Duration Of Construction Projects Research Articles

Analysis of the Application of Hollow Core Slab to Cost and Time Efficiency in High Rise Building Construction Project

The floor slab is one of the factors that affect the cost and duration of construction projects because it has the largest volume of work among other jobs. The selection of the method of implementation of floor slab work also affects the efficiency of development. The use of precast slabs can be an alternative to conventional floor slabs because of their potential to increase cost efficiency, speed up implementation time, and increase structural durability. In this study, a comparative analysis of cost efficiency and scheduling time of precast hollow core slab (HCS) method as an alternative to conventional slabs was conducted, using primary data obtained from the project and in accordance with government regulations. Time analysis and scheduling were calculated with the help of Microsoft Project software and determination of plate work items. As for the cost analysis, it is calculated based on the literature and applicable regulations to get real results by field conditions. Based on the analysis, it is known that the implementation of the 4-storey building slab work with the alternative precast slab method takes 8 days and costs Rp. 1,691,887,497. While the conventional slab method takes 38 days with a total cost of Rp. 2,276,920,601.

VISUALISASI METODE PELAKSANAAN PEKERJAAN PELAT RAMP PROYEK PEMBANGUNAN GEDUNG WAREHOUSE DEPOK

The Project of Depok Warehouse Building Construction is located at JL. Raya Jakarta-Bogor, KM. 35, Jatijajar, Depok City, West Java, 16415. The project of Depok Warehouse Building is built on a land area of 38,000 m2, with a building area of 24,000 m2. The Depok Warehouse Building has 8 floors, consisting of 5 floors for the building area and 3 mezzanine floors used for offices. PT. Depok Logistik Properti is the owner of the project, PT. Trimatra Jasa Prakarsa as the construction management, PT. Gistama Intisemesta as the planning consultant, and PT. Total Persada Indonesia as the main contractor. The type of contract used is a lump sum with a contract value of Rp 350,000,000,000. The planned duration of the Warehouse Building Construction project is 670 days. Research made on the field include upper structure works such as column, beam, floor slab, and ramp slab. The stages of the implementation method for the ramp Truck Plate Work start from preparation, marking, reinforcement fabrication, reinforcement installation, concrete decking installation, reinforcement checklist, formwork installation, verticality test, casting, formwork removal, and concrete curing.

Artificial Neural Networks for Construction Project Cost and Duration Estimation

Artificial Neural Networks for Construction Project Cost and Duration Estimation

Estimation of building project completion duration using a natural gradient boosting ensemble model and legal and institutional variables

Estimation of building project completion duration using a natural gradient boosting ensemble model and legal and institutional variables

Investment process and the ways to reduce the duration of investment construction projects

The urgent task of the state is to intensify investment activities and significantly increase the volume of investments.
 The general legal, economic and social conditions of investment activity on the territory of Ukraine are defined by the Law of Ukraine "On Investment Activity", which is aimed at ensuring equal protection of the rights, interests and property of subjects of investment activity regardless of the forms of ownership, as well as at effective investment of the economy of Ukraine. development of international economic cooperation and integration.
 The investment process means constant and growing investment of capital in material production for the purpose of successful social and economic development of Ukraine. For construction, the investment process means the creation of specific objects (or their complexes) for production and non-production purposes in the interests of specific investors (investor). The investment process consists of the implementation of separate investment construction projects (ICP). Each ICP is characterized by the duration of the life (or investment) cycle, which is measured by the interval of calendar time from the date of making the investment decision to the moment when the project goal is achieved. There are three stages of this cycle: justification of the idea and planning of investment, development of funds, reimbursement of invested funds or achievement of the project goal.
 The article examines the main, key procedures of each stage, which emphasize the importance of solving the financing issue, since the full set of procedures depends on the scope of the project. Reducing the duration of the investment cycle of a construction project depends on the intensification of each of its stages. The main factors affecting the reduction of the duration of each stage of the investment cycle of the construction project are given.
 The results of the conducted research should be taken into account in the further improvement of the legislative acts of Ukraine in order to activate investment activities and significantly increase the volume of investments in Ukraine.

