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A Combined Fuzzy-QFD-BDANP Approach for Identifying Lean Wastes and Lean Practices

Year 2025, Issue: 85, 279 - 309, 20.07.2025
https://doi.org/10.51290/dpusbe.1688408

Abstract

Lean manufacturing is a management philosophy that aims to improve the performance of a business or production process by eliminating waste through globally recognized practices. This study aims to determine the priority types of waste encountered in the production process and the appropriate lean practices for eliminating these wastes. The study, which presents a hybrid model that takes into account the relationships between waste types and lean applications both among themselves and with each other, has integrated Quality Function Deployment (QFD), fuzzy numbers, DEMATEL, and Analytical Network Process (ANP) methods. According to the analysis results, which used the opinions of experts providing consultancy services on lean production as data, overstock is the most important type of waste; employee participation, kanban, and cellular manufacturing are critical lean practices in eliminating waste. While the study contributes to the literature by considering the type of waste of unused talent that has recently been identified, the hybrid approach that considers uncertainty and dependencies increases the study's importance in the relevant field.

References

  • Anggraini, W., Harpito, Siska, M. ., & Novitri, D. (2022). Implementation of lean construction to eliminate waste: a case study construction project in Indonesia. Jurnal Teknik Industri, 23(1), 1–16. doi: 10.22219/JTIUMM.Vol23.No1.1-16
  • Ayçin, E. (2019). Çok kriterli karar verme-bilgisayar uygulamalı çözümler. Ankara: Nobel Yayınevi.
  • Başkaya, Z. ve Öztürk, B. A. (2011). Bulanık analitik hiyerarşi süreci ile bir alışveriş merkezinde mağaza kuruluş yerinin seçimi. Yönetim ve Ekonomi Araştırmaları Dergisi, 9(15),110-133.
  • Belekoukias, I., Garza-Reyes, J. A., & Kumar, V. (2014). The impact of lean methods and tools on the operational performance of manufacturing organisations. International Journal of Production Research, 52(18), 5346-5366.
  • Bergmiller, G. G., & McCright, P. R. (2009, May). Parallel models for lean and green operations. Proceedings of the 2009 Industrial Engineering Research Conference içinde (Vol. 1, No. 1, s. 22-26). Tampa, FL, USA: University of South Florida and Zero Waste Operations Research and Consulting.
  • Bhasin, S. & Burcher, P. (2006). Lean viewed as a philosophy. Journal of Manufacturing Technology Management, 17(1), 56-72.
  • Bhuvanesh Kumar, M., & Parameshwaran, R. (2018). Fuzzy integrated QFD, FMEA framework for the selection of lean tools in a manufacturing organisation. Production Planning & Control, 29(5), 403–417. doi: 10.1080/09537287.2018.1434253.
  • Brito, M., Ramos, A.L., Carneiro, P & Gonçalves, M.A. (2019). The eighth waste: non-utilized talent. Lean Manufacturing: Implementation (Ed: F.J.G. Silva, L.C.P. Ferreira), Opportunities and Challenges, içinde (s. 151-163) New York: Nova Science Publishing.
  • Büyüközkan, G. & Çifçi, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164-174.
  • Caldera, S., Desha, C., & Dawes, L. (2019). Evaluating the enablers and barriers for successful implementation of sustainable business practice in 'lean' SMEs. Journal of Cleaner Production, 218, 575-590.
  • Chen, C. (2015). Construct a multi criteria decision making tool: DEMATEL and MMDE methods. International Journal of Decision Support System Technology (IJDSST), 7(4), 36-50. doi: 10.4018/IJDSST.2015100103
  • Choudhary, S., Nayak, R., Dora, M., Mishra, N., & Ghadge, A. (2019). An integrated lean and green approach for improving sustainability performance: a case study of a packaging manufacturing SME in the U.K. Production Planning & Control, 30(5–6), 353–368.
