Supplier Selection via Axiomatic Design: An Application in Turkey for Baby Formula Production

Yıl 2018, Cilt: 11 Sayı: 2, 195 - 201, 30.04.2018

Gül Didem Batur Bahar Özyörük

https://doi.org/10.17671/gazibtd.392093

Cited By: 1

Öz

In
today's world, researchers work harder in order to improve the manufacturing
processes and to produce with lower cost values. Many different analytical and
heuristic approaches are proposed for these aims. In this study, the supplier
selection problem is taken into account for a baby formula producer, which is
one of the largest ones of the market in Turkey. Food production is of high
importance for human life; besides, production of baby formulas and the
decisions related to this process are even more important. In the literature,
there are no studies related to this major problem. Throughout the solution
procedure, the problem is approached using Fuzzy Axiomatic Design (AD), which
enables to use both qualitative and quantitative factors together in supplier
selection problems. In the context of this work, the second axiom of AD, Fuzzy
Information Axiom, which is more advantageous compared to other Multi Criteria
Decision Making methods as it allows both fuzzy and certain information to be
evaluated together. is used and a hierarchical evaluation related is presented to
the suppliers.

Anahtar Kelimeler

Supply Chain Management, Supplier Selection, Multi Criteria Decision Making, Axiomatic Design

Aksiyomatik Tasarim ile Tedarikçi Seçimi: Bebek Mamasi Üretimi için Türkiye'de Bir Uygulama

Öz

Günümüz dünyasında araştırmacılar, üretim süreçlerini iyileştirmek ve daha düşük maliyet değerleri ile üretim yapmak için daha fazla çalışmaktadırlar. Bu amaçlara yönelik olarak birçok analitik ve sezgisel yaklaşım önerilmiştir. Bu çalışmada, Türkiye'de pazarın en büyüklerinden biri olan bir bebek maması üreticisi için tedarikçi seçim problemi ele alınmaktadır. Gıda üretimi insan hayatı için büyük önem taşımaktadır; bebek formüllerinin üretimi ve bu süreçle ilgili kararlarsa daha da önemlidir. Literatürde bu önemli probleme ilişkin bir çalışma bulunmamaktadır. Çözüm prosedürü boyunca, tedarikçi seçiminde hem nitel hem de nicel faktörlerin birlikte değerlendirilmesini sağlayan Bulanık Aksiyomatik Tasarım (AD) kullanılmıştır. Bu çalışma kapsamında, bulanık ve kesin bilgilerin birlikte değerlendirilebilmesine izin verdiği için, diğer Çok Kriterli Karar Verme yöntemlerine kıyasla daha avantajlı olan AD'nin ikinci aksiyomu olan bulanık bilgi aksiyomu kullanılmış ve tedarikçilere, hiyerarşik bir değerlendirme sunulmuştur.

Anahtar Kelimeler

Tedarik Zinciri Yönetimi, Tedarikçi Seçimi, Çok Kriterli Karar Verme, Aksiyomatik Tasarım

