Material selection for sintered pulley in automobile: An integrated CRITIC-MARCOS model
DOI:
https://doi.org/10.31181/rme040105102023rKeywords:
Sintered pulleys, Material selection, MCDM, MARCOS, CRITIC, Spearman rank correlation coefficientAbstract
Material selection plays a pivotal role in engineering and design, profoundly influencing product performance, cost, and sustainability. Traditional approaches to material selection typically involve an intricate interplay of multiple criteria, encompassing mechanical properties, environmental impact, cost, and availability. To grapple with this complexity, multi-criteria decision-making (MCDM) methods have risen to prominence as systematic frameworks for facilitating well-informed material selection decisions. MCDM methods offer a structured approach to evaluating and ranking materials based on a set of criteria, thereby empowering engineers and designers to make informed choices. In this paper, Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) method has been employed to determine the most suitable material for sintered pulleys used in automobiles. CRiteria Importance Through Intercriteria Correlation (CRITIC) method is applied to assign criteria weights. The analysis reveals that sintered hardened steel emerges as the best choice for sintered pulleys in automotive applications. To validate the outcomes obtained from the proposed method, a performance analysis has been conducted, comparing the results with those generated by other well-established MCDM methods. Additionally, a sensitivity analysis has been carried out using Spearman rank correlation coefficient.
References
Abishini, A. H., & Karthikeyan, K. M. B. (2023). Application of MCDM and Taguchi super ranking concept for materials selection problem. Materials Today: Proceedings, 72, 2480-2487.
Anand, S. K., & Mitra, S. (2021). Material Selection for Tool Holder using MCDM Methods. International Journal of Emerging Technologies in Engineering Research, 9, 1-13.
Anojkumar, L., Ilangkumaran, M., & Sasirekha, V. (2014). Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, 41, 2964-2980.
Anojkumar, L., Ilangkumaran, M., & Vignesh, M. (2015). A decision-making methodology for material selection in sugar industry using hybrid MCDM techniques. Int. J. Materials and Product Technology, 51, 102-126.
Boyaci, A. Ç., & Tüzemen, M. Ç. (2021). Multi-criteria decision-making approaches for aircraft-material selection problem. International Journal of Materials and Product Technology, 64, 45-68.
Çalıskan, H., Kursuncu, B., Kurbanog˘lu, C., & Güven, S. Y. (2013). Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods. Materials & Design, 45, 473- 479.
Chandrasekar, V. S., & Raja, K. (2016). Material selection for automobile torsion bar Using fuzzy topsis tool. Int J Adv Engg Tech, 7, 343-349.
Chatterjee, S., & Chakraborty, S. (2022). A multi-attributive ideal-real comparative analysis-based approach for piston material selection. OPSEARCH, 59, 207-228.
Chatterjee, S., & Chakraborty, S. (2021). Material selection of a mechanical component based on criteria relationship evaluation and MCDM approach. Materials Today: Proceedings, 44, 1621-1626.
Das, A., & kumar, A. (2015). Selection of Spring Material Using PROMETHEE Method. IOSR Journal of Mechanical and Civil Engineering, 12, 82-91.
Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22, 763-770.
Dušan, P., Miloš, M., Miroslav, R., & Predrag, J. (2015). Application of Recently Developed MCDM Methods for Materials Selection. Applied Mechanics and Materials, 810, 1468-1473.
Emovon, I., & Oghenenyerovwho, O. S. (2020). Application of MCDM method in material selection for optimal design: A review. Results in Materials, 7, 100115.
Farid, H. M. A., & Riaz M. (2022). Single-valued neutrosophic Einstein interactive aggregation operators with applications for material selection in engineering design: case study of cryogenic storage tank. Complex & Intelligent Systems, 8, 2131–2149.
Garmode, R. K., Gaval, V. R., Kale, S. A., & Nikhade S. D. (2022). Comprehensive Evaluation of Materials for Small Wind Turbine Blades Using Various MCDM Techniques. International journal of renewable energy research, 12, 981- 992.
Goswami, S. S., & Behera D. K. (2021). Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38, 2256-2262.
Gupta, N., Ramkumar, PL., & Abhishek, K. (2021). Material selection for rotational molding process utilizing distinguished multi criteria decision making techniques. Materials Today: Proceedings, 44, 1770-1775.
Hosouli, S., Elvins, J., Searle, J. Boudjabeur S., Bowyer J., & Jewell E. (2023). A Multi-Criteria decision making (MCDM) methodology for high temperature thermochemical storage material selection using graph theory and matrix approach. Materials & Design, 227, 111685.
