International Journal of Engineering Technology and Management Sciences

2023, Volume 7 Issue 6

Comparative Study on Steel Structure Auditorium Estimation

AUTHOR(S)

Sujith P, Surya Prakash R, Venkatesh Prasath K, Anish A, Dr.K.Thirumalai Raja

DOI: https://doi.org/10.46647/ijetms.2023.v07i06.025

ABSTRACT
Construction cost estimation is a critical aspect of project management in the construction industry. Accurate estimation of construction costs, material costs, and labour costs is essential for effective project planning, budgeting, and resource allocation. With the advancement of technology, various software options are available to assist in construction cost estimation, offering different features, advantages, and limitations. In this project report, we have compared different software methods for construction cost estimation, including Microsoft Excel, Estimator 2.0, Primavera P6, and Construction Calculator mobile apps. The report provides an overview of these software options, highlighting their advantages and disadvantages in terms of accuracy, flexibility, efficiency, transparency, customization, collaboration, reporting capabilities, scalability, historical data tracking, user-friendliness, automation, cost-effectiveness, and compatibility. The report also discusses the strengths and limitations of each software option, including potential errors, learning curve, cost of licenses, customization options, updates and maintenance requirements, integration limitations, and platform compatibility. The report concludes by emphasizing the importance of carefully considering the specific needs and requirements of the project and the expertise of the team members when selecting the most suitable software for construction cost estimation.

Page No: 144 - 166

References:

