Machine learning applied to an intelligent and adaptive robotic inspection station

Variz, Luis; Piardi, Luis; Rodrigues, Pedro João; Leitão, Paulo

Publication

Machine learning applied to an intelligent and adaptive robotic inspection station

2019Conference object

dc.contributor.author	Variz, Luis
dc.contributor.author	Piardi, Luis
dc.contributor.author	Rodrigues, Pedro João
dc.contributor.author	Leitão, Paulo
dc.date.accessioned	2020-04-01T08:18:29Z
dc.date.available	2020-04-01T08:18:29Z
dc.date.issued	2019
dc.description.abstract	Industry 4.0 promotes the use of emergent technologies, such as Internet of Things (IoT), Big Data, artificial intelligence (AI) and cloud computing, sustained by cyber-physical systems to reach smart factories. The idea is to decen-tralize the production systems and allow to reach monitoring, adaptation and optimization to be made in real time, based on the large amount of data available at shop floor that feed the use of machine learning techniques. This technological revolution will bring significant productivity gains, resources savings and reduced maintenance costs, as machines will have information to operate more efficiently, adaptable and following demand fluctuations. This paper discusses the application of supervised Machine Learning techniques allied with artificial vision, to implement an intelligent, collaborative and adaptive robotic inspection station, which carries out the quality control of Human Machine Interface (HMI) consoles, equipped with pressure buttons and LCD displays. Machine learning techniques were applied for the recognition of the operator's face, to classify the type of HMI console to be inspected, to classify the state condition of the pressure buttons and detect anomalies in the LCD displays. The developed solution reaches promising results, with almost 100% accuracy in the correct classification of the consoles and anomalies in the pressure buttons, and also high values in the detection of defects in the LCD displays.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Variz, Luis; Piardi, Luis; Rodrigues, Pedro Joao; Leitão, Paulo (2019). Machine learning applied to an intelligent and adaptive robotic inspection station. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). Helsinki, Finland	pt_PT
dc.identifier.doi	10.1109/INDIN41052.2019.8972298	pt_PT
dc.identifier.uri	http://hdl.handle.net/10198/21304
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Machine learning	pt_PT
dc.subject	Artificial vision	pt_PT
dc.subject	Quality control	pt_PT
dc.subject	Convolution neural network	pt_PT
dc.title	Machine learning applied to an intelligent and adaptive robotic inspection station	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.citation.conferencePlace	Helsinki, Finland	pt_PT
oaire.citation.endPage	295	pt_PT
oaire.citation.startPage	290	pt_PT
oaire.citation.title	2019 IEEE 17th International Conference on Industrial Informatics (INDIN)	pt_PT
person.familyName	Piardi
person.familyName	Rodrigues
person.familyName	Leitão
person.givenName	Luís
person.givenName	Pedro João
person.givenName	Paulo
person.identifier	A-8390-2011
person.identifier.ciencia-id	C51A-82DB-016F
person.identifier.ciencia-id	1316-21BB-9015
person.identifier.ciencia-id	8316-8F13-DA71
person.identifier.orcid	0000-0003-1627-8210
person.identifier.orcid	0000-0002-0555-2029
person.identifier.orcid	0000-0002-2151-7944
person.identifier.scopus-author-id	35584388900
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