WO Internship Data Science Building a physics-informed ML model

Ondertitel

Building a physics-informed ML model for predicting mechanical properties of rolled steel products

Wat ga je doen?

Tata Steel R&D have developed a through-process physics based model (MeCoMeP) for predicting mechanical properties of steel grades using measurement data obtained throughout the processing of a steel coil. The model is comprised of a data pipeline used to gather the data, combined with standalone C++ executables which perform the model calculations. The results can be used to assist the different production facilities in product development and optimisation, root cause analysis of product and process failures and for supplying customers with positional mechanical property data to enable pre-setup in forming parts for the automotive industry.

The MeCoMeP model is a phenomenological model that tries to describe all relevant metallurgical processes during strip hot rolling and galvanising e.g. grain growth, recrystallisation, phase transformation, precipitation, cementite formation and carbon rejection. Physical equations describe the microstructural evolution taking place during each step of the process and the mechanical behaviour of the resultant microstructure in order to predict the mechanical properties of the steel after processing.

The advantage of this approach is that process steps are identified which are known to affect mechanical properties and are consistent throughout all grades produced over a particular production line. The limitation is that the model does not take into account other process parameters which could affect properties especially when subject to significant variations during operation.

The goal of this research is to combine the physics based model with a more generalised data driven model to improve the predictive ability of existing and future steel products.

• Aim: Improve accuracy of excisting physics and ML models in predicting mechanical properties
• Deliverable: Algorithm for fitting the generalised physics based model prediction to individual steel grades and continuous monitoring of model fit quality:
  • ​​​​​​​Start from base model with 4 steel grade families
  • Improving the model fit for individual steel grades
    • ​​​​​​​Investigate alternative fitting models for grade specific model predictions
    • Compare non-linear modelling techniques against current linear regression model to improve the model performance
  • Create model quality monitor to track model fit over time

Herken jij jezelf hierin?

• You are a MSC student in the field of data science.
• You are familiar with programming languages such as C++, SQL and Python.
• You have an affinity for physical sciences
• You are looking for a graduate internship.

The assignment is intended for an internship of nine months.

Wat bieden wij jou?

We offer you a paid internship with proper guidance. In consultation with you, we start with drawing up your assignment to make sure that it fits the requirements of your university. You can gain valuable experience within a large organization and Dutch only manufacturing industry. You can count on a no-nonsense and result-oriented organization, within which you can make a concrete contribution to the realization of improvement objectives. During your training period you can regularly participate in events such as student tours and lunch lectures. We also offer the possibility to make use of our Library Services. When you are in your final Master of Bachelor internship, you can temporarily become part of our internal Association for young professionals "The Magnet"

Wat is jouw werkomgeving?

The project will be conducted within R&D department of Tata Steel Ijmuiden with great opportunities for networking and being closely involved in the future developments. On a daily base you will working in the R&D innovation centre office, surrounded with other students and colleaguas with different kinds of know-how.

Solliciteren of meer weten?

Is this the assignment for you? Please apply directly via the application button below, don’t forget to upload your motivation letter. If you have any questions or want to have more information first? Please contact one of our Campus Recruiters (Phone +31 (0)251- 494 000).