International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Selection and Experimentation of the Best Hybrid Green Composite Using Advanced MCDM Methods for Clean Sustainable Energy Recovery: A Novel Approach

Soutrik Bose
Department of Mechanical Engineering, MCKV Institute of Engineering, 243 G.T. Road (N), Liluah, Howrah, 711204, West Bengal, India.

Nabankur Mandal
Department of Mechanical Engineering, MCKV Institute of Engineering, 243 G.T. Road (N), Liluah, Howrah, 711204, West Bengal, India.

Titas Nandi
Department of Mechanical Engineering, Jadavpur University, Kolkata, 700032, West Bengal, India.

DOI https://doi.org/10.33889/IJMEMS.2020.5.3.046

Received on November 26, 2018
  ;
Accepted on December 23, 2019

Abstract

Relevant and appropriate selection of best hybrid material is a challenging task for the recent industries. The mandatory criterion is to deal with the enhanced productivity with minimum cost. Therefore, this paper highlights on the comparative study between the advanced multi-criteria approaches namely ARAS, MABAC, COPRAS and MOOSRA methods for the selection of the best hybrid composite material using aluminum (Al) as base material varying different reinforcement weights and recycling with various industrial wastes by stir casting. Al/WCE gives superior tribomechanical properties at lower cost than any other reinforcements. These advanced MCDM methods are applied, based on the properties and attributes of the hybrid composites, to compare between the computational and experimental results. The results exactly corroborate with the previous research results, which authenticate the expediency of these methods during the solving of complex hybrid material selection problems for sustainable energy recovery. Out of 48 different samples, A30 is obtained to be the best sample by ARAS approach (rank 1) which is Al+Al2O3 at 12.5%wt. addition. A24 is ranked 2 which is heat treated 12.5%wt. WCE. But the same A30 is obtained to be rank 5 and A24 is obtained to be rank 1 by MABAC method, A30 is obtained to be rank 2 and A24 to be rank 1 by COPRAS method, and A30 is calculated to be rank 1 and A24 to be rank 11 by MOOSRA method. A24 is also obtained to be the best hybrid composite as per the experimentation. This paper also aims for proper recovering of environmental friendly renewable energy for the society by fabricating the best hybrid green composite for sustainable development.

Keywords- ARAS, MABAC, COPRAS, MOOSRA, Energy recovery.

Citation

Bose, S., Mandal, N., & Nandi, T. (2020). Selection and Experimentation of the Best Hybrid Green Composite Using Advanced MCDM Methods for Clean Sustainable Energy Recovery: A Novel Approach. International Journal of Mathematical, Engineering and Management Sciences, 5(3), 556-566. https://doi.org/10.33889/IJMEMS.2020.5.3.046.

Conflict of Interest

The authors confirm and declare that there is no conflict of interest for this publication.

Acknowledgements

The authors would like to express their sincere gratitude and thanks to the editor and all the anonymous reviewers for their busy time and valuable suggestions.

References

Adali, E.A., & Işik, A.T. (2017). The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem. Journal of Industrial Engineering International, 13(2), 229-237.

Biswas, T.K., & Das, M.C. (2018). Selection of hybrid vehicle for green environment using multi-attributive border approximation area comparison method. Management Science Letters, 8(2), 121-130.

Bose, S., Pandey, A., & Mondal, A. (2018). Comparative analysis on aluminum-silicon carbide hybrid green metal matrix composite materials using waste egg shells and snail shell ash as reinforcements. Materials Today: Proceedings, 5(14), 27757-27766.

Bose, S., Pandey, A., Mondal, A., & Mondal, P. (2019). A novel approach in developing aluminum hybrid green metal matrix composite material using waste eggshells, cow dung ash, snail shell ash and boron carbide as reinforcements. In: Shanker, K., Shankar, R., Sindhwani, R. (eds) Advances in Industrial and Production Engineering (pp. 551-562). Springer, Singapore.

Chatterjee, P., & Chakraborty, S. (2013). Gear material selection using complex proportional assessment and additive ratio assessment-based approaches: a comparative study. International Journal of Materials Science and Engineering, 1(2), 104-111.

Chatterjee, P., Athawale, V.M., & Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials & Design, 32(2), 851-860.

Deep, G., Idrisi, A.H., & Siddiqui, T.U. (2016). Investigation and analysis for mechanical properties of aluminium silicon carbide composite. International Journal of Innovative Research in Science, Engineering and Technology, 5(9), 16720-16725.

Hassan, S.B., & Aigbodion, V.S. (2015). Effects of eggshell on the microstructures and properties of Al–Cu–Mg/eggshell particulate composites. Journal of King Saud University-Engineering Sciences, 27(1), 49-56.

Maity, S.R., Chatterjee, P., & Chakraborty, S. (2012). Cutting tool material selection using grey complex proportional assessment method. Materials & Design, 36, 372-378.

Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028.

Popović, G., Stanujkić, D., & Stojanović, S. (2012). Investment project selection by applying COPRAS method and imprecise data. Serbian Journal of Management, 7(2), 257-269.

Sarkar, A., Panja, S.C., Das, D., & Sarkar, B. (2015). Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA. Production and Manufacturing Research, 3(1), 324-342.

Xue, Y.X., You, J.X., Lai, X.D., & Liu, H.C. (2016). An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Applied Soft Computing, 38, 703-713.

Zavadskas, E.K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy, Baltic Journal on Sustainability, 16(2), 159-172.

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