A Control Model for Reinforced Concrete Work Materials on the Construction of Duta Mall 2

Authors

  • S. Daslim Department of Civil Engineering, Faculty of Engineering, Lambung Mangkurat University, Indonesia
  • A. Mursadin Department of Civil Engineering, Faculty of Engineering, Lambung Mangkurat University, Indonesia

Abstract

Controlling is a crucial stage in achieving a project target, covering aspects of cost, quality, and time. In the construction industry, the cost aspect is often the main focus. The project of Duta Mall 2 (DM 2) is the development of an existing building and the cost aspect is a major concern to the owner. Dynamic internal and external factors of the DM 2 project cause the project control to be quite difficult, with the materials becoming the most dominant factor in construction cost. Cost control starts from reinforced concrete work materials, consisting of ready mixed concrete, concrete steel, wire, plywood, timber, and nails. Bad control of material purchasing can lead to cost escalation, degradation of material quality, and impact on the execution schedule of works. This research was conducted to obtain quantitative correlations between material components based on reinforced concrete works material supply data. From these data, some linear regression models can be designed to obtain a more accurate and effective prediction of material volume needs in the future. Model equations can be applied to control material demand, measure waste, reference of material volume in arranging the project cost budget, in addition to the process in the control procedure of the request for goods (materials and equipment).

Keywords:

reinforced concrete works, material control, linear regression, predictive capabilities, control procedure

Downloads

Download data is not yet available.

References

M. W. Newell, Preparing for the project management professional, American Management Association, 2002

D. Battini, M. Calzavara, I. Isolan, F. Sgarbossa, F. Zangaro, F. “Sustainability in material purchasing: A multi-objective economic order quantity model under carbon trading”, Sustainability, Vol. 2018, No. 10, Article ID 4438, 2018 DOI: https://doi.org/10.3390/su10124438

C. March, Operations management for construction, Taylor and Francis, 2009 DOI: https://doi.org/10.4324/9780203928035

I. Suharto, Project management from conceptual to operational, Erlangga, 2017 (in Indonesian)

Project Management Institute, Inc., A guide to the project management body of knowledge, Sixth Edition, Newtown Square, 2017

K. Kupusamy, S. Nagapan, A. H. Abdullah, S. Kaliannan, S. Sohu, S. Subramaniam, H. Maniam, “Construction waste estimation analysis in residential projects of malaysia”, Engineering, Technology & Applied Science Research, Vol. 9, No. 5, pp. 4842-4845, 2019 DOI: https://doi.org/10.48084/etasr.2986

S. Sohu, A. H. Abdullah, S. Nagapan, T. A. Rind, A. A. Jhatial, “Controlling measures for cost overrun causes in highway projects of Sindh province”, Engineering, Technology & Applied Science Research, Vol. 9, No. 3, pp. 4276-4280, 2019 DOI: https://doi.org/10.48084/etasr.2749

Q. Yu, K. Li, H. Luo, “A BIM-based dynamic model for site material supply”, Procedia Engineering, Vol. 164, pp. 526-533, 2016 DOI: https://doi.org/10.1016/j.proeng.2016.11.654

R. E. Walpole, R. H. Myers, Probability & statistics for engineers & scientists, 9th edition, Prentice Hall, 2012

M. F. Quadratullah, Applied statistics: Theory, examples of cases and applications with SPSS, Andi Offset, 2014 (in Indonesian)

A. Mursadin, Module of applied statistical Volume 4: Measures of association, University of Lambung Mangkurat, 2019 (in Indonesian)

Downloads

How to Cite

[1]
Daslim, S. and Mursadin, A. 2020. A Control Model for Reinforced Concrete Work Materials on the Construction of Duta Mall 2. Engineering, Technology & Applied Science Research. 10, 2 (Apr. 2020), 5483–5486. DOI:https://doi.org/10.48084/etasr.3444.

Metrics

Abstract Views: 1016
PDF Downloads: 440

Metrics Information