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YALIN ÜRETİM SİSTEMLERİNDE RİSK ANALİZİ: BULANIK VIKOR YÖNTEMİ İLE SERAMİK FİRMASINDA BİR UYGULAMA

Yıl 2024, Cilt: 35 Sayı: 1, 61 - 91, 30.04.2024

Öz

Ticaret sınırlarının ortadan kalması pazarın genişlemesine ve rekabetinde yoğunlaşmasına neden olur. İşletmelerin küresel rekabette ayakta kalabilmesi müşterilere kaliteli ürünleri en uygun fiyatta sunmasına bağlıdır. Müşterilere sunulan uygun fiyatla birlikte karın arttırılması yalnız maliyetlerin düşürülmesi ile gerçekleşebilir. Üretimde gereksiz kaynak kullanımı ortadan kaldırarak verim artışı sağlayan ve maliyetleri düşüren yalın üretim tekniği kritik bir üretim aracı olarak ortaya çıkar. Bu çalışma, yalın üretim sistemlerinin uygulanması sürecinde karşılaşılan engellerin belirlenmesini ve etkilerinin gözlenmesi amaçlanır. Çalışma Bilecik ilinde bulunan bir seramik şirketinin tesislerindeki yalın üretim sistemleri ile ilgilenilir ve toplanan veriler ile uygulama önündeki risk faktörleri ve faktörlerin önem ağırlıklarını belirler. Veriler çalışanların bilgi ve tecrübelerine dayalı dilsel değerlendirmelerden elde edilir. Bulanık mantık teorisine dayalı yamuk aralıklı tip-2 bulanık kümeleri değerlendirmelerdeki bilgi kaybını azaltmak için başvurulur. Literatür taraması ve seramik sektöründeki tecrübeler yalın üretim sistemlerindeki on kritik risk faktörünü öne çıkarır. Uzmanlar tarafından önem ağırlıkları dilsel değerlendirilen risk faktörlerinin yamuk aralıklı tip-2 bulanık hesaplamaları on risk faktörünün sıralama değerlerinin 0,145-0,155 arasında değiştiğini ve faktörler arasında önemli bir fark olmadığını gösterir. Bu durum 23 faktör arasından ön değerlendirme ile 10 faktörün kritik faktörler olarak seçilmesinden kaynaklanır. İşletme koşul ve çalışan kabulünün risk faktörleri ile uyumuna göre yalın üretim sisteminin gerçekleşebilirliğini açıklamak için seramik işletmesinin üç farklı tesisi için uygulama çalışması yapılır. Tesisler risk faktörlerine göre dilsel değerlendirilir ve yamuk aralıklı tip-2 bulanık kümelere dayalı bulanık VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) karar verme yöntemi ile yalın üretim sisteminin uygulamasına en uygun tesis belirlenir.

Teşekkür

Çalışmamızın geliştirilmesinde veri sağlama ve anket değerlendirmeleri ile katkıda bulunan Bilecik Seranit fabrikası yönetimine katkılarından dolayı teşekkür ederiz.