Estimating Construction Project Duration and Costs upon Completion Using Monte Carlo Simulations and Improved Earned Value Management

Earned value management (EVM) is widely used when monitoring and estimating operations related to construction projects. As the scope and complexity of construction projects expand, traditional EVM is sometimes ineffective and even results in conclusions that are contrary to the actual situation. Additionally, the estimate produced by EVM is a deterministic value that does not account for the uncertainty of activities involved in a construction project. This study proposes an estimation approach that combines an improved EVM, critical path method (CPM), program evaluation and review technique (PERT), and Monte Carlo simulation (MCS). The contribution is threefold. Firstly, a path-based schedule measurement approach is described using network diagrams and CPM to capture the logical relationships among activities. Secondly, the resource input categorizes activities to improve the accuracy of the duration and cost estimates. The remaining duration and cost will be estimated based on the execution performance of the activities in the same category. Thirdly, PERT and MCS approaches are used to reveal the uncertainty of estimates upon completion by replacing a deterministic value with a possible completion range. An experimental research study was used to apply the proposed approach. The result displayed that the commercial expansion project faced serious schedule delays and cost overruns. Based on the result, the project manager should focus highly on activities J, H, and G (in order of priority) and take corrective actions. In conclusion, the proposed approach demonstrates good performance when identifying deviations, estimating precise results, and determining the importance (priority) of activities that need to be controlled.

The Impact of Lean Thinking on Organizational Learning

Purpose: The purpose of this paper is to investigate the effect of the lean concept on organizational learning in the real estate industry. The objectives are to determine the impact of the lean concept on knowledge and leadership and evaluate the challenges affecting the implementation of lean and provide recommendations to remedy the situation.
 Design/Methodology/Approach: The study employed a quantitative method. Questionnaires were used to measure the variables. A five-point Likert scale was used for both lean thinking to measure the various perspectives and dimensions. The questionnaires were administered to 200 respondents drawn from the real estate industry in Ghana using a simple random sampling technique. The data collected was then summarized through relevant thematic areas and analyzed statistically through descriptive statistics, correlations and multiple regression to establish the nexus between lean concept and organizational learning with help of SPSS version 22.
 Findings: The finding of the study established that lean thinking affects organizational learning except for experience sharing. The findings also revealed that the lean concept has a positive effect on development, leadership and organizational culture.
 Research Limitations: The study focused on the effects of lean thinking on organizational learning in the real estate industry in Ghana. Hence the questionnaires were administered mainly to 200 companies in the real estate industry in Ghana.
 Practical Implication: The knowledge advanced in this study will help managers of real estate companies as a matter of necessity embrace lean thinking if they are to meet customer-focused requirements, remain profitable and shorten the duration of construction projects, waste elimination and cost reduction.
 Originality/Value: This paper is focused on the effects of lean principles on organizational learning in the real estate industry with a positive impact on organizational development, leadership and organizational culture.

DETERMINATION OF CONSTRUCTION PROJECT DURATION WITH ARTIFICIAL INTELLIGENCE

Aim: With Industry 4.0, the period of digitalization has begun in the construction industry, as in many other industries. The use of artificial intelligence techniques or algorithms instead of traditional methods to solve the problems experienced in construction projects and increase the risk of the project has increased in recent years. These studies have shown that artificial intelligence techniques or algorithms give successful results in solving problems in construction projects. This study investigates the applications of artificial intelligence techniques on construction project duration and demonstrates the use of the Gene Expression Programming method in estimating construction project duration. Method: In this study, analyzes were made with Gene Expression Programming (GEP) technique to estimate the project duration by using the variables of the number of floors, floor area and total construction area of 71 construction projects (60 training and 11 test data) built between 2011-2016. Results: The determination coefficient (R2) for this study was calculated as 0.78 for the training set and as 0.72 for the testing set. Conclusion: In this study, it has been seen that the ability of the created algorithm to estimate the construction time with limited data provides partially acceptable performance.

Bim Machine Learning and Design Rules to Improve the Assembly Time in Steel Construction Projects

Integrating the knowledge and experience of fabrication during the design phase can help reduce the cost and duration of steel construction projects. Building Information Modeling (BIM) are technologies and processes that reduce the cost and duration of construction projects by integrating parametric digital models as support of information. These models can contain information about the performance of previous projects and allow a classification by linear regression of design criteria with a high impact on the duration of the fabrication. This paper proposes a quantitative approach that applies linear regressions on previous projects’ BIM models to identify some design rules and production improvement points. A case study applied on 55,444 BIM models of steel joists validates this approach. This case study shows that the camber, the weight of the structure, and its reinforced elements greatly influence the fabrication time of the joists. The approach developed in this article is a practical case where machine learning and BIM models are used rather than interviews with professionals to identify knowledge related to a given steel structure fabrication system.

Life Cycle Assessment of Biocement: An Emerging Sustainable Solution?

