ENDÜSTRİYEL ENERJİ VERİMLİLİĞİ TEKNİKLERİNİN COPRAS TABANLI ÇOK KRİTERLİ ANALİZİ: TEKSTİL ENDÜSTRİSİ ÖRNEĞİ

Abstract

Endüstriyel temiz üretim uygulamalarında karşılaşılan temel sorunlardan biri, işletmeler için en uygun tekniğin belirlenmesidir. Bu çalışma, entegre bir tekstil işletmesinde enerji verimliliği tekniklerinin seçimine yönelik yeni bir yaklaşım sunmakta ve karar verme aracı olarak “Karmaşık Oransal Değerlendirme (COPRAS)” yöntemini kullanmaktadır. Çalışmanın yürütüldüğü tesis; eski ve yeni tekstil teknolojilerini bir arada barındırması, büyük ölçekli bir baskı ünitesine sahip olması ve Avrupa’nın önemli ev tekstili üreticilerinden biri olması nedeniyle seçilmiştir. İşletmede ayrıntılı enerji verimliliği etütleri gerçekleştirilmiş, elde edilen bulgular doğrultusunda “mevcut en iyi teknikler (MET/BAT)” kapsamında kapsamlı bir iyileştirme listesi oluşturulmuştur. COPRAS değerlendirmesi sonucunda yedi tekniğin öncelikli olduğu belirlenmiştir: ramözlerde kumaş neminin izlenmesi ve hız optimizasyonu, ramözlerde devridaim havası kontrolü, terbiye proseslerinin optimizasyonu, klima ve nemlendirme sisteminin iyileştirilmesi, iç aydınlatma optimizasyonu, enerji izleme sisteminin kurulması ve boru/vana/tank izolasyonu. Bu tekniklerin uygulanmasıyla elektrik, buhar, doğal gaz ve hava emisyonlarında sırasıyla %2,2–3,5, %0,5–1,5, %6,3–13,5 ve %8–16,5 azalma potansiyeli hesaplanmıştır. Ayrıca tüm tekniklerin geri ödeme süresi 40 ayın altında bulunmuştur. Sonuç olarak COPRAS modeli, tekstil sektöründe uygun enerji verimliliği tekniklerinin belirlenmesinde etkili bir yol haritası sunmaktadır.

Keywords

• COPRAS
• Enerji verimliliği
• Mevcut en iyi teknikler (MET’ler)
• Tekstil
• Temiz üretim.

Supporting Institution

TÜBİTAK, YÖK, SDÜ BAP

Project Number

Proje No: 3170583

Ethical Statement

Hazırlanan makalede etik kurul izni alınmasına gerek yoktur.

Thanks

Bu çalışma, “Entegre bir tekstil tesisinde temiz üretim yaklaşımıyla kaynak verimliliğini ve çevresel performansı iyileştirmeye yönelik Mevcut En İyi Tekniklerin (MET) Geliştirilmesi” başlıklı projenin bir bölümünü oluşturacak şekilde yürütülmüştür. Proje, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) tarafından TEYDEB Projesi (Proje No: 3170583) kapsamında desteklenmiştir. Yazarlar, çalışma süresince sundukları desteklerden dolayı ZORLUTEKS Tekstil firması (Türkiye) Ar-Ge departmanı çalışanlarına ve Murat Yıldırım’a teşekkür eder. Elif Şimşek Yeşil, Yükseköğretim Kurulu (YÖK) 100/2000 Doktora Programı ile TÜBİTAK 2211/A Yurt İçi Genel Doktora Burs Programı kapsamında “Sürdürülebilir Su Kaynakları” tematik alanında doktora çalışmalarını yürütmüş ve bu programlar tarafından desteklenmiştir. Bu çalışma ayrıca Süleyman Demirel Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi (SDÜ BAP, Proje No: FDK-2022-8638) ve YÖK 100/2000 Doktora Programı tarafından mali olarak desteklenmiştir. Yazarlar, destekleri için SDÜ BAP Birimine, YÖK’e ve TÜBİTAK’a teşekkür eder.

