Loading...

Simulation-based Service Allocation in Cloud Manufacturing Environments for a Specific Product Type Considering Focusing on Uncertainty in Services' Supply Demand

Rezghi, Atieh | 2019

522 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52060 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Fatahi Valilai, Omid
  7. Abstract:
  8. Nowadays, both academic and industrial environment have come to the conclusion that recent manufacturing paradigms are probably no longer applicable to the ever-changing today’s business environments. That is why manufacturing is moving gradually from production-oriented to service-oriented approaches. Service-oriented manufacturing results in a variety of services through a product life cycle which create an abundance of high value-added markets promoting efficient collaboration and amazing innovation. Cloud Manufacturing as an intelligent newly developed service-oriented manufacturing paradigm provides platforms of shared and interconnected distributed manufacturing resources and capabilities through which customers can easily and directly have access to different services, such as design, social networking for marketing, production, assembling, test, logistics and etc. Therefore, lots of service providers and customers interact with each other in such a highly nondeterministic, real-time changing of demand and supply environments. Truly considering the inevitable high uncertainty of service allocation in Cloud Manufacturing environments is still a great challenge, today. Because most previous researches use deterministic or stochastic optimization techniques to deal with the uncertainty of service allocation problem. However, such methods aren’t efficient enough to live up this goal. Since they just have tried to turn such uncertainty into deterministic conditions and then use common deterministic approaches to solve that problem. That’s why there is still a need for a method considering the vast dynamic changes of the system’s status over time via a rolling horizon approach. It’s promising to know that simulation methods are exactly developed for dealing with such problems and environments. The simulation approach proposed in this research is the first effort in academia to truly overcome the uncertainty conditions of allocating the logistic service- providers in a highly dynamic cloud manufacturing environment. The proposed simulation model helps decision making to be more efficient through considering not only past but also possible future events. The more realistic manufacturing environment considered in this simulation model results in more accurate estimates of system parameters which helps other researchers in developing their optimization models. Hence, how to simulate the allocation of logistic service providers in a Cloud Manufacturing environment will be studied in this research
  9. Keywords:
  10. Simulation Optimization ; Cloud Manufacturing ; Cloud Service Selection ; Services Allocation

 Digital Object List

 Bookmark

No TOC