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Ontology for cloud manufacturing based Product Lifecycle Management

Author

Listed:
  • Asma Talhi

    (Khtema sas, Lamih, CNRS, Arts et métiers, ParisTech)

  • Virginie Fortineau

    (Khtema sas)

  • Jean-Charles Huet

    (EIGSI)

  • Samir Lamouri

    (Lamih, CNRS, Arts et métiers, ParisTech)

Abstract

The manufacturing environment has become increasingly competitive in the past few years, and product development is getting even more complex. The agility of an information system is a way to manage this complexity, and cloud technologies enable the sharing of tools and information in a new way. In particular, in the field of Product Lifecycle Management, a review of the literature demonstrates that there are technical issues that limit the efficient collaboration between the various stakeholders along the product lifecycle. Cloud manufacturing is a new concept that enables the virtualization of manufacturing resources and capabilities and provides them as a service. Therefore it offers new prospects for usage and collaboration in the extended enterprise, and along the product lifecycle. For instance, it helps to manage variations in production demand, by providing a large set of potential manufacturing resources on demand. However, to share the resources within the cloud manufacturing environment, a unification model of the domain information is required, to which any provider and/or user of cloud manufacturing must conform in order to dialog with the other CM stakeholders. This study provides an ontological model of the cloud manufacturing domain in order to support information exchange between the cloud manufacturing resources. The concepts of the proposed ontology are based on a literature review of models of cloud and models of manufacturing. The detailed ontology is then validated using the OntoClean methodology and within its implementation in an industrial scenario.

Suggested Citation

  • Asma Talhi & Virginie Fortineau & Jean-Charles Huet & Samir Lamouri, 2019. "Ontology for cloud manufacturing based Product Lifecycle Management," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2171-2192, June.
  • Handle: RePEc:spr:joinma:v:30:y:2019:i:5:d:10.1007_s10845-017-1376-5
    DOI: 10.1007/s10845-017-1376-5
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    References listed on IDEAS

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    1. Hong Jin & Xifan Yao & Yong Chen, 2017. "Correlation-aware QoS modeling and manufacturing cloud service composition," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1947-1960, December.
    2. Yang-Kuei Lin & Chin Soon Chong, 2017. "Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1189-1201, June.
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    Citations

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    Cited by:

    1. Xiaobao Zhu & Jing Shi & Fengjie Xie & Rouqi Song, 2020. "Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1985-2002, December.
    2. Wei Nie & Katharina Vita & Tariq Masood, 2024. "An ontology for defining and characterizing demonstration environments," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3501-3521, October.
    3. Shashi Bhushan Jha & Radu F. Babiceanu & Remzi Seker, 2020. "Formal modeling of cyber-physical resource scheduling in IIoT cloud environments," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1149-1164, June.
    4. Juan José Montero Jiménez & Rob Vingerhoeds & Bernard Grabot & Sébastien Schwartz, 2023. "An ontology model for maintenance strategy selection and assessment," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1369-1387, March.
    5. Shiyong Yin & Jinsong Bao & Jie Zhang & Jie Li & Junliang Wang & Xiaodi Huang, 2020. "Real-time task processing for spinning cyber-physical production systems based on edge computing," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 2069-2087, December.
    6. Reza Vatankhah Barenji, 2022. "A blockchain technology based trust system for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1451-1465, June.
    7. Xiaochen Zheng & Xiaodu Hu & Rebeca Arista & Jinzhi Lu & Jyri Sorvari & Joachim Lentes & Fernando Ubis & Dimitris Kiritsis, 2024. "A semantic-driven tradespace framework to accelerate aircraft manufacturing system design," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 175-198, January.

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