PLM Ontology Exploitation through Inference and Statistical Analysis A Case Study for LCC

Milicic, Ana; Perdikakis, Apostolos; Kadiri, Soumaya El; Kiritsis, Dimitris

doi:10.3182/20130619-3-ru-3018.00043

Cited by 9 publications

(10 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A significant feature offered by ontologies, which is particularly important in the context of PLM, is the possibility to bridge multiple domains, in reference to the concept of multi-facets (Lim et al 2010(Lim et al , 2011. Finally, although not fully explored yet by the engineering community, ontology has shown promising results in data integration using Linked Data principles, one of the main challenges in PLM, as discussed in El Kadiri, Milicic, and Kiritsis (2013). It can be highlighted from the literature review that ontology acts as a key enabler for overcoming simultaneously several issues.…”

Section: Analysis Of the Work Related To Ontology-based Applicationsmentioning

confidence: 97%

“…This framework is based on five root concepts: product, process, resource, rule and business. Milicic et al (2012aMilicic et al ( , 2013 propose a tool for ontology exploitation based on first reasoning mechanisms and second on ontology instances extraction for the purpose of data mining and pattern discovery. El Kadiri, Milicic, and Kiritsis (2013) propose a methodology to support PLM taking advantage from the emerging paradigm of Linked Data which offer a promising approach for data integration.…”

Section: Ontology-based Applicationsmentioning

confidence: 99%

“…Milicic et al (2012aMilicic et al ( , 2013 propose a tool for ontology exploitation based on first reasoning mechanisms and second on ontology instances extraction for the purpose of data mining and pattern discovery. El Kadiri, Milicic, and Kiritsis (2013) propose a methodology to support PLM taking advantage from the emerging paradigm of Linked Data which offer a promising approach for data integration. Additional ontology applications are provided in Kiritsis (2012) putting the light on the benefits of applying such technologies in the context of Asset Lifecycle Management.…”

Section: Ontology-based Applicationsmentioning

confidence: 99%

See 2 more Smart Citations

Ontologies in the context of product lifecycle management: state of the art literature review

Kadiri

Kiritsis

2015

International Journal of Production Research

View full text Add to dashboard Cite

The use of ontologies in the context of product lifecycle management (PLM) is gaining importance and popularity, while at the same time it generates a lot of controversy in discussions within scientific and engineering communities. Yet, what is ontology? What challenges have been addressed so far? What role does ontology play? Do we really need ontology? These are the core questions this paper seeks to address. We propose to conduct a comprehensive study of the concept of Ontology firstly in its domain of origin, Philosophy, and secondly in information science. Based on the understanding of this concept and an in-depth analysis of the state of the art, seven key roles of ontology are defined. These roles serve as a framework describing the general state of research on the use of ontologies in the context of PLM.

show abstract

Section: Analysis Of the Work Related To Ontology-based Applicationsmentioning

confidence: 97%

Section: Ontology-based Applicationsmentioning

confidence: 99%

Section: Ontology-based Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Ontologies in the context of product lifecycle management: state of the art literature review

Kadiri

Kiritsis

2015

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…In this problem-solving process, existing LCC domain ontologies are considered as the first source of knowledge that we use LCC concepts from PLM Ontology [16], [17]. The LCC concepts are used to extend the MLCA ontology.…”

Section: Collaborative Framework Exploitationsmentioning

confidence: 99%

“…As literature in Sect. 2.2, we select LCC ontology, namely Product Life Cycle Management (PLM) Ontology [16], [17], to represent an efficient and convenient method for structuring and modeling the LCC domain in a case of manufacturing company. Therefore, a result of our adaptive ontology development is MLCA ontology containing 396 concepts, 21 concepts properties, 105 datatype properties, and 20 instances.…”

Section: Ontological Engineering Processesmentioning

confidence: 99%

Collaborative Ontology Development Approach for Multidisciplinary Knowledge: A Scenario-Based Knowledge Construction System in Life Cycle Assessment

Takhom

Usanavasin²,

Supnithi

et al. 2018

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYCreating an ontology from multidisciplinary knowledge is a challenge because it needs a number of various domain experts to collaborate in knowledge construction and verify the semantic meanings of the cross-domain concepts. Confusions and misinterpretations of concepts during knowledge creation are usually caused by having different perspectives and different business goals from different domain experts. In this paper, we propose a community-driven ontology-based application management (CD-OAM) framework that provides a collaborative environment with supporting features to enable collaborative knowledge creation. It can also reduce confusions and misinterpretations among domain stakeholders during knowledge construction process. We selected one of the multidisciplinary domains, which is Life Cycle Assessment (LCA) for our scenariobased knowledge construction. Constructing the LCA knowledge requires many concepts from various fields including environment protection, economic development, social development, etc. The output of this collaborative knowledge construction is called MLCA (multidisciplinary LCA) ontology. Based on our scenario-based experiment, it shows that CD-OAM framework can support the collaborative activities for MLCA knowledge construction and also reduce confusions and misinterpretations of crossdomain concepts that usually presents in general approach. key words: sematic web, ontology-based knowledge management, collaborative framework, multidisciplinary ontology development, life cycle assessment

show abstract

Linked Data Exploration in Product Life-Cycle Management

Kadiri

Milicic

Kiritsis

2013

IFIP Advances in Information and Communication Technology

View full text Add to dashboard Cite

PLM Ontology Exploitation through Inference and Statistical Analysis A Case Study for LCC

Cited by 9 publications

References 5 publications

Ontologies in the context of product lifecycle management: state of the art literature review

Ontologies in the context of product lifecycle management: state of the art literature review

Collaborative Ontology Development Approach for Multidisciplinary Knowledge: A Scenario-Based Knowledge Construction System in Life Cycle Assessment

Linked Data Exploration in Product Life-Cycle Management

Contact Info

Product

Resources

About