Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design

Released on by Ali Jahan
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  • Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design Book Detail

  • Author : Ali Jahan
  • Release Date : 2016-02-17
  • Publisher : Butterworth-Heinemann
  • Genre : Technology & Engineering
  • Pages : 254
  • ISBN 13 : 0081005415
  • File Size : 75,75 MB
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Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design by Ali Jahan PDF Summary

Book Description: Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design, Second Edition, provides readers with tactics they can use to optimally select materials to satisfy complex design problems when they are faced with the vast range of materials available. Current approaches to materials selection range from the use of intuition and experience, to more formalized computer-based methods, such as electronic databases with search engines to facilitate the materials selection process. Recently, multi-criteria decision-making (MCDM) methods have been applied to materials selection, demonstrating significant capability for tackling complex design problems. This book describes the rapidly growing field of MCDM and its application to materials selection. It aids readers in producing successful designs by improving the decision-making process. This new edition updates and expands previous key topics, including new chapters on materials selection in the context of design problem-solving and multiple objective decision-making, also presenting a significant amount of additional case studies that will aid in the learning process. Describes the advantages of Quality Function Deployment (QFD) in the materials selection process through different case studies Presents a methodology for multi-objective material design optimization that employs Design of Experiments coupled with Finite Element Analysis Supplements existing quantitative methods of materials selection by allowing simultaneous consideration of design attributes, component configurations, and types of material Provides a case study for simultaneous materials selection and geometrical optimization processes

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