Araştırma Makalesi
BibTex RIS Kaynak Göster

Cam Elyaf Takviyeli Beton Üretim Sektöründe Risk Faktörlerinin Belirlenmesi ve Tahmini

Yıl 2017, Cilt: 5 Sayı: 4, 215 - 221, 22.12.2017
https://doi.org/10.29109/http-gujsc-gazi-edu-tr.345755

Öz

Cam elyaf takviyeli
betonunun inşaat endüstrisinde kullanımı estetik ve mekanik özelliklerine,
hızlı ve güvenli üretimine bağlı olarak son on yılda popüler hale gelmektedir.
Ancak diğer beton türleri ile karşılaştırıldığında daha karmaşık üretim
süreçlerine sahiptir. Bundan dolayı detaylı üretimi için yüksek yatırımlar
gerektirmektedir. Bu yüksek yatırımlar ise beraberinde çok çeşitli ve fazla
risk faktörlerini getirmekte ve bunların yönetimi önemli hale gelmektedir. Bu
çalışma, cam elyaf takviyeli beton sektöründe risk faktörlerinin güncel
tanılarını tanımlamaktadır. Öngörülemeyen maliyet artışlarının ve bu tür beton
üretimindeki gecikmelerin azaltılması hedeflenmektedir ve sektördeki
işverenler, müteahhitler ve çevreler için değer katması düşünülmektedir.

Kaynakça

  • [1] M. S. B. A. A. El-Karim, O. A. M. E. N., A. M. Abdel-Alim. Identification and assessment of risk factors affecting construction projects, HBRC Journal, Housing and Building National Research Center, 2015, Article in Press.
  • [2] ANSI/PMI 99-001-2004: A Guide to the Project Management Body of Knowledge, Third Edition.
  • [3] Cooper, D. F. (2005). Project risk management guidelines: Managing risk in large projects and complex procurements. John Wiley & Sons, Inc.
  • [4] Bernstein, P. L., & Bernstein, P. L. (1996). Against the gods: The remarkable story of risk (pp. 1269-1275). New York: Wiley.
  • [5] Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13.
  • [6] Tian Y., (2008) Compiling principle and method of railway and highway engineering budget, Beijing: China railway press.
  • [7] Jin D., (2004) The study of the system theory and integration of life-cycle engineering project risk management, Tianjin: Tianjin University.
  • [8] Wang L., Li Y., Wang E. Research on Risk Management of Railway Engineering Construction. Systems Engineering Procedia 1 (2011) 174–180.
  • [9] Ding, L. Y., Yu, H. L., Li, H., Zhou, C., Wu, X. G., & Yu, M. H. (2012). Safety risk identification system for metro construction on the basis of construction drawings. Automation in construction, 27, 120-137.
  • [10] Zhixing Cai, Guangyou Xu, Artificial Intelligence: Principles and Applications, third edition Tsinghua University Press, Beijing, 2003.
  • [11] M. Molag, I.J.M. Trijssenaar-Buhre, Risk Assessment Guidelines for Tunnels, Safe & Reliable Tunnels, Lausanne, 2006.
  • [12] Chinese Civil Engineering Society, Guideline of Risk Management for Construction of Subway and Underground Works, China Architecture & Building Press, Beijing, 2007.
  • [13] M. Holický, L. Šajtar, Probabilistic risk assessment and optimization of road tunnels, in: C. Guedes Soares, E. Zio (Eds.), Safety and Reliability for Managing Risk, Tailor and Francis Group, London, 2006, pp. 297–304.
  • [14] AACE, AACE international’s risk management dictionary, Cost Eng. 42 (4) (2000) 28–31.
  • [15] K. Iyer, K. Jha, Critical factors affecting schedule performance: evidence from Indian construction projects, J. Constr. Eng. Manage. 132 (8) (2006) 871–881.
  • [16] N. Boskers, S. AbouRizk, Modeling scheduling uncertainty in capital construction projects, Proc. Winter Simulat. Conf. (2005) 1500–1507.
  • [17] G. Barraza, Probabilistic estimation and allocation of project time contingency, J. Constr. Eng. Manage. 137 (4) (2011) 259–265.
  • [18] Kasprowicz, T. (2017). Quantitative Assessment of Construction Risk. Archives of Civil Engineering, 63(2), 55-66

