Abstract
Reduction of environmental effect from material uses is a big challenge on the view of material selection as per recent scientific reports. This paper aims to identify the major challenges of material selection for the future use and suggest an appropriate energy-efficient material based on the performance by the decision maker on the various issues. The proposed work presents a multi-criteria decision-making (MCDM) analysis—Technique for order of preference by similarity to ideal solution (TOPSIS) to find the appropriate selection and evaluate the best energy-efficient material on the basis of criteria. In this paper, different energy-efficient materials have been taken into consideration under multiple uncertainties. Firstly, materials are figure out acquiesce to one and the other approximate and perceptible precedent ensue from entropy analysis. Entropy is a convenient technique in critical administration and takes advantage of this crucial executive strategy for criteria weight to deal with material selection in environment-friendly way. Thereafter, the results are used as an input for TOPSIS to designate the array of materials. To our observation, this is the first analysis in the energy-efficient material selection which considers environmental threats. The effect of weighting factors has also been deliberated.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- A1:
-
Alkaline earth lead glass
- A2:
-
Silicon
- A3:
-
Cast Magnesium
- A4:
-
Wrought Magnesium
- A5:
-
Cast Nickel–Iron alloy
- A6:
-
Lanthanum commercial purity min 99%
- A7:
-
Magnesium commercial purity
- A8:
-
Nickel–Iron Chromium alloy HW grade; aged
- A9:
-
Cerium commercial purity
- M1:
-
Density
- M2:
-
Bulk modulus
- M3:
-
Compressive strength
- M4:
-
Thermal conductivity
- M5:
-
Thermal expansion
- M6:
-
Resistivity
- M7:
-
Cost
- M8:
-
Energy production
- M9:
-
CO2 Emission
- MCDM:
-
Multi-criteria decision making
- TOPSIS:
-
Technique for order of preference by similarity to ideal solution
References
Akyene, T.: Cell phone evaluation base on entropy and TOPSIS. Interdisc. J. Res. Bus. 1(12), 9–15 (2012)
Ashby, M.F.: Multi-objective optimization in material design and selection. Acta Mater. 48(1), 359–369 (2000)
Bligaard, T., Jóhannesson, G.H., Ruban, A.V., Skriver, H.L., Jacobsen, K.W., Nørskov, J.K.: Pareto-optimal alloys. Appl. Phys. Lett. 83(22), 4527–4529 (2003)
Chang, C.W.: Collaborative decision making algorithm for selection of optimal wire saw in photovoltaic wafer manufacture. J. Intell. Manuf. 23(3), 533–539 (2012)
Chauhan, A., Vaish, R.: Magnetic material selection using multiple attribute decision making approach. Mater. Des. 36, 1–5 (2012)
Dashore, K., Pawar, S.S., Sohani, N., Verma, D.S.: Product evaluation using entropy and multi criteria decision making methods. Int. J. Eng. Trends Tech. 4(5), 2183–2187 (2013)
Hwang, C.L., Yoon, K.: Multiple attribute decision making: methods and applications a state-of-the-art survey, p. 186. Springer, Berlin (2012)
Hwang, C.L., Yoon, K.: Multiple attribute decision making: methods and applications. Springer, New York (1981)
Jahan, A., Ismail, M.Y., Sapuan, S.M., Mustapha, F.: Material screening and choosing methods–a review. Mat. Design. 31(2), 696–705 (2010)
Kou, G., Wu, W., Zhao, Y., Peng, Y., Yaw, N.E., Shi, Y.: A dynamic assessment method for urban eco-environmental quality evaluation. J Multi-Criteria Decis. Anal. 18(1–2), 23–38 (2011)
Kumar, R., Bhomik, C., Ray, A.: Selection of cutting tool material by TOPSIS method. In: National Conference on Recent Advancement in Mechanical Engineering. NERIST, Itanagar, India. pp. 978–993 (2013)
Kumar, D.S., Suman, K.N.S.: Selection of magnesium alloy by MADM methods for automobile wheels. Int. J. Eng. Manuf. 4(2), 31 (2014)
Lotfi, F.H., Fallahnejad, R.: Imprecise Shannon’s entropy and multi attribute decision making. Entropy 12(1), 53–62 (2010)
Milani, A.S., Shanian, A., Madoliat, R., Nemes, J.A.: The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection. Strut. Multi. Optim. 29(4), 312–318 (2005)
Senan, S., Arik, S.: Global robust stability of bidirectional associative memory neural networks with multiple time delays. IEEE Trans. Syst. Man Cybern. B 37(5), 1375–1381 (2007)
Vaish, R.: Piezoelectric and pyroelectric materials selection. Int. J. App. Ceramic Tech. 10(4), 682–689 (2013)
CES Edu pack 2005
Govindan, K., Shankar, K.M., Kannan, D.: Sustainable material selection for construction industry–a hybrid multi criteria decision making approach. Renew. Sustain. Energy Rev. 55, 1274–1288 (2016)
Hafezalkotob, A., Hafezalkotob, A.: Risk-based material selection process supported on information theory: a case study on industrial gas turbine. Appl. Soft Comp. J. http://dx.doi.org/10.1016/j.asoc.2016.09.018
Hafezalkotob, A., Hafezalkotob, A., Sayadi, K.M.: Extension of MULTIMOORA method with interval numbers: an application in materials selection. Appl. Math. Mod. 40, 1372–1386 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bhowmik, C., Gangwar, S., Bhowmik, S., Ray, A. (2018). Selection of Energy-Efficient Material: An Entropy–TOPSIS Approach. In: Pant, M., Ray, K., Sharma, T., Rawat, S., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 584. Springer, Singapore. https://doi.org/10.1007/978-981-10-5699-4_4
Download citation
DOI: https://doi.org/10.1007/978-981-10-5699-4_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5698-7
Online ISBN: 978-981-10-5699-4
eBook Packages: EngineeringEngineering (R0)