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A Novel Model for Optimization of Operation and Routing Service Composition in Cloud Manufacturing Considering the Joint Mechanisms in OPCs

Agha Mohammadzadeh, Ehsan | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50741 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Fatahi Valilai, Omid
  7. Abstract:
  8. In recent years, economic globalization and resource globalization as two key factors have driven organizations to adjust their processes to survive in the competitive environments. Also, customers have been provided with high-quality products, lower cost, product customization and quick delivery. Moreover, globalization has let suppliers to geographically distribute across the globe, and for accomplishing the final product resources need to be gathered. Distributed infrastructure enables organizations to decrease delivery time and increase flexibility but leads to higher investment costs and lower efficiency of the system. For responding to existing issues Cloud manufacturing has been proposed. Cloud manufacturing is a new paradigm which provides ubiquitous, convenient, on-demand network access to a shared pool of configurable manufacturing resources (e.g. servers, facilities, applications, machines, and services) that can be rapidly provisioned with minimal management effort and service provider interaction. Cloud manufacturing offers a service-oriented architecture that is based on information technology (IT) in which each manufacturing resources is expressed as a service. In this paper, to achieve ideal goal of Cloud manufacturing, every production tasks, and logistics operations would be defined as a service considering operation process chart flows. Operation process chart a thorough look over the entire manufacturing processes required for production. The paper proposes a mathematical model which selects an optimal service composition in order to lower operation and logistics costs while fulfilling a novel idea for configured cloud entropy. Finally, the paper has presented a numerical example and concluded the remarks, and outlined the future researches
  9. Keywords:
  10. Cloud Manufacturing ; Service Composition ; Service Quality ; Transportation Planning ; Non-Dominate Sorting Genetic Algorithm (NSGAII) Method

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