Kaynakça

• N.P. Suh, The principles of design, Oxford University Press, New York, 1990.
• O. Kulak, S. Cebi, C. Kahraman, “Applications of axiomatic design principles: A literature review”, Expert Systems with Applications, 37: 6705-6717, 2010.
• X. Chen, Z. Li, Z.-P. Fan, X. Zhou, X. Zhang, “Matching demanders and suppliers in knowledge service: A method based on fuzzy axiomatic design”, Information Sciences, 346–347:130-145, 2016.
• A.V. Khandekar, S. Chakraborty, “Application of fuzzy axiomatic design principles for selection of non-traditional machining processes”, The International Journal of Advanced Manufacturing Technology, 83(1): 529-543, 2016.
• A.V. Khandekar, S. Chakraborty, “Personnel selection using fuzzy axiomatic design principles”, Business: Theory and Practice, 17(3): 251-260, 2016.
• Y. Kır, H. Yazgan, “A sequence dependent single machine scheduling problem with fuzzy axiomatic design for the penalty costs”, Computers and Industrial Engineering, 92: 95-104, 2016.
• D. Kannan, K. Govindan, S. Rajendran, “Fuzzy axiomatic design approach based green supplier selection: a case study from Singapore”, Journal of Cleaner Production, 96: 194-208, 2015.
• A.V. Khandekar, S. Chakraborty, “Selection of industrial robot using axiomatic design principles in fuzzy environment”, Decision Science Letters, 4(2):181-192, 2015.
• A.V. Khandekar, S. Chakraborty, “Selection of material handling equipment using fuzzy axiomatic design principles”, Informatica, 26(2): 259-282, 2015.
• A.V. Khandekar, J. Antuchevičienė, S. Chakraborty, “Small hydro-power plant project selection using fuzzy axiomatic design principles”, Technological and Economic Development of Economy, 21-5: 756-772, 2015.
• O. Kulak, H.G. Goren, A.A. Supciller, “A new multi criteria decision making approach for medical imaging systems considering risk factors”, Applied Soft Computing, 35: 931–941, 2015.
• A. Maldonado-Macías, J. García-Alcaraz, R.M. Reyes, J. Hernández, “Application of a fuzzy axiomatic design methodology for ergonomic compatibility evaluation on the selection of plastic molding machines: a case study”, Procedia Manufacturing, 3: 5769-5776, 2015.
• S. Vinodh, V. Kamala and K. Jayakrishna, “Application of fuzzy axiomatic design methodology for selection of design alternatives”, Journal of Engineering, Design and Technology, 13(1): 2-22, 2015.
• J. Weber, D. Förster, J. Kößler, K. Paetzoldb, “Design of changeable production units within the automotive sector with Axiomatic Design”, Procedia CIRP, 34: 93-97, 2015.
• M.C. Bahadir, S.I. Satoglu, “A novel robot arm selection methodology based on axiomatic design principles”, International Journal of Advanced Manufacturing Technology, 71(9):2043-2057, 2014.
• L.G. Beng, B. Omar, “Integrating axiomatic design principles into sustainable product development”, International Journal of Precision Engineering and Manufacturing - Green Technology, 1-2: 107-117, 2014.
• Ö.N. Bilişik, N. Demirtaş, U.R. Tuzkaya, H. Baraçlı, “Garage location selection for public transportation system in İstanbul: an ıntegrated fuzzy AHP and fuzzy axiomatic design based approach”, Journal of Applied Mathematics, 2014: 1-13, 2014.
• H.G. Goren and O. Kulak, “A new fuzzy multi-criteria decision making approach: extended hierarchical fuzzy axiomatic design approach with risk factors”, Lecture Notes in Business Information Processing, LNBIP, 184: 141-156, 2014.
• C.A. Weber, “A data envelopment analysis approach to measuring vendor performance”, Supply Chain Management: An International Journal, 1(1): 28-39, 1996.
• Y.Z. Mehrjerdi, “Developing fuzzy TOPSIS method based on interval valued fuzzy sets”, International Journal of Computer Applications, 42(14), 7-18, 2012.
• L.A. Zadeh, “Fuzzy sets”. Information and Control, 8: 338-353, (1965).
• O. Kulak, C. Kahraman, “Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process”, Information Sciences, 170:191-210, 2005.
• N.P. Suh, Axiomatic design: advances and applications, Oxford University Press, New York, 2001.
• A. Aktas, S. Cebi, İ. Temiz, “A new evaluation model for service quality of health care systems based on AHP and information axiom”. Journal of Intelligent and Fuzzy Systems, 28(3): 1009-1021, 2015.
• O. Kulak, C. Kahraman, “Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach”, International Journal of Production Economics, 95(3): 415-424, 2005.
• M. H. Calp, İ. Şahin, “The determination by using fuzzy expert system of the usability level of website user interface design”, International Journal of Human Science, Volume: 10, Special Issue, 141-150, 2013.