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.

中文翻译：

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快速、自动化地配置机器人制造单元


本研究提出了可重构和响应式机器人制造 （R3M） 架构，这是一种新颖的框架，旨在自主适应制造环境中波动的产品变体和需求。R3M 的核心是一个集成架构，可确保关键模块之间的无缝数据流，并由先进的通信平台提供便利。这些模块是提供对运营效率至关重要的一系列服务的核心。该架构的关键是纳入符合 ISO-12100 标准的自动风险评估，利用 ROS2 Gazebo 以即插即用的方式动态修改机器人技能。该架构独特的需求定义方法采用 AutomationML （AML），可实现有效的系统集成和各种信息源的整合。这是通过创新地使用基于技能的概念和 AML 类库来实现的，增强了系统的适应性和在制造环境中的集成。该叙述深入探讨了 AML 框架内对产品、设备和流程的复杂描述，强调了对产品领域盈利能力的战略考虑，并区分了设备表征中的原子技能和复合技能。过程域充当宝贵的知识库，通过过程模式弥合高级产品需求和特定设备功能之间的差距。R3M 框架中这些元素的结合提供了一个多功能且可扩展的解决方案，有望彻底改变制造流程。 实证结果强调了该架构的强大感知能力，特别关注机器人层压堆叠中的实际应用，阐明了 R3M 部署的固有挑战和切实成果。