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A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm

Delaram, J ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jmsy.2021.07.012
  3. Publisher: Elsevier B.V , 2021
  4. Abstract:
  5. Cloud Manufacturing (CM) as a successful manufacturing business model and a major driver of Industry 4.0 has attracted a lot of attention in recent years. CM idea aims to streamline the on-demand provisioning of manufacturing resources and capabilities as services, providing end-users with flexible and scalable services accessible through global networks. This idea created many opportunities and challenges. One of the critical challenges is resource allocation, which determines who interacts with whom and how in the CM platform. The type of the platform is a determining factor for the selection of the appropriate resource allocation. To analyze the impact of the allocation on the utilities, the paper models the behavior of the manufacturing providers and consumers based on their preference attributes. Then, the paper discusses the influence of the platform, matching algorithm, and resource availability on the utility of the manufacturing providers and consumers. As a result, the paper presents a framework to obtain managerial insights to decide about the appropriate matching algorithm under different situations. The framework suggests Consumer as Proposer Deferred Acceptance algorithm for public platforms when the resources are greater than or equal to the demand, and Provider as Proposer Deferred Acceptance algorithm when the resources are less than the demand in the same platform. In private platform, Consumer-oriented Kuhn-Munkres is suggested when the resources are greater than or equal to the demand, and Provider-oriented Kuhn-Munkres when the resources are less than the demand. © 2021 The Society of Manufacturing Engineers
  6. Keywords:
  7. Computer aided manufacturing ; Consumer behavior ; Manufacture ; Resource allocation ; Cloud Manufacturing ; Critical challenges ; Manufacturing business ; Manufacturing resource ; Matching algorithm ; Matching mechanisms ; Optimal resource allocation ; Resource availability ; Computational complexity
  8. Source: Journal of Manufacturing Systems ; Volume 60 , 2021 , Pages 569-584 ; 02786125 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0278612521001497