Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Diagnosis of COVID-19 on Chest X-ray (CXR) Images Using CNN with Transfer Learning and Integrated Stacking Ensemble Learning Read chapter Read first chapter

2024 | OriginalPaper | Chapter

Development of Joining Process Ontology for Ensuring Data Consistency in Knowledge Management Systems

Authors : Muhammad Alif Hafizan Bin Mohd Zaini, Munira Binti Mohd Ali

Published in: Intelligent Manufacturing and Mechatronics

Publisher: Springer Nature Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Inconsistency data from the knowledge management system comes from unstable data and entities that have been defined. Data not being saved on the proper platform will result in inconsistent data. This research aims to develop an ontology for the selected joining process that provides a standard understanding structure to support user interoperability across heterogeneous data. Based on that, it is important to develop the ontology by identifying and classifying the correct entities. The basic formal ontology has been adopted as the top-level ontology for the development of the ontology for the joining process. The ontology is then expanded with entities related to the joining process. The ontology needs to be evaluated based on consistency, accuracy, and adaptability. A sample of data from research related to the welding process was used to test the capability of the ontology to infer information. As a result, proper ontology development will solve the inconsistency of data in the knowledge management system.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Enhancing WEDM Efficiency by Teaching–Learning-Based Optimization for Machining Process Parameter Optimization
next chapter Brain Lesion Image Segmentation Using Modified U-NET Architecture
Literature
1.
Rus I, Lindvall M, Sinha SS (2001) Data & analysis center for software
2.
Santoro G, Vrontis D, Thrassou A, Dezi L (2018) The internet of things: building a knowledge management system for open innovation and knowledge management capacity’. Technol Forecast Soc Chang 136:347–354CrossRef
3.
Wang Z, Chen CH, Zheng P, Li X, Khoo LP (2021) A graph-based context-aware requirement elicitation approach in smart product-service systems. Int J Prod Res 59(2):635–651CrossRef
4.
Brunoe TD, Andersen AL, Sorensen DG, Nielsen K, Bejlegaard M (2020) Integrated product-process modelling for platform-based co-development. Int J Prod Res 58(20):6185–6201CrossRef
5.
Tchoffa D, Figay N, Ghodous P, Exposito E, Apedome KS, El Mhamedi A (2019) Dynamic manufacturing network—from flat semantic graphs to composite models. Int J Prod Res 57(20):6569–6578CrossRef
6.
Leo Kumar SP (2019) Knowledge-based expert system in manufacturing planning: state-of-the-art review. Int J Prod Res 57(15–16):4766–4790CrossRef
7.
Ali MM, Rai R, Otte JN, Smith B (2019) A product life cycle ontology for additive manufacturing. Comput Ind 105:191–203CrossRef
8.
Ali MM, Doumbouya MB, Louge T, Rai R, Karray MH (2020) Ontology-based approach to extract product’s design features from online customers’ reviews. Comput Ind 116:103175CrossRef
9.
Mohd Ali M, Yang R, Zhang B, Furini F, Rai R, Otte JN, Smith B (2021) Enriching the functionally graded materials (FGM) ontology for digital manufacturing. Int J Prod Res 59(18):5540–5557CrossRef
10.
Saha S, Usman Z, Li WD, Jones S, Shah N (2019) Core domain ontology for joining processes to consolidate welding standards. Robot Comput Integ Manuf 59:417–430CrossRef
11.
Sankar BV, Lawrence ID, Jayabal S (2018) Experimental study and analysis of weld parameters by GRA on MIG welding. Mater Today Proc 5(6):14309–14316CrossRef
12.
Tewari SP, Gupta A, Prakash J (2010) Effect of welding parameters on the weldability of material. Int J Eng Sci Technol 2(4):512–516
Metadata
Title
Development of Joining Process Ontology for Ensuring Data Consistency in Knowledge Management Systems
Authors
Muhammad Alif Hafizan Bin Mohd Zaini
Munira Binti Mohd Ali
Copyright Year
2024
Publisher
Springer Nature Singapore
Book
Intelligent Manufacturing and Mechatronics

Print ISBN: 978-981-9988-18-1

Electronic ISBN: 978-981-9988-19-8

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-981-99-8819-8_45

Premium Partners

    Image Credits