Kaynakça

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  • Apak, S. (2022). Pandemi döneminde yalın üretim uygulamalarının önceliklendirilmesi: Otomotiv parçası üreticileri örneği. Endüstri Mühendisliği (TMMOB), 33(1), 62-74. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
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  • Ayyildiz, E., Taskin Gumus, A. ve Erkan, M. (2020). Individual credit ranking by an integrated interval type-2 trapezoidal fuzzy Electre methodology. Soft Computing, 24, 16149-16163. Doi: https://doi.org/10.1007/s00500-020-04929-1
  • Bai, C., Satir, A., ve Sarkis, J. (2019). Investing in lean manufacturing practices: An environmental and operational perspective. International Journal of Production Research, 57(4), 1037-1051. Doi: https://doi.org/10.1080/00207543.2018.1498986
  • Basu, P., Chatterjee, D., Ghosh, I., ve Dan, P. K. (2021). Lean manufacturing implementation and performance: The role of economic volatility in an emerging economy. Journal of Manufacturing Technology Management, 32(6), 1188-1223. Doi: https://doi.org/10.1108/JMTM-12-2019-0455
  • Başak, E. E., Yılmaz, İ. S. ve Deniz, N. (2019). Endüstriyel ürün imalatı yapan bir işletmede yalın üretim uygulaması. Endüstri Mühendisliği, 30(3), 157-172. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
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  • Bhalaji, R., Bathrinath, S. ve Saravanasankar, S. (2021). A Fuzzy VIKOR method to analyze the risks in lean manufacturing implementation. Materials Today: Proceedings, 45, 1294-1299. Doi: https://doi.org/10.1016/ j.matpr.2020.05.123
  • Brauers, W. K., ve Zavadskas, E. K. (2009). Robustness of the multi‐objective MOORA method with a test for the facilities sector. Technological and Economic Development of Economy, 15(2), 352-375. Doi: https://doi.org/10.3846/1392-8619.2009.15.352-375
  • Brauers, W. K. M. (2013). Multi-objective seaport planning by MOORA decision making. Annals of Operations Research, 206, 39-58. Doi: https://doi.org/10.1007/s10479-013-1314-7
  • Castillo, O., Amador-Angulo, L., Castro, J. R. ve Garcia-Valdez, M. (2016). A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Information Sciences, 354, 257-274. Doi: https://doi.org/10.1016/j.ins.2016.03.026
  • Chan, S. W., Ismail, F., Ahmad, M., Zaman, I. ve Lim, H. Q. (2019). Factors and barriers influencing Lean Production System adoption in manufacturing industries. International Journal of Supply Chain Management, 8(2), 939-946. Erişim adresi: http://excelingtech.co.uk/
  • Chen, P.-K., Lujan-Blanco, I., Fortuny-Santos, J., ve Ruiz-de-Arbulo-López, P. (2020). Lean manufacturing and environmental sustainability: The effects of employee involvement, stakeholder pressure and ISO 14001. Sustainability, 12(18), 7258. Doi: https://doi.org/10.3390/su12187258
  • Dora, M., Kumar, M. ve Gellynck, X. (2016). Determinants and barriers to lean implementation in food-processing SMEs–a multiple case analysis. Production Planning & Control, 27(1), 1-23. Doi: https://doi.org/10.1080/09537287.2015.1050477
  • Ecer, F. (2022). Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer. Operational Research, 22(1), 199-233. Doi: https://doi.org/10.1007/s12351-020-00552-y
  • Ghorabaee, M. K. (2016). Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing, 37, 221-232. Doi: https://doi.org/10.1016/j.rcim.2015.04.007
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RISK ANALYSIS IN LEAN MANUFACTURING SYSTEMS: AN APPLICATION IN A CERAMICS COMPANY WITH THE FUZZY VIKOR METHOD

Yıl 2024, Cilt: 35 Sayı: 1, 61 - 91, 30.04.2024

Öz

The disappearance of trade borders causes market expansion and competition intensifies. The survival of institutions in global competition depends on offering quality products to customers at affordable prices. Increasing the profit of the institution while offering affordable prices to customers can only be achieved by reducing costs. Lean production technique, which increases efficiency and reduces costs by eliminating unnecessary resource use in production, emerges as a critical production tool. This study aims to identify the obstacles encountered during the implementation of lean production systems and observe their effects. The study deals with lean production systems in the facilities of a ceramic company in Bilecik and determines the risk factors and the importance weights of the factors with the collected data. Data is obtained from linguistic assessments based on employees' knowledge and experience. Trapezoidal spaced type-2 fuzzy sets based on fuzzy logic theory are used to reduce information loss in evaluations. Literature review and experience in the ceramics industry highlight ten critical risk factors in lean production systems. Trapezoidal type-2 fuzzy calculations of risk factors whose importance weights were evaluated linguistically by experts show that the ranking values of ten risk factors vary between 0.145-0.155 and there is no significant difference between the factors. This situation arises from the fact that 10 factors were selected as critical factors by preliminary evaluation among 23 factors. In order to explain the feasibility of the lean production system according to the compliance of operating conditions and employee acceptance with risk factors, an application study is carried out for three different facilities of the ceramic business. Facilities are evaluated linguistically according to risk factors, and the most suitable facility for the application of the lean production system is determined by the fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) decision-making method based on trapezoidal spaced type-2 fuzzy sets.

