Comparison of MCDM methods effectiveness in the selection of plastic injection molding machines
DOI:
https://doi.org/10.24036/teknomekanik.v7i1.29272Keywords:
MCDM, PIV method, PSI method, FUCA method, CURLI methodAbstract
In each specific problem of finding the best solution among many available options, where each option has multiple criteria, multi criteria decision making methods are considered equally effective when they converge to the same optimal solution. Proximity Indexed Value, Preference Selection Index, Faire Un Choix Adéquat (in French), and Collaborative Unbiased Rank List Integration are four Multi Criteria Decision Making methods with very different characteristics. All these four methods have been used a lot in recent times. The effectiveness of these four methods have been confirmed to be comparable to other multi criteria decision making methods in many applications. However, the comparison of these four methods with each other has never been performed in any studies. This article is performed to fill that gap. These four methods have been used to find to the best option among five types of plastic injection molding machine. Ten criteria have been chosen to describe each alternative. Two different methods that have been used to calculate the weights for the criteria are the MEAN weight method and the CRiteria Importance Through Intercriteria Correlation weight method. Different scenarios have been created to compare the effectiveness of these four methods. The results have shown that the four multi criteria decision making methods mentioned above are equally effective in the selection of plastic injection molding machines. Among the five types of plastic injection molding machines, namely JSW J350EII-SPA ANBE-002-02, Meiki M-200B-SJ, Meiki M-350C-DF-SJ, JSW J350E II, and JSW J550E-C5, the JSW J550E-C5 is the best type.
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M. Baydaş, T. Eren, Ž. Stević, V. Starčević, and R. Parlakkaya, “Proposal for an objective binary benchmarking framework that validates each other for comparing MCDM methods through data analytics,” PeerJ Comput Sci, vol. 9, p. e1350, Apr. 2023, https://doi.org/10.7717/peerj-cs.1350
H.-Q. Nguyen, V.-T. Nguyen, D.-P. Phan, Q.-H. Tran, and N.-P. Vu, “Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods,” Applied Sciences, vol. 12, no. 8, p. 3720, Apr. 2022, https://doi.org/10.3390/app12083720
T. H. Danh, T. Q. Huy, P. D. Lam, N. M. Cuong, H. X. Tu, and V. N. Pi, “A study on multi-criteria decision-making in powder mixed electric discharge machining cylindrical shaped parts,” EUREKA: Physics and Engineering, no. 5, pp. 123–129, Sep. 2022, https://doi.org/10.21303/2461-4262.2022.002367
H.-Q. Nguyen, X.-H. Le, T.-T. Nguyen, Q.-H. Tran, and N.-P. Vu, “A Comparative Study on Multi-Criteria Decision-Making in Dressing Process for Internal Grinding,” Machines, vol. 10, no. 5, p. 303, Apr. 2022, https://doi.org/10.3390/machines10050303
S. Mufazzal and S. M. Muzakkir, “A new multi-criterion decision making (MCDM) method based on proximity indexed value for minimizing rank reversals,” Comput Ind Eng, vol. 119, pp. 427–438, May 2018, https://doi.org/10.1016/j.cie.2018.03.045
S. Wakeel, S. Bingol, M. N. Bashir, and S. Ahmad, “Selection of sustainable material for the manufacturing of complex automotive products using a new hybrid Goal Programming Model for Best Worst Method–Proximity Indexed Value method,” Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, vol. 235, no. 2, pp. 385–399, Feb. 2021, https://doi.org/10.1177/1464420720966347
S. Wakeel et al., “A New Hybrid LGPMBWM-PIV Method for Automotive Material Selection,” Informatica, vol. 45, no. 1, Mar. 2021, https://doi.org/10.31449/inf.v45i1.3246
F. Jahan, M. Soni, S. Wakeel, S. Ahmad, and S. Bingol, “Selection of Automotive Brake Material Using Different MCDM Techniques and Their Comparisons,” Journal of Engineering Science and Technology Review, vol. 15, no. 1, pp. 24–33, 2022, https://doi.org/10.25103/jestr.151.04
K. Maniya and M. G. Bhatt, “A selection of material using a novel type decision-making method: Preference selection index method,” Mater Des, vol. 31, no. 4, pp. 1785–1789, Apr. 2010, https://doi.org/10.1016/j.matdes.2009.11.020
