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Adaptive capacity management in cloud manufacturing hyper-network platform: Case of COVID-19 equipment production

Rezapour Niari, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1080/17509653.2021.2009389
  3. Publisher: Taylor and Francis Ltd , 2022
  4. Abstract:
  5. Cloud Manufacturing (CMfg) is a service-oriented manufacturing (SOM) paradigm that provides a dynamic, scalable, and virtualized working ecosystem. The CMfg collaborative structure can be modeled as a hyper-network-based service-demand matching architecture. It is enriched with quality of service (QoS) characteristics to produce customized products in a stable and reliable network. This stability should be considered in the overall manufacturing network mechanism. This paper has provided adaptive strategies utilizing available resources and capacities to enhance the system’s stability and reliability against the unexpected events. The capabilities of the enhanced framework are utilized to handle the unexpected situation that has occurred during the COVID-19 disruption treatment in Iran, Tehran. The paper has designed the reliable CMfg network to analyze the virtual ventilator production processes. The proposed framework successfully and efficiently enabled the CMfg architecture to use small and medium enterprises (SMEs) and knowledge-based companies’ capabilities in producing common components. These components were transferred among the stakeholders using the adaptive capacities of vehicles. The results of analysis indicated that the adaptive strategies increased collaborations among CMfg members and provided more serving alternatives as possible solutions to decision-makers. An increase in the number of feasible solutions makes the structure more resilient to unexpected events. © 2022 International Society of Management Science and Engineering Management
  6. Keywords:
  7. Adaptive capacity ; Cloud Manufacturing network management ; Covid-19 ; Reliability ; SOM system ; Ventilator
  8. Source: International Journal of Management Science and Engineering Management ; Volume 17, Issue 4 , 2022 , Pages 239-258 ; 17509653 (ISSN)
  9. URL: https://www.tandfonline.com/doi/full/10.1080/17509653.2021.2009389