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Sürekli Tavlama Hatları Isıtma Optimizasyonu İle Enerji Tasarrufu Sağlanması

Yıl 2016, Cilt 4, Sayı 1, 2016, 0 - 0, 11.04.2016
https://doi.org/10.17093/aj.2016.4.1.5000178199

Öz

Demir ve Çelik Sanayi enerji tüketimi ülkemizde nihai enerji tüketimlerinde en yüksek paya sahiptir. Küreselleşen dünyada rekabet koşullarının ve çevre koşullarına uyum şartlarının gün geçtikçe daha da ağırlaşması enerjinin etkin kullanımını ön plana çıkarmaktadır. Gelişen sanayiler enerjiyi etkin takip ederek ve enerji tüketimini verimli kullanarak ayakta kalabileceklerdir. Enerji kaynaklarını üretimde etkin ve verimli kullanmayan işletmelerin başarısızlığa uğraması kaçınılmazdır. Bu tezin konusu olan sürekli tavlama hatlarındaki enerji tasarrufu önemli bir konudur ve birçok parametreye bağlıdır. Tavlama otomasyon sisteminde şerit sıcaklığının ölçülmesi sürekli tavlama hat kontrolünde oldukça önemlidir. Belirli ısıtma kapasitesine sahip ısıtıcıların değerlerinin arttırılıp azaltılması ile fırın içi sıcaklarının dolayısıyla şerit sıcaklıklarının kontrolü sağlanır. Her bir şerit tavlama sıcaklığı şerit kalitesine bağlı olarak farklıdır. Ayrıca fırın sıcaklık değeri şerit boyutlarına ve hat hızına da bağlı olarak değişir. Hat hızını arttırmak için en uygun kalite sırasında üretimi gerçekleştirmek gerekir. Üretim seviyesinin arttırılması ve sıcaklık değişimlerinin en uygun olduğu sırada ürünlerin üretilmesi enerji tasarrufu oluşturmaktadır; bu da maliyetlerin azalmasına neden olur. Yukarıdaki parametrelerin modellendiği bulanık mantık hedef programlama fonksiyonları ile en uygun üretim sıralamasının bulunması araştırılmıştır.

