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Material selection for magnetic levitated GPS activated car using complex proportional assessment and additive ratio assessment approaches

EasyChair Preprint no. 1685

11 pagesDate: October 16, 2019

Abstract

Magnetic levitation is a technology that uses magnetism to lift vehicles on the basis of electromagnetism. It is the key substitute to fuels and other alternating fuels. The levitating force arises between the superconductor and the magnetic source used on the railway transport system or on the track provided under the road. In this research, it is proposed to design a prototype on the basis of development of high speed grand transportation system maglev car which will minimize the transport area, minimize time, no friction losses, no energy emission and zero pollution, thus bringing about environmental sustainability. It is also planned to design a GPS (Global Positioning System) and implementing sensors to detect barriers and to retard the motion of the car. Further improvement can be done to levitate the car without track for reducing the project cost and minimize the area. The main criterion of this paper is to select the best material for this maglev car. Therefore, complex proportional assessment (COPRAS) and additive ratio assessment (ARAS) approaches are used for selecting the best magnetic levitated car material in a given manufacturing arena. Ten different magnetic materials are selected based on their mechanical and physical properties and compared considering all the multi-conflicting material selection attributes. AA7075 is obtained to be the best material by ranking method and by comparing between these two methods.

Keyphrases: ARAS, COPRAS, Global Positioning System, magnetic levitation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:1685,
  author = {Soutrik Bose},
  title = {Material selection for magnetic levitated GPS activated car using complex proportional assessment and additive ratio assessment approaches},
  howpublished = {EasyChair Preprint no. 1685},

  year = {EasyChair, 2019}}
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