Adaptive Robot Control as a Service in Cloud Manufacturing

Author:

Adamson Göran1,Wang Lihui12,Holm Magnus1,Moore Philip3

Affiliation:

1. University of Skövde, Skövde, Sweden

2. Royal Institute of Technology, Stockholm, Sweden

3. Falmouth University, Cornwall, UK

Abstract

The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appear. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of Cloud Manufacturing will not be fulfilled. By utilising smart and distributable decision modules such as event-driven Function Blocks, run-time manufacturing operations in a distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, they will satisfy the control needs. By combining different resource types, such as hard, soft and capability resources, the cloud service Robot Control-as-a-Service can be realised. This paper describes the functional perspective and enabling technologies for a distributed control approach for robotic assembly tasks in Cloud Manufacturing.

Publisher

American Society of Mechanical Engineers

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enterprise and service−level scheduling of robot production services in cloud manufacturing with deep reinforcement learning;Journal of Intelligent Manufacturing;2023-12-16

2. Feature-based function block control framework for manufacturing equipment in cloud environments;International Journal of Production Research;2018-11-27

3. Scheduling in cloud manufacturing: state-of-the-art and research challenges;International Journal of Production Research;2018-03-20

4. Latest Advancement in Cloud Technologies;Cloud-Based Cyber-Physical Systems in Manufacturing;2017-11-17

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