COPRAS BASED MULTI-CRITERIA ANALYSIS OF INDUSTRIAL ENERGY EFFICIENCY TECHNIQUES: THE TEXTILE INDUSTRY EXAMPLE

Abstract

One of the main challenges in industrial cleaner production practices is determining the most appropriate technique for a facility. This study presents a new approach for selecting energy efficiency techniques in an integrated textile plant and employs the “Complex Proportional Assessment (COPRAS)” method as a decision-making tool. The facility was selected because it incorporates both old and modern textile technologies, includes a large-scale printing unit, and is one of Europe’s prominent home textile manufacturers. Detailed energy efficiency audits were carried out in the plant, and based on the findings, a comprehensive improvement list was prepared within the scope of “Best Available Techniques (BAT)”. The COPRAS evaluation identified seven priority techniques: monitoring fabric moisture and optimizing speed in stenters, controlling stenter recirculation air, optimizing finishing processes, improving the air-conditioning and humidification system, optimizing indoor lighting, installing an energy monitoring system, and insulating pipes/valves/tanks. Application of these techniques offers reduction potentials of 2.2–3.5% for electricity, 0.5–1.5% for steam, 6.3–13.5% for natural gas, and 8–16.5% for air emissions. Additionally, all prioritized techniques were found to have payback periods of less than 40 months. Overall, the study demonstrates that the COPRAS model provides an effective roadmap for determining suitable energy efficiency techniques in the textile sector.

Keywords

• Best available techniques (BATs)
• Cleaner production
• COPRAS
• Energy efficiency
• Textile.

Supporting Institution

TÜBİTAK, YÖK, SDÜ BAP

Project Number

Proje No: 3170583

Ethical Statement

There is no need for ethics committee approval for the prepared article.

Thanks

This study was carried out as a part of the project titled “Development of Best Available Techniques (BAT) for Improving Resource Efficiency and Environmental Performance through a Cleaner Production Approach in an Integrated Textile Plant.” The project was supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) within the scope of TEYDEB Project (Project No: 3170583). The authors would like to thank the R&D department staff of ZORLUTEKS Tekstil (Turkey) and Murat Yıldırım for their support throughout the study. Elif Şimşek Yeşil conducted her doctoral studies in the thematic area of ​​“Sustainable Water Resources” within the scope of the Council of Higher Education (YÖK) 100/2000 Doctoral Program and the TÜBİTAK 2211/A Domestic General Doctoral Scholarship Program, and was supported by these programs. This study was also financially supported by the Süleyman Demirel University Scientific Research Projects Coordination Unit (SDÜ BAP, Project No: FDK-2022-8638) and the YÖK 100/2000 Doctoral Program. The authors would like to thank the SDÜ BAP Unit, YÖK, and TÜBİTAK for their support.

References

1. Aksakal, B., Ulutaş, A., Balo, F., Karabasevic, D., 2022. A new hybrid MCDM model for insulation material evaluation for healthier environment. Buildings, 12(5), 655.
2. Aruldoss, M., Lakshmi, T.M., Venkatesan, V.P., 2013. A survey on multi criteria decision making methods and its applications. American Journal of Information Systems, 1(1), 31–43.
3. Balkan, M., Ozturk, E., Kitis, M., 2023. Economic and cross-media effect analyses of best available techniques for caustic recovery from mercerization textile wastewater. Clean Technologies and Environmental Policy, 25, 1043–1058.
4. Bhatia, S.C., 2017. Pollution Control in Textile Industry. Editor: Devraj, S. Woodhead Publishing India in Textiles, Daryaganj, New Delhi, India.
5. Cakır, N., Alp, E., Yetis, U., 2020. Assessing technologies for reducing dust emissions from sintermaking based on cross-media effects and economic analysis. Clean Technologies and Environmental Policy, 22, 1909–1928.
6. Chapman, A., 2010. Mistra Future Fashion – Review of Life Cycle Assessments of Clothing. MISTRA Foundation for Strategic Environmental Research, Stockholm, Sweden.
7. Cınar, Y., 2020. Finansal analiz. http://ocw.ankara.edu.tr:81/eduCommons/isletme/yatirim-projeleri-ve analizi/materyal/finansal-analiz (Erişim Tarihi: 13.05.2020).
8. Dane, E., Pratt, M.G., 2007. Exploring intuition and its role in managerial decision making. Academy of Management Review, 32(1), 33–54.

