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A framework for weighting of criteria in ranking stage of material selection process

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Abstract

Material selection is an onerous process of design activities which needs to be carefully carried out in order to increase the probability of success. A lot of multi-criteria decision-making methods have been proposed in material selection, many of which require quantitative weights for the attributes. Since weights play a very significant role in the ranking results of the materials, this paper presents a framework for determining importance degree of criteria to overcome the shortcomings of this subject in material selection. Furthermore, the suggested framework covers the situation of interdependent relationship between the criteria which has not been surveyed in material selection yet. An example was considered to illustrate how this framework is conducted. On the basis of the numerical results, it can be concluded that the proposed method can soundly deal with the material selection problems.

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References

  1. Chan JWK, Tong TKL (2007) Multi-criteria material selections and end-of-life product strategy: grey relational analysis approach. Mater Des 28:1539–1546

    Article  Google Scholar 

  2. Karana E, Hekkert P, Kandachar P (2008) Material considerations in product design: a survey on crucial material aspects used by product designers. Mater Des 29:1081–1089

    Article  Google Scholar 

  3. Farag MM (2002) Quantitative methods of materials selection. In: Kutz M. (ed) Handbook of materials selection. Wiley, 1–24

  4. Chiner M (1988) Planning of expert systems for materials selection. Mater Des 9:195–203

    Article  Google Scholar 

  5. Ashby MF, Brechet YJM, Cebon D, Salvo L (2004) Selection strategies for materials and processes. Mater Des 25:51–67

    Article  Google Scholar 

  6. Jahan A, Ismail MY, Sapuan SM, Mustapha F (2010) Material screening and choosing methods—a review. Mater Des 31:696–705

    Article  Google Scholar 

  7. Farag M (1997) Materials selection for engineering design. Prentice-Hall, New York

    Google Scholar 

  8. Rao RV (2008) A decision making methodology for material selection using an improved compromise ranking method. Mater Des 29:1949–1954

    Article  Google Scholar 

  9. Jee DH, Kang KJ (2000) A method for optimal material selection aided with decision making theory. Mater Des 21:199–206

    Article  Google Scholar 

  10. Shanian A, Savadogo O (2006) A material selection model based on the concept of multiple attribute decision making. Mater Des 27:329–337

    Article  Google Scholar 

  11. Jahan A, Ismail MY, Mustapha F, Sapuan SM (2010) Material selection based on ordinal data. Mater Des 31:3180–3187

    Article  Google Scholar 

  12. Zhou CC, Yin GF, Hu XB (2009) Multi-objective optimization of material selection for sustainable products: artificial neural networks and genetic algorithm approach. Mater Des 30:1209–1215

    Article  Google Scholar 

  13. Diakoulaki D, Mavrotas G, Papayannakis L (1995) Determining objective weights in multiple criteria problems: the critic method. Comput Oper Res 22:763–770

    Article  MATH  Google Scholar 

  14. Rongxi Z, Jianrong X, Dayi H (2009) Approach of determining interval entropy weight based on the subjective preference of decision-maker and its application in Control and Decision Conference, Guilin

  15. Shanian A, Savadogo O (2006) TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell. J Power Sourc 159:1095–1104

    Article  Google Scholar 

  16. Von Winterfeldt D, Edwards W (1986) Decision analysis and behavioral research. Cambridge University Press, Cambridge

    Google Scholar 

  17. Keeney RL, Raiffa H (1993) Decisions with multiple objectives: preferences and value tradeoffs. Cambridge University Press

  18. Pöyhönen M, Hämäläinen RP (2001) On the convergence of multiattribute weighting methods. Eur J Oper Res 129:569–585

    Article  MATH  Google Scholar 

  19. Bottomley PA, Doyle JR (2001) A comparison of three weight elicitation methods: good, better, and best. Omega 29:553–560

    Article  Google Scholar 

  20. Doyle JR, Green RH, Bottomley PA (1997) Judging relative importance: direct rating and point allocation are not equivalent. Organ Behav Hum Decis Process 70:65–72

    Article  Google Scholar 

  21. Hwang CL, Lin MJ (1987) Group decision making under multiple criteria: methods and applications. Springer

  22. Edwards W (1977) How to use multiattribute utility measurement for social decision making. IEEE Trans Syst Man Cybern 7:326–340

    Article  Google Scholar 

  23. Ward E, Hutton BF (1994) SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organ Behav Hum Decis Process 60:306–325

    Article  Google Scholar 

  24. Shanian A, Milani AS, Carson C, Abeyaratne RC (2008) A new application of ELECTRE III and revised Simos' procedure for group material selection under weighting uncertainty. Knowl Base Syst 21:709–720

    Article  Google Scholar 

  25. Figueira J, Roy B (2002) Determining the weights of criteria in the ELECTRE type methods with a revised Simos' procedure. Eur J Oper Res 139:317–326

    Article  MATH  Google Scholar 

  26. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  MATH  Google Scholar 

  27. Rao RV, Davim JP (2008) A decision-making framework model for material selection using a combined multiple attribute decision-making method. Int J Adv Manuf Technol 35:751–760

