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dc.contributor.authorDelice, Elif
dc.contributor.authorTozan, Hakan
dc.contributor.authorKaradayı, Melis Almula
dc.contributor.authorHarnicarova, Marta
dc.contributor.authorTuran, Başak
dc.date.accessioned2022-11-11T09:37:31Z
dc.date.available2022-11-11T09:37:31Z
dc.date.issued2022en_US
dc.identifier.citationDelice, E., Tozan, H., Karadayı, M. A., Harnicarova, M. ve Turan, B. (2022). An integrated framework for non-traditional machining process technology selection in healthcare applications. Tehnicki Vjesnik, 29(6), 2137-2146. https://dx.doi.org/10.17559/TV-20220503130337en_US
dc.identifier.issn1330-3651
dc.identifier.urihttps://dx.doi.org/10.17559/TV-20220503130337
dc.identifier.urihttps://hdl.handle.net/20.500.12511/9953
dc.description.abstractIn spite of continuous progress in technical advancement, the conventional machining process became unsatisfactory in the healthcare field due to its disadvantages. This inadequacy lead researchers to consider using the application of nontraditional machining that can machine extremely hard and brittle materials into complicated shapes such as medical devices and implants in healthcare. In this study, the three most popular nontraditional machining process technologies: Laser Beam Machining, Water Jet Machining, and Electrocautery are evaluated to determine the most appropriate technology using the Health Technology Assessment based Multi-criteria Decision-Making framework. HTA is organized evaluation of effects and properties of health technology that enables the application of systematic skills to solve a health problem. HTA's main goal is to raise awareness of new health technologies among decision makers. For these reasons, the HTA core model that enables the production of HTA-related information was utilized.The comparison of selected technologies was carried out via integrating the HTA core model, Best Worst, and Evaluation Based on Distance from Average Solution methods. Finally, a comparison was made to find the most suitable technology to create the necessary infrastructure. As a result, evaluation scores were computed as 0,673; 0,538 and 0,500 for WJM, LBM, and EC, respectively.en_US
dc.description.sponsorshipVedecká Grantová Agentúra MŠVVaŠ SR a SAVen_US
dc.description.sponsorshipVedecka grantova agentura MSVVaS SR a SAV (VEGA) European Commissionen_US
dc.language.isoengen_US
dc.publisherStrojarski Faculteten_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBest Worst Methoden_US
dc.subjectEDASen_US
dc.subjectHealth Technology Selectionen_US
dc.subjectMulti-Criteria Decision Makingen_US
dc.subjectNon-Traditional Machiningen_US
dc.titleAn integrated framework for non-traditional machining process technology selection in healthcare applicationsen_US
dc.typereviewen_US
dc.relation.ispartofTehnicki Vjesniken_US
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.departmentİstanbul Medipol Üniversitesi, Fen Bilimleri Enstitüsü, Sağlık Sistemleri Mühendisliği Ana Bilim Dalıen_US
dc.authorid0000-0002-6959-9168en_US
dc.authorid0000-0002-2689-1222en_US
dc.identifier.volume29en_US
dc.identifier.issue6en_US
dc.identifier.startpage2137en_US
dc.identifier.endpage2146en_US
dc.relation.publicationcategoryDiğeren_US
dc.identifier.doi10.17559/TV-20220503130337en_US
dc.institutionauthorTozan, Hakan
dc.institutionauthorKaradayı, Melis Almula
dc.institutionauthorTuran, Başak
dc.identifier.wosqualityQ4en_US
dc.identifier.wos000884079900015en_US
dc.identifier.scopus2-s2.0-85140849459en_US
dc.identifier.scopusqualityQ3en_US


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