Araştırma Makalesi
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Selection of Industrial Machinery for Sustainable Production in Footwear Manufacturing: An Integrated Approach Based on SWARA and Fuzzy VIKOR

Yıl 2026, Cilt: 40 Sayı: 1, 27 - 41, 01.01.2026
https://doi.org/10.16951/trendbusecon.1597767

Öz

The global footwear industry faces increasing pressure to adopt sustainable manufacturing practices while maintaining competitiveness. This study develops an integrated decision framework for selecting optimal production machinery in footwear manufacturing, addressing critical challenges in production efficiency, energy saving, and quality optimization. Due to limited systematic approaches for footwear production equipment selection in literature, the research evaluates five advanced manufacturing technologies (automated cutting, robotik assembly, 3D printing, intelligent sewing, and automated quality control systems) across 11 strategic criteria. While the SWARA method determines criteria weights, Fuzzy VIKOR ranks alternatives under uncertainty. The results, validated by high expert consistency (Kendall's W= 0.95) and sensitivity analyses, demonstrate that automated cutting technology offers the best cost-performance trade-off. The findings contribute to the technological transformation of footwear production and provide a systematic approach for sustainable production capacity development. This methodology offers practical implications for manufacturers seeking to increase competitive advantages through strategic equipment investment decisions.

