Applied Mathematics Researcher | Furman University & Industry-Sponsored Project with Michelin and BMW
Introduction:
Throughout the summer, I worked on a project sponsored by Michelin and BMW. My role was to develop a mathematical model to predict tire demand for Michelin, and contribute to a data-driven project at BMW aimed at making plant operations more efficient.
Project Overview:
Michelin:
Develop a mathematical model to predict tire demand for Michelin as precise as possible because it is a key factor in the production process. If overestimated, the production will be wasted, including commodity, labor cost, time and resources. If underestimated, the production will be short that Michelin can't meet the need of customer.
BMW:
Contribute to a data-driven project at BMW aimed at making plant operations more efficient.
Results:
Michelin:
- The model was able to predict the commodity production with an accuracy of 90%.
- Linear regression model was used to predict the commodity production because we believe gives out the good result with high r^2 score.
BMW:
- The data-driven project at BMW was able to make plant operations more efficient .
Conclusion:
I have learnt a lot about through this summer experience since I have a chance to work the real-life project that none of the classes can bring the same experience. This unique experience allows me to apply the knowledge I have learned in the classroom to the real-world problems and also develop my skills in the industry. It is different from the classroom experience because there is not one right answer or clear path to the solution. It requires me to think creatively and critically to find the best solution with uncertainty. However, this is how the industry works and I am glad to have the opportunity to experience it. I am grateful for the opportunity to work on this project with my team, Michelin and BMW. And I am excited to see the results. As the projects come to an end, I am looking forward to the next challenge and opportunity to learn and grow.