R. Attri and S. Grover, “Application of preference selection index method for decision making over the design stage of production system life cycle,” Journal of King Saud University - Engineering Sciences, vol. 27, no. 2, pp. 207–216, Jul. 2015, https://doi.org/10.1016/j.jksues.2013.06.003
A. DEMİRCİ, “LOJİSTİK SEKTÖRÜNDE PERSONEL SEÇİMİ İÇİN ÇOK KRİTERLİ KARAR VERME TEKNİĞİ YAKLAŞIMI: PSI ÖRNEĞİ,” Toros Üniversitesi İİSBF Sosyal Bilimler Dergisi, Oct. 2022, https://doi.org/10.54709/iisbf.1167228
M. Baydaş and D. Pamučar, “Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data,” Mathematics, vol. 10, no. 7, p. 1115, Mar. 2022, https://doi.org/10.3390/math10071115
X. T. Hoang, “Multi-Objective Optimization of Turning Process by Fuca Method,” Strojnícky časopis - Journal of Mechanical Engineering, vol. 73, no. 1, pp. 55–66, May 2023, https://doi.org/10.2478/scjme-2023-0005
A.-T. Nguyen, “Combining FUCA, CURLI, and Weighting Methods in the Decision-Making of Selecting Technical Products,” Engineering, Technology & Applied Science Research, vol. 13, no. 4, pp. 11222–11229, Aug. 2023, https://doi.org/10.48084/etasr.6015
N. H. Son et al., “Choosing the best machine tool in mechanical manufacturing,” EUREKA: Physics and Engineering, no. 2, pp. 97–109, Mar. 2023, https://doi.org/10.21303/2461-4262.2023.002771
D. Van Tran, “Application of the Collaborative Unbiased Rank List Integration Method to Select the Materials,” Applied Engineering Letters : Journal of Engineering and Applied Sciences, vol. 7, no. 4, pp. 133–142, 2022, https://doi.org/10.18485/aeletters.2022.7.4.1
T. Van Dua, “Combination of symmetry point of criterion, compromise ranking of alternatives from distance to ideal solution and collaborative unbiased rank list integration methods for woodworking machinery selection for small business in Vietnam,” EUREKA: Physics and Engineering, no. 2, pp. 83–96, Mar. 2023, https://doi.org/10.21303/2461-4262.2023.002763
A.-T. Nguyen, “The Improved CURLI Method for Multi-Criteria Decision Making,” Engineering, Technology & Applied Science Research, vol. 13, no. 1, pp. 10121–10127, Feb. 2023, https://doi.org/10.48084/etasr.5538
A. ULUTAŞ and C. B. KARAKUŞ, “Location selection for a textile manufacturing facility with GIS based on hybrid MCDM approach,” Industria Textila, vol. 72, no. 02, pp. 126–132, Apr. 2021, https://doi.org/10.35530/IT.072.02.1736
N. Z. Khan, T. S. A. Ansari, A. N. Siddiquee, and Z. A. Khan, “Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method,” Journal of Computers in Education, vol. 6, no. 2, pp. 241–256, Jun. 2019, https://doi.org/10.1007/s40692-019-00135-7
S. E. Tuzcu and S. P. Türkoğlu, “How vulnerable are high-income countries to the covid-19 pandemic? An MCDM approach,” Decision Making: Applications in Management and Engineering, vol. 5, no. 2, pp. 372–395, Oct. 2022, https://doi.org/10.31181/dmame0318062022t
A. Ulutaş, F. Balo, L. Sua, E. Demir, A. Topal, and V. Jakovljević, “A new integrated grey MCDM model: Case of warehouse location selection,” Facta Universitatis, Series: Mechanical Engineering, vol. 19, no. 3, p. 515, Oct. 2021, https://doi.org/10.22190/FUME210424060U
N. Husna, Y. Yupianti, and R. Supardi, “Comparison of the Preference Selection Index (PSI) Method with the Simple Additive Weight (SAW) Method in The Selection of the Best Foreman at PT. Agro Muko,” Jurnal Komputer, Informasi dan Teknologi, vol. 1, no. 2, Dec. 2021, https://doi.org/10.53697/jkomitek.v1i2.294
A. TUŞ and E. AYTAÇ ADALI, “CODAS ve PSI Yöntemleri İle Personel Değerlendirmesi,” Alphanumeric Journal, vol. 6, no. 2, pp. 243–256, Dec. 2018, https://doi.org/10.17093/alphanumeric.432843
M. Stanujkic, D. Stanujkic, D. Karabasevic, C. Sava, and G. Popovic, “Comparison of Tourism Potentials Using Preference Selection Index Method,” Quaestus Multidisciplinary Research Journal, vol. 16, no. April, 2020.
D. Stanujkic, E. K. Zavadskas, D. Karabasevic, F. Smarandache, and Z. Turskis, “The use of the pivot pairwise relative criteria importance assessment method for determining the weights of criteria,” Romanian Journal of Economic Forecasting, vol. 20, no. 4, 2017.