Kaynakça

  • Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods. Engineering Economics, 24(1), 5-17. [CrossRef]
  • Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533-548. [CrossRef]
  • Anojkumar, L., Ilangkumaran, M., & Sasirekha, V. (2014). Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, 41(6), 2964-2980. [CrossRef]
  • Barbe, P., Genest, C., Ghoudi, K., & Rémillard, B. (1996). On Kendall's process. Journal of Multivariate Analysis, 58(2), 197-229. [CrossRef]
  • Chatterjee, S., & Chakraborty, S. (2023, June). 3D printing machine selection using novel integrated MEREC-MCRAT MCDM method. In AIP Conference Proceedings (Vol. 2786, No. 1). AIP Publishing. [CrossRef]
  • Duan, Y., Stević, Ž., Novarlić, B., Hashemkhani Zolfani, S., Görçün, Ö. F., & Subotić, M. (2025). Application of the Fuzzy MCDM Model for the Selection of a Multifunctional Machine for Sustainable Waste Management. Sustainability, 17(6), 2723. [CrossRef]
  • Emovon, I., Norman, R. A., & Murphy, A. J. (2018). Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems. Journal of Intelligent Manufacturing, 29(3), 519-531. [CrossRef]
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J. (2018). A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering, 18(1), 32-49. [CrossRef]
  • Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making. International Journal of Computers Communications & Control, 11(3), 358-371. [CrossRef]
  • Głuszek, E. (2021). Use of the e-Delphi method to validate the corporate reputation management maturity model (CR3M). Sustainability, 13(21), 12019. [CrossRef]
  • Hagag, A. M., Yousef, L. S., & Abdelmaguid, T. F. (2023). Multi-criteria decision-making for machine selection in manufacturing and construction: Recent trends. Mathematics, 11(3), 631. [CrossRef]
  • Hagag, A. M., Yousef, L. S., & Abdelmaguid, T. F. (2023). Multi-criteria decision-making for machine selection in manufacturing and construction: Recent trends. Mathematics, 11(2), 432. [CrossRef]
  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. [CrossRef]
  • Li, H., Wang, W., Fan, L., Li, Q., & Chen, X. (2020). A novel hybrid MCDM model for machine tool selection using fuzzy DEMATEL, entropy weighting and later defuzzification VIKOR. Applied Soft Computing, 91, 106207. [CrossRef]
  • Mardani, A., Zavadskas, E. K., Govindan, K., Senin, A. A., & Jusoh, A. (2016). VIKOR technique: A systematic review of the state of the art literature on methodologies and applications. Sustainability, 8(1), 37. [CrossRef]
  • Mishra, D., & Satapathy, S. (2023). Reliability and maintenance of agricultural machinery by MCDM approach. International Journal of System Assurance Engineering and Management, 14(1), 135-146. [CrossRef]
  • Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253. [CrossRef]
  • Nguyen, H. T., Dawal, S. Z. M., Nukman, Y., & Aoyama, H. (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes. Expert Systems with Applications, 41(6), 3078-3090. [CrossRef]
  • Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990. [CrossRef]
  • Önüt, S., Kara, S. S., & Efendigil, T. (2008). A hybrid fuzzy MCDM approach to machine tool selection. Journal of Intelligent Manufacturing, 19(4), 443-453. [CrossRef]
  • Raja, S., & Rajan, A. J. (2022). A decision‐making model for selection of the suitable FDM machine using fuzzy TOPSIS. Mathematical Problems in Engineering, 2022(1), 7653292. [CrossRef]
  • Rani, P., Mishra, A. R., Mardani, A., Cavallaro, F., Alrasheedi, M., & Alrashidi, A. (2020). Pythagorean fuzzy SWARA--VIKOR framework for performance evaluation of solar panel selection. Sustainability, 12(10), 4278. [CrossRef]
  • Savkovic, S., Jovancic, P., Djenadic, S., Tanasijevic, M., & Miletic, F. (2022). Development of the hybrid MCDM model for evaluating and selecting bucket wheel excavators for the modernization process. Expert Systems with Applications, 201, 117199. [CrossRef]
  • Štirbanović, Z., Stanujkić, D., Miljanović, I., & Milanović, D. (2019). Application of MCDM methods for flotation machine selection. Minerals Engineering, 137, 140-146. [CrossRef]
  • Tran, N. T., Trinh, V. L., Nguyen, T. S., & Tran, V. H. (2025). A Hybrid Triangular Fuzzy MCDM Model for Evaluating and Selecting the Optimal Industrial Robot for Manufacturing Plants based on Fuzzy AHP and Fuzzy ARAS. Engineering, Technology & Applied Science Research, 15(4), 24270-24276. [CrossRef]
  • Van Dua, T., Van Duc, D., Bao, N. C., & Trung, D. D. (2024). Integration of objective weighting methods for criteria and MCDM methods: application in material selection. EUREKA: Physics and Engineering, (2), 131-148. [CrossRef]
  • Wang, C. N., Yang, F. C., Vo, T. M. N., Nguyen, V. T., & Singh, M. (2023). Enhancing efficiency and cost-effectiveness: A groundbreaking bi-algorithm MCDM approach. Applied Sciences, 13(2), 908. [CrossRef]
  • Yin, R., Ab Rahman, M. N., Hishamuddin, H., & Ikram, M. (2024). Assessing Machine Tool Selection Process in Sustainable Production to Address Climate Change Based on Hybrid MCDM Methods. Engineering Journal, 28(1), 1-14. [CrossRef]
  • Yücenur, G. N., & Şenol, M. B. (2021). Sequential SWARA and fuzzy VIKOR methods in elimination of waste and creation of lean construction processes. Journal of Building Engineering, 44, 102636. [CrossRef]
  • Zhang, W. ve Li X. (2015). General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures. Network Biology, 5(4), 163-174. [CrossRef]
  • Zolfani, S. H., & Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Engineering Economics, 24(5), 408-414. [CrossRef]

Ayakkabı İmalatında Sürdürülebilir Üretim için Endüstriyel Makine Seçimi: SWARA ve Bulanık VIKOR Temelli Bütünleşik Bir Yaklaşım

Yıl 2026, Cilt: 40 Sayı: 1, 27 - 41, 01.01.2026
https://doi.org/10.16951/trendbusecon.1597767