Kaynakça

  • Adalı, M. R. ve Erdem, H. (2017). Isıtma soğutma sistemleri üreten bir fabrikada yalın üretim araçları kullanılarak montaj hattı dengelenmesi. Endüstri Mühendisliği, 28(2), 19-32. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
  • Apak, S. (2022). Pandemi döneminde yalın üretim uygulamalarının önceliklendirilmesi: Otomotiv parçası üreticileri örneği. Endüstri Mühendisliği (TMMOB), 33(1), 62-74. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
  • Atmaca, E., Bulut, İ. ve Kalender, Y. (2023). Süreç iyileştirme: hizmet sektöründe bir uygulama. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 26(1), 1-16. Erişim Adresi: https://dergipark.org.tr/tr/pub/cuiibfd
  • Ayyildiz, E., Taskin Gumus, A. ve Erkan, M. (2020). Individual credit ranking by an integrated interval type-2 trapezoidal fuzzy Electre methodology. Soft Computing, 24, 16149-16163. Doi: https://doi.org/10.1007/s00500-020-04929-1
  • Bai, C., Satir, A., ve Sarkis, J. (2019). Investing in lean manufacturing practices: An environmental and operational perspective. International Journal of Production Research, 57(4), 1037-1051. Doi: https://doi.org/10.1080/00207543.2018.1498986
  • Basu, P., Chatterjee, D., Ghosh, I., ve Dan, P. K. (2021). Lean manufacturing implementation and performance: The role of economic volatility in an emerging economy. Journal of Manufacturing Technology Management, 32(6), 1188-1223. Doi: https://doi.org/10.1108/JMTM-12-2019-0455
  • Başak, E. E., Yılmaz, İ. S. ve Deniz, N. (2019). Endüstriyel ürün imalatı yapan bir işletmede yalın üretim uygulaması. Endüstri Mühendisliği, 30(3), 157-172. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
  • Becker, R. M. (1998). Lean manufacturing and the Toyota production system. Encyclopedia of world biography. Erişim adresi: http://vietnamsupplychain.com/
  • Bhadu, J., Singh, D. ve Bhamu, J. (2022). Analysis of lean implementation barriers in Indian ceramic industries: Modeling through an interpretive ranking process. International Journal of Productivity and Performance Management, 71(8), 3606-3635. Doi: https://doi.org/10.1108/IJPPM-10-2020-0540
  • Bhalaji, R., Bathrinath, S. ve Saravanasankar, S. (2021). A Fuzzy VIKOR method to analyze the risks in lean manufacturing implementation. Materials Today: Proceedings, 45, 1294-1299. Doi: https://doi.org/10.1016/ j.matpr.2020.05.123
  • Brauers, W. K., ve Zavadskas, E. K. (2009). Robustness of the multi‐objective MOORA method with a test for the facilities sector. Technological and Economic Development of Economy, 15(2), 352-375. Doi: https://doi.org/10.3846/1392-8619.2009.15.352-375
  • Brauers, W. K. M. (2013). Multi-objective seaport planning by MOORA decision making. Annals of Operations Research, 206, 39-58. Doi: https://doi.org/10.1007/s10479-013-1314-7
  • Castillo, O., Amador-Angulo, L., Castro, J. R. ve Garcia-Valdez, M. (2016). A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Information Sciences, 354, 257-274. Doi: https://doi.org/10.1016/j.ins.2016.03.026
  • Chan, S. W., Ismail, F., Ahmad, M., Zaman, I. ve Lim, H. Q. (2019). Factors and barriers influencing Lean Production System adoption in manufacturing industries. International Journal of Supply Chain Management, 8(2), 939-946. Erişim adresi: http://excelingtech.co.uk/
