Högskolan i Skövde

his.sePublications
Planned maintenance
A system upgrade is planned for 10/12-2024, at 12:00-13:00. During this time DiVA will be unavailable.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Manufacturing Knowledge Management Using a Virtual Factory-Based Ontology Implemented in a Graph Database
University of Skövde, School of Engineering Science.
2022 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Ontology-based technologies like Semantic Web and Knowledge Graphs are promising for knowledge management in manufacturing industries. In the literature there are abundant of publications related to using ontologies to represent and capture knowledge in manufacturing. Many of them cover the use of ontologies for managing knowledge in different aspects of Product Lifecycle Management (PLM). Nevertheless, very few of them cover how ontologies can be used with virtual factory models, data and information as well as the knowledge generated from using these models and their corresponding engineering activities. An “extension” of existing ontologies is badly needed as digital, virtual models in terms of simulation and digital twins have become more popular in the industry. Without such an extended knowledge management process and system, it is difficult to re-use the artefacts and knowledge generated from the expensive and valuable virtual engineering activities. Relying on the cutting-edge graph database technologies and what they can offer regarding knowledge management, and also recent developments in the domain ontology field, an extended knowledge management implementation, specifically designed for virtual engineering has been done. Moreover, a clear roadmap for establishment of knowledge bases around production systems armed with Virtual Factory(VF) and Multi-Objective Optimization (MOO) processes has been provided. This, includes defining key elements of manufacturing procedures, constructing an ontology, defining data structure in preferably a graph database, and accessing valuable historical (provenance) data regarding different engineering entities and/or activities.

Place, publisher, year, edition, pages
2022. , p. 61
Keywords [en]
Knowledge Management, Ontology, Graph database, Graph theory, Virtual Factory, Knowledge-Driven Optimization
National Category
Robotics
Identifiers
URN: urn:nbn:se:his:diva-22038OAI: oai:DiVA.org:his-22038DiVA, id: diva2:1709935
Subject / course
Virtual Product Realization
Educational program
Intelligent Automation - Master's Programme, 120 ECTS
Supervisors
Examiners
Available from: 2022-11-10 Created: 2022-11-10 Last updated: 2022-11-10Bibliographically approved

Open Access in DiVA

fulltext(2428 kB)296 downloads
File information
File name FULLTEXT01.pdfFile size 2428 kBChecksum SHA-512
e4d74c35fa7bdaacdd7773dbcb3dd2eec54bc6ae4b399a538f044f24d0a7e71ab2bfaec81b27d723c825d0eb25eaca5fabadcbf86716691ddca486c800da88fe
Type fulltextMimetype application/pdf

By organisation
School of Engineering Science
Robotics

Search outside of DiVA

GoogleGoogle Scholar
Total: 296 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 698 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf