Coding, Ranking and Optimum selection of Nanomaterials

The paper presents attribute based characterization of nanomaterials method for computer storage and retrieval as knowledgebase. The knowledgebase permits indepth understanding and comparison between nanomaterials available with the scientists and product developers to satisfy their research and development (R & D) needs. Techniques for order preference by similarity to ideal solution (TOPSIS) is proposed to evaluate nanomaterials in the presence of multiple attributes. The method normalizes attributes to nullify the effect of different units and their values in the range of 0 to 1. The relative importance of different attributes for different applications is considered. The weight vector is derived using Eigen value formulation. The positive and negative benchmark solutions are derived. Euclidean distance of alternatives from these best and worst solution leads to the development of proximity /goodness/suitability index for ranking. Final decision is taken by decision makers by SWOT analysis and short and long term strategies of the organisation. The methodology is illustrated with the help of an example and step-by-step procedure. Results, discussion and conclusion highlights the importance and practical application.

[1]  A. Abedian,et al.  A simplified fuzzy logic approach for materials selection in mechanical engineering design , 2009 .

[2]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[3]  W.-L. Gau,et al.  Vague sets , 1993, IEEE Trans. Syst. Man Cybern..

[4]  Ali Shanian,et al.  A non-compensatory compromised solution for material selection of bipolar plates for polymer electrolyte membrane fuel cell (PEMFC) using ELECTRE IV , 2006 .

[5]  Mahmoud M. Farag,et al.  Materials selection for engineering design , 1997 .

[6]  Y.-M. Deng,et al.  Supporting design decision-making when applying materials in combination , 2007 .

[7]  R. Venkata Rao,et al.  Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods , 2013 .

[8]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[9]  V. P. Agrawal,et al.  A DIGRAPH APPROACH TO QUALITY EVALUATION OF AN AUTOMOTIVE VEHICLE , 1997 .

[10]  K. L. Edwards,et al.  Selecting materials for optimum use in engineering components , 2005 .

[11]  Michael F. Ashby,et al.  Materials and Design: The Art and Science of Material Selection in Product Design , 2002 .

[12]  A. Abedian,et al.  A novel method for materials selection in mechanical design: Combination of non-linear normalization and a modified digital logic method , 2007 .

[13]  M. Ashby.  MULTI-OBJECTIVE OPTIMIZATION IN MATERIAL DESIGN AND SELECTION , 2000 .

[14]  Thomas L. Saaty.  Fundamentals of decision making and priority theory , 2000 .

[15]  Thomas K. L. Tong,et al.  Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach , 2007 .

[16]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .

[17]  K Suresh Babu,et al.  THE MATERIAL SELECTION FOR TYPICAL WIND TURBINE BLADES USING A MADM APPROACH& ANALYSIS OF BLADES , 2006 .

[18]  P. E. Fisher.  Selection of Engineering Materials and Adhesives , 2005 .

[19]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[20]  Ali Shanian,et al.  A material selection model based on the concept of multiple attribute decision making , 2006 .

[21]  Gwo-Hshiung Tzeng,et al.  Comparison among three analytical methods for knowledge communities group-decision analysis , 2007, Expert Syst. Appl..

[22]  Y.-M. Deng,et al.  The role of materials identification and selection in engineering design , 2007 .

[23]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[24]  A. Abedian,et al.  Introducing a novel method for materials selection in mechanical design using Z-transformation in statistics for normalization of material properties , 2009 .

[25]  T. Liao,et al.  A fuzzy multicriteria decision-making method for material selection , 1996 .

[26]  Mao-Jiun J. Wang,et al.  Tool steel materials selection under fuzzy environment , 1995 .

[27]  R. Venkata Rao,et al.  A decision making methodology for material selection using an improved compromise ranking method , 2008 .

[28]  R. Rao.  A material selection model using graph theory and matrix approach , 2006 .

[29]  Prasenjit Chatterjee,et al.  Selection of materials using compromise ranking and outranking methods , 2009 .

[30]  Willi Hock,et al.  Lecture Notes in Economics and Mathematical Systems , 1981 .

[31]  Ali Shanian,et al.  TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell , 2006 .