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dc.contributor.author
Vegetti, Maria Marcela
dc.contributor.author
Leone, Horacio Pascual
dc.contributor.author
Henning, Gabriela Patricia
dc.date.available
2017-02-24T14:47:43Z
dc.date.issued
2011-08
dc.identifier.citation
Vegetti, Maria Marcela; Leone, Horacio Pascual; Henning, Gabriela Patricia; PRONTO: An ontology for comprehensive and consistent representation of product information; Elsevier; Engineering Applications Of Artificial Intelligence; 24; 8; 8-2011; 1305-1327
dc.identifier.issn
0952-1976
dc.identifier.uri
http://hdl.handle.net/11336/13365
dc.description.abstract
Nowadays, it is quite common for collaborating organizations (or even different areas within a company) to develop and maintain their own product model. This situation leads to information duplication and its associated problems. Besides, traditional product models do not properly handle the high number of variants managed in today competitive markets. In addition, there is a need for an integrated product model to be shared by all the organizations participating in global supply chains (SCs) or all the areas within a company. One way to reach an intelligent integration among product models is by means of an ontology. PRoduct ONTOlogy (PRONTO) is an ontology for the product modeling domain, able to efficiently handle product variants. It defines and integrates two hierarchies to represent product information: the abstraction hierarchy (AH) and the structural one (SH). This contribution presents a ConceptBase formal specification of PRONTO that focuses on the structural hierarchy of products. This hierarchy is a tool to handle product information associated with the multiple available recipes or processes to manufacture a particular product or a set of similar products. The formal specification presented in the paper also includes mechanisms to infer structural information from the explicit knowledge represented at each of the AH levels: Family, VariantSet and Product. This proposal efficiently handles a great number of variants and allows representing product information with distinct granularity degrees, which is a requirement for planning activities taking place at different time horizons. PRONTO easily manages crucial features that should be taken into account in a product representation, such as the efficient handling of product families and variants concepts, composition and decomposition structures and the possibility of specifying constraints. To demonstrate the semantic expressiveness of the proposed ontology a food industry related case-study is addressed and discussed in detail.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
Product Model
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Domain Ontology
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Product Structure
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Product Family
dc.subject.classification
Otras Ciencias de la Computación e Información
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
PRONTO: An ontology for comprehensive and consistent representation of product information
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-02-17T13:25:27Z
dc.journal.volume
24
dc.journal.number
8
dc.journal.pagination
1305-1327
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Vegetti, Maria Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina. Universidad Tecnologica Nacional; Argentina
dc.description.fil
Fil: Leone, Horacio Pascual. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina. Universidad Tecnologica Nacional; Argentina
dc.description.fil
Fil: Henning, Gabriela Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
dc.journal.title
Engineering Applications Of Artificial Intelligence
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.engappai.2011.02.014
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0952197611000388
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