11971

Bir risk temelli karar verme yaklaşımı ile metalik biyomalzeme değerlendirme

Bu çalışma, bulanık analitik hiyerarşi prosesi (AHP), bulanık hata türleri ve etkileri analizi (HTEA) ve bulanık ortalama çözüm uzaklığına göre değerlendirme (EDAS) yöntemini kombine eden bir karar verme yaklaşımı ile metalik biyomalzemeleri incelemektedir. Çalışmada, paslanmaz çelik, titanyum ve kobalt-krom alaşımları altı ana kriter, otuz bir alt kriter ve üç risk faktörü kullanılarak değerlendirilmiştir. Bulanık AHP yöntemi değerlendirme kriterlerinin ve risk faktörlerinin önemini belirlemek için kullanılırken, bulanık EDAS yöntemi bulanık HTEA yönteminden elde edilen risk öncelik katsayılarını analiz etmek için kullanılmıştır. Sonuçlara göre, ilk üç önemli kriter enfeksiyon, kanserojenlik ve çekme mukavemetidir. Malzemelerin sıralaması; titanyum > paslanmaz çelik > kobalt-krom alaşımları şeklindedir. Sonuç olarak bu çalışma, mevcut malzemelerin tarafsız değerlendirilmesi ve önceliklendirilmesi için bir temel oluşturmaktadır.

Anahtar Kelimeler:

