Integrating robotic systems into Learning Factories (LF) within modern manufacturing education settings is overly rigid and specialised, limiting their applicability to various project-based learning scenarios. This study developed a modular robotic system framework to address the need for a flexible robotic system, that can adapt to various educational projects while supporting versatile and practical student learning experiences. The study’s approach involves developing and evaluating a modular robotic framework using ABB robot studio software easily adapted to various project-based learning scenarios including pick and place, object detection and sorting, automated assembly, and visual inspection. The framework was implemented in a higher institution’s industrial engineering learning factory settings to assess its effectiveness and impact on students’ learning outcomes. Data was captured and analysed through observational studies, student engagement and educator feedback, across multiple learning projects using ABB IRB 1600 as a case study. The results obtained illuminated how the proposed framework enhances the student’s problem-solving, critical thinking, and collaborative skills. The main contributions of this research include the development of a flexible and scalable robotic system framework addressing diverse project types, and fostering a more interactive and engaging project-based learning experience. The study’s relevance in learning factories bridges the gap between rigid robotic systems and the dynamic needs of Industry 4.0.