  • Chen, P.-K., Lujan-Blanco, I., Fortuny-Santos, J., ve Ruiz-de-Arbulo-López, P. (2020). Lean manufacturing and environmental sustainability: The effects of employee involvement, stakeholder pressure and ISO 14001. Sustainability, 12(18), 7258. Doi: https://doi.org/10.3390/su12187258
  • Dora, M., Kumar, M. ve Gellynck, X. (2016). Determinants and barriers to lean implementation in food-processing SMEs–a multiple case analysis. Production Planning & Control, 27(1), 1-23. Doi: https://doi.org/10.1080/09537287.2015.1050477
  • Ecer, F. (2022). Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer. Operational Research, 22(1), 199-233. Doi: https://doi.org/10.1007/s12351-020-00552-y
  • Ghorabaee, M. K. (2016). Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing, 37, 221-232. Doi: https://doi.org/10.1016/j.rcim.2015.04.007
  • Golec, A., ve Kahya, E. (2007). A fuzzy model for competency-based employee evaluation and selection. Computers and Industrial Engineering, 52(1), 143-161. Doi: https://doi.org/10.1016/j.cie.2006.11.004
  • Jadhav, J. R., Mantha, S. S. ve Rane, S. B. (2014). Exploring barriers in lean implementation. International Journal of Lean Six Sigma, 5(2), 122-148. Doi: https://doi.org/10.1108/IJLSS-12-2012-0014
  • Jing, S., Tang, Y. ve Yan, J. (2018). The application of fuzzy VIKOR for the design scheme selection in lean management. Mathematical Problems in Engineering, 2018. Doi: https://doi.org/10.1155/2018/9253643
  • Kahraman, C., Öztayşi, B., Sarı, İ. U. ve Turanoğlu, E. (2014). Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowledge-Based Systems, 59, 48-57. Doi: https://doi.org/10.1016/j.knosys.2014.02.001
  • Kalyar, M. N., Shafique, I., ve Abid, A. (2019). Role of lean manufacturing and environmental management practices in eliciting environmental and financial performance: The contingent effect of institutional pressures. Environmental Science and Pollution Research, 26, 24967-24978. Doi: https://doi.org/10.1007/s11356-019-05729-3
  • Ghorabaee, K. M., Amiri, M., Salehi Sadaghiani, J., ve Hassani Goodarzi, G. (2014). Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets. The International Journal of Advanced Manufacturing Technology, 75, 1115-1130. Doi: https://doi.org/10.1007/s00170-014-6142-7
  • Keykavoussi, A., ve Ebrahimi, A. (2020). Using fuzzy cost–time profile for effective implementation of lean programmes; SAIPA automotive manufacturer, case study. Total Quality Management and Business Excellence, 31(13-14), 1519-1543. Doi: https://doi.org/10.1080/14783363.2018.1490639
  • Lopez, L. M., Ishizaka, A., Qin, J., ve Alvarez-Carrillo, P. A. (2023). Multi-Criteria Decision-Making Sorting Methods: Applications to Real-World Problems. Academic Press.
  • Maghsoodi, A. I., Rasoulipanah, H., López, L. M., Liao, H., ve Zavadskas, E. K. (2020). Integrating interval-valued multi-granular 2-tuple linguistic BWM-CODAS approach with target-based attributes: Site selection for a construction project. Computers & Industrial Engineering, 139, 106147. Doi: https://doi.org/10.1016/j.cie.2019.106147
  • Mardani, A., Zavadskas, E. K., Govindan, K., Amat Senin, A. ve Jusoh, A. (2016). VIKOR technique: A systematic review of the state of the art literature on methodologies and applications. Sustainability, 8(1), 37. Doi: https://doi.org/10.3390/su8010037
  • Marodin, G. A. ve Saurin, T. A. (2015). Classification and relationships between risks that affect lean production implementation: A study in Southern Brazil. Journal of Manufacturing Technology Management, 26(1), 57-79. Doi: https://doi.org/10.1108/JMTM-12-2012-0113