Biyomalzeme, Bulanık HTEA, Bulanık AHP, Bulanık EDAS, Metal

PDF

___

1. Hussein M.A., Mohammed A.S., Al-Aqeeli N., Wear characteristics of metallic biomaterials: a review, Materials, 8 (5), 2749-2768, 2015.
2. Prasad K., Bazaka O., Chua M., Rochford M., Fedrick L., Spoor J., Symes R., Tieppo M., Collins C., Cao A., Markwell D., Ostrikov K., Bazaka K., Metallic biomaterials: current challenges and opportunities, Materials, 10 (8), 1-33, 2017.
3. Jayabalan M., Biological interactions: causes for risks and failures of biomaterials and devices, Journal of Biomaterials Applications, 8 (1), 64-71, 1993.
4. Manivasagam G., Dhinasekaran D., Rajamanickam A., Biomedical implants: corrosion and its prevention-a Review, Recent Patents on Corrosion Science, 2, 40-54, 2010.
5. Turskis Z., Keršulienė V., Vinogradova I., A new fuzzy hybrid multi-criteria decision-making approach to solve personnel assessment problems. case study: director selection for estates and economy office, Economic Computation and Economic Cybernetics Studies and Research, 51 (3), 211-229, 2017.
6. Stević Ž., Vasiljević M., Puška A., Tanackov I., Junevičius R., Vesković S., Evaluation of suppliers under uncertainty: a multiphase approach based on Fuzzy AHP and Fuzzy EDAS, Transport, 34 (1), 52-66, 2019.
7. Yürüyen A.A., Ulutaş A., Selection of the third party logistics company with fuzzy AHP and fuzzy EDAS methods, Journal of Social Sciences of Mus Alparslan University, 8, 283-294, 2020.
8. Singer H., Özşahin Ş., Multicriteria evaluation of structural composite lumber products, Journal of Anatolian Environmental and Animal Sciences, 5 (5), 807-813, 2020.
9. Srivastava P.R., Zhang Z., Eachempati P., Lyu H., An intelligent framework for analyzing the feasible modes of transportation in metropolitan cities: a hybrid multicriteria approach, Journal of Advanced Transportation, 2021, 1-22, 2021.
10. Ravindran A.R., Bilsel R.U., Wadhwa V., Yang T., Risk adjusted multicriteria supplier selection models with applications, International Journal of Production Research, 48 (2), 405-424, 2010.
11. Farajiparvar N., Maintenance policy selection using fuzzy FMEA and key performance indicators. Master Thesis, University of Regina, Regina, 2016.
12. Zhou Q., Thai V.V., Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction, Safety Science, 83, 74-79, 2016.
13. Jahangoshai-Rezaee M., Yousefi S., Valipour M., Dehdar M.M., Risk analysis of sequential processes in food industry integrating multi-stage fuzzy cognitive map and process failure mode and effects analysis, Computers and Industrial Engineering, 123, 325-337, 2018.
14. Jahangoshai-Rezaee M., Yousefi S., Eshkevari M., Valipour M., Saberi M., Risk analysis of health, safety and environment in chemical industry integrating linguistic FMEA, fuzzy inference system and fuzzy DEA, Stochastic Environmental Research and Risk Assessment, 34 (1), 201-218, 2020.
15. Hafezalkotob A., Hafezalkotob A., Risk-based material selection process supported on information theory: a case study on industrial gas turbine, Applied Soft Computing, 52, 1116-1129, 2017.
16. Bahraminasab M., Jahan A., Material selection for femoral component of total knee replacement using comprehensive VIKOR, Materials and Design, 32 (8-9), 4471-4477, 2011.
17. Kabir G., Lizu A., Material selection for femoral component of total knee replacement integrating fuzzy AHP with PROMETHEE, Journal of Intelligent and Fuzzy Systems, 30 (6), 3481-3493, 2016.
18. Jahan A., Edwards K.L., Weighting of dependent and target-based criteria for optimal decision-making in materials selection process: biomedical applications, Materials and Design, 49, 1000-1008, 2013.
19. Jahan A., Material selection in biomedical applications: comparing the comprehensive VIKOR and goal programming models, International Journal of Materials and Structural Integrity, 6 (2-4), 230-240, 2012.
20. Petković D., Madić M., Radenković G., Manić M., Trajanović M., Decision support system for selection of the most suitable biomedical material, 5th International Conference on Information Society and Technology, Kopaonik-Serbia, 27-31, 8-11 March, 2015.
21. Chatterjee P., Panchal D., Chakraborty S., A developed meta-model for biomaterials selection, Trends in Biomaterials and Artificial Organs, 34 (1), 20-32, 2020.
22. Chowdary Y., Ram V.S., Nikhil E.V.S., Krishna P.N.S.V., Nagaraju D., Evaluation and prioritizing of biomaterials for the application of implantation in human body using fuzzy AHP and TOPSIS, International Journal of Control Theory and Applications, 9 (40), 527-533, 2016.
23. Hafezalkotob A., Hafezalkotob A., Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications, Materials and Design, 87, 949-959, 2015.
24. Hafezalkotob A., Hafezalkotob A., Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection, Journal of Industrial Engineering International, 13 (2), 181-198, 2017.
25. Messellek A.C., Ould-Ouali M., Benabid Y., Amrouche A., Beloulla A., Material selection process for femoral component of hip prosthesis using finite element analysis and ranking method, Computer Methods in Biomechanics and Biomedical Engineering, 20, 133-134, 2017.
26. Das S.S., Chakraborti P., Bhowmik C., Singh R., Decision-making for selection of most suitable materials for biomedical applications, Lecture Notes in Mechanical Engineering. Springer, Singapore, 2019.
27. Falchete do Prado R., Esteves G.C., De E.L., Santos S., Griti Bueno D.A., Alves Cairo C.A., Gustavo L., De Vasconcellos O., Sagnori R.S., Bastos F., Tessarin P., Oliveira F.E., De Oliveira L.D., Fernanda M., Villaça-Carvalho L., Rodrigues Henriques V.A., Carvalho Y.R., Reis De Vasconcellos L.M., In vitro and in vivo biological performance of porous Ti alloys prepared by powder metallurgy, PLoS ONE, 13 (5), e0196169, 2018.
28. Zhu D., Cockerill I., Su Y., Zhang Z., Fu J., Lee K.W., Ma J., Okpokwasili C., Tang L., Zheng Y., Qin Y.X., Wang Y., Mechanical strength, biodegradation, and in vitro and in vivo biocompatibility of Zn biomaterials, ACS Applied Materials and Interfaces, 11 (7), 6809-6819, 2019.
29. Li P., Zhou N., Qiu H., Maitz M.F., Wang J., Huang N., In vitro and in vivo cytocompatibility evaluation of biodegradable magnesium-based stents: a review, Science China Materials, 61 (4), 501-515, 2018.
30. Kaya T., Kahraman C., Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: the case of Istanbul, Energy, 35 (6), 2517-2527, 2010.
31. Wang Y.M., Chin K.S., Poon G.K K., Yang J.B., Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean, Expert Systems with Applications, 36, 1195-1207, 2009.
32. Singer H., Özşahin, Ş., Employing an analytic hierarchy process to prioritize factors influencing surface roughness of wood and wood-based materials in the sawing process, Turkish Journal of Agriculture and Forestry, 42 (5), 364-371, 2018.
33. Ahammed F., Azeem A., Selection of the most appropriate package of solar home system using analytic hierarchy process model in rural areas of Bangladesh, Renewable Energy, 55, 6-11, 2013.
34. Buckley J.J., Fuzzy hierarchical analysis, Fuzzy Sets and Systems, 17 (3), 233-247, 1985.
35. Budak A., Ustundag A., Fuzzy decision making model for selection of real time location systems, Applied Soft Computing, 36, 177-184, 2015.
36. Carnero M.C., Waste segregation FMEA model integrating intuitionistic fuzzy set and the PAPRIKA method, Mathematics, 8 (8), 1-29, 2020.
37. Bozdag E., Asan U., Soyer A., Serdarasan S., Risk prioritization in failure mode and effects analysis using interval type-2 fuzzy sets, Expert Systems with Applications, 42 (8), 4000-4015, 2015.
38. Mızrak Özfırat P., A new risk analysis methodology integrating fuzzy prioritization method and failure modes and effects analysis, Journal of the Faculty of Engineering and Architecture of Gazi University, 29 (4), 755-768, 2014.
39. Li Z., Chen L., A novel evidential FMEA method by integrating fuzzy belief structure and grey relational projection method, Engineering Applications of Artificial Intelligence, 77, 136-147, 2019.
40. Ghorabaee M.K., Zavadskas E.K., Amiri M., Turskis Z., Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection, International Journal of Computers, Communications and Control, 11 (3), 358-371, 2016.
41. Hasheminasab H., Zolfani S.H., Bitarafan M., Chatterjee P., Ezabadi A.A., The role of facade materials in blast-resistant buildings: an evaluation based on fuzzy delphi and fuzzy edas, Algorithms, 12 (6), 1-15, 2019.
42. Gosain A.K., Chim H., Arneja J.S., Application-specific selection of biomaterials for pediatric craniofacial reconstruction: developing a rational approach to guide clinical use, Plastic and Reconstructive Surgery, 123 (1), 319-330, 2009.