Regression model for predicting productivity of RC slab concreting process

doi:10.14256/jce.1538.2016

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Construction productivity provides the basic information for cost estimates, budget planning, and scheduling of construction activities [22,23]. Management practices for increasing productivity can vary considerably between project types and countries, as well as between different local construction markets [24].…”

Section: Context Of This Studymentioning

confidence: 99%

Potential management factors influencing construction projects

2023

JCE

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Project management is the application of specialized knowledge, abilities, techniques, and methodologies to deliver something of value to people. To measure these applications, terms such as productivity, performance, and efficiency are utilised. In addition, construction is a highly competitive industry that necessitates the enhancement of management-oriented aspects. Thereby, this study focused on identifying the potential management factors that influence construction projects. From the literature, the factors were collected and grouped as organisation system, operational management, management & control, management & limitation, and recruitment & selection. Questionnaire survey was opted as the research method and was completed among the frontline practitioners in the Indian construction industry. As a result, 108 responses were analysed using the frequency tests, reliability tests, and the relative importance index (RII). The findings highlight the importance of resource availability, individual learning, decision making, proper work design, and resource allocation as the most influencing management factors. Moreover, this study provides improved insights for management teams and allows them to focus on the influencing factors that are necessary to execute a project successfully.

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Section: Context Of This Studymentioning

confidence: 99%

Potential management factors influencing construction projects

2023

JCE

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Comparative Representation of Two Models for Predicting the Productivity of Column and Wall Concreting Process

Matejević-Nikolić

Živković

2022

Buildings

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One of the most important tasks of managing the construction process is to achieve the highest possible productivity. The productivity that can be achieved on a construction site depends on a number of influencing factors and on the type of work that is executed. Concrete works are a crucial activity when constructing high-rise buildings built in the RC frame structural system. Therefore, it is very important to adequately manage the concreting process in order to meet the set deadlines and reduce costs. This paper presents an approach for predicting the productivity of the concreting process based on the conducted quantitative research, by recording the concreting process on construction sites of buildings in Niš, Serbia. The concreting of reinforced concrete columns and walls on seven construction sites was recorded for 20 months. The total amount of fresh concrete that is built into the elements is 848 m3 and the total duration is 114 h of work. Factors that can affect productivity have been identified and, by applying the multiple linear regression and simulation methods and techniques and using the discrete event method and the agent-based method, models have been developed to predict the productivity of the concreting of reinforced concrete columns and walls. An analysis of the developed models was performed, and a comparative presentation was provided.

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Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review

et al. 2021

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Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance.

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Regression model for predicting productivity of RC slab concreting process

Cited by 3 publications

References 12 publications

Potential management factors influencing construction projects

Potential management factors influencing construction projects

Comparative Representation of Two Models for Predicting the Productivity of Column and Wall Concreting Process

Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review

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