Davlumbazlarda Kullanılan 1 fazlı Asenkron Motorun Tedarikçi Seçiminin Bulanık TOPSIS Yöntemiyle Belirlenmesi

Yıl 2023, , 1307 - 1321, 15.12.2023

Mehmet Ekici , Hakan Tekbaş

https://doi.org/10.31466/kfbd.1207783

Öz

Davlumbazlar mutfaklarımızda kullanılan ve ortamın havalandırılmasına katkı sağlayan en önemli cihazlardır. Davlumbazlarda kullanılan elektrik motorlarının %95'ini 1 fazlı asenkron motorlar oluşturmaktadır. Davlumbaz sektörüne yönelik üretim yapan yerli ve yabancı pek çok elektrik motoru üreticisi bulunmaktadır. Davlumbaz üreten firmalarda tedarikçi seçimi sürdürülebilir üretim için hayati ve kritik öneme sahiptir. Tedarik edilen ürünlerin satın alma sürecinde doğru karar vermek son derece önemlidir. Alınan kararlar bazen birbirinden net bir şekilde ayrılırken bazen de iç içe ve birbiriyle bağlantılı olmaktadır. Açıkça ayrıştırılamayan veya sayısal verilerle açıklanamayan kararların alınmasında çok kriterli karar verme teknikleri kullanılmaktadır. Bu çalışmada, davlumbazlarda kullanılan 1 fazlı asenkron motorların tedariğinde bulanık TOPSIS yöntemi kullanılarak Türkiye/Amasya bölgesinde faaliyet gösteren ankastre firması için en uygun tedarikçinin belirlenmesi amaçlandı. Şirkette çalışan 5 uzmanın, karar verici olarak belirlenmesinin ardından kalite, sistem kapasitesi, finans ve sevkiyat performansı olmak üzere 4 kriter belirlendi. 6 farklı tedarikçi içinden en uygun seçim gerçekleştirilmiştir. 1 fazlı asenkron motorun tedarikçi seçimi için ilk defa Bulanık TOPSIS yöntemi ile çözüm önerisi sunularak literatüre katkı sağlanmıştır.

Anahtar Kelimeler

Topsis, Bulanık, Davlumbaz, Asenkron motor

Determination of Supplier Selection For 1-Phase Induction Motor Used in Hoods by Fuzzy TOPSIS Method

Öz

Hoods are the most important devices used in our kitchens that contribute to the ventilation of the environment. 95% of the electric motors used in hoods are single-phase asynchronous motors. There are many domestic and foreign electric motor manufacturers producing for the hood industry. Supplier selection in companies producing hoods is vital and critical for sustainable production. It is extremely important to make the right decision in the purchasing process of the supplied products. While the decisions taken can sometimes be clearly separated from each other, sometimes they can be intertwined and interconnected. Multi criteria decision making techniques are used when making decisions that cannot be clearly separated or explained with numerical data. The aim of this study was to determine the most suitable Supplier for the built-in appliance company operating in the Turkiye/Amasya region by using fuzzyTOPSIS method in the supply of 1-phase asynchronous motors used in hoods. After 5 experts working in the company were determined as decision makers, 4 criteria were determined: quality, system capacity, finance and logistics performance. The best supplier selection among 6 different suppliers was made using this method. For the first time, a solution proposal was presented with the fuzzyTOPSIS technique for the 1-phase induction motor supplier selection and a contribution was made to the literature.

Anahtar Kelimeler

Topsis, Fuzzy, Hood, Induction motor

Kaynakça

• Aydemir, S,.B., Gunduz, S.,(2020). Fermatean fuzzy TOPSIS method with Dombi aggregation operators and its application in multi-criteria decision making. Journal of Intelligent & Fuzzy Systems, 39, 851-869.
• Bilgili,F., Zarali, F., Ilgün, M.F, , Dumrul ,C., ve Dumrul,Y.,(2022). The evaluation of renewable energy alternatives for sustainable development in Turkey using intuitionistic fuzzy-TOPSIS method. Renewable Energy, 189, 1443-1458.
• Bozdağ, C. E., Kahraman, C., ve Ruan, D. (2003). Fuzzy group decision making for selection among computer integrated manufacturing systems. Computers in Industry, 51(1), 13-29.
• Cakar, T., Çavuş, B., (2021). Supplier selection process in dairy industry using fuzzy TOPSIS method. Operational Research in Engineering Sciences: Theory and Applications,4, 82-98.
• Chen, C.T., (2000). Extensions of the Topsis for Group Decision-Making Under Fuzzy Environment. Fuzzy Sets and Systems. 114(1), 1-9.
• Chen, C.T., Lin,C.T., ve Huang, S.F., (2006). A Fuzzy Approach for Supplier Evaluation and Selection in Supply Chain Management. International Journal of Production Economies, 102(2), 289-301.
• Doğanalp, B., (2016). Bulanık Çok Kriterli Karar Verme İle Öğretim Üyesi Değerleme Çalışması. Kastamonu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(1), 498-517.
• Govil,N., Sharma, A.,(2022). Validation of agile methodology as ideal software development process using Fuzzy-TOPSIS method. Advances in Engineering Software,168 ,103-125.
• Gündoğdu, F., Kahraman, C. (2019). A novel fuzzy TOPSIS method using emerging interval-valued spherical fuzzy sets. Engineering Applications of Artificial Intelligence, 85, 307-323.
• Han, H., Trimi, S. (2018). A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms. Expert Systems with Applications, 103, 133-145.
• Ho, W., Xu, X., ve Dey P. K., (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research. 202(1),16–24.
• Hwang, C.L., Yoon, K., (1981). Multiple attribute decision making methods and applications A State-of-the-Art Survey. New York: Springer-Verlag.
• Mamavi, O., Nagati, H., Pache, G., ve Wehrle, F.T.,(2015). How does performance history impact supplier selection in public sector. Industrial Management & Data Systems,115(1), 1-29.
• Memari, A., Dargi, A., Jokar, M., Ahmad, R., ve Rahim, A. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method, Journal of Manufacturing Systems, 50(1), 9-24.
• Orçun, Ç., Eren, B. S. (2017). TOPSIS Yöntemi Ile Finansal Performans Değerlendirmesi: XUTEK Üzerinde Bir Uygulama. Muhasebe ve Finansman Dergisi,75,139–154.
• Özen, E., Yeşildağ, E., ve Soba, M., (2015). TOPSIS Performance Evaluation Measures and Relation between Financial Ratios and Stock Returns. Journal of Economics, Finance and Accounting, 2(4), 482–482.
• Öztürk, C., Yildizbaşi, A., (2020). Barriers to implementation of blockchain into supply chain management using an integrated multi-criteria decision-making method: a numerical example. Soft Computing, 24(1), 14771–14789.
• Rudnik, K., Kacprzak, D. (2017). Fuzzy TOPSIS method with ordered fuzzy numbers for flow control in a manufacturing system, Applied Soft Computing, 52, 1020-1041.
• Sun, C.C, (2010). A Performance Evaluation Model By Integrating Fuzzy AHP and Fuzzy TOPSIS Methods. Expert Systems with Applications, 37, 7745-7754.
• Tekez, E., Bark, N.,(2016). Mobilya sektöründe bulanık TOPSIS yöntemi ile tedarikçi seçimi. SAÜ Fen Bilimleri Dergisi, 20(1), 55-63.
• Zadeh, L.A.,(1965).Fuzzy Sets. Information Control,8(1), 338-353.
• Zimmerman, B. J., Kitsantas, A. (1997). Developmental phases in self-regulation: Shifting from process goals to outcome goals. Journal of educational psychology, 89(1), 29-36.