Arbetsbeskrivning

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 thinking and optimization techniques to real-world manufacturing challenges.

You are currently pursuing a Master's degree in:

• Applied Mathematics
• Industrial Engineering
• Computer Science
• Artificial Intelligence
• Production Engineering
• Or a related field

Additionally, you have:

• A strong interest in optimization, operations research, algorithms, simulation, or industrial AI.
• Programming skills and a structured approach to problem-solving.
• Strong analytical and quantitative abilities.
• An interest in manufacturing, logistics, and digitalization.
• The ability to work independently while collaborating with experts across disciplines.

This Is Us

At Scania, we are driving the transformation towards sustainable transport solutions. By combining engineering excellence, digital innovation, and a strong focus on continuous improvement, we create products and production systems that make a real difference. The department behind this thesis is developing the digital capabilities needed to enable future factory planning. Through the use of PFEP data, virtual factory environments, and advanced optimization techniques, we are building smarter and more connected production systems. Many of our employees started their Scania journey through a thesis project. This is your opportunity to gain valuable industry experience, collaborate with experienced professionals, and contribute to solutions that have a direct impact on our operations.

Scania Offers

We offer a dynamic, flexible workplace with hybrid work options, including Scania Sergel and Midway hubs. With a structured development plan and courses, Scania supports your career growth both locally and internationally.

Benefits include training at our health center Gröndal or wellness allowance, result bonus, flexible hours, and company car leasing. Scania also hosts events for employees and their families, and Stockholm residents enjoy direct access to Södertälje via Scania Job express buses.

Application

Your application should include a CV and any relevant certificates. We welcome all applicants and strive for diversity in our recruitment processes.

Apply as soon as possible, no later than 2026-10-08. Screening will take place on an ongoing basis during the application period. Logical and personality tests may be used as part of the selection process, and a background check may be required for this role.

If you have questions or would like more information, please contact:

Andreas Lind, [email protected]

We look forward to your application!