  • Marodin, G., Frank, A. G., Tortorella, G. L., ve Netland, T. (2018). Lean product development and lean manufacturing: Testing moderation effects. International Journal of Production Economics, 203, 301-310. Doi: https://doi.org/10.1016/j.ijpe.2018.07.009
  • Mendel, J. M. (2007). Computing with words: Zadeh, turing, popper and occam. IEEE computational intelligence magazine, 2(4), 10-17. Doi: https://doi.org/10.1109/MCI.2007.9066897 Mendel, J. M. ve John, R. B. (2002). Type-2 fuzzy sets made simple. IEEE Transactions on Fuzzy Systems, 10(2), 117-127. Doi: https://doi.org/10.1109/91.995115
  • Ndahi, H. B. (2006). Lean manufacturing in a global and competitive market. Technology and Engineering Teacher, 66(3), 14. Erişim adresi: https://www.proquest.com/
  • Nordin, N., Md Deros, B. ve Abd Wahab, D. (2010). A survey on lean manufacturing implementation in Malaysian automotive industry. International Journal of Innovation, Management and Technology, 1(4), 374-380. Erişim adresi: http://www.ijimt.org/
  • Ohno, T. (1988). Toyota production system: Beyond large-scale production. CRC Press. Erişim adresi: http://www.taylorfrancis.com
  • Opricovic, S. (1998). Multicriteria optimization of civil engineering systems. Faculty of civil engineering, Belgrade, 2(1), 5-21.
  • Ovali, S. (2014). Küresel rekabet gücü açısından Türkiye’nin konumu üzerine bir değerlendirme. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 13, 17-36. Doi: https://doi.org/10.18092/ijeas.58881
  • Özmez, D. (2006). Bir Uretim Organizasyonu Olarak Yalın Uretim Sistemi (Doctoral dissertation, Bursa Uludag University (Turkey)). Erişim adresi: http://hdl.handle.net/11452/9214
  • Panwar, A., Jain, R., ve Rathore, A. (2015). Lean implementation in Indian process industries–some empirical evidence. Journal of Manufacturing Technology Management, 26(1), 131-160. Doi: https://doi.org/10.1108/JMTM-05-2013-0049
  • Prabowo, H. A., ve Adesta, E. Y. T. (2017). A study of total productive maintenance (TPM) and lean manufacturing tools and their impact on manufacturing performance. Economics, 1990, 1. Erişim adresi: https://www.ijrte.org
  • Qin, J., Liu, X. ve Pedrycz, W. (2015). An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowledge-Based Systems, 86, 116-130. Doi: https://doi.org/10.1016/j.knosys.2015.05.025
  • Ramadas, T., Satish, K., ve Mathew, K. A. (2018). A model to identify the factors of supplier communication and financial availability to support the lean manufacturing implementation in small and medium scale enterprises. International Journal of Services and Operations Management, 31(4), 480-493. Doi: https://doi.org/10.1504/IJSOM.2018.096169
  • Rubio, E., Castillo, O., Valdez, F., Melin, P., Gonzalez, C. I. ve Martinez, G. (2017). An extension of the fuzzy possibilistic clustering algorithm using type-2 fuzzy logic techniques. Advances in Fuzzy Systems, 2017. Doi: https://doi.org/10.1016/j.knosys.2015.05.025
  • Sahoo, S. (2020). Assessing lean implementation and benefits within Indian automotive component manufacturing SMEs. Benchmarking: An International Journal, 27(3), 1042-1084. Doi: https://doi.org/10.1108/BIJ-07-2019-0299
  • Salentijn, W., Beijer, S., ve Antony, J. (2021). Exploring the dark side of Lean: A systematic review of the lean factors that influence social outcomes. The TQM Journal, 33(6), 1469-1483. Doi: https://doi.org/10.1108/TQM-09-2020-0218
