This repository contains the results and analysis of the LEGO Project, conducted as part of the SCM 517 coursework. The objective was to design and optimize a LEGO race car using a Designed Experiment (DOE) to maximize the distance traveled after descending a ramp.
- Experimental Setup:
- Designed and tested LEGO race cars with varying configurations.
- Used a ramp with a consistent angle, height, and surface.
- Factors Studied:
- Wheelbase length (Long/Narrow, Long/Broad).
- Tire size (Big/Small).
- Weight distribution (Front/Back).
- Data Analysis:
- Conducted half-factorial DOE using Minitab.
- Analyzed main effects and interactions between factors.
- Evaluated trade-offs between performance and cost.
- Optimization:
- Identified the most cost-effective and highest-performance car configurations.
- Presentation Slides:
- Includes project objectives, experimental setup, results, and recommendations.
- Data Files:
- Experimental results and cost breakdown.
- Analysis Code:
- Python scripts for visualizations and cost-effectiveness calculations.
- Plots and Graphs:
- Main Effects Plot, Interaction Plot, Residual Analysis, and Trade-Off Visualizations.
- Best Performance Configuration:
- Long Wheelbase + Broad Base + Big Tires + Back Weight.
- Distance: 124.7 cm.
- Cost: $18,400.
- Most Cost-Effective Configuration:
- Long Wheelbase + Broad Base + Small Tires + Front Weight.
- Distance: 105 cm.
- Cost: $13,600.