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A roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System
International Journal of Production Research ( IF 9.2 ) Pub Date : 2020-05-20 , DOI: 10.1080/00207543.2020.1762944
Daqiang Guo 1, 2 , Ray Y. Zhong 1 , Shiquan Ling 1, 2 , Yiming Rong 2 , George Q. Huang 1
Affiliation  

The layout of fixed-position assembly islands (FPAI) is widely used for producing fragile or bulky products. With the increasing customised demand and unique operation patterns, manufacturing practitioners are facing challenges on flexible and efficient production arrangement to meet customer demand, which lead to inappropriate assembly islands configuration, frequent setups and long waiting times in FPAI. Industry 4.0 comes with the promise of improved flexibility and efficiency in manufacturing. In the context of Industry 4.0, this paper proposes a 5-layer APICS (assembly layer, perception layer, interaction layer, cognition layer, and service layer) roadmap for transformation and implementation of Assembly 4.0. Following the 5-layer APICS roadmap, a Graduation Intelligent Manufacturing System (GiMS) is presented as the pioneering implementation in FPAI. A graduation-inspired assembly system is designed for FPAI at assembly layer. Internet of Things (IoT) and industrial wearable technologies are deployed for perception, connection, and collaboration among various manufacturing resources at perception and interaction layer. A self-configuration model is proposed at cognition layer for autonomously configuring optimal assembly islands and corresponding production activities to meet customer demand. Cloud-based services are developed for managers and onsite operators to facilitate their decision-making and daily operations at service layer. Finally, a demonstrative case is conducted to verify the feasibility of the proposed methods.

中文翻译:

装配4.0路线图:毕业智能制造系统下固定位置装配岛的自配置

固定位置组装岛 (FPAI) 的布局广泛用于生产易碎或笨重的产品。随着定制化需求的增加和独特的运营模式,制造从业者面临着灵活高效的生产安排以满足客户需求的挑战,导致FPAI中组装岛配置不当、设置频繁和等待时间长。工业 4.0 承诺提高制造的灵活性和效率。在工业4.0的背景下,本文提出了5层APICS(装配层、感知层、交互层、认知层和服务层)路线图,用于装配4.0的转型和实施。遵循 5 层 APICS 路线图,毕业智能制造系统 (GiMS) 是 FPAI 中的开创性实施。在装配层为 FPAI 设计了一个受毕业启发的装配系统。物联网(IoT)和工业可穿戴技术被部署用于感知和交互层的各种制造资源之间的感知、连接和协作。在认知层提出了一种自配置模型,用于自主配置最优装配岛和相应的生产活动,以满足客户需求。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。在装配层为 FPAI 设计了一个受毕业启发的装配系统。物联网(IoT)和工业可穿戴技术被部署用于感知和交互层的各种制造资源之间的感知、连接和协作。在认知层提出了一种自配置模型,用于自主配置最优装配岛和相应的生产活动,以满足客户需求。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。在装配层为 FPAI 设计了一个受毕业启发的装配系统。物联网(IoT)和工业可穿戴技术被部署用于感知和交互层的各种制造资源之间的感知、连接和协作。在认知层提出了一种自配置模型,用于自主配置最优装配岛和相应的生产活动,以满足客户需求。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。以及各种制造资源在感知和交互层之间的协作。在认知层提出了一种自配置模型,用于自主配置最优装配岛和相应的生产活动,以满足客户需求。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。以及各种制造资源在感知和交互层之间的协作。在认知层提出了一种自配置模型,用于自主配置最优装配岛和相应的生产活动,以满足客户需求。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。为管理者和现场操作人员开发基于云的服务,以方便他们在服务层的决策和日常运营。最后,通过一个示范案例来验证所提出方法的可行性。
更新日期:2020-05-20
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