  1. Sayid Amir Mohsen Faghih, Hamed Kashani (2021)“Forecasting Construction Material Prices Using Vector Error Correction Model” Journal of Construction Engineering and Management(ASCE)
  2. Marc -Antoine Vigneault,Conrad Boton,Heap-Yih Chong,Barry Cooper Cooke(2019)”An Innovative Framework of 5D BIM Solutions for Construction Cost Management: A Systematic Review” Archievs of Computational Methods in Engineering(CIMNE)
  3. Moon,Taenam,Shin,Do Hyoung(2018)”R. Nicole, “Forecasting Construction cost index using interrupted time series,” Journal of Civil Engineering(KSCE)
  4. Hemanta Doloi(2013)” Cost Overruns and Failure in Project Management: Understanding the Roles of Key Stakeholders in Construction Projects” Journal of Construction Engineering and Management(ASCE)
  5. Xuequing Zhang(2013)“Concessionaire’s Financial Capability in Developing Build-Operate-Transfer Type Infrastructure Projects.” Journal of Construction Engineering and Management(ASCE)
  6. Tarjei Kristiansen(2012)”Forecasting Nord Pool day Ahead prices using auto regressive model” Energy Policy “(ELSEVIER) [8] Sungjoo Hwang,Moonseo Park,Hyun-Soo Lee,Hyunsoo Kim;(2012) “Automated Time Series Cost Forecasting for cost forecasting” Construction Engineering and Management(ASCE)
  7. AntonioConejo,JavierContreras,RosaEspinola(2005)”F orecasting electricity prices for a day-ahead pool-based electric energy market”. International Journal of Forecasting”(ELSEVIER)
  8.  H.Ahuja. Successful construction cost control. Wiley, New York,1980
  9. Gwang-Hee Kim, Jae-Min Shin, Sangyong Kim, Yoonseok Shin (2013), " Comparison of School Building Construction Costs Estimation Methods Using Regression Analysis, Neural Network, and Support Vector Machine", Journal of Building Construction and Planning Research, 2014 [1, 1-7].
  10.  Savas Bayram and Saad Al-Jibouri (2016) “Efficacy of Estimation Methods in Forecasting Building Projects’ Costs”. 10.1061/ (ASCE) CO.1943-7862.0001183. American Society of Civil Engineers. Journal of Construction Engineering and Management. 05016012.
  11. WisnuIsvara, Yusuf Latief, Andreas Wibowo, Murthada Askari (2015), "Comparison of Cost Estimation Methods using Hybrid Artificial Intelligence on Schematic Design Stage: RANFIS and CBR-GA", International Journal of Engineering Research and Applications ISSN: 2248-9622, Vol. 5, Issue 11, (Part - 4) November 2015, pp.33-38.
  12. S. Shanmugapriya, Dr. K. Subramanian, (2013) “Investigation of Significant Factors Influencing Time and Cost Overruns in Indian Construction Projects". International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 10, October 2013).
  13. Nedal Salah Jameel Al Sheikh, (2013) "Cost Estimation Of Construction Projects At Gaza Strip Using Fuzzy Logic", Msc Thesis (Civil Engineering), The Islamic University of Gaza-Palestine.
  14. T.M.S. Elhag and A.H. Boussabaine (1998), “An Artificial Neural System for Cost Estimation of Construction Projects", In: Hughes, W (Ed.), 14th Annual ARCOM Conference, University of Reading. Association of Researchers in Construction Management, Vol. 1, 219-26.
  15. Sivanandam, S., Sumathi, S. and Deepa, S. (2007) “Introduction to Fuzzy Logic using MATLAB”. Springer-Verlag Berlin Heidelberg.
  16. Lorterapong, P., and Moselhi, O. (1996). ‘‘Project-network analysis using fuzzy sets theory.’’ Journal of Construction Engineering and Management.
  17. Sonmez, R. (2004). “Conceptual cost estimation of building projects with regression analysis and neural networks” Canadian Journal of Civil Engineering, 31(4), 677 – 683.
  18.  Nabil Ibrahim El Sawalhi (2012), "Modeling the Parametric Construction Project Cost Estimate using Fuzzy Logic", International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 4, and April 2012.
  19. Adnan Enshassi, Sherif Mohamed and Saleh Abushaban, (2009) “Factors affecting the performance of construction projects in the Gaza strip”,; JCEM, Vol.15, No.3, 20pp.: 269- 280.
  20. Afshin Firouzi, Wei Yang, and Chun-Qing Li (2016) “Prediction of Total Cost of Construction Project with Dependent Cost Items”. 10.1061/ (ASCE) CO.1943-7862.0001194. American Society of Civil Engineers. Journal of Construction Engineering and Management. 2016, 142(12): 04016072.
  21. Ahmad Soltani, Rasoul Haji (2007). “A Project Scheduling Method Based on Fuzzy Theory” Journal of Industrial and Systems Engineering Vol. 1, No. 1, pp 70-80 spring.
  22. Ali Touran and Ramon Lopez, (2006), “Modeling Cost Escalation in Large Infrastructure Projects”, Journal of Construction Engineering and Management. , 132,853-860.
  23. Anil K Jain, Jianchang Mao, K.M. Mohiuddin, (1996). ― Artificial Neural Network: A Tutorial‖, IEEE, 0018-9162.
  24. Karanci (2010), “A Comparative Study of Regression Analysis, Neural Networks and Case – Based Reasoning For Early Range Cost Estimation of Mass Housing Projects” M.S. Thesis, Department of Civil Engineering , The Graduate School of Natural And Applied Sciences Of Middle East Technical University ,85 Pages.
  25. Karla Grace Knight (2001), “A Fuzzy Logic Mode1 for Predicting Commercial Building Design Cost Overruns”, MSc Thesis in Construction Engineering and Management, Edmonton, Alberta, spring 2001.
  26. Karl Blyth and Ammar Kaka (2006), “A novel multiple linear regression model for forecasting S-curves”, Engineering, Construction and Architectural Management Vol. 13 No. 1, pp. 82-95.
  27. Maravas, A., Pantouvakis, J. P., and Kaltsas, D. (2009). “An artificial neural network for the pre-estimation of construction costs for electrical and mechanical installations on road tunnels.” Collaboration and Integration in Engineering, Management and Technology, Middle East Technical Univ., Ankara, Turkey, 33–40.
  28. Mehdi Neshat, Ali Adeli, Azra masoumi, Mehdi sargolzae (2011), "A Comparative Study on ANFIS and Fuzzy Expert System Models for Concrete Mix Design", IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 2, May 2011 ISSN (Online): 1694-0814.
  29.  Min-Yuan Cheng, Hsing-Chih Tsai, and Erick Sudjono (2009) “Evolutionary Fuzzy Hybrid Neural Network for Conceptual Cost Estimates in Construction Projects”, Information and Computational Technology26th International Symposium on Automation and Robotics in Construction (ISARC 2009).
  30. Mohammed Arafa and Mamoun Alqedra (2011) on the study “Early Stage Cost Estimation of Buildings Construction Projects using Artificial Neural Networks”, Journal of Artificial Intelligence, Volume: 4 | Issue: 1 | Page No.: 63-75,10.3923/jai.2011.63.75.
  31. Olagunju Mukaila, Owolabi K.M and Afolayan A.O (2014) “Determination of a Price Index for Escalation of Building Material Cost in Nigeria”. International Journal of Managerial Studies and Research (IJMSR) Volume 2, Issue 10, November 2014, PP 116-133 ISSN 2349-0330.
  32. Onur Dursun and Christian Stoy (2016) “Conceptual Estimation of Construction Cost Using the Multistep Ahead Approach”. 10.1061/(ASCE)CO. 1943-7862.0001150. American Society of Civil Engineers. Journal of Construction Engineering and Management 04016038.

How to Cite This Article:
Sujith P, Surya Prakash R, Venkatesh Prasath K, Anish A, Dr.K.Thirumalai Raja . ijetms;7(6):144-166. DOI: 10.46647/ijetms.2023.v07i06.025

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