  • Samuel, D., Found, P. ve Williams, S. J. (2015). How did the publication of the book The Machine That Changed The World change management thinking? Exploring 25 years of lean literature. International Journal of Operations & Production Management, 35(10), 1386-1407. Doi: https://doi.org/10.1108/IJOPM-12-2013-0555
  • Shah, R., ve Ward, P. T. (2003). Lean manufacturing: Context, practice bundles, and performance. Journal of Operations Management, 21(2), 129-149. Doi: https://doi.org/10.1016/S0272-6963(02)00108-0
  • Singh, J., Singh, H., ve Singh, G. (2018). Productivity improvement using lean manufacturing in manufacturing industry of Northern India: A case study. International Journal of Productivity and Performance Management, 67(8), 1394-1415. Doi: https://doi.org/10.1108/IJPPM-02-2017-0037
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  • Tortorella, G. L., de Castro Fettermann, D., Frank, A. ve Marodin, G. (2018). Lean manufacturing implementation: Leadership styles and contextual variables. International Journal of Operations & Production Management. Doi: https://doi.org/10.1108/IJOPM-08-2016-0453
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  • Widiasih, W., Karningsih, P. D. ve Ciptomulyono, U. (2015). Development of integrated model for managing risk in lean manufacturing implementation: A case study in an Indonesian manufacturing company. Procedia Manufacturing, 4, 282-290. Doi: https://doi.org/10.1016/ j.promfg.2015.11.042
  • Wu, D. ve Mendel, J. M. (2007). Uncertainty measures for interval type-2 fuzzy sets. Information Sciences, 177(23), 5378-5393. Doi: https://doi.org/10.1016/j.ins.2007.07.012
  • Xu, Z. S. (2004). A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Information Sciences, 166(1-4), 19-30. Doi: https://doi.org/10.1016/j.ins.2003.10.006
  • Yalçın, S. E., Selin, A., ELMAS, B., Murat, E. ve Gündüz, T. (2020). Çeli̇k boru imalatinda hazirlik süreleri̇ne yöneli̇k yalin üreti̇m ve SMED çalişmasi. Endüstri Mühendisliği, 31(1), 87-104. Erişim adresi: https://dergipark.org.tr/en/pub/endustrimuhendisligi
  • Yildiz, A., Deveci, M. (2013). Bulanik VIKOR Yöntemine Dayali Personel Seçim Süreci/Based on Fuzzy VIKOR Approach to Personnel Selection Process. Ege Akademik Bakis, 13(4), 427. Erişim adresi: https://dergipark.org.tr/tr/pub/eab
  • Zadeh, L. A. ve Aliev, R. A. (2018). Fuzzy logic theory and applications: Part I and part II. World Scientific Publishing. Erişim adresi: https://www.worldscientific.com/
  • Zhang, Z., Zhang, S. (2013). A novel approach to multi attribute group decision making based on trapezoidal interval type-2 fuzzy soft sets. Applied Mathematical Modelling, 37(7), 4948-4971. Doi: https://doi.org/10.1016/j.apm.2012.10.006
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Endüstri Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Veysel Çoban 0000-0002-7885-1935

Güngör Çakır 0000-0002-4374-1971

Erken Görünüm Tarihi 21 Nisan 2024
Yayımlanma Tarihi 30 Nisan 2024
Gönderilme Tarihi 21 Kasım 2023
Kabul Tarihi 4 Nisan 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 35 Sayı: 1

Kaynak Göster

APA Çoban, V., & Çakır, G. (2024). YALIN ÜRETİM SİSTEMLERİNDE RİSK ANALİZİ: BULANIK VIKOR YÖNTEMİ İLE SERAMİK FİRMASINDA BİR UYGULAMA. Endüstri Mühendisliği, 35(1), 61-91.

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