Pregled bibliografske jedinice broj: 988393
An ontology based semantic data model supporting a MaaS digital platform
An ontology based semantic data model supporting a MaaS digital platform // IS 2018 Proceedings
Madeira, Portugal, 2018. str. 1-8 (radionica, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 988393 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
An ontology based semantic data model supporting a MaaS digital platform
Autori
Landolfi, Giuseppe ; Barni, Andrea Francesco ; Izzo, Gabriele ; Montini, Elias ; Bettoni, Andrea ; Vujasinović, Marko ; Gugliotta, Alessio ; Soares, António Lucas ; Silva, Henrique Diogo
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IS 2018 Proceedings
/ - , 2018, 1-8
Skup
9th international Conference on Intelligent Systems 2018
Mjesto i datum
Madeira, Portugal, 05.09.2018. - 27.09.2018
Vrsta sudjelovanja
Radionica
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
proizvodne ontologije ; semantički podatkovni model ; otkriće znanja
(manufacturing ontologies ; semantic data-model ; knowledge discovery)
Sažetak
The integration of IoT infrastructures across production systems, together with the extensive digitalisation of industrial processes, are drastically impacting manufacturing value chains and the business models built on the top of them. By exploiting these capabilities companies are evolving the nature of their businesses shifting value proposition towards models relying on product servitization and share, instead of ownership. In this paper, we describe the semantic data-model developed to support a digital platform fostering the reintroduction in the loop and optimization of unused industrial capacity. Such data-model aims to establish the main propositions of the semantic representation that constitutes the essential nature of the ecosystem to depict their interactions, the flow of resources and exchange of production services. The inference reasoning on the semantic representation of the ecosystem allows to make emerge non-trivial and previously unknown opportunities. This will apply not only to the matching of demand and supply of manufacturing services, but to possible and unpredictable relations. For instance, a particular kind of waste being produced at an ecosystem node can be linked to the requirements for an input material needed in a new product being developed on the platform, or new technologies can be suggested to enhance processes under improvement. The overall architecture and individual ontologies are presented and their usefulness is motivated via the application to use cases.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Visoka škola za menadžment i dizajn Aspira, Split
Profili:
Marko Vujasinović
(autor)