Öz

Küresel ayakkabı endüstrisi, rekabet gücünü korurken sürdürülebilir üretim uygulamalarını benimseme konusunda artan baskıyla karşı karşıyadır. Bu çalışma, üretim verimliliği, enerji tasarrufu ve kalite optimizasyonundaki kritik zorlukları ele alarak, ayakkabı üretiminde en uygun üretim makinelerini seçmek için entegre bir karar çerçevesi geliştirmiştir. Literatürde ayakkabı üretim ekipmanı seçimine yönelik sistematik yaklaşımların sınırlı olması nedeniyle, araştırma beş gelişmiş üretim teknolojisini (otomatik kesim, robotik montaj, 3D baskı, akıllı dikiş ve otomatik kalite kontrol sistemleri) 11 stratejik kriter üzerinden değerlendirmektedir. SWARA yöntemi kriter ağırlıklarını belirlerken, Bulanık VIKOR belirsizlik altında alternatifleri sıralamaktadır. Uzman görüşlerinin yüksek tutarlılığı (Kendall W= 0.95) ve duyarlılık analizleri ile doğrulanan sonuçlar, otomatik kesim teknolojisinin en uygun maliyet-performans dengesini sunduğunu göstermektedir. Bulgular, ayakkabı üretiminin teknolojik dönüşümüne katkıda bulunmakta ve sürdürülebilir üretim kapasitesi gelişimi için sistematik bir yaklaşım sağlamaktadır. Bu metodoloji, stratejik ekipman yatırım kararları yoluyla rekabet avantajlarını artırmak isteyen üreticiler için pratik çıkarımlar sunmaktadır.

