Keywords
quality
compressive strength
costs
production
affecting factors
How to Cite
Abstract
Structured and unstructured factors affect concrete product. Structured factors are related to concrete production and unstructured factors are related to the construction process. This study focuses on examining the perceived importance of unstructured factors (i.e., construction-related factors) on concrete compressive strength, concrete costs and production rates on the jobsite and understanding the influence of construction experts"™ characteristics, such as profession, on their perceptions. A comprehensive literature review was performed to identify unstructured factors. A survey was then designed and deployed to 297 experts from the construction industry and academia to examine the importance of the identified factors through the relative importance index (RII) method and to further identify additional unstructured factors. Likert aggregation and tests for equality of odds were used to compare and analyze responses of two groups of participants, namely architects and engineers. Curing humidity, crew experience and compaction method are the top three factors perceived to affect concrete compressive strength, whereas crew experience, mixing time and compaction method are the factors perceived to affect concrete costs and production rates the most. Crew experience, compaction method and mixing time dominate the global ranking of perceived affecting factors for concrete compressive strength, costs and production rates. Architects were found to be more likely to perceive high or very high impacts of these factors on concrete. The present study increases our understanding of construction-related factors to facilitate project management and preserve concrete characteristics.
References
Neville, A. M. & Brooks, J. J. (2010). Concrete Technology (2nd ed.), Prentice Hall, Harlow, England.
Okasha, N. M. & Aichouni, M. (2015). Proposed structural reliability-based approach for the classification of concrete quality. Journal of Materials in Civil Engineering, 27(5), 04014169, doi: https://doi.org/10.1061/(ASCE)MT.1943-5533.0001131
Portland Cement Association (2015). Cement & concrete applications: Products, available at http://www.cement.org/cement-concrete-basics/products (accessed 17 February 2016).
Kosmatka, S. H., Kerkhoff, B. & Panarese, W. C. (2002). Design and Control of Concrete Mixtures (14th ed.), Portland Cement Association, Skokie, Ill.
Mehta, P. K. & Monteiro, P. J. M. (2006). Concrete: Microstructure, Properties, and Materials (3rd ed.), McGraw-Hill, New York, NY.
Demirboğa, R., Örüng, I. & Gül, R. (2001). Effects of expanded perlite aggregate and mineral admixtures on the compressive strength of low-density concretes. Cement and Concrete Research, 31(11), 1627-1632.
Jongpradist, P., Jumlongrach, N., Youwai, S. & Chucheepsakul, S. (2010). Influence of fly ash on unconfined compressive strength of cement-admixed clay at high water content. Journal of Materials in Civil Engineering, 22(1), 49-58, doi: https://doi.org/10.1061/(ASCE)0899-1561(2010)22:1(49)
O"™Connor, J. T. & Huh, Y. (2006). Crew production rates for contract time estimation: Beam erection, deck, and rail of highway bridges. Journal of Construction Engineering and Management, 132(4), 408-415, doi: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:4(408)
Jarkas, A. M. (2010). Analysis and measurement of buildability factors affecting edge formwork. Journal of Engineering Science and Technology Review, 3(1), 142-150.
Jarkas, A. M. (2012). Buildability factors influencing concreting labor productivity. Journal of Construction Engineering and Management, 138(1), 89-97, doi: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000404
Heravi, G. & Eslamdoost, E. (2015). Applying artificial neural networks for measuring and predicting construction-labor productivity. Journal of Construction Engineering and Management, 141(10), 04015032, doi: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001006
Yuan, Z., Wang, L.N. & Ji, X. (2014). Prediction of concrete compressive strength: Research on hybrid models genetic based algorithms and ANFIS. Advances in Engineering Software, 67, 156-163, doi: http://dx.doi.org/10.1016/j.advengsoft.2013.09.004
Rodríguez-Garzón, I., Martínez-Fiestas, M., Delgado-Padial, A. & Lucas-Ruiz, V. (2016). An exploratory analysis of perceived risk among construction workers in three Spanish-speaking countries. Journal of Construction Engineering and Management, 142(11), 04016066, doi: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001187
Dai, J., Goodrum, P. M. & Maloney, W. F. (2009). Construction craft workers"™ perceptions of the factors affecting their productivity. Journal of Construction Engineering & Management, 135(3), 217-226, doi: https://doi.org/10.1061/(ASCE)0733-9364(2009)135:3(217)
Lu, S. & Yan, H. (2013). A comparative study of the measurements of perceived risk among contractors in China. International Journal of Project Management, 31(2), 307-312.
Zhang, P., Lingard, H., Blismas, N., Wakefield, R. & Kleiner, B. (2015). Work-health and safety-risk perceptions of construction-industry stakeholders using photograph-based Q methodology. Journal of Construction Engineering & Management, 141(5), 04014093, doi: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000954
Tymvios, N. & Gambatese, J. A. (2016). Perceptions about design for construction worker safety: Viewpoints from contractors, designers, and university facility owners. Journal of Construction Engineering and Management, 142(2), 04015078, doi: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001067
Heeringa, S., West, B. T. & Berglund, P. A. (2010). Applied Survey Data Analysis, Chapman & Hall/CRC , Boca Raton, FL.
