Rapid and automated configuration of robot manufacturing cells

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dc.contributor.authorAsif, Seemal
dc.contributor.authorBueno, Mikel
dc.contributor.authorFerreira, Pedro
dc.contributor.authorAnandan, Paul
dc.contributor.authorZhang, Ze
dc.contributor.authorYao, Yue
dc.contributor.authorRagunathan, Gautham
dc.contributor.authorTinkler, Lloyd
dc.contributor.authorSotoodeh-Bahraini, Masoud
dc.contributor.authorLohse, Niels
dc.contributor.authorWebb, Phil
dc.contributor.authorHutabarat, Windo
dc.contributor.authorTiwari, Ashutosh
dc.date.accessioned2024-10-16T15:49:00Z
dc.date.available2024-10-16T15:49:00Z
dc.date.freetoread2024-09-16
dc.date.issued2025-04-01
dc.date.pubOnline2024-09-05
dc.description.abstractThis 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.
dc.description.journalNameRobotics and Computer-Integrated Manufacturing
dc.description.sponsorshipEngineering and Physical Sciences Research Council
dc.description.sponsorshipThis research is supported by EPSRC grant (EP/V051180/1) for the Reconfigurable Robotics for Responsive Manufacture - R3M.
dc.identifier.citationAsif S, Bueno M, Ferreira P, et al., (2025) Rapid and automated configuration of robot manufacturing cells. Robotics and Computer-Integrated Manufacturing, Volume 92, April 2025, Article number 102862
dc.identifier.eissn1879-2537
dc.identifier.elementsID553291
dc.identifier.issn0736-5845
dc.identifier.paperNo102862
dc.identifier.urihttps://doi.org/10.1016/j.rcim.2024.102862
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23035
dc.identifier.volumeNo92
dc.languageEnglish
dc.language.isoen
dc.publisherElsevier
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S0736584524001492?via%3Dihub
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectReconfigurable manufacturing
dc.subjectModular robotics
dc.subjectCommon communication platform
dc.subjectAutonomous systems
dc.subjectRobot perception
dc.subjectAutonomous program generation
dc.subjectReconfigurable architecture
dc.subjectManufacturing automation
dc.subject46 Information and Computing Sciences
dc.subject4014 Manufacturing Engineering
dc.subject40 Engineering
dc.subjectBioengineering
dc.subject9 Industry, Innovation and Infrastructure
dc.subjectIndustrial Engineering & Automation
dc.subject40 Engineering
dc.subject46 Information and computing sciences
dc.titleRapid and automated configuration of robot manufacturing cells
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.dateAccepted2024-08-27

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