An integrated framework for non-traditional machining process technology selection in healthcare applications
| dc.authorid | 0000-0002-6959-9168 | |
| dc.authorid | 0000-0002-2689-1222 | |
| dc.contributor.author | Delice, Elif | |
| dc.contributor.author | Tozan, Hakan | |
| dc.contributor.author | Karadayı, Melis Almula | |
| dc.contributor.author | Harnicarova, Marta | |
| dc.contributor.author | Turan, Başak | |
| dc.date.accessioned | 2022-11-11T09:37:31Z | |
| dc.date.available | 2022-11-11T09:37:31Z | |
| dc.date.issued | 2022 | |
| dc.department | İstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü | |
| dc.department | İstanbul Medipol Üniversitesi, Fen Bilimleri Enstitüsü, Sağlık Sistemleri Mühendisliği Ana Bilim Dalı | |
| dc.description.abstract | In 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. | |
| dc.description.sponsorship | Vedecká Grantová Agentúra MŠVVaŠ SR a SAV | en_US |
| dc.description.sponsorship | Vedecka grantova agentura MSVVaS SR a SAV (VEGA) European Commission | en_US |
| dc.identifier.citation | Delice, 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-20220503130337 | |
| dc.identifier.doi | 10.17559/TV-20220503130337 | |
| dc.identifier.endpage | 2146 | |
| dc.identifier.issn | 1330-3651 | |
| dc.identifier.issue | 6 | |
| dc.identifier.scopus | 2-s2.0-85140849459 | |
| dc.identifier.scopusquality | Q3 | |
| dc.identifier.startpage | 2137 | |
| dc.identifier.uri | https://dx.doi.org/10.17559/TV-20220503130337 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12511/9953 | |
| dc.identifier.volume | 29 | |
| dc.identifier.wos | 000884079900015 | en_US |
| dc.identifier.wosquality | Q4 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | Tozan, Hakan | |
| dc.institutionauthor | Karadayı, Melis Almula | |
| dc.institutionauthor | Turan, Başak | |
| dc.language.iso | en | |
| dc.publisher | Strojarski Facultet | |
| dc.relation.ispartof | Tehnicki Vjesnik | en_US |
| dc.relation.publicationcategory | Diğer | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Best Worst Method | |
| dc.subject | EDAS | |
| dc.subject | Health Technology Selection | |
| dc.subject | Multi-Criteria Decision Making | |
| dc.subject | Non-Traditional Machining | |
| dc.title | An integrated framework for non-traditional machining process technology selection in healthcare applications | |
| dc.type | Review Article |