  • Çetindere Filiz A., Duran C., & Behdioğlu S. (2018). Just in Time (JIT) Production System. Özer Özçelik (Ed.), Studies on Interdisciplinary Economics and Business -Volume I içinde (s.85-99). Berlin: Peter Lang GmbH Internationaler Verlag der Wissenschaften.
  • Dara, H.M., Raut, A., Adamu, M., Ibrahim, Y.E. & Ingle, P.V. (2024). Reducing non-value added (NVA) activities through lean tools for the precast industry, Heliyon, 10, 7.
  • Devnath, A., Islam, M. S., Rashid, S., & Islam, E. (2020). An integrated QFD-TOPSIS method for prioritization of major lean tools: a case study. International Journal of Research in Industrial Engineering, 9(1), 65-76.
  • Dubey, H., Paharia A.K. & Joshi, C. (2017). Application of quality function deployment and lean to minimize industrial wastes. International Journal of Research in Management, 7(1), 15-35.
  • Duque, F.M.D. & Cadavid, L.R. (2007). Lean manufacturing measurement: the relationship between lean activities and lean metrics. Estudios gerenciales, 23(105), 69-83.
  • Elmalky, A., Mohamed, S. A., & Eldash, K. (2024). Impact of adopting lean principles on construction waste in developing countries. Engineering Research Journal (Shoubra), 53(2), 82-93.
  • Eroğlu, Ö. ve Gencer, C. (2021). Lojistik destek üssü yer seçiminde kriter ağırlıklarının bulanık DEMATEL yöntemi ile değerlendirilmesi. Kabak ve Erdebilli (Ed). Bulanık çok kriterli karar verme yöntemleri (s. 65-87), Ankara: Nobel Akademik Yayıncılık.
  • Eurofound (2015). Working conditions and sustainable work - How does employee involvement in decision-making benefit organisations?. https://www.eurofound.europa.eu/en/public ations/2020/how-does-employee-involvement-decision-making-benefit-organisations Erişim Tarihi: 18.04.2025
  • Farooq, M. U., Thaheem, M. J., & Arshad, H. (2018). Improving the risk quantification under behavioural tendencies: A tale of construction projects. International Journal of Project Management, 36(3), 414-428.
  • Gallup (2024). State of Globak Workplace. https://www.gallup.com/workplace /349484/state-of-the-global-workplace.aspx Erişim Tarihi: 15.03.2025
  • Gładysz, B., Buczacki, A., & Haskins, C. (2020). Lean management approach to reduce waste in Horeca food services. Resources, 9(12), 144.
  • Hatefi, S. M. & Tamošaitienė, J. (2019). An integrated fuzzy DEMATEL-fuzzy ANP model for evaluating construction projects by considering interrelationships among risk factors. Journal of Civil Engineering and Management, 25(2), 114-131.
  • Herat, A.T., Noorossana, R., Parsa, S., & Serkani, E.S. (2012). Using DEMATEL-Analytic network process (ANP) hybrid algorithm approach for selecting improvement projects of Iranian excellence model in healthcare sector. African Journal of Business Management, 6, 627-645.
  • Hilmola, O. (2020). Role of inventory and assets in shareholder value creation. Expert Systems with Applications, 5, 100027.
  • Hsu, C. H., Yu, R. Y., Chang, A. Y., Liu, W. L., & Sun, A. C. (2022). Applying integrated QFD-MCDM approach to strengthen supply chain agility for mitigating sustainable risks. Mathematics, 10(4), 552.
  • Jiang, P., Hu, Y. C., Yen, G. F., & Tsao, S. J. (2018). Green supplier selection for sustainable development of the automotive industry using grey decision‐making. Sustainable Development, 26(6), 890-903.
  • Kabak, M. ve Erdebilli, B. (2021). Bulanık çok kriterli karar verme yöntemleri - MS Excel ve software çözümlü uygulamalar (1. baskı), Ankara: Nobel Yayınevi.
  • Kecek, G. ve Akinci, Ö.C. (2016). Quality function deployment and an application in an insurance company. International Journal of Academic Research in Business and Social Sciences, 6(4), 111-135.
  • Kim, S. Y., Nguyen, M. V., & Dao, T. T. (2021). Prioritizing complexity using fuzzy DANP: Case study of international development projects. Engineering, Construction and Architectural Management, 28(4), 1114-1133.
  • Knapić, V., Rusjan, B. &Božič, K. (2023), Importance of first-line employees in lean implementation in SMEs: a systematic literature review. International Journal of Lean Six Sigma, 14(2), 277-308.
