Master thesis student AI-Assisted Requirements Management and Supplier Response Analysis

30 hp, AI-Assisted Requirements Management and Supplier Response Analysis in Procurement Processes 

Are you a Master’s student interested in generative AI, information modelling and business processes? We are looking for 1–2 Master’s students to develop and evaluate a prototype for AI-assisted requirements management and supplier analysis in procurement processes. 

Background 

Our department develops test rigs for validating and testing various truck components. Together with other functions across the company, we procure CE-marked machines and equipment. To ensure compliance with legal requirements, safety standards, and internal regulations, every procurement must meet a comprehensive set of requirements supported by definitions, guidelines, and technical documentation. 

Managing a large and evolving requirements library is a significant challenge. Requirements must be continuously reviewed, updated, refined, and eventually retired. At the same time, each procurement project requires a tailored set of requirements that accurately reflects the specific needs of the solution being purchased. Today, much of this work is performed manually, making the process both time-consuming and difficult to maintain consistently. 

Objective 

The objective of this thesis is to develop and evaluate a prototype that combines Artificial Intelligence (AI) with structured information modelling to support and streamline the procurement process. 

The prototype should assist in several areas, including: 

• Management and maintenance of procurement requirements 

• Selection of relevant requirements for a specific procurement case 

• Analysis of supplier responses 

• Preparation of documentation required for order placement 

An important aspect of the project is that AI should support and enhance human decision-making rather than replace it. The solution should therefore provide transparent and traceable results that can be reviewed, verified, and challenged by procurement specialists and engineers. 

This thesis offers a unique opportunity to gain insight into procurement and engineering processes within a leading technology company. You will be involved in the practical application of AI in an industrial environment and have the opportunity to influence how AI can be used to improve future ways of working. 

Preferred Qualifications 

• 1–2 MSc students in Computational Science, Machine Learning, Artificial Intelligence or a master student with high interest/knowledge in AI modelling. 
  
  

Start date of thesis work: January 2027 

Estimated time required: 20 weeks 

Contact persons and supervisors  

Sara Carlen, Head of Mechanical and Process for test rig development (TGRPPID), sara.carlen@se.traton.com, +468 553 749 52

Tom Stenberg, Development Engineer (TGRPPID). tom.stenberg@se.traton.com, +468 553 833 90