andreas.lind@scania.com 

Application:

Your application must include a CV, personal letter and transcript of grades

A background check might be conducted for this position. We are conducting

interviews continuously and may close the recruitment earlier than the date

specified.    

Publication date from-to.

2026-10-01–2026-11-22