Loading...

A Novel Service Selection in Cloud Manufacturing System Considering Uncertainty and Strategic Perspective

Abbaspour, Solmaz | 2019

353 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51791 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Fatahi Valilai, Omid
  7. Abstract:
  8. Nowadays. global competition in manufacturing industries is increasing dramatically. In fact, the traditional production systems are not able to satisfy the needs of customers whom their production complexity is increasing. In order to fulfill the mentioned challenge, a new manufacturing system entitled “cloud Manufacturing” is introduced. In this new paradigm, manufacturing resources and capabilities of production are virtualized through internet and in the whole life cycle of manufacturing and production. These resources are available for end-users via the internet based on an XaaS (everything as aservice) approach. Moreover, although there are some limitations when manufacturing services are considered individually without their relationship with each other. So there is a need to have model to consider the combination of manufacturing resources in order to reach more efficient systems with more functionalities in order to appeal to the customers. The problem of service composition in cloud manufacturing is one of dominant subjects in the literature and it has got a lot of attention by researchers. The goal of service composition problem is optimum allocation of resources into services so that the total quality of service accomplishments become optimum. However, long term provision in services composition problem distinguishes it from services composition problems in cloud computing environments, whose its lacking is obviously recognized in the literature review.In the thesis, it is endeavored to present a model in order to select the optimum allocated services to operations by considering quality of service norms including time and cost and considering uncertainty and long term provision in cloud manufacturing environment. In this model, demands of the service consumers are sent to clouds in the form of operation process chart, and manufacturing cloud with long perspective is designed to sent operations process chart and considering flexibility for operation allocation while observing all existing prerequisites among operations. This is accomplished while the best allocation of services in which time and cost is optimized is considered. This perspective realizes service composition long term perspective like service oriented and operation perspective. In order to evaluate the validity of proposed model, two sample problems are investigated in small and large scales. In order to solve the problems in a optimum method, exact and metaheuristic genetic approaches are applied, and finally, evaluation and comparison of the results of two methods reveal the ability of genetic solution in optimum solving and close to optimum answer resulted for large scale problem as efficient as the exact method in small size problems
  9. Keywords:
  10. Cloud Computing ; Cloud Manufacturing ; Service Composition ; Service Quality ; Genetic Algorithm

 Digital Object List

 Bookmark

No TOC