Ilangkumaran, M., Avenash, A., Balakrishnan, V., Kumar, S., B., & Raja M. B. (2013). Material selection using hybrid MCDM approach for automobile bumper. Int. J. Industrial and Systems Engineering, 14, 20- 39.
Jahan, F., Soni, M., Parveen, A., & Waseem, M. (2021). Application of Combined Compromise Solution Method for Material Selection. Advancement in Materials, Manufacturing and Energy Engineering, 1, 379–387.
Jajimoggala, S., & Karri, R. R. (2013). Decision making model for material selection using a hybrid MCDM technique. Int. J. Applied Decision Sciences, 6, 144-159.
Kumar, B. S., Varghese, J., & Jacob, J. (2022). Optimal thermochemical material selection for a hybrid thermal energy storage system for low temperature applications using multi criteria optimization technique. Materials Science for Energy Technologies, 5, 452-472.
Lohakare, P., Bewoor A., Kumar, R., Said, N. M., & Sharifpur M. (2022). Benchmark using multi criteria decision making (MCDM) technique to optimally select piston material. Engineering Analysis with Boundary Elements, 142, 52-60.
Mousavi-Nasab, S. H., & Sotoudeh-Anvai, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 17, 1-102.
Moradian, M., Modanloo, V., & Aghaiee, S. (2018). Comparative analysis of multi criteria decision making techniques for material selection of brake booster valve body. Journal of Traffic and Transportation Engineering, 6, 526-534.
Okokpujie, I. P., Okonkwo, U. C., Bolu C. A., Ohunakin, O. S., Agboola, M. G., & Atayero, A. A. (2020). Implementation of multi-criteria decision method for selection of suitable material for development of horizontal wind turbine blade for sustainable energy generation. Heliyon, 6, e03142.
Patnaik, P., K., Swain, P., T., R., & Purohit, A. (2019). Selection of composite materials for structural applications through MCDM approach. Materials Today: Proceedings, 18, 3454-3461.
Patnaik, P. K., Swain, P. T. R., Mishra, S. K., Purohit A., & Biswas, S. (2020). Composite material selection for structural applications based on AHP-MOORA approach. Materials Today: Proceedings, 1-5.
Puška, A., Stojanović, I., Maksimović, A., & Osmanović, N. (2020). Evaluation software of project management by using measurement of alternatives and ranking according to compromise solution (MARCOS) method. Operational Research in Engineering Sciences: Theory and Applications, 3, 89–102.
Raju, S. S., Murali, G. B., & Patnaik, P. K. (2020). Ranking of Al-CSA composite by MCDM approach using AHP–TOPSIS and MOORA methods. Journal of Reinforced Plastics and Composites, 39, 19-20.
Rahim, A. AA., Musa, S. N., & Lim M. K. (2020). A systematic review on material selection methods. The Journal of Materials: Design and Applications, 234.
Rahim, A. AA., Musa, S. N., & Lim M. K. (2021). Development of a fuzzy-TOPSIS multi-criteria decision-making model for material selection with the integration of safety, health and environment risk assessment. The Journal of Materials: Design and Applications, 235.
Sen, B., Bhattacharjee, P., & Mandal, U. K. (2016). A comparative study of some prominent multi criteria decision making methods for connecting rod material selection. Perspectives in Science, 8, 547-549.
Sharma, P., & Kondhalkar, G. (2018). Design and analysis of conical spring for performance enhancement of mirror aseembly using hybrid approach. International Research Journal of Engineering and Technology, 5, 808-8013.
Singh, M., Pant, M., Godiyal, R. D., & Sharma, A. K. (2020). MCDM approach for selection of raw material in pulp and papermaking industry. Materials and Manufacturing Processes, 1532-2475.
Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231.
Zafar, S., Alamgir, Z., & Rehman, M. H. (2021). An effective blockchain evaluation system based on entropy-CRITIC weight method and MCDM techniques. Peer-to-Peer Networking and Applications, 14, 3110–3123.
Zakeri, S., Chatterjee, P., Konstantas, D., & Ecer, F. (2023). A decision analysis model for material selection using simple ranking process. Scientifc Reports, 13, 8631.
Zhang, Q., Hu, J., Feng, J., & Liu, A. (2020). A novel multiple criteria decision-making method for material selection based on GGPFWA operator. Materials and Design, 195, 109038.
Zindani, D., Maity., S. R., & Bhowmik, S. (2020). Excogitating Material Rankings Using Novel Aggregation Multiplicative Rule (AMR): A Case for Material Selection Problems. Arabian Journal for Science and Engineering, 1-16.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Reports in Mechanical Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.