Laungrungrong, B., Mobasher, B., Montgomery, D. & Borror, C. M. (2010). Hybrid control charts for active control and monitoring of concrete strength. Journal of Materials in Civil Engineering, 22(1), 77-87, doi: https://doi.org/10.1061/(ASCE)0899-1561(2010)22:1(77)
Wight, J. K., Richart, F. E. & MacGregor, J. G. (2012). Reinforced Concrete: Mechanics and Design (6th ed.), Pearson Prentice Hall, Upper Saddle River, N.J.
Li, Z. (2011). Advanced Concrete Technology, Wiley, Hoboken, NJ.
Hassoun, M. N. & Al-Manaseer, A. A. (2012). Structural Concrete: Theory and Design (5th ed.), Wiley, Hoboken, N.J.
Unanwa, C. & Mahan, M. (2014). Statistical analysis of concrete compressive strengths for California highway bridges. Journal of Performance of Constructed Facilities, 28(1), 157-167, doi: https://doi.org/10.1061/(ASCE)CF.1943-5509.0000404
Chen, X., Wu, S. & Zhou, J. (2014). Variability of compressive strength of concrete cores. Journal of Performance of Constructed Facilities, 28(4), 06014001, doi: https://doi.org/10.1061/(ASCE)CF.1943-5509.0000513
Sears, S. K., Sears, G. A., Clough, R. H., Rounds, J. L. & Segner, R. O. (2015). Construction Project Management: A Practical Guide to Field Construction Management (Sixth ed.), Wiley, Hoboken, NJ.
Day, K. W. (1995). Concrete Mix Design, Quality Control and Specification, E & FN Spon, London, England.
Groves, R. M., Fowler, F. J., Couper, M. P., Lepkowski, J. M., Singer, E. & Tourangeau, R. (2004). Survey Methodology, Wiley, Hoboken, N.J.
Chambers, R. L. & Skinner, C. J. (2003). Analysis of Survey Data, John Wiley & Sons, Chichester, England.
Davies R. & Harty, C. (2013). Implementing site BIM: A case study of ICT innovation on a large hospital project. AUTCON Automation in Construction, 30, 15-24.
El-Gohary, K. M. & Aziz, R. F. (2014). Factors influencing construction labor productivity in Egypt. Journal of Management in Engineering, 30(1), 1-9, doi: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168
Gündüz, M., Nielsen, Y. & Özdemir, M. (2013). Quantification of delay factors using the relative importance index method for construction projects in Turkey. Journal of Management in Engineering, 29(2), 133-139, doi: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000129
Gunduz, M., Nielsen, Y. & Ozdemir, M. (2015). Fuzzy assessment model to estimate the probability of delay in Turkish construction projects. Journal of Management in Engineering, 31(4), 04014055, doi: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000261
Jin, R., Hancock, C., Tang, L., Chen, C., Wanatowski, D. & Yang, L. (2017). Empirical study of BIM implementation-based perceptions among Chinese practitioners. Journal of Management in Engineering, 33(5), 04017025, doi: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000538
Kometa, S., Olomalaiye, P. & Harris, F. (1994). Attributes of UK construction clients influencing project consultants"™ performance. Construction Management and Economics, 12(5), 433-443.
Odusami, K. T. (2002). Perceptions of construction professionals concerning important skills of effective project leaders. Journal of Management in Engineering, 18(2), 61-67, doi: https://doi.org/10.1061/(ASCE)0742-597X(2002)18:2(61)
Sambasivan, M. & Soon, Y. W. (2007). Causes and effects of delays in Malaysian construction industry. International Journal of Project Management, 25(5), 517-526.
Siegel, S. & Castellan, N. J. (1988). Nonparametric Statistics for the Behavioral Sciences (2nd ed.), McGraw-Hill, New York, NY.
Lavrakas, P. J. (Ed.). (2008). Encyclopedia of Survey Research Methods, SAGE Publications, Thousand Oaks, Ca.
Ramsey, F. L. & Schafer, D. W. (2013). The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed.), Brooks/Cole, Cengage Learning, Boston, MA.
ASTM International (2015). ASTM C31/C31M − 15a: Standard Practice for Making and CuringConcrete Test Specimens in the Field, ASTM International, West Conshohocken, PA.
ASTM International (2016). ASTM C39/C39M − 16b: Standard Test Method for Compressive Strength of Cylindrical Concrete Specimens, ASTM International, West Conshohocken, PA.
ACI Committee 318 (2014). Building Code Requirements for Structural Concrete (ACI 318-14): An ACI Standard: Commentary on Building Code Requirements for Structural Concrete (ACI 318R-14), an ACI Report, American Concrete Institute, Farmington Hills, MI.
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