A Cloud Service Control Approach for Distributed and Adaptive Equipment Control in Cloud Environments
2016 (English)In: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems / [ed] Roberto Teti, Elsevier, 2016, Vol. 41, 644-649 p.Conference paper (Refereed)
A developing trend within the manufacturing shop-floor domain is the move of manufacturing activities into cloud environments, as scalable, on-demand and pay-per-usage cloud services. This will radically change traditional manufacturing, as borderless, distributed and collaborative manufacturing missions between volatile, best suited groups of partners will impose a multitude of advantages. The evolving Cloud Manufacturing (CM) paradigm will enable this new manufacturing concept, and on-going research has described many of its anticipated core virtues and enabling technologies. However, a major key enabling technology within CM which has not yet been fully addressed is the dynamic and distributed planning, control and execution of scattered and cooperating shop-floor equipment, completing joint manufacturing tasks.
In this paper, the technological perspective for a cloud service-based control approach is described, and how it could be implemented. Existing manufacturing resources, such as soft, hard and capability resources, can be packaged as cloud services, and combined to create different levels of equipment or manufacturing control, ranging from low-level control of single machines or devices (e.g. Robot Control-as-a-Service), up to the execution of high level multi-process manufacturing tasks (e.g. Manufacturing-as-a-Service). A multi-layer control approach, featuring adaptive decision-making for both global and local environmental conditions, is proposed. This is realized through the use of a network of intelligent and distributable decision modules such as event-driven Function Blocks, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system’s integration to the CM cloud service management functionality is also described.
Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 41, 644-649 p.
Procedia CIRP, ISSN 2212-8271 ; 41
cloud manufacturing, cloud service, adaptive manufacturing, robot control
Production Engineering, Human Work Science and Ergonomics
Research subject Technology
IdentifiersURN: urn:nbn:se:his:diva-11372DOI: 10.1016/j.procir.2015.12.020ISI: 000379247600110ScopusID: 2-s2.0-84968752806OAI: oai:DiVA.org:his-11372DiVA: diva2:847042
CIRP CMS 2015, 48th CIRP Conference on Manufacturing Systems, Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future, 24-26 June 2015, Ischia (Naples), Italy