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Supplier selection using the integrated MEREC – CoCoSo methods in a medical device company

Year 2024, Issue: 056, 116 - 133, 31.03.2024

Gülnihal Özel Sönmez Pelin Toktaş

https://doi.org/10.59313/jsr-a.1420728

Abstract

The medical device industry is a rapidly developing industry that includes various dynamics. Developed technologies show continuous improvement depending on diagnosis and treatment applications in health services. To keep up with this change and survive in an increasingly competitive environment, medical device manufacturers must be engaged in continuous improvement activities. This situation, necessary for many companies producing in the industrial field, gains even more importance in the medical device sector when the direct impact of product safety and quality on human life is considered. In companies producing medical devices, the legal requirements of the product being a medical device are followed by the notified bodies and authorized authorities within the framework of standards and regulations within the scope of quality processes. Increasing costs and liabilities with MDR 2017/45 have pushed medical device manufacturers to question their methods. In this study, it was determined that customer requests could not be met in a company producing medical devices, and it was observed that delivery times increased. In evaluating the reasons for the increase in delivery time, it was determined that supplier selection could have been carried out more effectively. For this purpose, six suppliers and six criteria were selected because of the company's sector knowledge and the evaluations of the company managers. The Combined Compromise Solution (CoCoSo) method, one of the new generation multi-criteria decision-making (MCDM) methods, is proposed for ranking the suppliers in the supplier selection problem. Method The removal effects of criteria (MEREC) weighting method was used to weight supplier selection criteria. In this study, a new generation supplier selection method application in medical devices has been carried out. Considering the inadequacy of the studies on supplier selection in medical devices, the relevant research will contribute to the literature.

Keywords

MEREC CoCoSo Supplier Selection Medical Device MCDM

References

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Year 2024, Issue: 056, 116 - 133, 31.03.2024

