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dc.contributor.author
Hentz, Jean-Bernhard
dc.contributor.author
Nguyen, V.K.
dc.contributor.author
Maeder, W.
dc.contributor.author
Panarese, D.
dc.contributor.author
Gunnink, J.W.
dc.contributor.author
Gontarz, Adam
dc.contributor.author
Stavropoulos, P.
dc.contributor.author
Hamilton, Kelvin
dc.contributor.author
Hascoët, Jean-Yves
dc.contributor.editor
Teti, Roberto
dc.date.accessioned
2019-10-15T14:03:43Z
dc.date.available
2017-06-10T14:40:53Z
dc.date.available
2017-08-10T13:27:08Z
dc.date.available
2018-11-01T14:43:54Z
dc.date.available
2019-10-15T14:03:43Z
dc.date.issued
2012
dc.identifier.issn
2212-8271
dc.identifier.other
10.1016/j.procir.2013.09.042
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/64480
dc.identifier.doi
10.3929/ethz-a-007590615
dc.description.abstract
Today's major challenges for manufacturing companies in the aerospace and automotive industries are clear: global cooperation with multiple supply chain partners, production optimization, management and tracking of information so as to meet new requirements in terms of traceability, security and sustainability. The need for a data exchange standard that allows disparate entities and their associated devices in a manufacturing system to share data seamlessly is clearly obvious. And the first expected impact is the ‘next generation’ smart controller that could really enable an intelligent machining process based on real-time monitoring and diagnosis, self-learning decision and adaptive optimization. The four-year project titled FoFdation envisions a ‘Digital and Smart Factory’ architecture and implementation. This has the potential to achieve significant benefits in earlier visibility of manufacturing issues, faster production ramp-up time, faster time to volume production and subsequently shorter time to market, reduced manufacturing costs and improved product quality, as well as sustainability objectives like low energy consumption and waste reduction. The present paper describes the on-going work with specific focus on the definition and implementation of the FoFdation Smart Machine Controller (SMC) in an adaptable architecture that satisfies both commercial and open source CNC controllers. It highlights the project's end use validation framework as well as sets a strong Manufacturing Information System foundation on which process optimization and control as well as sustainable practices can be based. It presents the general vision of the target solution for the SMC developed in the FoFdation project. It is based on efforts past and present both by academia and industry in various capacities and proposes tentative implementations based on the STEP-NC standard to define the machine controller of the future.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject
Computer aided design
en_US
dc.subject
CAD (RECHNERGESTÜTZTES ENTWERFEN UND KONSTRUIEREN)
en_US
dc.subject
Adaptive control
en_US
dc.subject
CAD (COMPUTER AIDED DESIGN)
en_US
dc.subject
Computer aided planning
en_US
dc.subject
Computer automated process planning
en_US
dc.subject
Computer aided manufacturing
en_US
dc.subject
FABRIK DER ZUKUNFT (BETRIEBSWIRTSCHAFT)
en_US
dc.subject
Monitoring
en_US
dc.subject
FACTORY OF THE FUTURE (BUSINESS ECONOMICS)
en_US
dc.subject
Computer numerical control
en_US
dc.title
An enabling digital foundation towards smart machining
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
dc.date.published
2013-10-14
ethz.book.title
Eighth CIRP Conference on Intelligent Computation in Manufacturing Engineering
en_US
ethz.journal.title
Procedia CIRP
ethz.journal.volume
12
en_US
ethz.pages.start
240
en_US
ethz.pages.end
245
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::620 - Engineering & allied operations
en_US
ethz.event
8th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME)
en_US
ethz.event.location
Napoli, Italy
en_US
ethz.event.date
July 18-20, 2012
en_US
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
ethz.date.deposited
2017-06-10T14:41:18Z
ethz.source
ECOL
ethz.source
ECIT
ethz.identifier.importid
imp5936506997b7521207
ethz.identifier.importid
imp59366b33a660570303
ethz.ecolpid
eth:6376
ethz.ecitpid
pub:102461
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T05:22:18Z
ethz.rosetta.lastUpdated
2019-10-15T14:03:55Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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