On knowledge reuse for manufacturing systems design and planning: A semantic technology approach

Efthymiou, Konstantinos; Σίψας, Κωνσταντίνος; Mourtzis, Dimitris; Chryssolouris, George

doi:10.1016/j.cirpj.2014.10.006

Cited by 59 publications

(27 citation statements)

References 17 publications

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“…This is supported by the European Factories of the Future (FoF) initiative and outlined in many recent calls, thus placing the core of this research in the centre of European manufacturing research (Ferreira et al, 2013). Key research output from the FoF agenda include virtual factory framework (VFF) (Efthymiou et al, 2015), EUPASS (Agyapong-Kodua et al, 2014b) and the Sustainable Factory Semantic Framework (SuFSeF) (Tolio et al, 2013). These researches led to the development of the concept of Digital Factory (DF) which has been known to be a collection of methods, models and tools to provide support for factory design, factory planning based on manufacturing systems simulations and the VFF (Stef et al, 2013, Wenzel et al, 2005.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition, semantic integration improves query efficiency and reduces labour costs in terms of data rebuilding. In the future, many excellent semantic-based application systems will be widely used in industry design systems (Efthymiou et al, 2015). This will include assembly sequence planning, e-procurement and information retrieval systems.…”

Section: Literature Reviewmentioning

confidence: 99%

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Integrated Ontologies in Support of Factory Systems Design

Zhang

Agyapong-Kodua

2015

IFAC-PapersOnLine

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Digital factory modelling based on virtual design and simulation has emerged as part of the mainstream activities geared towards reducing product design cycle. Some basic industrial systems are currently integrated via semantic modelling technologies so that products matching processes and resource requirements are integrated to fulfil customer demands. Despite these achievements, product design is still dependent on the knowledge of designers and do not benefit from existing process and resource knowledge, which are in separate domains. This paper therefore presents an integration method based on semantic technologies and PPR ontologies to enable the reuse of known and unknown knowledge. The method relies on the use of cloud manufacturing to improve the efficiency of responses generated by querying the PPR ontology.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Integrated Ontologies in Support of Factory Systems Design

Zhang

Agyapong-Kodua

2015

IFAC-PapersOnLine

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“…On this way ontology enables the possibility of combining information based on its abstraction levels and method of improvement in capturing as well as reusing (Chang et al, 2006). According to SMEs (Efthymiou et al, 2015), the knowledge management lack in performing the classification of past projects which take more time in identifying the similarity between new and past projects available in the memory.…”

Section: Related Workmentioning

confidence: 99%

An Advanced ontology based automatic approach in improving the similarity by means of combining the sub‐graphs between the information

Sumathy

Chidambaram

2016

Int. j. adv. appl. sci

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In this research an advanced and automatic approach in finding the new products which are similar to the previous one that results in a rapid experience in production of design of manufacturing procedure of the new product has been proposed. The proposed work is based on advanced ontology based semantic model which computes similarity between the subgraphs in an effective manner. It builds a hierarchical structure by means of new similarity index that forms by overlapping sub-graph of existing two product concepts. By means of stored data the similarity measurement is calculated by matching the similar characteristics with the new one that helps in discovering knowledge. The examined result with the real-time data shows minimum computation cost along with high processing speed in similarity according to the global environment. Thus proves the proposed scheme is far better than other existing similarity approaches.

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“…VFF is a framework to integrate process and resource information into a shareable virtual environment, while supporting manufacturing planning design for whole product lifecycle [10,11]. The key aspect of VFF architecture is a Virtual Factory Data Model (VFDM) based on the semantic technologies to define various types of data and knowledge stored in a shared knowledge repository using a universal language.…”

Section: A Current Framework For Integrated Manufacturingmentioning

confidence: 99%

Ontology based semantic-predictive model for reconfigurable automation systems

Zhang

Ahmad

Vera

et al. 2016

2016 IEEE 14th International Conference on Industrial Informatics (INDIN)

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Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here is a working paper or pre-print that may be later published elsewhere. If a published version is known of, the above WRAP url will contain details on finding it. Abstract-Due to increasing product variety and complexity, capability to support reconfiguration is a key competitiveness indicator for current automation system within large enterprises. Reconfigurable manufacturing systems could efficiently reuse existing knowledge in order to decrease the required skills and design time to launch new products. However, most of the software tools developed to support design of reconfigurable manufacturing system lack integration of product, process and resource knowledge, and the design data is not transferred from domain-specific engineering tools to a collaborative and intelligent platform to capture and reuse design knowledge. The focus of this research study is to enable integrated automation systems design to support a knowledge reuse approach to predict process and resource changes when product requirements change. The proposed methodology is based on a robust semantic-predictive model supported by ontology representations and predictive algorithms for the integration of Product, Process, Resource and Requirement (PPRR) data, so that future automation system changes can be identified at early design stages.

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On knowledge reuse for manufacturing systems design and planning: A semantic technology approach

Cited by 59 publications

References 17 publications

Integrated Ontologies in Support of Factory Systems Design

Integrated Ontologies in Support of Factory Systems Design

An Advanced ontology based automatic approach in improving the similarity by means of combining the sub‐graphs between the information

Ontology based semantic-predictive model for reconfigurable automation systems

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