Background
Quintus Technologies are preparing to move our warehouse to a new facility, creating a unique opportunity to rethink our warehouse structure and material flows from the ground up. We are looking for a Master’s student who wants to help us develop an efficient, data-driven warehouse setup that can be implemented in our new facility.
Our warehouse operates in a high-mix, low-volume environment, with approximately 7,000 unique articles in different sizes, weights and with varying demand patterns. The warehouse supports two main flows:
- Production and assembly
- Aftermarket and spare parts
Many articles are used in both flows, while others are specific to either production or aftermarket. In the previous year, the warehouse handled approximately 35,000 pick lines for production and 5,000 for spare parts. The new facility gives us the opportunity to design a warehouse that creates efficient flows throughout the entire process – from receiving and storage to picking, internal transportation and packing.
Task description
The purpose of the thesis is to develop a data-driven recommendation for how the new warehouse should be structured and how articles should be positioned to create efficient material flows.
The project could investigate questions such as:
- How should the warehouse be divided into zones and how should different material flows be designed?
- How should articles be classified and positioned based on factors such as picking frequency, size, weight and usage?
- Should we use fixed, dynamic or hybrid storage locations?
- How should fast- and slow-moving articles be handled?
- How can picking routes and internal transportation distances be reduced?
- Should production and spare-parts articles be separated or integrated?
- Which articles are frequently picked together and could therefore benefit from being stored close to each other?
- How can historical transaction data and future demand be used to create smarter warehouse slotting?
Expected outcome
The goal is to develop a practical and implementable recommendation for our new warehouse. The result could include a recommended warehouse layout and zoning structure, principles for article placement, and a methodology for assigning articles to suitable storage locations.
We also want to understand the expected improvements compared with the current setup and how the solution can be maintained as our product mix and demand change over time.
Suitable background
We are looking for a Master’s student within Industrial Engineering & Management with specialization in Supply Chain Management, Logistics, Operations Management or a similar field. Preferably with high interest in data analysis, optimization and real-world problem solving.
Experience with Excel, Power BI, Python, optimization or simulation is a plus, but not a requirement.
Application Information
The thesis will take place at Quintus office in Västerås and is expected to start January 2027. The selection will be ongoing so therefore apply as soon as possible, but no later than October 31st.
Send your resume and a short introduction of yourself together with grades to recruitment@quintusteam.com