Kaynakça

  • Arumugam, M. S., Chandramohan , A., Murthy G. R.(2011). On the optimal control of steel annealing processes via various versions of genetic and particle swarm optimization algorithms. International Journal of Bio-Inspired Computation, 12, 371-392
  • Carvalho, S.R., Ong, T.H. ve Guimaraes, G.(2006). A mathematical and computational model of furnaces for continuous steel strip processing. Journal of Materials Processing Technology , 178, 379 – 387
  • Charnes A., Cooper, W.W. ve Ferguson,R. (1955). Optimal estimation of executive compensation by linear programming. Journal of Management Science, 1, 138-151.
  • Chen, Y., Chen, L. and Chien-Yu Huang. (2009). Fuzzy Goal Programming Approach to Solve the Equipment - Purchasing Problem of an FMC. International Journal of Industrial Engineering, 270-281.
  • Choa, Y.C. , Cassandrasb, C. G. ve Kwon W. H. (2004). Optimal control for steel annealing processes as hybrid systems. Journal of Control Engineering Practice, 12, 1319–1328
  • Dini, G. , Vaghefi, S.M.M. ve Lotfiani,M. (2008). Computational and experimental failure analysis of continuous-annealing furnace radiant tubes. Journal of Engineering Failure Analysis, 15, 445–457.
  • Erdin, Dr. C. (2008). Bulanık Hedef Programlama ve Su havzasında bir uygulama. Journal of İstanbul University Social Sciences, 89-108
  • Erkan, K. ve Kale, S. (2007) Bulanık Hedef Programlama Yöntemi ile Süre-Maliyet-Kalite Eniyilemesi. Construction Management Congress, 109-118
  • Ertuğrul, İ. ve Güneş, M. (2007). Fuzzy Goal Programming and an Application of Production Process. Analysis and Design of Intelligent Systems using Soft Computing Techniques Advances in Soft Computing, 41, 649-659.
  • Ertuğrul, İ. (2005). Bulanık Hedef Programlama Ve Bir Tekstil Firmasında Uygulama Örneği. Journal of Eskişehir Osmangazi University Social Sciences, 45-78
  • Goswami, A., A., Singh, R.K., Prasad, A., Chowdhuri, Dr.S. (2012). Mathematical model based control system for Silicon Steel Mill of Rourkela Steel Plant. Journal of Procedia Technology, 4, 867-872
  • Guo C. , Zhang, Y. , You, X., Chen X. and Zhang, Y.(2009). Optimal Control of Continuous Annealing Process Using PSO. Int. Conference on Automation and Logistics, 602-606
  • Güneş, M. ve Umarosman, N. (2005). Fuzzy Goal Programming Approach on Computation of the Fuzzy Arithmetic Mean. Mathematical and Computational Applications, 211-220
  • Güneş, M. ve Umarusman N. (2007). Bir Karar Destek Aracı Bulanık Hedef Programlama ve Yerel Yönetimlerde Vergi Optimizasyonu Uygulaması. Review of Social, Economic & Business Studies, 242-255
  • Hans, J. Z. (1991). Fuzzy Set Theory and its Application. Kluwer Academic Publisher, Boston.
  • Kağnıcıoğlu, C.H. (2006). Hedef Programlama ve Bulanık Hedef Programlama Arasındaki ilişki. Journal of Gazi University Economics and Administrative Sciences Faculty, 17-38
  • Kelly, C. D. , Watanapongse, D. ve Gaskey, K. M.(1998). Application of Modern Control to a Continuous Anneal Line. IEEE Control Systems Magazine, 32-37.
  • Jeong, S. H., Yi, J.J., Kim, J.K. ve Ha, M.Y. (1991). Computer Modeling of the Continuous Annealing Furnace. Journal of KSME, 5, 16-21
  • Liang, T. (2006). Applying fuzzy goal programming to production / transportation planning decisions in a supply chain. International Journal of Systems Science, 293-304
  • Liang, T. ve Cheng, H. (2011). Multi-Objective Aggregate Production Planning Decisions Using Two-Phase Fuzzy Goal Programming Method. Journal Of Industrial And Management Optimization, 7, 365-385.
  • Lia, S., Qing Chena, Q. ve Huang, G.(2006). Dynamic temperature modeling of continuous annealing furnace using GGAP-RBF neural network. Journal of Neurocomputing, 69, 523–536
  • Marlow D.O. (1996). Modelling direct-fired annealing furnaces fortransient operations. Journal of Application Mathematics Modelling, 20, 34-40
  • Mekidiche, M., Hocine, M. ve Abdelkader S. (2013). Application of tolerance approach to fuzzy goal programming to aggregate production planning. Int. J. Mathematics in Operational Research, 5, 183-204.
  • Mekidiche, M. ve Belmokaddem, M. (2013). Weighted Additive Fuzzy Goal Programming Approach to Aggregate Production Planning. I.J. Intelligent Systems and Applications, 4, 20-29.
  • Özcan, U. ve and Toklu, B. (2009). Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models. Journal of Computers & Operations Research, 36, 1955 - 1965
  • Özkan, M. M. (2003). Bulanık Hedef Programlama. Ekin Kitabevi, İstanbul.
  • Selim, H. , Araz, C. ve Özkarahan İ. (2008). Collaborative production–distribution planning in supply chain: A fuzzy goal programming approach. Transportation Research Part E: Logistics and Transportation Review, 396-419.
  • Sert, Ü. (2015).Haddeleme Hakkında. http://www.arsivbelge.com/yaz.php?sc=2418
  • Wan F., Wang Y. ve Qin S.(2012). Modeling of Strip Heating Process in Vertical Continuous Anealing Furnace, Journal Of Iron And Steel Research, 19, 29-36
  • Wen-Ie, W., Jian-ping, L. , Fu-an, H. ve Xiang-hua L.(2010). Application of Self-Learning to Heating Process Control of Simulated Continuous Anneal. Journal Of Iron And Steel Research, 17, 27-31
  • Yaghoobi, M.A., Jons, D.F., Tamiz. (2008). Weighted additive models for solving fuzzy goal programming problems. Int. Journal of Intelligent Systems and Applications. Asia Pacific Journal of Operation Research , 25, 715-730
  • Yanagishima,F., Shimoyama, Y., Suzuki,M., Sunami, H., Haga, T., Ida, Y. ve Irie T.(1981). Characteristics and Operation of Multipurpose Continuous Annealing Line at Chiba Works. Kawasaki Steel Technical Report, 2, 1-13
  • Yoshitani, N. ve Hasegawa A. (1998). Model-Based Control of Strip Temperature for the Heating Furnace in Continuous Annealing, IEEE Transactions on Control Systems Technology, 6, 146-156
  • Zhang, Y. , Li, S. ve Tenga, Y. (2012). Dynamic processes monitoring using recursive kernel principal component analysis. Journal of Chemical Engineering Science , 72, 78–86
  • Zhou, M., Yu D. ve Zhou J. (2008). A New Strip Temperature Control Method for the Heating Section of Continuous Annealing Line. Cybernetics and Intelligent Systems 2008 IEEE Conference, 861 – 864

