• Journal of Construction Engineering and Project Management
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• v.3 no.4
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• pp.1-4
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• 2013

Excavation is most commonly used activity in all construction projects. All contracting agencies prefer to use bigger and heavier excavators and dumpers on site to do excavations if quantity of excavation is huge. Estimation of required number of excavators and dumpers for completion of excavation could be rather a tedious process involving repetitive calculation on which professionals spend their valuable time. As the Information Technology is highly involved in construction section there os need to have IT model for estimation of number of excavators and dumpers. The developed model is useful to calculate required equipments within short period of time. The purpose of the developed IT model is to save the time and efforts of the construction professional. The paper discusses about model which can be used on site to estimate numbers of excavators and dumpers required for completion of certain quantity of excavation within the given time. The calculation considers various existing formulas and method to generate the output. This information could certainly be useful in planning equipments on construction project sites. The tool is user friendly where any non IT background person can use it on construction sites.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.550-557
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• 2009

The concepts of 'sustainable development', 'sustainable construction' and 'green building' have been elevated to priority levels in all types and phases of construction project development worldwide. Consultants and contractors are now required to seriously consider the impact of their operations on the natural environment and the society, and consequently adopt sustainable construction practices in the development process to minimize and mitigate the negative impacts of their activities. However, existing sustainability rating tools apply to the design, post-construction and operation phases of a building; no tool exists for the rating of the performance of the contractor or the project team at the construction phase. This study aimed to develop a model for evaluating the sustainability of construction operations, drawing on the global best practice standards on sustainability. Practical applications of the model were carried out through case studies to evaluate the performances of fifteen construction firms in New Zealand. The developed model and the outcomes of the case studies were presented, including potential areas of weaknesses, strengths, constraints to achievement or adoption of sustainable construction practices and areas for improvement in the operations of the firms. The successful application of the developed model in practice shows its usefulness and ease of application. It is therefore recommended for adoption as a simple but effective system for measuring and reporting on sustainability performance or sustainability of construction operations of firms in New Zealand and elsewhere.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.768-773
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• 2005

Among various joint ventures, International Construction Joint Ventures (ICJVs) have emerged as a popular approach worldwide to developing large scale projects through international participation. A model, based on economic analysis and represented by several hypotheses obtained from the analysis, will be developed. Furthermore, we will empirically test the hypotheses/model using Structural Equation Model (SEM). This research is expected to explain why there exist different organizational forms for ICJVs, and to develop a framework for choosing appropriate forms with respect to various characteristics of ICJVs.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.382-388
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• 2011

Being aware of the risk in advance necessitates intricate processes but is feasible. Although previous studies have demonstrated high accuracy, their performance still leaves room for improvement. A self-organizing feature map (SOM) based neurofuzzy model is developed in this study to provide another alternative for forecasting corporate financial distress. The model is designed to yield high prediction accuracy, as well as reference rules for evaluating corporate financial status. As a database, the study collects all financial reports from listed construction companies during the latest decade, resulting in over 1000 effective samples. The proportion of "failed" and "non-failed" companies is approximately 1:2. Each financial report is comprised of 25 ratios which are set as the input variable s. The proposed model integrates the concepts of pattern classification, fuzzy modeling and SOM-based optimization to predict corporate financial distress. The results exhibit a high accuracy rate at 85.1%. This model outperforms previous tools. A total of 97 rules are extracted from the proposed model which can be also used as reference for construction practitioners. Users may easily identify their corporate financial status by using these rules.

• Architectural research
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• v.12 no.2
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• pp.85-92
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• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• Journal of KIBIM
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• v.14 no.1
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• pp.22-29
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• 2024

BIM is a practical and economical technology used in the construction process. Despite the fact that BIM is widely used in the design and another stage before construction, it is not largely applied during the construction stage itself. However, it is important to opt for BIM during construction stage because there may occur a number of risks such as construction delay and increased construction costs. Therefore, the present paper contains the analysis of the model use, which is mainly applied to respond to the BMI RFI that represents an information requirement of construction site workers, by analysing the BMI RFI application at the construction site. In addition, there is an analysis of the way the derived model use affects the project goal aimed at the project success.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.361-362
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• 2023

In construction work, there is often a difference between the estimated construction period and the actual construction period. Accordingly, the project may be delayed from the scheduled date, leading to huge losses due to problems such as increased costs during construction. In this way, it is important to calculate the appropriate construction period at the project planning stage in construction work. To solve this problem, we would like to study a model that will increase the accuracy of the scheduled construction period at the project planning stage. This study compared and analyzed linear regression, Lasso regression, Ridge regression among the types of regression analysis to select an appropriate construction period prediction model to secure an appropriate construction period at the project planning stage to reduce problems during construction.

• Journal of Construction Engineering and Project Management
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• v.1 no.2
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• pp.18-27
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• 2011

Egyptian construction firms (ECF) started recently to adopt quality management system (QMS) as a way to develop and improve their performance as previous studies have shown. However, considering all the firm's aspects in a competitive way is a crucial process for the ECF's culture. This research is trying to indicate the role of the QMS implementation in measuring performance (MP) through developing a model for measuring performance at the organizational level, and to explore its impact on the organizations that adopt QMS. This model is based on specific elements and their related indicators which have been derived from national approaches and models of MP. This model determines the performance level (PL) of the organization that is measured by means of a point system. Weights of the elements in the point system considered both the elements' importance in the international models and its real practice in the ECFs. This model has been validated using another questionnaire and the majority of surveyed experts agreed that the proposed model can be applied effectively.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.9-16
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• 2014

The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.