Proposal of a Methodology for Mechatronic Design From Ideation to Embodiment Design: Application in a Masonry Robot Case Study Design
Luis A. Salazar-Calderón, Javier Izquierdo-Reyes, Javier A. de la Tejera
- 发表年份
- 2025
- 引用次数
- 2
摘要
The growing complexity of industrial automation requires advanced design methodologies that integrate mechanical, electronic, and software systems into cohesive mechatronic products. This paper introduces an innovative engineering design methodology focused on the development of mechatronic products, covering from ideation to embodiment design. For its validation, the methodology was applied in a case study involving the design of a construction robot that automates key tasks such as block transportation, mortar application, and block placement. The robot was designed using a modular approach, allowing for scalability and adaptability to various tasks within the construction environment. To evaluate the methodology’s effectiveness, a comparative assessment was conducted using five key criteria: Iterative Process, Multidisciplinary Work, Design Complexity, Usability, and Adaptability. The proposed methodology scored 3, 3, 3, 2, and 2 respectively, on a 0–3 scale, demonstrating strong performance in early-stage iteration, cross-disciplinary integration, and handling of complex designs, with moderate usability and adaptability. These results position the methodology among the most balanced approaches, bridging both classical and modern design methods, such as those proposed by Ulrich or the V-model. Initial validation of this case study, through simulations and conceptual design, highlights the robot’s potential to improve efficiency and reduce labor costs. Although the case study targets construction, the methodology is adaptable to various industrial contexts, particularly manufacturing processes requiring automation, modularity, and flexibility. Future work includes the development of a physical prototype and further validation, with the potential to expand the methodology to broader manufacturing environments, fostering human-robot collaboration and adaptive production systems.
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