Energy Saving In Continuous Annealing Line Using Heating Optimization

Yıl 2016, Cilt 4, Sayı 1, 2016, 0 - 0, 11.04.2016
https://doi.org/10.17093/aj.2016.4.1.5000178199

Öz

Energy consumption of Iron and Steel Industry sector in Turkey has the highest share in final energy consumption. In the globalized world, day by day, worsening of the conditions of competition and negative environmental pressures, more efficient energy usage is come to the forefront. Growing industries can survive by providing efficient energy consumption and effective energy follow-up. The failure of businesses is become inevitable with ineffective and inefficient usage of energy resources used in the production. Energy savings in the continuous annealing line which is the subject of this article is an important issue and it is based on many parameters. Measuring strip's temperature is so important to continuous annealing line control in the annealing automation system. Increasing or decreasing the oven temperature provides the process control with the adjustment of the heater which is specific heating capacity in these furnaces. Each strip annealing temperature is different which depends on the strip quality. Also strip thickness, strip width and the line speed are the other factors of the oven temperature conditions. It needs to realize the production of an optimal quality ranking to increase the line speed. This improves the production level and because of the oven temperature changes in the order that causes the reduction of costs due to energy savings, optimized production is achieved. Finding the most suitable production sequence is modeled by fuzzy goal programming functions used the above parameters were investigated

