Introduction
Philips Drachten plays an important role in driving innovation in the Personal Health industry. With over 2000 employees from over 35 different nationalities, Philips Drachten is a global hub for consumer product innovation, employing experts who design products with outstanding end-user experience.
Problem Description
Understanding and predicting the physical behavior of hair interacting with (rotary) cutting systems (e.g., electric shavers, trimmers) is essential to improve cutting performance, comfort, and reliability. This assignment focuses on simulating hair cutting using multibody dynamics and comparing simulated behavior with experimental measurements from real cutting systems.
Relevance
Validating and improving hair-cutting models against real-hair experiments is crucial for both product performance and engineering science. High-fidelity validation minimizes reliance on expensive and time-consuming physical prototyping by boosting confidence in simulation-driven design decisions for rotary cutting systems (e.g., shavers, trimmers). Traditional validation methods—manual model parameter tuning and ad-hoc comparisons—are slow and may fail to detect systematic errors stemming from contact, friction, or cutting physics. A robust, data-driven validation workflow (paired experiments and simulations, quantitative metrics, and sensitivity analysis) facilitates automated, repeatable assessment of model accuracy and highlights which physical assumptions or parameters contribute to the largest discrepancies.
Aimed output
- Validate the existing haircutting model against real-hair experiments.
- Collect, preprocess, and store experimental and simulation data in analysis-ready formats.
- Run sensitivity and simple calibration analyses to identify key model parameters.
- Detailed technical report.
Student Profile
- Bachelor's or Master's student in (Bio)Mechanical Engineering, Applied Physics, Data Science, Computer Science, or a related discipline.
- Strong analytical, research, and problem-solving skills.
- Able to plan and execute experiments and simulations within an agreed scope and timeframe.
- Familiar with MATLAB and/or Python programming languages.
- Familiarity with multibody dynamics concepts and some CAD literacy is desirable.
- Basic knowledge of system identification, regression, or calibration techniques, and statistical analysis.
- Team player, contributing to effective teamwork and offering a point of view.
For more information, please contact:
Monique Schoeman