Lean Six Sigma Process Improvement via Python Simulation
Project Overview -- This project uses a discrete-event simulation built in Python with the SimPy library to model a coffee shop's customer flow. The goal is to apply the DMAIC (Define, Measure, Analyze, Improve, Control) methodology to identify bottlenecks and demonstrate the impact of process improvements in a quantifiable, data-driven way.
The Results -- The simulation proved that the initial process ("As-Is") with one barista was unable to handle the customer arrival rate, resulting in an average wait time of over 35 minutes. By implementing a simple process change—adding a second barista—we achieved over a 90% decrease in average wait times.
How to Run This Project
- Clone the repository:
git clone https://github.com/AdamElsaadany/Lean-Python-Project.git - Navigate to the project directory.
- Create and activate a virtual environment.
- Install the required libraries:
pip install -r requirements.txt - Run the simulation:
python simulation.py
Tools Used
- Python
- SimPy: For the discrete-event simulation.
- Matplotlib: For data visualization.
- Lean Six Sigma (DMAIC): As the guiding methodology for process improvement.