As 3D printing technology advances, the demand for precise, reliable production methods grows, with tighter product specifications and higher quality standards becoming essential. This study focuses on students learning experience as they explore the statistical analysis of process capabilities in 3D Printing, specifically assessing the accuracy and precision of vertically and horizontally printed objects. Through hands-on experimentation, students gain valuable skills in evaluating critical factors influencing 3D printer performance, such as geometry, material selection, and printer settings. The research enables students to assess the process limits of 3D printers and develop strategies to minimize variability and improve production quality. Students learn how these factors affect the final product by experimenting with different printer configurations, internal designs, and operational parameters. The study also highlights cost-effective solutions by identifying print settings that optimize performance and reduce defects. Ultimately, this learning experience deepens students understanding of 3D printing process control, enhances their ability to make data-driven decisions, and equips them with practical knowledge for improving efficiency in advanced manufacturing applications.