  • Knol, W. H., Lauche, K., Schouteten, R. L., & Slomp, J. (2022). Establishing the interplay between lean operating and continuous improvement routines: a process view. International Journal of Operations & Production Management, 42(13), 243-273.
  • Koca, G., Eğilmez, Ö., & Güler, S., (2021). Kayıt dışı istihdama neden olan faktörlerin DEMATEL tabanlı Analitik Ağ Süreci yöntemi ile değerlendirilmesi. Sosyoekonomi, 29(48), 249-270.
  • Lee, A. H., & Lin, C. Y. (2011). An integrated fuzzy QFD framework for new product development. Flexible Services and Manufacturing Journal, 23, 26-47.
  • Lee, Y. C., Zeng, P. S., Huang, C. H., & Wu, H. H. (2018). Causal relationship analysis of the patient safety culture based on safety attitudes questionnaire in Taiwan. Journal Of Healthcare Engineering, 2018(1), 4268781.
  • Leksic, I., Stefanic, N., & Veza, I. (2020). The impact of using different lean manufacturing tools on waste reduction. Advances in Production Engineering & Management, 15(1), 81-92.
  • Marin-Garcia, J. A., & Bonavia, T. (2014). Relationship between employee involvement and lean manufacturing and its effect on performance in a rigid continuous process industry. International Journal of Production Research, 53(11), 3260–3275.
  • Maxwell, J., Briscoe, F., Schenk, B., & Rothenberg, S. (1998). Case study: Honda of America Manufacturing, Inc.: Can lean production practices increase environmental performance? Environmental Quality Management, 8(1), 53-61.
  • Minh, N. D., Nguyen, N. D., & Cuong, P. K. (2019). Applying lean tools and principles to reduce cost of waste management: An empirical research in Vietnam. Management and Production Engineering Review, 10(1), 37-49.
  • Novirani, D., Zulkarnain, F. P., & Darrent, T. (2024). Application of lean manufacturing to minimize waste in the production process of tin stabilizer. In E3S Web of Conferences (Vol. 484, s. 01002). EDP Sciences.
  • Opricovic, S. & Tzeng, G.H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(05), 635-652.
  • Pavnaskar, S. J., Gershenson, J. K., & Jambekar, A. B. (2003). Classification scheme for lean manufacturing tools. International Journal of Production Research, 41(13), 3075-3090.
  • Popa, A.M. & Gupta, K. (2024). Using lean manufacturing to ımprove process efficiency in a fabrication company. Applied Engineering Letters, 9(3), 2024: 172-184.
  • Rahmanasari, D., Sutopo, W., & Rohani, J. M. (2021, March). Implementation of lean manufacturing process to reduce waste: a case study. In IOP Conference Series: Materials Science and Engineering (Vol. 1096, No. 1, s. 012006). IOP Publishing.
  • Ramesh, N., & Ravi, A. (2017). Determinants of total employee involvement: a case study of a cutting tool company. International Journal of Business Excellence, 11(2), 221-240.
  • Rawabdeh, I.A. (2011). Waste elimination using quality function deployment. International Journal of Services And Operations Management, 10(2), 216-238.
  • Rawabdeh, I.A. (2005). A model for the assessment of waste in job shop environments, International Journal of Operations & Production Management, 25(8), 800-822.
  • Reda, H., & Dvivedi, A. (2022). Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry. Expert Systems with Applications, 192, 116416.
  • Rewers P., Trojanowska J. & Chabowski P. (2016-June). Tools and methods of lean manufacturing-a literature review. Proceedings of 7th International Technical Conference Technologıcal Forum, Czech Republic.
  • Shams Bidhendi, S., Goh, S., & Wandel, A. (2018). A multi-objective methodology for selecting lean initiatives in modular construction companies. World Academy of Science, Engineering and Technology (Industrial and Manufacturing Engineering),12(9),1254.
  • Srdjevic, B., & Lakicevic, M. (2022). Causality and importance of sustainable forestry goals: Strategic and tactical assessment by DEMATEL and AHP. Forests, 14(1), 77.
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Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı

