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A Service Composition Model Considering Shared Logistic Costs Using a Capacity-Based Sharing Cost Structure in Cloud Manufacturing Systems

Akbari, Parastoo | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53696 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Hoshmand, Mahmoud; Fatahi Valilai, Omid
  7. Abstract:
  8. With the rapid growth of technology in recent decades, a revolution has been started, known as Industry 4.0, in current manufacturing systems. In this revolution, cloud manufacturing systems play an important role. Cloud manufacturing is a new service-driven business model developed from existing advanced manufacturing models with the aid of innovative technologies, such as cloud computing, virtualization, Internet of Things (IoT), service-oriented technologies, semantic web, and so forth. This manufacturing paradigm allows service providers to share their manufacturing resources in a cloud platform, converts these distributed manufacturing resources into manufacturing services, and arranges them in a centralized way. One of the most controversial aspects of this centralized management is regarding the planning and scheduling of tasks, which refers to the process of allocating single/multiple tasks to manufacturing services in order to optimize the system in terms of time, cost, availability, reliability, and other criteria of service quality.In this research, a comprehensive literature review of planning and scheduling cloud manufacturing services is conducted, and a research gap is observed regarding the possibility of sharing logistic costs among customers that use similar logistic services for transporting their semi-products in proportion to their products load weight. Based on previous studies and considering this research gap, a multi-objective mathematical optimization model for task scheduling in cloud manufacturing systems is presented. This model is categorized as assignment models and aims to minimize operations costs, to complete the production tasks, and the logistic costs, to transport the semi-products between distributed locations. In order to illustrate the validation of the model, a case study is conducted, and the model is solved in small-size.The obtained results reveal that by using this approach, the total costs of logistics will be decreased, and therefore, the total costs of cloud manufacturing systems will be reduced compared to the previous model. Adopting the proposed model will improve the efficiency and performance of cloud manufacturing systems and increases customer satisfaction
  9. Keywords:
  10. Cloud Manufacturing ; Resource Sharing ; Service Composition ; Task Scheduling Algorithm ; Cloud Service Selection ; Logistic Service Sharing

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