Gülnihal Özel Sönmez Pelin Toktaş

https://doi.org/10.59313/jsr-a.1420728

Abstract

References

  • [1] “TIBBİ CİHAZ YÖNETMELİĞİ Sayfa 2 / 143,” Türkiye İlaç ve Tıbbi Cihaz Kurumundan.
  • [2] T. W. Li, P. W. Tu, L. L. Liu, and S. I. Wu, “Assurance of medical device quality with quality management system: An analysis of good manufacturing practice implementation in Taiwan,” Biomed Res. Int., vol. 2015, 2015, doi: 10.1155/2015/670420.
  • [3] V. Jain, A. K. Sangaiah, S. Sakhuja, N. Thoduka, and R. Aggarwal, “Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry,” Neural Comput. Appl., vol. 29, no. 7, pp. 555–564, Apr. 2018, doi: 10.1007/s00521-016-2533-z.
  • [4] A. Fallahpour, E. Udoncy Olugu, S. Nurmaya Musa, K. Yew Wong, and S. Noori, “A decision support model for sustainable supplier selection in sustainable supply chain management,” Comput. Ind. Eng., vol. 105, pp. 391–410, Mar. 2017, doi: 10.1016/J.CIE.2017.01.005.
  • [5] W. Song, Z. Xu, and H.-C. Liu, “Developing sustainable supplier selection criteria for solar air-conditioner manufacturer: An integrated approach,” 2017, doi: 10.1016/j.rser.2017.05.081.
  • [6] M. Yazdani, P. Chatterjee, E. K. Zavadskas, and S. Hashemkhani Zolfani, “Integrated QFD-MCDM framework for green supplier selection,” J. Clean. Prod., vol. 142, pp. 3728–3740, Jan. 2017, doi: 10.1016/J.JCLEPRO.2016.10.095.
  • [7] N. Banaeian, H. Mobli, B. Fahimnia, I. E. Nielsen, and M. Omid, “Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry,” Comput. Oper. Res., vol. 89, pp. 337–347, Jan. 2018, doi: 10.1016/J.COR.2016.02.015.
  • [8] M. Abdel-Basset, G. Manogaran, A. Gamal, and F. Smarandache, “A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria,” Des. Autom. Embed. Syst., vol. 22, no. 3, pp. 257–278, Sep. 2018, doi: 10.1007/S10617-018-9203-6/METRICS.
  • [9] M. Yazdani, Z. Wen, H. Liao, A. Banaitis, and Z. Turskis, “A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management,” J. Civ. Eng. Manag., vol. 25, no. 8, pp. 858–874, Nov. 2019, doi: 10.3846/JCEM.2019.11309.
  • [10] Ž. Stević, D. Pamučar, A. Puška, and P. Chatterjee, “Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS),” Comput. Ind. Eng., vol. 140, p. 106231, Feb. 2020, doi: 10.1016/J.CIE.2019.106231.
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  • [12] D. Sumrit, “Supplier selection for vendor-managed inventory in healthcare using fuzzy multi-criteria decision-making approach,” Decis. Sci. Lett., vol. 9, no. 2, pp. 233–256, 2020, doi: 10.5267/J.DSL.2019.10.002.
  • [13] K. K. Göncü and O. Çetin, “A Decision Model for Supplier Selection Criteria in Healthcare Enterprises with Dematel ANP Method,” Sustain. 2022, Vol. 14, Page 13912, vol. 14, no. 21, p. 13912, Oct. 2022, doi: 10.3390/SU142113912.
  • [14] T. L. Nguyen et al., “A Novel Integrating Data Envelopment Analysis and Spherical Fuzzy MCDM Approach for Sustainable Supplier Selection in Steel Industry,” Math. 2022, Vol. 10, Page 1897, vol. 10, no. 11, p. 1897, Jun. 2022, doi: 10.3390/MATH10111897.
  • [15] P. Ghadimi and C. Heavey, “Sustainable supplier selection in medical device industry: Toward sustainable manufacturing,” Procedia CIRP, vol. 15, pp. 165–170, 2014, doi: 10.1016/J.PROCIR.2014.06.096.
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  • [17] A. A. Forouzeshnejad, “Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool,” Environ. Sci. Pollut. Res., vol. 30, pp. 13418–13437, 2023, doi: 10.1007/s11356-022-22916-x.
  • [18] M. Keshavarz-Ghorabaee, M. Amiri, E.K. Zavadskas, Z. Turskis, & J. Antucheviciene “Determination of objective weights using a new method based on the removal effects of criteria (MEREC)”. Symmetry, vol 13, no.4, p.525, 2021.
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  • [20] D. Trung, & H. T.-A. in P. E., and undefined 2021, “A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study,” researchgate.net, vol. 16, no. 4, pp. 443–456, 2021, doi: 10.14743/apem2021.4.412.
  • [21] M. K.-G.-S. Reports and undefined 2021, “Assessment of distribution center locations using a multi-expert subjective–objective decision-making approach,” nature.com, Accessed: May 06, 2023. [Online]. Available: https://www.nature.com/articles/s41598-021-98698-y.
