Thesis Internship Network Capacity Planning

Job Description:

- Type of internship: Full time thesis internship

- Compensation: between €800 and €900 (per 4 weeks)

- Location: Veghel

- Start date: September

About Mars

Mars is a family-owned company with more than a century of history. We make products and provide services for both people and pets. With sales of nearly $45 billion, we operate in 180 countries and stand behind some of the world's best-loved brands such as M&M'S®, SNICKERS®, TWIX®, MILKY WAY®, DOVE®, PEDIGREE®, ROYAL CANIN®, WHISKAS® and FREEDENT®.

The Network Capacity Planning (NCP) team at Mars is responsible for the mid- and long-term planning of all production lines across 11 internal European factories and various external production sites. The team focuses on network utilization balancing, capacity management, inventory management, and ensuring that all production planning parameters are up to date in the planning system.

We are looking for a graduation intern who can provide an external perspective by leveraging scientific research and industry best practices.

The research topic can be defined in collaboration with the student and the guiding professor. Possible research topics include:

• Manufacturing lot sizes & production cycles: Traditional models use static data to calculate batch sizes and production frequencies. How can we adapt these models to a dynamic and agile world with advanced planning systems?

• Network balancing: Some products can be produced on multiple production lines across Europe. How can we develop an automated model that recommends production locations based on factors such as costs, manufacturing constraints, and legal requirements?

• Frozen horizon: Currently, production planning operates in weekly buckets, with the first two weeks frozen. What would be the benefits and system requirements for reducing the frozen horizon to just 48 hours?

• Segmentation: Many companies use segmentation in planning processes (e.g., A-items for high-runners, B-items for mid-level, C-items for low-runners). How could Mars implement segmentation, and how would planning processes need to change to gain benefits?

• Cost of bias: When markets overestimate demand, excess inventory accumulates. What is the full end-to-end supply chain cost of a positive bias, and how can we mitigate this risk?

Candidate Profile

We are looking for a motivated student with a strong analytical mindset and excellent communication skills:

• Master’s student in Industrial Engineering (OML Master)

• Strong analytical and problem-solving skills.

• Ability to translate theoretical insights into practical business applications.

• Strong communication skills to present findings and recommendations.

• Dutch preferred, English required.

This is an exciting opportunity to contribute to real-world supply chain challenges at Mars while working on a graduation project that combines academic research with practical implementation.

Questions about this vacancy? Please send an email to: earlytalent.nl@effem.com