Rapid and automated configuration of robot manufacturing cells

摘要

• Introduction of the R3M Architecture: The paper introduces a novel framework called Reconfigurable and Responsive Robot Manufacturing (R3M), which autonomously adapts to fluctuating product variants and demands within manufacturing environments. • Integration of Automated Program Generation: R3M integrates advanced Automated Program Generation (APG) technology that reduces reliance on human input, thereby enhancing the autonomy of robotic cells. • Modular and Reconfigurable Components: The study emphasizes the use of modular and reconfigurable components, which allow manufacturing systems to quickly adapt to changes in the production environment. • Empirical Validation with Robotic Lamination Stacking: The architecture is empirically validated through a real-world application in robotic lamination stacking, demonstrating robust perception abilities and operational adaptability. • Utilization of Industry 4.0 Technologies: The paper discusses how Industry 4.0 technologies are leveraged to transform traditional manufacturing systems, focusing on scalability and adaptability. This study presents the Reconfigurable and Responsive Robot Manufacturing (R3M) architecture, a novel framework engineered to autonomously adapt to fluctuating product variants and demands within manufacturing environments. At the heart of R3M lies an integrated architecture that ensures a seamless data flow between critical modules, facilitated by an advanced communication platform. These modules are central to delivering a range of services crucial for operational efficiency. Key to the architecture is the incorporation of Automated Risk Assessment aligned with ISO-12100 standards, utilizing ROS2 Gazebo for the dynamic modification of robot skills in a plug-and-produce manner. The architecture's unique approach to requirements definition employs AutomationML (AML), enabling effective system integration and the consolidation of varied information sources. This is achieved through the innovative use of skill-based concepts and AML Class Libraries, enhancing the system's adaptability and integration within manufacturing settings. The narrative delves into the intricate descriptions of products, equipment, and processes within the AML framework, highlighting the strategic consideration of profitability in the product domain and distinguishing between atomic and composite skills in equipment characterization. The process domain serves as an invaluable knowledge repository, bridging the gap between high-level product demands and specific equipment capabilities via process patterns. The culmination of these elements within the R3M framework provides a versatile and scalable solution poised to revolutionize manufacturing processes. Empirical results underscore the architecture's robust perception abilities, with a particular focus on a real-world application in robotic lamination stacking, elucidating both the inherent challenges and the tangible outcomes of the R3M deployment.