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  • [23] J. F. Nicolalde, M. Cabrera, J. Martínez-Gómez, R. B. Salazar, and E. Reyes, “Selection of a phase change material for energy storage by multi-criteria decision method regarding the thermal comfort in a vehicle,” J. Energy Storage, vol. 51, p. 104437, Jul. 2022, doi: 10.1016/J.EST.2022.104437.
  • [24] G. Shanmugasundar, G. Sapkota, R. Čep, and K. Kalita, “Application of MEREC in Multi-Criteria Selection of Optimal Spray-Painting Robot,” Process. 2022, Vol. 10, Page 1172, vol. 10, no. 6, p. 1172, Jun. 2022, doi: 10.3390/PR10061172.
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  • [26] D. T. Do and N. T. Nguyen, “Applying Cocoso, Mabac, Mairca, Eamr, Topsis and Weight Determination Methods for Multi-Criteria Decision Making in Hole Turning Process,” Stroj. Cas., vol. 72, no. 2, pp. 15–40, Nov. 2022, doi: 10.2478/SCJME-2022-0014.
  • [27] K. Diaconu, Y. F. Chen, S. Manaseki-Holland, C. Cummins, and R. Lilford, “Medical device procurement in low- and middle-income settings: Protocol for a systematic review,” Syst. Rev., vol. 3, no. 1, pp. 1–11, Oct. 2014, doi: 10.1186/2046-4053-3-118/TABLES/4.
  • [28] B. Ayan, S. Abacıoğlu, and M. P. Basilio, “A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making,” Inf. 2023, Vol. 14, Page 285, vol. 14, no. 5, p. 285, May 2023, doi: 10.3390/INFO14050285.
  • [29] R. Chaurasiya and D. Jain, “A New Algorithm on Pythagorean Fuzzy-Based Multi-Criteria Decision-Making and Its Application,” Iran. J. Sci. Technol. - Trans. Electr. Eng., pp. 1–16, May 2023, doi: 10.1007/S40998-023-00600-1/TABLES/15.
  • [30] M. Yazdani, P. Zarate, E. K. Zavadskas , & Z. Turskis. A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, vol.57, no.9, pp. 2501-2519, 2019.
  • [31] F. Ecer, D. Pamucar, S. Zolfani, M. E.-J. of Cleaner, and undefined 2019, “Sustainability assessment of OPEC countries: Application of a multiple attribute decision making tool,” Elsevier, Accessed: May 19, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0959652619331944.
  • [32] Ž. Erceg, V. Starčevi, D. Pamučar, G. Mitrovi, Ž. Stevi, and S. Žiki, “A new model for stock management in order to rationalize costs: ABC-FUCOM-interval rough CoCoSo model,” mdpi.com, 2019, doi: 10.3390/sym11121527.
  • [33] Z. Wen, H. Liao, E. Kazimieras Zavadskas, and A. Al-Barakati, “Selection third-party logistics service providers in supply chain finance by a hesitant fuzzy linguistic combined compromise solution method,” http://www.tandfonline.com/action/authorSubmission?journalCode=rero20&page=instructions, vol. 32, no. 1, pp. 4033–4058, Jan. 2019, doi: 10.1080/1331677X.2019.1678502.
  • [34] S. H. Zolfani and M. Yazdani, “A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model CALL FOR BOOK PROPOSALS View project 1st Indo-Serbian International Conference on Computational Intelligence for Engineering and Management Applications (CIEMA)-2022 View project,” 2019, doi: 10.3846/cibmee.2019.081.
  • [35] D. Bagal, B. Naik, B. Parida, … A. B.-I. C., and undefined 2020, “Comparative mechanical characterization of M30 concrete grade by fractional replacement of portland pozzolana cement with industrial waste using CoCoSo and,” iopscience.iop.org, Accessed: May 19, 2023. [Online]. Available: https://iopscience.iop.org/article/10.1088/1757-899X/970/1/012015/meta.
  • [36] A. Barua, S. Jeet, D. Bagal, … P. S.-I. J. I. T., and undefined 2019, “Evaluation of mechanical behavior of hybrid natural fiber reinforced nano sic particles composite using hybrid Taguchi-CoCoSo method,” researchgate.net, no. 10, pp. 2278–3075, 2019, doi: 10.35940/ijitee.J1232.0881019.
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There are 45 citations in total.

Details

Primary Language English
Subjects Multiple Criteria Decision Making
Journal Section Research Articles
Authors

Gülnihal Özel Sönmez 0000-0002-8503-2321

Pelin Toktaş 0000-0001-6622-4646

Publication Date March 31, 2024
Submission Date January 16, 2024
Acceptance Date February 20, 2024
Published in Issue Year 2024 Issue: 056

Cite

IEEE G. Özel Sönmez and P. Toktaş, “Supplier selection using the integrated MEREC – CoCoSo methods in a medical device company”, JSR-A, no. 056, pp. 116–133, March 2024, doi: 10.59313/jsr-a.1420728.
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