9. Demirel, Y.E., Simsek, E., Ozturk, E., Kitis, M., 2021. Selection of priority energy efficiency practices for industrial steam boilers by PROMETHEE decision model. Energy Efficiency, 14(89).
10. Erkan, N., Ok, K., Parlak, S., 2020. ENAT Karacabey industrial afforestation investment revenue and internal profitability analysis. Forestry Research Journal, 7(1), 62–75.
11. Erkut, E., Tarimcilar, M., 1991. On sensitivity analysis in the analytic hierarchy process. IMA Journal of Management Mathematics, 3(1), 61–83.
12. Esteve-Turrilas, F.A., Guardia, M., 2017. Environmental impact of recovery cotton in textile industry. Resources, Conservation & Recycling, 116, 107–115.
13. European Commission (EC), 2003. Integrated Pollution Prevention and Control (IPPC) Reference Document on Best Available Techniques for the Textile Industry. EC IPPC Bureau, Seville, Spain.
14. European Commission (EC), 2006. Integrated Pollution Prevention and Control (IPPC) reference document on economics and cross-media effects. EC IPPC Bureau, Seville, Spain.
15. European Commission (EC), 2022. Integrated Pollution Prevention and Control (IPPC) Reference Document on Best Available Techniques (BAT) for the Textiles Industry. European IPPC Bureau, Seville, Spain.
16. Hasanbeigi, A., Price, L., 2012. A review of energy use and energy efficiency technologies for the textile industry. Renewable and Sustainable Energy Reviews, 16, 3648–3665.
17. Hasanzadeh, R., Mojaver, M., Azdast, T., Park, C.B., 2022. A novel systematic multi-objective optimization to achieve high-efficiency and low-emission waste polymeric foam gasification using response surface methodology and TOPSIS method. Chemical Engineering Journal, 430(3), 132958.
18. Ibrahim, A.Y., Ghallab, A.O., Gadalla, M.A., Makary, S.S., Ashour, F.H., 2017. Technical and economical/financial feasibility analyses of flared gas recovery in Egypt from oil and gas industry. Clean Technologies and Environmental Policy, 19, 1423–1436.
19. Ishfaq, S., Ali, S., Ali, Y., 2018. Selection of optimum renewable energy source for energy sector in Pakistan by using MCDM approach. Process Integration and Optimization for Sustainability, 2, 61–71.
20. Kahraman, C., Onar, S.C., Oztaysi, B., 2015. Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 8(4), 637–666.
21. Kaklauskas, A., Zavadskas, E.K., Raslanas, S., 2005. Multivariant design and multiple criteria analysis of building refurbishments. Energy and Buildings, 37(4), 361–372.
22. Kır, A., Ozturk, E., Yetis, U., Kitis, M., 2024. Resource utilization in the sub-sectors of the textile industry: opportunities for sustainability. Environmental Science and Pollution Research, 31, 25312–25328.
23. Koc, E., Kaplan, E., 2007. The energy consumption of textile finishing mills general utilization. Journal of Textile Engineering, 65, 39–47.
24. Kumar, A., Sah, B., Singh, A.R., Deng, Y., Kumar, X.H.P., Bansal, R.C., 2017. A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596–609.
25. Kurshid, M.F., Asad, M., Khan, A.A., Chaudhry, M.A., 2012. Investigation of specific energy consumption and possible reduction measures of textile spinning mills. Journal of American Science, 8, 535–542.
26. Lawrence, A., Thollander, P., Andrei, M., Karlsson, M., 2018. Specific energy consumption/use (SEC) in energy management for improving energy efficiency in industry: meaning, usage and differences. Energies, 12(2), 247.
27. Li, T., Li, A., Guo, X., 2020. The sustainable development-oriented development and utilization of renewable energy industry – A comprehensive analysis of MCDM methods. Energy, 212, 118694.
28. Mahdavi, N., Mojaver, P., Khalilarya, S., 2022. Multi-objective optimization of power, CO₂ emission and exergy efficiency of a novel solar-assisted CCHP system using RSM and TOPSIS coupled method. Renewable Energy, 185, 506–524.
29. Mulliner, E., Smallbone, K., Maliene, V., 2013. An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega, 41, 270–279.
30. Oyelaran, O.A., Twada, Y.Y., Sanusi, O.M., 2016. Energy audit of an industry: a case study of fabrication company. Aceh International Journal of Science and Technology, 5(2), 45–53.
31. Ozbek, A., 2017. Multi Criteria Decision Making Methods and Problem Solution with Excel. Seçkin Publishing, Ankara, Türkiye.