Year 2025, Issue: 85, 279 - 309, 20.07.2025
https://doi.org/10.51290/dpusbe.1688408

Abstract

Yalın üretim, tüm dünyada tanınan uygulamalar aracılığıyla israfları ortadan kaldırarak işletmenin veya üretim sürecinin performansını iyileştirmeyi hedefleyen bir yönetim felsefesidir. Bu çalışma, üretim sürecinde karşılaşılan öncelikli israf türlerinin ve bu israfların ortadan kaldırılması için uygun yalın uygulamaların belirlenmesini amaçlamaktadır. İsraf türlerinin ve yalın uygulamaların gerek kendi aralarında gerek birbirleriyle olan ilişkilerini dikkate alan bir hibrit modelin sunulduğu çalışmada; Kalite Fonksiyon Göçerimi (QFD), bulanık sayılar, DEMATEL ve Analitik Ağ Süreci (ANP) yöntemleri entegre edilmiştir. Yalın üretim konusunda danışmanlık hizmeti veren uzmanların görüşlerinin veri olarak kullanıldığı analiz sonuçlarına göre fazla stok bulundurmak en öncelikli israf türüyken; israfların ortadan kaldırılmasında; çalışan katılımı, kanban ve hücresel imalat önemli yalın uygulamalardır arasında yer almaktadır. Literatürde yenice yer bulan kullanılmayan yetenek israf türünün de dikkate alınmasıyla literatüre katkı sağlanırken; belirsizliğin ve bağımlılıkların hesaba katılması açısından sunulan hibrit yaklaşım; çalışmanın ilgili alandaki önemini artırmaktadır.

Ethical Statement

Etik kurul izni alınmıştır

Thanks

Araştırmaya katılmayı kabul ederek yalın israf ve yalın uygulamalar hakkında değerli görüşlerini paylaşan M. Biricik ve diğer yalın üretim danışmanlarına teşekkür ederim

