Okvir za informacijsko podporo procesom v proizvodnih sistemih na osnovi velepodatkov

doktorsko delo

Dominik Kozjek (Author), Peter Butala (Mentor), Rok Vrabič (Co-mentor)

Abstract

Intenziven razvoj informacijskih in komunikacijskih tehnologij, ki smo mu priča v zadnjih letih, povzroča na področju proizvodnje nastajanje velikih količin podatkov. Pojavljajo pa se tudi novi pristopi, metode, tehnike in orodja za napredno podatkovno analitiko, kar ponuja nove možnosti za uporabo velikih količin kompleksnih podatkov oz. velepodatkov za doseganje večje konkurenčnosti. Vendar apliciranje napredne podatkovne analitike na področju proizvodnje v primerjavi z drugimi področji ni tako prodorno in raznoliko, podatki, ki so na voljo, pa največkrat ostanejo neizkoriščeni. V delu je razvit okvir za informacijsko podporo procesom v proizvodnih sistemih in predstavljena njegova uporaba. Okvir je zastavljen kot konceptualno orodje, ki olajšuje uvajanje analitike velepodatkov v proizvodnih sistemih. Namen okvira je po korakih predstaviti postopek uvedbe analitike velepodatkov v proizvodnih sistemih ter sistematično predstaviti, katera znanja in spretnosti, referenčni modeli, orodja in drugi elementi so za to potrebni. Razvoj okvira temelji na rešitvah za podatkovno analitiko, razvitih in preučevanih v okviru te študije, ter na drugih obstoječih rešitvah iz literature in prakse. Demonstrirani in potrjeni sta izvedljivost in široka uporabnost okvira na vseh nivojih proizvodnega sistema.

Keywords

podatkovna analitika;velepodatki;konceptualni okvir;informacijska podpora;odkrivanje znanja;podatkovno rudarjenje;

Data

Language:	Slovenian
Year of publishing:	2019
Typology:	2.08 - Doctoral Dissertation
Organization:	UL FS - Faculty of Mechanical Engineering
Publisher:	[D. Kozjek]
UDC:	658.5:004.451.5(043.3)
COBISS:	302904832
Views:	1177
Downloads:	384
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Information support framework for processes in manufacturing systems based on big data
Secondary abstract:	Due to the intensive development of information and communication technologies in the domain of production, large amounts of data are being generated. Many new approaches, methods, techniques, and tools for advanced data analytics are being developed and, consequently, additional possibilities of using large amounts of complex data - also referred to as big data, are emerging. However, the application of advanced data analytics in the production domain lags behind in penetration and diversity in comparison to other domains, and the data available often remains unexploited. This work presents the development and demonstrates the use of a framework for information support for processes in manufacturing systems. The framework is a conceptual tool that facilitates the introduction of big data analytics into manufacturing systems. The objective of the framework is to present a step-by-step procedure of introducing big data analytics into manufacturing systems and to systematically show what knowledge and skills, reference models, software and hardware tools, etc., are needed. The framework is based on the development and research of several data-analytics solutions developed during the course of this study, as well as on other existing applications and conceptual solutions from literature and practice. The feasibility and wide applicability of the framework at all manufacturing-system levels are demonstrated and validated.
Secondary keywords:	manufacturing systems;data analytics;big data;conceptual framework;information support;knowledge discovery;data mining;Proizvodni sistemi;Disertacije;
Type (COBISS):	Dissertation
Study programme:	0
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za strojništvo
Pages:	XXVI, 150 str.
ID:	11299381