Nucor Steel — Manufacturing Planning & Saleability Analytics

I worked on a manufacturing analytics project focused on improving planning decisions for non-standard steel coil transitions at Nucor Steel. The project analyzed how production, quality, demand, and variability factors influence the saleability and cost impact of different grade transitions within a steel manufacturing environment.

I developed a data-driven penalty model to evaluate transition risk and built a Python/Streamlit decision-support tool that ranked steel grade transitions by saleability risk, expected cost impact, and planning priority. The goal was to help manufacturing and planning teams better identify which transitions could create operational inefficiencies, excess cost, or downstream saleability concerns.

This project strengthened my understanding of industrial operations, supply planning, manufacturing tradeoffs, and continuous improvement in a real-world steel production context. It also allowed me to apply data analytics and optimization thinking to a complex operational problem with direct business impact.

👉Link to Nucor App

👉Link to Project Report

👉Link to Presentation Deck

Skills/Tools: Python, Streamlit, Excel, Manufacturing Analytics, Supply Chain Planning, Cost Modeling, Process Improvement