Microbially Induced Calcium Carbonate Precipitation (MICP) is a natural biocementation that takes place in corals, stromatolites and beach rocks. In recent years, researchers have explored the emulation of this process as a sustainable alternative of engineered cement. Although the natural process is undoubtedly sustainable, its engineered variant deviates substantially from the natural process. In this paper, we investigate the environmental and economic performance of the engineered biocementation process vis-à-vis present manufacturing of calcium carbonate. SimaPro 8.0 software and the Ecoinvent V2.2 database were used for materials inputs and AUSLCI along with Cumulative Energy Demand 2.01 software were used for carbon footprint and eutrophication potential. Our results show that different metabolic pathways of MICP have considerably varying environmental impact. We observe that nature performs MICP sustainably at ambient conditions and geological time scales utilizing naturally occurring sources of carbon and calcium at micromoles concentrations. Due to the mandate on duration of construction projects, highly purified reactants in a high concentration are used in the engineered process. This has a negative environmental impact. We conclude that the sustainability of engineered MICP is directly impacted by the metabolic pathway of bacteria as well as the purity of the input chemicals. A few biotic processes are superior to the present industrial process for manufacturing calcium carbonate if ingredients of laboratory grade purity are replaced by industrial grade products. A bigger dividend can be obtained by introducing industry by-products as nutrients. The results of this study help to direct future research for developing sustainable biocement for the construction industry.

Stochastic scheduling optimization of repetitive construction projects to minimize project duration and cost

Considering risk and uncertainty during the scheduling optimization of repetitive construction projects is a challenging task. This article presents the development of a novel multi-objective stochastic scheduling optimization model for minimizing the expected project duration and cost of repetitive construction projects. The developed model integrated Monte Carlo simulation with a multi-objective genetic algorithm to: (1) consider uncertainties associated with the production rates of the construction crews; and (2) identify an optimal crew formation and crew deployment date for each activity that minimize the project duration and cost. The performance of the developed model was analyzed using a real-life case study that highlighted the novel model capabilities in generating a set of optimal trade-off solutions between expected project duration and cost while considering all uncertainties in crew production rates. These novel capabilities of the developed model enable construction planners to identify and implement an optimal resource utilization plan that account for inherent project risks.

Earned Duration Management Control Charts: Role of Control Limit Width Definition for Construction Project Duration Monitoring

AbstractThe design of control charts refers to the selection of the sample, the sampling interval, and the width of the control limits. The literature on the use of control charts for project monit...

Use of the EVM method for analysis of extending the construction project duration as a result of realization disturbances - case study

Use of the EVM method for analysis of extending the construction project duration as a result of realization disturbances - case study

Optimization of Earthmoving Operations Planning: A Novel Approach Considering Interferences

Abstract The purpose of this paper is to present an optimization model for planning the distribution of materials in earthmoving operations, considering possible interferences between cut-and-fill sections such as rivers, vegetation, topographical features, or expropriations. The earth allocation problem incorporating interferences was modeled as a linear programming problem, aiming to minimize the total earthmoving cost while considering the constraints related to volume balance, construction project duration, and time for the release of traffic. The proposed linear programming model was run by an integrated system, using Excel for data analysis and IBM CPLEX as the optimizer. The mathematical model was evaluated by a sensitivity analysis and validated by a real-world project of a dam access road in the state of Ceará, Brazil. The unit costs and productivity rates used in the fictional example and in the real-world application followed the referential cost system created by Ceará’s Secretariat of Infrastructure (SEINFRA-CE). The proposed optimization model achieved reasonable processing times for all tested applications, presenting itself as a viable and efficient option for planning earthmoving operations. Furthermore, the linear programming approach provided a 2.12% cost reduction for the real-world case study, when comparing the optimized solution and original budget. This study explored the problem of earth allocation with interferences using a linear programming approach, while avoiding complex modeling issues found in recent literature. As a result, this paper proposes a user-friendly optimization system that can be easily utilized by construction companies and departments.

A Comparative Study of Models for the Construction Duration Prediction in Highway Road Projects of India

Predicting the duration of construction projects with acceptable accuracy is a problem for contractors and researchers. Numerous researchers and tools are involved in sorting out this problem. The aim of the study is to predict the construction duration using four analytical tools as an approach. The success of construction projects in regard to time depends on various factors such as selection of contractors, consultants, cost of the projects, quality of the projects, the quantity of the projects, environmental factors, etc. Presently available commercial tools in the market are not designed as universally common and concerned. Every tool performs well in a particular situation. The prediction of India’s highway road projects duration is the biggest construction issue in the country due to various reasons. To overcome this problem, the methodology of the paper adopts various strategies to find suitable tools to predict the highway road projects’ duration, in which it classifies and analyzes the collected data. As a part of this work, the details of 363 government infrastructure projects (traditional procurement) were collected from 2000 to 2018. The present study also adopts various tools for duration prediction such as artificial neural networks (ANNs), smoothing techniques, time series analysis, and Bromilow’s time–cost (BTC) model. The results of the study recommend smoothing techniques with a constant value of 0.3, which gave the remarkable very small error of 1.2%, and its outcomes become even better when compared to other techniques.