32. Ozturk, E., 2014. Applications of Integrated Pollution Prevention and Control and Cleaner Production in Textile Industry. PhD Thesis, Suleyman Demirel University, Isparta, Turkey.
33. Ozturk, E., Cinperi, N.C., Kitis, M., 2020. Improving energy efficiency using the most appropriate techniques in an integrated woolen textile facility. Journal of Cleaner Production, 254, 120145.
34. Ozturk, E., Koseoglu, H., Karaboyacı, M., Yigit, N.O., Yetis, U., Kitis, M., 2016. Sustainable textile production: cleaner production assessment/eco-efficiency analysis study in a textile mill. Journal of Cleaner Production, 138, 248–263.
35. Palamutcu, S., 2010. Electric energy consumption in the cotton textile processing stages. Energy, 35, 2945–2952.
36. Paradowski, B., Drazek, Z., 2020. Identification of the decision-making model for selecting an information system. Procedia Computer Science, 176, 3802–3809.
37. Raja, A.S.M., Arputharaj, A., Saxena, S., Patil, P.G., 2019. Water requirement and sustainability of textile processing industries. In: Muthu, S.S. (Ed.). Water in Textiles and Fashion Consumption, Footprint, and Life Cycle Assessment. Woodhead Publishing, Cambridge, UK.
38. Samantha, K.K., Pandit, P., Samantha, P., Basak, S., 2019. Water consumption in textile processing and sustainable approaches for its conservation. In: Muthu, S.S. (Ed.). Water in Textiles and Fashion Consumption, Footprint, and Life Cycle Assessment. Woodhead Publishing, Cambridge, UK.
39. Saxena, S., Raja, A.S.M., Arputharaj, A., 2017. Challenges in sustainable wet processing of textiles. In: Muthu, S.S. (Ed.). Textiles and Clothing Sustainability. Textile Science and Clothing Technology, Springer, Singapore.
40. Simsek, E., Demirel, Y.E., Ozturk, E., Kitis, M., 2022. Use of multi-criteria decision models for optimization of selecting the most appropriate best available techniques in cleaner production applications: A case study in a textile industry. Journal of Cleaner Production, 335, 130311.
41. Srdjevic, Z., Samardzic, M., Srdjevic, B., 2012. Robustness of AHP in selecting wastewater treatment method for the coloured metal industry: Serbian case study. Civil Engineering and Environmental Systems, 29(2), 147–161.
42. Strand, J., 2015. Environmental Impact of the Swedish Textile Consumption – A General LCA Study. Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden. https://w-program.nu/filer/exjobb/Jelina_Strand.pdf (Erişim Tarihi: 09.12.2023).
43. Taherdoost, H., Madanchian, M., 2023. Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia, 3, 77–87.
44. Tamborrino, A., Catalano, F., Berardi, A., Bianchi, B., 2021. New modelling approach for the energy and steam consumption evaluation in a fresh pasta industry. Chemical Engineering Transactions, 87, 409–414.
45. Tschiggerl, K., Topic, M., 2019. Cleaner Production and Sustainable Development. In: Leal Filho, W. (Ed.). Encyclopedia of Sustainability in Higher Education. Springer, Cham.
46. Türkiye Cumhuriyeti Merkez Bankası (TCMB), 2021. Annual Reports: 2021. Ankara, Turkey.
47. Uddin, F., 2014. Energy management and energy crisis in textile finishing. American Journal of Energy Research, 2, 53–59.
48. United Nations Industrial Development Organization (UNIDO), 2010. Global Industrial Energy Efficiency Benchmarking: An Energy Policy Tool Working Paper. UNIDO, Vienna, Austria.
49. Wang, J.J., Jing, Y.Y., Zhang, C.F., Zhao, J.H., 2009. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews, 13, 2263–2278.
50. World Wide Fund (WWF), 2014. Training Manual on BWMPs in Textile Sector of Pakistan. WWF-Pakistan.
51. Yang, K., Zhu, N., Chang, C., Wang, D., Yang, S., Ma, S., 2018. A methodological concept for phase change material selection based on multi-criteria decision making (MCDM): A case study. Energy, 165, 1085–1096.
52. Zavadskas, E.K., Antucheviciene, J., 2007. Multiple criteria evaluation of rural building’s regeneration alternatives. Building and Environment, 42(1), 436–451.
53. Zavadskas, E.K., Kaklauskas, A., Banaitis, A., Kvederyte, N., 2004. Housing credit access model: the case for Lithuania. European Journal of Operational Research, 155(2), 335–352.
54. Zolfani, S.H., Pourhossein, M., Yazdani, M., Zavadskas, E.K., 2017. Evaluating construction projects of hotels based on environmental sustainability with MCDM framework. Alexandria Engineering Journal.