Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations

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Fältnamn	Indikatorer	Metadata
000		04095naa a2200493 4500
001		oai:research.chalmers.se:24d2efc0-c4d4-4d5b-8406-6ee90cfe6fde
003		SwePub
008		200319s2020 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
024	7	a https://research.chalmers.se/publication/5160032 URI
024	7	a https://doi.org/10.1080/00207543.2020.17356602 DOI
040		a (SwePub)cth
041		a engb eng
042		9 SwePub
072	7	a art2 swepub-publicationtype
072	7	a ref2 swepub-contenttype
100	1	a Farooqui, Ashfaq Hussain,d 1990u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)ashfaqf
245	1 0	a Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations
264		c 2020-03-09
264	1	b Informa UK Limited,c 2020
338		a electronic2 rdacarrier
520		a Published by Informa UK Limited, trading as Taylor & Francis Group. The technological advancements of recent years have increased the complexity of manufacturing systems, and the ongoing transformation to Industry 4.0 will further aggravate the situation. This is leading to a point where existing systems on the factory floor get outdated, increasing the gap between existing technologies and state-of-the-art systems, making them incompatible. This paper presents an event-based data pipeline architecture, that can be applied to legacy systems as well as new state-of-the-art systems, to collect data from the factory floor. In the presented architecture, actions executed by the resources are converted to event streams, which are then transformed into an abstraction called operations. These operations correspond to the tasks performed in the manufacturing station. A sequence of these operations recount the task performed by the station. We demonstrate the usability of the collected data by using conformance analysis to detect when the manufacturing system has deviated from its defined model. The described architecture is developed in Sequence Planner–a tool for modelling and analysing production systems–and is currently implemented at an automotive company as a pilot project.
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Inbäddad systemteknik0 (SwePub)202072 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Embedded Systems0 (SwePub)202072 hsv//eng
650	7	a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe
650	7	a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Datorsystem0 (SwePub)202062 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Computer Systems0 (SwePub)202062 hsv//eng
653		a conformance checking
653		a data streams
653		a smart factories
653		a sequence anomaly detection
653		a big data
653		a Industry 4.0
653		a manufacturing systems
653		a data acquisition and aggregation
700	1	a Bengtsson, Kristofer,d 1979u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)benkri
700	1	a Falkman, Petter,d 1972u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)pf
700	1	a Fabian, Martin,d 1960u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)fabian
710	2	a Chalmers tekniska högskola4 org
773	0	t International Journal of Production Researchd : Informa UK Limitedg 58:16, s. 4947-4963q 58:16<4947-4963x 0020-7543x 1366-588X
856	4	u https://research.chalmers.se/publication/516003/file/516003_Fulltext.pdfx primaryx freey FULLTEXT
856	4	u https://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1735660?needAccess=true
856	4 8	u https://research.chalmers.se/publication/516003
856	4 8	u https://doi.org/10.1080/00207543.2020.1735660

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