Extension of Time (EoT) Considerations in Construction Duration Estimate for Public Construction Projects

Construction duration is defined as the time frame given by the Client of a project use to complete the project under normal working conditions, practice of construction. However, often times, projects faced time overruns and hence, needing to activate contractual remedies like Extension of Time (EoT). This paper aims to investigate the factors related to award the Extension of Time (EoT) for construction projects in especially in the public sector in Sarawak. A structured checklist was created as an instrument and employed to accomplish the objective of this research. A total of 111 previous public projects which were granted EoT were studied. The findings revealed several detailed factors that had typically led to project delays in the State. These findings are expected to offer the construction industry stakeholders in Sarawak a focal point on those delay that could be included in construction project duration estimates and management of construction performances, followed by the appropriate corrective and improvement measures for time management for construction projects.

Disparities of Factors Affecting the Duration of Construction Projects Among Countries

Delay is one of the most prevalent challenges that hamper the completion of construction projects. Previous studies have presented a substantial number of factors that cause delays. This research aims to identify the causes of construction project delays in many countries and highlights the discrepancy in these studies in terms of identifying the factors and ranking them according to their importance. Data have been derived from secondary sources through a detailed review of the related literature. The studies have been filtered to identify the top five factors that cause project delays. The collected data have been analyzed using different statistical tools. The analysis highlights the significant factors causing delays and the relationship of each factor with the country wherein a project is located. The results of this study provide a clear vision of the significant factors that cause delays in construction projects, thereby allowing the authorities to devise strategies to avoid these problems.

Risk Assessment and Prediction of Construction Project Based on 1D-CNN-Attention-BP

In order to solve the problem of low accuracy of construction project duration prediction, this paper proposes a CNN attention BP combination model project risk prediction model based on attention mechanism, one-dimensional convolutional neural network (1d-cnn) and BP neural network. Firstly, the literature analysis method is used to select the risk evaluation index value of construction project, and the attention mechanism is used to determine the weight of risk factors on construction period prediction; then, BP neural network is used to predict the project duration, and accuracy, cross entropy loss function and F1 score are selected to comprehensively evaluate the performance of 1d-cnn-attention-bp combined model. The experimental results show that the duration risk prediction accuracy of the risk prediction model proposed in this paper is more than 90%, which can meet the risk prediction of construction projects with high accuracy.

Engineering contract of construction industry (Subcontract) in Libya

There is an ever-growing body of literature related to construction contracts, administration, claims and disputes. Much of this is contextualized from the owner-general-contractor relationship perspective. Despite the prevalent engagement of subcontracting, approximately 80% of the work is done by subcontractors; the treatment of distinctively sub-contractual issues in such literature is relatively limited. Any special focus on subcontracts is often written with, "us against them" overtones, emphasizing the perspective of either the subcontractor or the general contractor. The hypothesis of this research centered upon Subcontracting being essential and necessary in the construction sector irrespective of building project complexity, and subcontracting is exposed to substantial risks, therefore, it being imperative to understand means and methods of regulation of subcontractor selecting to limit risk. Publications from a variety of research and sources were reviewed concerning the subcontractor's role, procedures, types, and relationships, administration of subcontractors and subcontracting work and risks in selecting subcontractors. Subsequently, what is presented in the findings is the necessity of subcontractor selection and its impact on the cost, duration and quality of construction projects and the associated risks of subcontracting. A comparative aspect is presented evaluating the Libyan Contractual Conditions relative to Subcontracting Work and the shortage in the items that concern the subcontracting work. Furthermore, the research has also sought to identify and provide the main contractor with an effective instrument of selecting his subcontractors.

Impact of familiar collaboration on construction project quality: perceptions from clients and contractors in Singapore's construction industry

PurposeDue to the fragmented and complex nature of the construction industry, many countries, including Singapore, have progressively encouraged greater collaboration amongst major stakeholders in the industry. It is hoped that doing so will result in an increase in the quality of construction projects. Given the long duration of typical construction projects, it is plausible for collaborating parties to develop close and personal relationships. In recent years, corruption cases arising from familiar collaboration have caught the public's attention. This study seeks to better understand familiar collaboration and its adverse impacts on the quality of construction projects.Design/methodology/approachA mixed research method was adopted, with a questionnaire survey distributed to 32 respondents representing client and contractors. This was followed by interviews to validate the survey findings.FindingsThe findings suggest that, when there is a lack of surveillance, familiar collaboration is likely to lead to favouritism and dishonesty, which can have an adverse impact on the quality of construction projects. The findings additionally suggest that value for money, conformance to specifications and fitness for purpose are the main aspects of quality that are likely to be adversely affected by corrupt practices bought about by familiar collaboration.Originality/valueIn this paper, these relationships are described using the term familiar collaboration. Strong and intimate relationships of this type may lead to a danger of parties committing corrupt practices. This study is one of the very attempts seek to better understand familiar collaboration and its adverse impacts on the quality of construction projects.