NXTGEN DDBL
AI & Data
Semester programme:Minor Data Driven Business Lab
Research group:Sustainable Data & AI Application
Project description
The NXTGEN project focuses on improving a data generator that creates synthetic supply-chain data for simulations. Currently, data is manually transferred from an ERP system to Excel before being used in the generator. The goal of this project is to replace this manual step with ERP-based data and make the generator more realistic. This helps TU/e test supply-chain scenarios such as Make-to-Order and Make-to-Stock.
Context
This project is set in the domain of production and supply chain management. It focuses on how manufacturing companies use ERP systems to plan sales, production, and purchasing. The project uses a fictional bike company to simulate a real supply chain with multiple suppliers and production tiers. Data from this supply chain is used to test scenarios in a simulation model. The project combines business processes with IT and data-driven decision making.
Results
The most important outcome of this project is a clear understanding of the current data flow from the ERP system to the data generator. Several documents were created, such as a research document, an MKG user manual, and API analysis documents, which together explain how the system works and where improvements are possible. These results were validated through feedback from clients, testing in MKG and Postman, and comparison with existing generator behavior. The outcomes add value by making the project more structured, easier to continue, and better aligned with real supply chain processes. This creates a strong foundation for replacing manual Excel input with ERP-driven data in the future.