This project aimed to optimize the performance of statapult, an educational tool used to demonstrate Six Sigma principles, by addressing its significant variability in projection accuracy. Utilizing the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, the team systematically identified and mitigated root causes affecting the device's consistency. The primary challenges included variations in tension pin settings, rubber band configurations, and pull-back angles, leading to deviations of over ±5 inches in 70% of trials from the target distance of 10 feet. In the Define phase, the team clarified project goals and outlined critical factors. The Measure phase established a baseline of performance metrics, revealing key inconsistencies. Through the Analyze phase, statistical tools and root cause analyses pinpointed the variables impacting reliability. The Improve phase implemented solutions, including adjusting launch angles, stabilizing the base, and standardizing settings. Finally, the Control phase focused on sustaining improvements through monitoring tools like control charts, developing Standard Operating Procedures (SOPs), and implementing mistake-proofing measures. The project successfully reduced variability, achieving a deviation of ±2 inches in 90% of trials, demonstrating the practical application of Six Sigma in process optimization. The structured approach provides insights into improving accuracy and consistency in engineering systems.