Kaynakça

  • Arumugam, M. S., Chandramohan , A., Murthy G. R.(2011). On the optimal control of steel annealing processes via various versions of genetic and particle swarm optimization algorithms. International Journal of Bio-Inspired Computation, 12, 371-392
  • Carvalho, S.R., Ong, T.H. ve Guimaraes, G.(2006). A mathematical and computational model of furnaces for continuous steel strip processing. Journal of Materials Processing Technology , 178, 379 – 387
  • Charnes A., Cooper, W.W. ve Ferguson,R. (1955). Optimal estimation of executive compensation by linear programming. Journal of Management Science, 1, 138-151.
  • Chen, Y., Chen, L. and Chien-Yu Huang. (2009). Fuzzy Goal Programming Approach to Solve the Equipment - Purchasing Problem of an FMC. International Journal of Industrial Engineering, 270-281.
  • Choa, Y.C. , Cassandrasb, C. G. ve Kwon W. H. (2004). Optimal control for steel annealing processes as hybrid systems. Journal of Control Engineering Practice, 12, 1319–1328
  • Dini, G. , Vaghefi, S.M.M. ve Lotfiani,M. (2008). Computational and experimental failure analysis of continuous-annealing furnace radiant tubes. Journal of Engineering Failure Analysis, 15, 445–457.
  • Erdin, Dr. C. (2008). Bulanık Hedef Programlama ve Su havzasında bir uygulama. Journal of İstanbul University Social Sciences, 89-108
  • Erkan, K. ve Kale, S. (2007) Bulanık Hedef Programlama Yöntemi ile Süre-Maliyet-Kalite Eniyilemesi. Construction Management Congress, 109-118
  • Ertuğrul, İ. ve Güneş, M. (2007). Fuzzy Goal Programming and an Application of Production Process. Analysis and Design of Intelligent Systems using Soft Computing Techniques Advances in Soft Computing, 41, 649-659.
  • Ertuğrul, İ. (2005). Bulanık Hedef Programlama Ve Bir Tekstil Firmasında Uygulama Örneği. Journal of Eskişehir Osmangazi University Social Sciences, 45-78
  • Goswami, A., A., Singh, R.K., Prasad, A., Chowdhuri, Dr.S. (2012). Mathematical model based control system for Silicon Steel Mill of Rourkela Steel Plant. Journal of Procedia Technology, 4, 867-872
  • Guo C. , Zhang, Y. , You, X., Chen X. and Zhang, Y.(2009). Optimal Control of Continuous Annealing Process Using PSO. Int. Conference on Automation and Logistics, 602-606
  • Güneş, M. ve Umarosman, N. (2005). Fuzzy Goal Programming Approach on Computation of the Fuzzy Arithmetic Mean. Mathematical and Computational Applications, 211-220
  • Güneş, M. ve Umarusman N. (2007). Bir Karar Destek Aracı Bulanık Hedef Programlama ve Yerel Yönetimlerde Vergi Optimizasyonu Uygulaması. Review of Social, Economic & Business Studies, 242-255
  • Hans, J. Z. (1991). Fuzzy Set Theory and its Application. Kluwer Academic Publisher, Boston.
  • Kağnıcıoğlu, C.H. (2006). Hedef Programlama ve Bulanık Hedef Programlama Arasındaki ilişki. Journal of Gazi University Economics and Administrative Sciences Faculty, 17-38
  • Kelly, C. D. , Watanapongse, D. ve Gaskey, K. M.(1998). Application of Modern Control to a Continuous Anneal Line. IEEE Control Systems Magazine, 32-37.
  • Jeong, S. H., Yi, J.J., Kim, J.K. ve Ha, M.Y. (1991). Computer Modeling of the Continuous Annealing Furnace. Journal of KSME, 5, 16-21
  • Liang, T. (2006). Applying fuzzy goal programming to production / transportation planning decisions in a supply chain. International Journal of Systems Science, 293-304
  • Liang, T. ve Cheng, H. (2011). Multi-Objective Aggregate Production Planning Decisions Using Two-Phase Fuzzy Goal Programming Method. Journal Of Industrial And Management Optimization, 7, 365-385.
  • Lia, S., Qing Chena, Q. ve Huang, G.(2006). Dynamic temperature modeling of continuous annealing furnace using GGAP-RBF neural network. Journal of Neurocomputing, 69, 523–536
  • Marlow D.O. (1996). Modelling direct-fired annealing furnaces fortransient operations. Journal of Application Mathematics Modelling, 20, 34-40
  • Mekidiche, M., Hocine, M. ve Abdelkader S. (2013). Application of tolerance approach to fuzzy goal programming to aggregate production planning. Int. J. Mathematics in Operational Research, 5, 183-204.
  • Mekidiche, M. ve Belmokaddem, M. (2013). Weighted Additive Fuzzy Goal Programming Approach to Aggregate Production Planning. I.J. Intelligent Systems and Applications, 4, 20-29.
  • Özcan, U. ve and Toklu, B. (2009). Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models. Journal of Computers & Operations Research, 36, 1955 - 1965
  • Özkan, M. M. (2003). Bulanık Hedef Programlama. Ekin Kitabevi, İstanbul.
  • Selim, H. , Araz, C. ve Özkarahan İ. (2008). Collaborative production–distribution planning in supply chain: A fuzzy goal programming approach. Transportation Research Part E: Logistics and Transportation Review, 396-419.
  • Sert, Ü. (2015).Haddeleme Hakkında. http://www.arsivbelge.com/yaz.php?sc=2418
  • Wan F., Wang Y. ve Qin S.(2012). Modeling of Strip Heating Process in Vertical Continuous Anealing Furnace, Journal Of Iron And Steel Research, 19, 29-36
  • Wen-Ie, W., Jian-ping, L. , Fu-an, H. ve Xiang-hua L.(2010). Application of Self-Learning to Heating Process Control of Simulated Continuous Anneal. Journal Of Iron And Steel Research, 17, 27-31
  • Yaghoobi, M.A., Jons, D.F., Tamiz. (2008). Weighted additive models for solving fuzzy goal programming problems. Int. Journal of Intelligent Systems and Applications. Asia Pacific Journal of Operation Research , 25, 715-730
  • Yanagishima,F., Shimoyama, Y., Suzuki,M., Sunami, H., Haga, T., Ida, Y. ve Irie T.(1981). Characteristics and Operation of Multipurpose Continuous Annealing Line at Chiba Works. Kawasaki Steel Technical Report, 2, 1-13
  • Yoshitani, N. ve Hasegawa A. (1998). Model-Based Control of Strip Temperature for the Heating Furnace in Continuous Annealing, IEEE Transactions on Control Systems Technology, 6, 146-156
  • Zhang, Y. , Li, S. ve Tenga, Y. (2012). Dynamic processes monitoring using recursive kernel principal component analysis. Journal of Chemical Engineering Science , 72, 78–86
  • Zhou, M., Yu D. ve Zhou J. (2008). A New Strip Temperature Control Method for the Heating Section of Continuous Annealing Line. Cybernetics and Intelligent Systems 2008 IEEE Conference, 861 – 864
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Ömer Faruk Sezer

Erman Coşkun

Yayımlanma Tarihi 11 Nisan 2016
Gönderilme Tarihi 17 Şubat 2016
Yayımlandığı Sayı Yıl 2016 Cilt 4, Sayı 1, 2016

Kaynak Göster

APA Sezer, Ö. F., & Coşkun, E. (2016). Energy Saving In Continuous Annealing Line Using Heating Optimization. Alphanumeric Journal, 4(1). https://doi.org/10.17093/aj.2016.4.1.5000178199

Cited By

Energy and Exergy Analysis of an Industrial Annealing Furnace
Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi
https://doi.org/10.19113/sdufenbed.678843

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