Estimation Model of Steel Waste Material: Verification on the Effectiveness of Multiple Regression Analysis

Asmawati Che Hasan; Zulkiflee Yusof; Nur Muizzah Nawi; Nazri Nasir; Raja Nor Husna Raja Mohd Noor; Herda Balqis Ismail

doi:10.4028/www.scientific.net/AMM.873.164

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 873Estimation Model of Steel Waste Material:...

Estimation Model of Steel Waste Material: Verification on the Effectiveness of Multiple Regression Analysis

Abstract:

Construction industry is one of the most important sectors for the Malaysian economic growth where it remains as the fastest growing activity for several years. The issue of rapid country development which has positive influence of generating high construction waste is very commonly related to this industry. One of the major contributors of construction waste is steel. Steel is expensive and can contribute to overall project cost implication. Hence, the amount of steel waste needsto be quantifiedat the initial stage. Thus,steel waste quantification model is an important element to be considered for better waste management. By using the data collected in the Central region in Malaysia, an empirical model, Estimation Model of Steel Waste Material has been developed to estimate the amount of steel waste generation based on certain variables. This study aims to investigate and verify the effectiveness of the model by using the data collected from the Northern region in Malaysia. The value of the Mean Absolute Percentage Error (MAPE), 23.02% indicates that the model performance is common and acceptable. Thus, the model has good potential to be adopted by the industry practitioners to plan a better and more effective waste management.

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Periodical:

Applied Mechanics and Materials (Volume 873)

Pages:

164-169

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.873.164

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Online since:

November 2017

Authors:

Asmawati Che Hasan*, Zulkiflee Yusof, Nur Muizzah Nawi, Nazri Nasir, Raja Nor Husna Raja Mohd Noor, Herda Balqis Ismail

Keywords:

Construction Waste, Material, Multiple Regression Analysis, Steel

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References

[1] E. Yeong, Rail projects to be construction sector's growth locomotive this year, The Sun Daily (31 Jan 2017).

Google Scholar

[2] Z. A. Nazirah, Sustainable Construction in Malaysia– Developers' Awareness, Int. J. Human Soc. Sci. 5(2) (2010)122-129.

Google Scholar

[3] R. A. Begum, C. Siwar, J. J. Pereira and A. H. Jaafar, A Benefit-Cost Analysis on the Economic Feasibility of Construction Waste Minimisation: The Case of Malaysia. Resources, Conserv. Recycl. 48 (2006) 86-98.

DOI: 10.1016/j.resconrec.2006.01.004

Google Scholar

[4] O. F. Kofoworola, and S. H. Gheewala, Estimation of Construction Waste Generation and Management in Thailand, Waste Manag. 29 (2009) 731-738.

DOI: 10.1016/j.wasman.2008.07.004

Google Scholar

[5] H. H. Tang, and I. B. Larsen, Managing Construction Waste - A Sarawak Experience. DANIDA / Sarawak Government UEMS Project, Natural Resources and Environmental Board (NREB), (2004).

Google Scholar

[6] Pengurusan Sisa Pepejal Bagi Projek Pembangunan, Solid Waste Corporation Malaysia, 24 Mei (2014).

Google Scholar

[7] Solid Waste Management and Public Cleansing. National Solid Waste Management Department, 7 September (2015).

Google Scholar

[8] C. F. Lee, A. R. Ismail, A. Ade, S. Nagapan and I. K. Khairul, Classification and Quantification of Construction Waste at Housing Project, Int. J. Zero Waste Generat. 1(1)(2013) 1-4.

Google Scholar

[9] H. H. Lau,A. WhyteandP. L. Law, Composition and Characteristics of Construction Waste Generated by Residential Housing Project. Int. J. Envir. Res. 2(3) (2008) 261-268.

Google Scholar

[10] C. H. Asmawati, M. R. Ahmad Ruslan, Y. Zulkiflee, R. M. N. Raja Nor Husna, A Review on Materials Waste Quantification and Management in Construction Activities, ASM Sci. J. 7(2) (2013) 113-117.

Google Scholar

[11] C. H. Asmawati, Z. Yusof,A. R. Mohd Ridzuan, I. Atan, B. Noordin, A. H. Abdul Ghani, Estimation model of construction waste materials in Malaysia: Steel. In BEIAC 2013 - 2013 IEEE Business Engineering and Industrial Applications Colloquium. (2013).

DOI: 10.1109/beiac.2013.6560224

Google Scholar

[12] R. Pooria, Energy and CO2 Emission Evaluation of Concrete Waste. Master Thesis. Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia, (2009).

DOI: 10.23939/chcht10.04.493

Google Scholar

[13] C. T. Formoso, L. Soibelman, C. D. Cesare and E. L. Issato, Material Waste in Building Industry: Main Causes and Prevention, J. Constr. Eng. Manag. 128(4) (2002) 316-325.

DOI: 10.1061/(asce)0733-9364(2002)128:4(316)

Google Scholar

[14] C. F. Douglas, Forecasting Tourism Demand: Methods and Strategies, Butterworth Heinman, (2001), p.24.

Google Scholar