    Article  Google Scholar 

  28. Dehghan-Manshadi B, Mahmudi H, Abedian A, Mahmudi R (2007) A novel method for materials selection in mechanical design: combination of non-linear normalization and a modified digital logic method. Mater Des 28:8–15

    Article  Google Scholar 

  29. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281

    Article  MATH  MathSciNet  Google Scholar 

  30. Chu ATW, Kalaba RE, Spingarn K (1979) A comparison of two methods for determining the weights of belonging to fuzzy sets. J Optim Theory Appl 27:531–538

    Article  MATH  MathSciNet  Google Scholar 

  31. Shirland LE, Jesse RR, Thompson RL, Iacovou CL (2003) Determining attribute weights using mathematical programming. Omega 31:423–437

    Article  Google Scholar 

  32. Deng H, Yeh CH, Willis RJ (2000) Inter-company comparison using modified TOPSIS with objective weights. Comput Oper Res 27:963–973

    Article  MATH  Google Scholar 

  33. Pratyyush S, Jian-Bo Y (1998) Multiple criteria decision support in engineering design. Springer, Berlin

    Google Scholar 

  34. Hwang CL, Yoon K (1981) Multiple attribute decision making—methods and applications. Springer, Berlin

    MATH  Google Scholar 

  35. Shanian A, Savadogo O (2009) A methodological concept for material selection of highly sensitive components based on multiple criteria decision analysis. Expert Syst Appl 36:1362–1370

    Article  Google Scholar 

  36. Zeleny M (1982) Multiple criteria decision making. McGraw-Hill, New York

    MATH  Google Scholar 

  37. Asgharpour MJ (1999) Multiple criteria decision making. Tehran University Publications, Tehran

    Google Scholar 

  38. Rao RV, Patel BK (2010) A subjective and objective integrated multiple attribute decision making method for material selection. Mater Des 31:4738–4747

    Article  Google Scholar 

  39. Maniya K, Bhatt MG (2010) A selection of material using a novel type decision-making method: preference selection index method. Mater Des 31:1785–1789

    Article  Google Scholar 

  40. Wang YM, Parkan C (2006) A general multiple attribute decision-making approach for integrating subjective preferences and objective information. Fuzzy Set Syst 157:1333–1345

    Article  MATH  MathSciNet  Google Scholar 

  41. Ma J, Fan ZP, Huang LH (1999) A subjective and objective integrated approach to determine attribute weights. Eur J Oper Res 112:397–404

    Article  MATH  Google Scholar 

  42. Xu X (2004) A note on the subjective and objective integrated approach to determine attribute weights. Eur J Oper Res 156:530–532

    Article  MATH  Google Scholar 

  43. Wang Y-M, Luo Y (2010) Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Math Comput Model 51:1–12

    Article  MATH  MathSciNet  Google Scholar 

  44. Chen SJJ, Hwang CL, Beckmann MJ, Krelle W (1992) Fuzzy multiple attribute decision making: methods and applications. Springer-Verlag New York, Inc, Secaucus

    Google Scholar 

  45. Ramík J, Perzina R (2010) A method for solving fuzzy multicriteria decision problems with dependent criteria. Fuzzy Optim Decis Making 9:123–141

    Article  MATH  Google Scholar 

  46. Angilella S, Greco S, Lamantia F, Matarazzo B (2004) Assessing non-additive utility for multicriteria decision aid. Eur J Oper Res 158:734–744

    Article  MATH  MathSciNet  Google Scholar 

  47. Durst O, Ellermeier J, Berger C (2008) Influence of plasma-nitriding and surface roughness on the wear and corrosion resistance of thin films (PVD/PECVD). Surf Coating Tech 203:848–854

    Article  Google Scholar 

  48. Jiang Y, Li B, Tanabashi Y (2006) Estimating the relation between surface roughness and mechanical properties of rock joints. Int J Rock Mech Min Sci 43:837–846

    Article  Google Scholar 

  49. Karana E, Hekkert P, Kandachar P (2009) Meanings of materials through sensorial properties and manufacturing processes. Mater Des 30:2778–2784

    Article  Google Scholar 

  50. Lee JW, Kim SH (2000) Using analytic network process and goal programming for interdependent information system project selection. Comput Oper Res 27:367–382

    Article  MATH  MathSciNet  Google Scholar 

  51. Yurdakul M, Tansel ÇY (2009) Application of correlation test to criteria selection for multi criteria decision making (MCDM) models. Int J Adv Manuf Technol 40:403–412

    Article  Google Scholar 

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Correspondence to Ali Jahan.

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Jahan, A., Mustapha, F., Sapuan, S.M. et al. A framework for weighting of criteria in ranking stage of material selection process. Int J Adv Manuf Technol 58, 411–420 (2012). https://doi.org/10.1007/s00170-011-3366-7

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  • DOI: https://doi.org/10.1007/s00170-011-3366-7

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