Risk Factors Identification and Estimation for Glass Fiber Reinforced Concrete Production Sector

Yıl 2017, Cilt: 5 Sayı: 4, 215 - 221, 22.12.2017
https://doi.org/10.29109/http-gujsc-gazi-edu-tr.345755

Öz

Glass
fiber reinforced concrete (GRC) usage in construction industry has been
becoming very popular due to its aesthetic, mechanical properties, fast and
reliable production in the last decade. However, it has more complex manufacturing
processes compared with the other types of concrete pouring systems. Hence, it
needs to make higher investments for its more detailed production line. Higher
investments carry along more and several types of risk factors, and it becomes
necessary to manage them. This paper describes the actual identification of
possible risk factors in glass fiber reinforced concrete production sector. And
it aims to decrease the unforeseen increase in cost and delays in this branch
of concrete production and it is considered to affiliate value for owners,
contractors, and the environments in the sector.

Kaynakça

  • [1] M. S. B. A. A. El-Karim, O. A. M. E. N., A. M. Abdel-Alim. Identification and assessment of risk factors affecting construction projects, HBRC Journal, Housing and Building National Research Center, 2015, Article in Press.
  • [2] ANSI/PMI 99-001-2004: A Guide to the Project Management Body of Knowledge, Third Edition.
  • [3] Cooper, D. F. (2005). Project risk management guidelines: Managing risk in large projects and complex procurements. John Wiley & Sons, Inc.
  • [4] Bernstein, P. L., & Bernstein, P. L. (1996). Against the gods: The remarkable story of risk (pp. 1269-1275). New York: Wiley.
  • [5] Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13.
  • [6] Tian Y., (2008) Compiling principle and method of railway and highway engineering budget, Beijing: China railway press.
  • [7] Jin D., (2004) The study of the system theory and integration of life-cycle engineering project risk management, Tianjin: Tianjin University.
  • [8] Wang L., Li Y., Wang E. Research on Risk Management of Railway Engineering Construction. Systems Engineering Procedia 1 (2011) 174–180.
  • [9] Ding, L. Y., Yu, H. L., Li, H., Zhou, C., Wu, X. G., & Yu, M. H. (2012). Safety risk identification system for metro construction on the basis of construction drawings. Automation in construction, 27, 120-137.
  • [10] Zhixing Cai, Guangyou Xu, Artificial Intelligence: Principles and Applications, third edition Tsinghua University Press, Beijing, 2003.
  • [11] M. Molag, I.J.M. Trijssenaar-Buhre, Risk Assessment Guidelines for Tunnels, Safe & Reliable Tunnels, Lausanne, 2006.
  • [12] Chinese Civil Engineering Society, Guideline of Risk Management for Construction of Subway and Underground Works, China Architecture & Building Press, Beijing, 2007.
  • [13] M. Holický, L. Šajtar, Probabilistic risk assessment and optimization of road tunnels, in: C. Guedes Soares, E. Zio (Eds.), Safety and Reliability for Managing Risk, Tailor and Francis Group, London, 2006, pp. 297–304.
  • [14] AACE, AACE international’s risk management dictionary, Cost Eng. 42 (4) (2000) 28–31.
  • [15] K. Iyer, K. Jha, Critical factors affecting schedule performance: evidence from Indian construction projects, J. Constr. Eng. Manage. 132 (8) (2006) 871–881.
  • [16] N. Boskers, S. AbouRizk, Modeling scheduling uncertainty in capital construction projects, Proc. Winter Simulat. Conf. (2005) 1500–1507.
  • [17] G. Barraza, Probabilistic estimation and allocation of project time contingency, J. Constr. Eng. Manage. 137 (4) (2011) 259–265.
  • [18] Kasprowicz, T. (2017). Quantitative Assessment of Construction Risk. Archives of Civil Engineering, 63(2), 55-66
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Sadık Alper Yıldızel

Yusuf Arslan

Yayımlanma Tarihi 22 Aralık 2017
Gönderilme Tarihi 23 Ekim 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 5 Sayı: 4

Kaynak Göster

APA Yıldızel, S. A., & Arslan, Y. (2017). Risk Factors Identification and Estimation for Glass Fiber Reinforced Concrete Production Sector. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji, 5(4), 215-221. https://doi.org/10.29109/http-gujsc-gazi-edu-tr.345755

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