References

  • Anggraini, W., Harpito, Siska, M. ., & Novitri, D. (2022). Implementation of lean construction to eliminate waste: a case study construction project in Indonesia. Jurnal Teknik Industri, 23(1), 1–16. doi: 10.22219/JTIUMM.Vol23.No1.1-16
  • Ayçin, E. (2019). Çok kriterli karar verme-bilgisayar uygulamalı çözümler. Ankara: Nobel Yayınevi.
  • Başkaya, Z. ve Öztürk, B. A. (2011). Bulanık analitik hiyerarşi süreci ile bir alışveriş merkezinde mağaza kuruluş yerinin seçimi. Yönetim ve Ekonomi Araştırmaları Dergisi, 9(15),110-133.
  • Belekoukias, I., Garza-Reyes, J. A., & Kumar, V. (2014). The impact of lean methods and tools on the operational performance of manufacturing organisations. International Journal of Production Research, 52(18), 5346-5366.
  • Bergmiller, G. G., & McCright, P. R. (2009, May). Parallel models for lean and green operations. Proceedings of the 2009 Industrial Engineering Research Conference içinde (Vol. 1, No. 1, s. 22-26). Tampa, FL, USA: University of South Florida and Zero Waste Operations Research and Consulting.
  • Bhasin, S. & Burcher, P. (2006). Lean viewed as a philosophy. Journal of Manufacturing Technology Management, 17(1), 56-72.
  • Bhuvanesh Kumar, M., & Parameshwaran, R. (2018). Fuzzy integrated QFD, FMEA framework for the selection of lean tools in a manufacturing organisation. Production Planning & Control, 29(5), 403–417. doi: 10.1080/09537287.2018.1434253.
  • Brito, M., Ramos, A.L., Carneiro, P & Gonçalves, M.A. (2019). The eighth waste: non-utilized talent. Lean Manufacturing: Implementation (Ed: F.J.G. Silva, L.C.P. Ferreira), Opportunities and Challenges, içinde (s. 151-163) New York: Nova Science Publishing.
  • Büyüközkan, G. & Çifçi, G. (2011). A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62(2), 164-174.
  • Caldera, S., Desha, C., & Dawes, L. (2019). Evaluating the enablers and barriers for successful implementation of sustainable business practice in 'lean' SMEs. Journal of Cleaner Production, 218, 575-590.
  • Chen, C. (2015). Construct a multi criteria decision making tool: DEMATEL and MMDE methods. International Journal of Decision Support System Technology (IJDSST), 7(4), 36-50. doi: 10.4018/IJDSST.2015100103
  • Choudhary, S., Nayak, R., Dora, M., Mishra, N., & Ghadge, A. (2019). An integrated lean and green approach for improving sustainability performance: a case study of a packaging manufacturing SME in the U.K. Production Planning & Control, 30(5–6), 353–368.
  • Çetindere Filiz A., Duran C., & Behdioğlu S. (2018). Just in Time (JIT) Production System. Özer Özçelik (Ed.), Studies on Interdisciplinary Economics and Business -Volume I içinde (s.85-99). Berlin: Peter Lang GmbH Internationaler Verlag der Wissenschaften.
  • Dara, H.M., Raut, A., Adamu, M., Ibrahim, Y.E. & Ingle, P.V. (2024). Reducing non-value added (NVA) activities through lean tools for the precast industry, Heliyon, 10, 7.
  • Devnath, A., Islam, M. S., Rashid, S., & Islam, E. (2020). An integrated QFD-TOPSIS method for prioritization of major lean tools: a case study. International Journal of Research in Industrial Engineering, 9(1), 65-76.
  • Dubey, H., Paharia A.K. & Joshi, C. (2017). Application of quality function deployment and lean to minimize industrial wastes. International Journal of Research in Management, 7(1), 15-35.
  • Duque, F.M.D. & Cadavid, L.R. (2007). Lean manufacturing measurement: the relationship between lean activities and lean metrics. Estudios gerenciales, 23(105), 69-83.
  • Elmalky, A., Mohamed, S. A., & Eldash, K. (2024). Impact of adopting lean principles on construction waste in developing countries. Engineering Research Journal (Shoubra), 53(2), 82-93.
  • Eroğlu, Ö. ve Gencer, C. (2021). Lojistik destek üssü yer seçiminde kriter ağırlıklarının bulanık DEMATEL yöntemi ile değerlendirilmesi. Kabak ve Erdebilli (Ed). Bulanık çok kriterli karar verme yöntemleri (s. 65-87), Ankara: Nobel Akademik Yayıncılık.
  • Eurofound (2015). Working conditions and sustainable work - How does employee involvement in decision-making benefit organisations?. https://www.eurofound.europa.eu/en/public ations/2020/how-does-employee-involvement-decision-making-benefit-organisations Erişim Tarihi: 18.04.2025
  • Farooq, M. U., Thaheem, M. J., & Arshad, H. (2018). Improving the risk quantification under behavioural tendencies: A tale of construction projects. International Journal of Project Management, 36(3), 414-428.
  • Gallup (2024). State of Globak Workplace. https://www.gallup.com/workplace /349484/state-of-the-global-workplace.aspx Erişim Tarihi: 15.03.2025
  • Gładysz, B., Buczacki, A., & Haskins, C. (2020). Lean management approach to reduce waste in Horeca food services. Resources, 9(12), 144.
  • Hatefi, S. M. & Tamošaitienė, J. (2019). An integrated fuzzy DEMATEL-fuzzy ANP model for evaluating construction projects by considering interrelationships among risk factors. Journal of Civil Engineering and Management, 25(2), 114-131.
  • Herat, A.T., Noorossana, R., Parsa, S., & Serkani, E.S. (2012). Using DEMATEL-Analytic network process (ANP) hybrid algorithm approach for selecting improvement projects of Iranian excellence model in healthcare sector. African Journal of Business Management, 6, 627-645.
