Intern assignment
By | Pawel Roman, Le Viet Duc |
Thesis or intern assignment | Causal root‑cause analysis for quality deviations in a continuous manufacturing process |
Wavin department | Discovery |
Education of candidate | Data Science / Computer Science / Applied Mathematics / Industrial Engineering (Bachelor) |
Description of the assignment
In continuous manufacturing, a key quality variable may occasionally deviate from its expected range. Many process variables change simultaneously, which makes it difficult to determine which factors caused the deviation and which only changed in parallel.
In this assignment you will develop a causal analysis approach using historical multivariate time‑series data. You will identify relevant deviation events, apply causal discovery or causal inference techniques, and assess which process variables are most likely to be true drivers. The results should be translated into clear, testable insights that support engineering decision‑making.
Goal of the assignment
Develop and validate a causal analysis pipeline that identifies the most likely root causes of quality deviations.
Additional information
Intern type: Bachelor assignment
Duration: 2 months
Workload: Full‑time (minimum 32 hours/week)
Gross reimbursement per month (full‑time): 400 EUR
About Wavin
Wavin is an innovative solution provider for the building and infrastructure industry globally. With over 60 years’ of expertise, we aim to solve global challenges in water supply, sanitation, climate-resilient cities and building performance. We are committed to building healthy, sustainable environments. Wavin is headquartered in the Netherlands, and has presence in over 25 countries.
Contact:
Le Viet Duc