Kaynakça

  • Aghdaie, M. H., Zolfani, S. H., & Zavadskas, E. K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods. Engineering Economics, 24(1), 5-17. [CrossRef]
  • Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533-548. [CrossRef]
  • Anojkumar, L., Ilangkumaran, M., & Sasirekha, V. (2014). Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, 41(6), 2964-2980. [CrossRef]
  • Barbe, P., Genest, C., Ghoudi, K., & Rémillard, B. (1996). On Kendall's process. Journal of Multivariate Analysis, 58(2), 197-229. [CrossRef]
  • Chatterjee, S., & Chakraborty, S. (2023, June). 3D printing machine selection using novel integrated MEREC-MCRAT MCDM method. In AIP Conference Proceedings (Vol. 2786, No. 1). AIP Publishing. [CrossRef]
  • Duan, Y., Stević, Ž., Novarlić, B., Hashemkhani Zolfani, S., Görçün, Ö. F., & Subotić, M. (2025). Application of the Fuzzy MCDM Model for the Selection of a Multifunctional Machine for Sustainable Waste Management. Sustainability, 17(6), 2723. [CrossRef]
  • Emovon, I., Norman, R. A., & Murphy, A. J. (2018). Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems. Journal of Intelligent Manufacturing, 29(3), 519-531. [CrossRef]
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J. (2018). A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering, 18(1), 32-49. [CrossRef]
  • Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making. International Journal of Computers Communications & Control, 11(3), 358-371. [CrossRef]
  • Głuszek, E. (2021). Use of the e-Delphi method to validate the corporate reputation management maturity model (CR3M). Sustainability, 13(21), 12019. [CrossRef]
  • Hagag, A. M., Yousef, L. S., & Abdelmaguid, T. F. (2023). Multi-criteria decision-making for machine selection in manufacturing and construction: Recent trends. Mathematics, 11(3), 631. [CrossRef]
  • Hagag, A. M., Yousef, L. S., & Abdelmaguid, T. F. (2023). Multi-criteria decision-making for machine selection in manufacturing and construction: Recent trends. Mathematics, 11(2), 432. [CrossRef]
  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. [CrossRef]
  • Li, H., Wang, W., Fan, L., Li, Q., & Chen, X. (2020). A novel hybrid MCDM model for machine tool selection using fuzzy DEMATEL, entropy weighting and later defuzzification VIKOR. Applied Soft Computing, 91, 106207. [CrossRef]
  • Mardani, A., Zavadskas, E. K., Govindan, K., Senin, A. A., & Jusoh, A. (2016). VIKOR technique: A systematic review of the state of the art literature on methodologies and applications. Sustainability, 8(1), 37. [CrossRef]
  • Mishra, D., & Satapathy, S. (2023). Reliability and maintenance of agricultural machinery by MCDM approach. International Journal of System Assurance Engineering and Management, 14(1), 135-146. [CrossRef]
  • Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253. [CrossRef]
  • Nguyen, H. T., Dawal, S. Z. M., Nukman, Y., & Aoyama, H. (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes. Expert Systems with Applications, 41(6), 3078-3090. [CrossRef]
  • Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990. [CrossRef]
  • Önüt, S., Kara, S. S., & Efendigil, T. (2008). A hybrid fuzzy MCDM approach to machine tool selection. Journal of Intelligent Manufacturing, 19(4), 443-453. [CrossRef]
  • Raja, S., & Rajan, A. J. (2022). A decision‐making model for selection of the suitable FDM machine using fuzzy TOPSIS. Mathematical Problems in Engineering, 2022(1), 7653292. [CrossRef]
  • Rani, P., Mishra, A. R., Mardani, A., Cavallaro, F., Alrasheedi, M., & Alrashidi, A. (2020). Pythagorean fuzzy SWARA--VIKOR framework for performance evaluation of solar panel selection. Sustainability, 12(10), 4278. [CrossRef]
  • Savkovic, S., Jovancic, P., Djenadic, S., Tanasijevic, M., & Miletic, F. (2022). Development of the hybrid MCDM model for evaluating and selecting bucket wheel excavators for the modernization process. Expert Systems with Applications, 201, 117199. [CrossRef]
  • Štirbanović, Z., Stanujkić, D., Miljanović, I., & Milanović, D. (2019). Application of MCDM methods for flotation machine selection. Minerals Engineering, 137, 140-146. [CrossRef]
  • Tran, N. T., Trinh, V. L., Nguyen, T. S., & Tran, V. H. (2025). A Hybrid Triangular Fuzzy MCDM Model for Evaluating and Selecting the Optimal Industrial Robot for Manufacturing Plants based on Fuzzy AHP and Fuzzy ARAS. Engineering, Technology & Applied Science Research, 15(4), 24270-24276. [CrossRef]
  • Van Dua, T., Van Duc, D., Bao, N. C., & Trung, D. D. (2024). Integration of objective weighting methods for criteria and MCDM methods: application in material selection. EUREKA: Physics and Engineering, (2), 131-148. [CrossRef]
  • Wang, C. N., Yang, F. C., Vo, T. M. N., Nguyen, V. T., & Singh, M. (2023). Enhancing efficiency and cost-effectiveness: A groundbreaking bi-algorithm MCDM approach. Applied Sciences, 13(2), 908. [CrossRef]
  • Yin, R., Ab Rahman, M. N., Hishamuddin, H., & Ikram, M. (2024). Assessing Machine Tool Selection Process in Sustainable Production to Address Climate Change Based on Hybrid MCDM Methods. Engineering Journal, 28(1), 1-14. [CrossRef]
  • Yücenur, G. N., & Şenol, M. B. (2021). Sequential SWARA and fuzzy VIKOR methods in elimination of waste and creation of lean construction processes. Journal of Building Engineering, 44, 102636. [CrossRef]
  • Zhang, W. ve Li X. (2015). General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures. Network Biology, 5(4), 163-174. [CrossRef]
  • Zolfani, S. H., & Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Engineering Economics, 24(5), 408-414. [CrossRef]
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Planlama ve Karar Verme, Üretim ve Operasyon Yönetimi
Bölüm Araştırma Makalesi
Yazarlar

Çağdaş Yildiz 0009-0006-8384-2466

Gönderilme Tarihi 7 Aralık 2024
Kabul Tarihi 9 Ekim 2025
Yayımlanma Tarihi 1 Ocak 2026
Yayımlandığı Sayı Yıl 2026 Cilt: 40 Sayı: 1

Kaynak Göster

APA Yildiz, Ç. (2026). Ayakkabı İmalatında Sürdürülebilir Üretim için Endüstriyel Makine Seçimi: SWARA ve Bulanık VIKOR Temelli Bütünleşik Bir Yaklaşım. Trends in Business and Economics, 40(1), 27-41. https://doi.org/10.16951/trendbusecon.1597767

Content of this journal is licensed under a Creative Commons Attribution 4.0 International License

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