  • Hilmola, O. (2020). Role of inventory and assets in shareholder value creation. Expert Systems with Applications, 5, 100027.
  • Hsu, C. H., Yu, R. Y., Chang, A. Y., Liu, W. L., & Sun, A. C. (2022). Applying integrated QFD-MCDM approach to strengthen supply chain agility for mitigating sustainable risks. Mathematics, 10(4), 552.
  • Jiang, P., Hu, Y. C., Yen, G. F., & Tsao, S. J. (2018). Green supplier selection for sustainable development of the automotive industry using grey decision‐making. Sustainable Development, 26(6), 890-903.
  • Kabak, M. ve Erdebilli, B. (2021). Bulanık çok kriterli karar verme yöntemleri - MS Excel ve software çözümlü uygulamalar (1. baskı), Ankara: Nobel Yayınevi.
  • Kecek, G. ve Akinci, Ö.C. (2016). Quality function deployment and an application in an insurance company. International Journal of Academic Research in Business and Social Sciences, 6(4), 111-135.
  • Kim, S. Y., Nguyen, M. V., & Dao, T. T. (2021). Prioritizing complexity using fuzzy DANP: Case study of international development projects. Engineering, Construction and Architectural Management, 28(4), 1114-1133.
  • Knapić, V., Rusjan, B. &Božič, K. (2023), Importance of first-line employees in lean implementation in SMEs: a systematic literature review. International Journal of Lean Six Sigma, 14(2), 277-308.
  • Knol, W. H., Lauche, K., Schouteten, R. L., & Slomp, J. (2022). Establishing the interplay between lean operating and continuous improvement routines: a process view. International Journal of Operations & Production Management, 42(13), 243-273.
  • Koca, G., Eğilmez, Ö., & Güler, S., (2021). Kayıt dışı istihdama neden olan faktörlerin DEMATEL tabanlı Analitik Ağ Süreci yöntemi ile değerlendirilmesi. Sosyoekonomi, 29(48), 249-270.
  • Lee, A. H., & Lin, C. Y. (2011). An integrated fuzzy QFD framework for new product development. Flexible Services and Manufacturing Journal, 23, 26-47.
  • Lee, Y. C., Zeng, P. S., Huang, C. H., & Wu, H. H. (2018). Causal relationship analysis of the patient safety culture based on safety attitudes questionnaire in Taiwan. Journal Of Healthcare Engineering, 2018(1), 4268781.
  • Leksic, I., Stefanic, N., & Veza, I. (2020). The impact of using different lean manufacturing tools on waste reduction. Advances in Production Engineering & Management, 15(1), 81-92.
  • Marin-Garcia, J. A., & Bonavia, T. (2014). Relationship between employee involvement and lean manufacturing and its effect on performance in a rigid continuous process industry. International Journal of Production Research, 53(11), 3260–3275.
  • Maxwell, J., Briscoe, F., Schenk, B., & Rothenberg, S. (1998). Case study: Honda of America Manufacturing, Inc.: Can lean production practices increase environmental performance? Environmental Quality Management, 8(1), 53-61.
  • Minh, N. D., Nguyen, N. D., & Cuong, P. K. (2019). Applying lean tools and principles to reduce cost of waste management: An empirical research in Vietnam. Management and Production Engineering Review, 10(1), 37-49.
  • Novirani, D., Zulkarnain, F. P., & Darrent, T. (2024). Application of lean manufacturing to minimize waste in the production process of tin stabilizer. In E3S Web of Conferences (Vol. 484, s. 01002). EDP Sciences.
  • Opricovic, S. & Tzeng, G.H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(05), 635-652.
  • Pavnaskar, S. J., Gershenson, J. K., & Jambekar, A. B. (2003). Classification scheme for lean manufacturing tools. International Journal of Production Research, 41(13), 3075-3090.
  • Popa, A.M. & Gupta, K. (2024). Using lean manufacturing to ımprove process efficiency in a fabrication company. Applied Engineering Letters, 9(3), 2024: 172-184.
  • Rahmanasari, D., Sutopo, W., & Rohani, J. M. (2021, March). Implementation of lean manufacturing process to reduce waste: a case study. In IOP Conference Series: Materials Science and Engineering (Vol. 1096, No. 1, s. 012006). IOP Publishing.
  • Ramesh, N., & Ravi, A. (2017). Determinants of total employee involvement: a case study of a cutting tool company. International Journal of Business Excellence, 11(2), 221-240.
  • Rawabdeh, I.A. (2011). Waste elimination using quality function deployment. International Journal of Services And Operations Management, 10(2), 216-238.
  • Rawabdeh, I.A. (2005). A model for the assessment of waste in job shop environments, International Journal of Operations & Production Management, 25(8), 800-822.
  • Reda, H., & Dvivedi, A. (2022). Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry. Expert Systems with Applications, 192, 116416.
  • Rewers P., Trojanowska J. & Chabowski P. (2016-June). Tools and methods of lean manufacturing-a literature review. Proceedings of 7th International Technical Conference Technologıcal Forum, Czech Republic.
  • Shams Bidhendi, S., Goh, S., & Wandel, A. (2018). A multi-objective methodology for selecting lean initiatives in modular construction companies. World Academy of Science, Engineering and Technology (Industrial and Manufacturing Engineering),12(9),1254.
  • Srdjevic, B., & Lakicevic, M. (2022). Causality and importance of sustainable forestry goals: Strategic and tactical assessment by DEMATEL and AHP. Forests, 14(1), 77.
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There are 62 citations in total.

