Adaptive robotic control in cloud environments
2014 (English)In: FAIM 2014 - Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing: Capturing Competitive Advantage via Advanced Manufacturing and Enterprise Transformation, DEStech Publications Inc , 2014, 37-44 p.Conference paper (Refereed)Text
The increasing globalization is a trend which forces manufacturing industry of today to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing (CM) is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. Providing a framework for collaboration within complex and critical tasks, such as manufacturing and design, it increases the companies' ability to successfully compete on a global marketplace. One of the major, crucial objectives for CM is the coordinated planning, control and execution of discrete manufacturing operations in a collaborative and networked environment. This paper describes the overall concept of adaptive Function Block control of manufacturing equipment in Cloud environments, with the specific focus on robotic assembly operations, and presents Cloud Robotics as "Robot Control-as-a-Service" within CM. © Copyright 2014 by DEStech Publications, Inc. All rights reserved.
Place, publisher, year, edition, pages
DEStech Publications Inc , 2014. 37-44 p.
Competition, Complex networks, Cost effectiveness, Manufacture, Robotic assembly, Supply chains, Coordinated planning, Discrete manufacturing operations, Manufacturing equipment, Manufacturing industries, Manufacturing networks, Manufacturing paradigm, Manufacturing units, Networked environments, Robotics
IdentifiersURN: urn:nbn:se:kth:diva-187593ScopusID: 2-s2.0-84960920841ISBN: 9781605951737OAI: oai:DiVA.org:kth-187593DiVA: diva2:935473
24th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2014, 20 May 2014 through 23 May 2014
QC 201606102016-06-102016-05-252016-06-10Bibliographically approved