Z. Gligorić, M. Gligorić, I. Miljanović, S. Lutovac, and A. Milutinović, “Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm,” Computer Modeling in Engineering & Sciences, vol. 136, no. 1, pp. 955–979, 2023, https://doi.org/10.32604/cmes.2023.025021
H. X. Thinh, N. T. Mai, N. T. Giang, and V. Van Khiem, “Applying multi-criteria decision-making methods for cutting oil selection,” Eastern-European Journal of Enterprise Technologies, vol. 3, no. 1 (123), pp. 52–58, Jun. 2023, https://doi.org/10.15587/1729-4061.2023.275717
E. A. Adalı and A. T. Işık, “Critic and Maut Methods for the Contract Manufacturer Selection Problem,” European Journal of Multidisciplinary Studies, vol. 5, no. 1, p. 93, May 2017, https://doi.org/10.26417/ejms.v5i1.p93-101
A. R. Krishnan, M. M. Kasim, R. Hamid, and M. F. Ghazali, “A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria,” Symmetry (Basel), vol. 13, no. 6, p. 973, May 2021, https://doi.org/10.3390/sym13060973
S. Jovčić and P. Průša, “A Hybrid MCDM Approach in Third-Party Logistics (3PL) Provider Selection,” Mathematics, vol. 9, no. 21, p. 2729, Oct. 2021, https://doi.org/10.3390/math9212729
S. Salimian, S. M. Mousavi, and Z. Turskis, “Transportation Mode Selection for Organ Transplant Networks by a New Multi-Criteria Group Decision Model Under Interval-Valued Intuitionistic Fuzzy Uncertainty,” Informatica, pp. 337–355, Mar. 2023, https://doi.org/10.15388/23-INFOR513
A. Kumari and B. Acherjee, “Selection of non-conventional machining process using CRITIC-CODAS method,” Mater Today Proc, vol. 56, pp. 66–71, 2022, https://doi.org/10.1016/j.matpr.2021.12.152
M. Mendoza Luis Fernando, J. L. Perez Escobedo, C. Azzaro-Pantel, L. Pibouleau, S. Domenech, and A. Aguilar-Lasserre, “Selecting the best portfolio alternative from a hybrid multiobjective GA-MCDM approach for New Product Development in the pharmaceutical industry,” in 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM), IEEE, Apr. 2011, pp. 159–166. https://doi.org/10.1109/SMDCM.2011.5949271
J. R. Kiger and D. J. Annibale, “A new method for group decision making and its application in medical trainee selection,” Med Educ, vol. 50, no. 10, pp. 1045–1053, Oct. 2016, https://doi.org/10.1111/medu.13112
X. T. Nguyen, A. Ašonja, and D. T. Do, “Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques,” Applied Engineering Letters : Journal of Engineering and Applied Sciences, vol. 8, no. 3, pp. 131–138, 2023, https://doi.org/10.18485/aeletters.2023.8.3.5
L. D. Ha, “Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision,” Applied Engineering Letters : Journal of Engineering and Applied Sciences, vol. 8, no. 1, pp. 24–35, 2023, https://doi.org/10.18485/aeletters.2023.8.1.4
D. D. Trung, N. X. Truong, H. T. Dung, and A. Ašonja, “Combining DOE and EDAS Methods for Multi-criteria Decision Making,” 2024, pp. 210–227. https://doi.org/10.1007/978-3-031-51494-4_19
D. Božanić, A. Milić, D. Tešić, W. Salabun, and D. Pamučar, “D numbers–FUCOM–fuzzy RAFSI model for selecting the group of construction machines for enabling mobility,” Facta Universitatis, Series: Mechanical Engineering, vol. 19, no. 3, p. 447, Oct. 2021, https://doi.org/10.22190/FUME210318047B
D. Stanujkić, D. Karabašević, and G. Popović, “Ranking alternatives using PIPRECIA method: A case of hotels’ website evaluation,” Journal of Process Management. New Technologies, vol. 9, no. 3–4, pp. 62–68, 2021, https://doi.org/10.5937/jouproman2103062S
S. Bošković, S. Jovčić, V. Simic, L. Švadlenka, M. Dobrodolac, and N. Bacanin, “A new criteria importance assessment (Cimas) method in multi-criteria group decision-making: Criteria evaluation for supplier selection,” Facta Universitatis, Series: Mechanical Engineering, pp. 11–16, 2024. https://doi.org/10.22190/FUME230730050B
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Copyright (c) 2024 Do Duc Trung, Branislav Dudić, Duong Van Duc, Nguyen Hoai Son, Aleksandar Ašonja (Author)
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