Details

Primary Language Turkish
Subjects Production and Operations Management
Journal Section Research Article
Authors

Esra Yıldırım Söylemez 0000-0003-4690-9298

Submission Date May 1, 2025
Acceptance Date July 17, 2025
Publication Date July 20, 2025
Published in Issue Year 2025 Issue: 85

Cite

APA Yıldırım Söylemez, E. (2025). Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi(85), 279-309. https://doi.org/10.51290/dpusbe.1688408
AMA Yıldırım Söylemez E. Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. July 2025;(85):279-309. doi:10.51290/dpusbe.1688408
Chicago Yıldırım Söylemez, Esra. “Yalın İsraflar Ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 85 (July 2025): 279-309. https://doi.org/10.51290/dpusbe.1688408.
EndNote Yıldırım Söylemez E (July 1, 2025) Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 85 279–309.
IEEE E. Yıldırım Söylemez, “Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 85, pp. 279–309, July2025, doi: 10.51290/dpusbe.1688408.
ISNAD Yıldırım Söylemez, Esra. “Yalın İsraflar Ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 85 (July2025), 279-309. https://doi.org/10.51290/dpusbe.1688408.
JAMA Yıldırım Söylemez E. Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2025;:279–309.
MLA Yıldırım Söylemez, Esra. “Yalın İsraflar Ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 85, 2025, pp. 279-0, doi:10.51290/dpusbe.1688408.
Vancouver Yıldırım Söylemez E. Yalın İsraflar ve Yalın Uygulamaların Belirlenmesi İçin Birleştirilmiş Bir Bulanık-QFD-BDANP Yaklaşımı. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2025(85):279-30.