Construction Project Cost Control Research Articles

Application Analysis of BIM Technology in Construction Engineering Cost Management

With the rapid development of information technology, Building Information Modeling (BIM) technology has gradually occupied an important position in the construction industry. With the introduction of BIM technology, the cost control of construction projects can be greatly improved [1]. The use of this technology can not only reduce the project approval time but also improve the quality of the project. In addition, it can also help the construction personnel to solve the project changes, maintenance costs, insurance rates, and other related issues, so that the operation of the project is more efficient and economical. This paper will discuss the role of BIM technology in depth, and explore the advantages and disadvantages of each link through the research of the project, to provide a reference for the promotion of this new project. By constantly adjusting the application strategy, the goal is to meet the current market demand.

Discussion on Construction Project Cost Budget Settlement Review

Construction project cost control involves many complex contents, forming a large amount of data information. If the processing method is unreasonable, it will likely affect the cost control efficiency. Therefore, in the current construction project management, the review of project cost budget settlement is the focus to solve the cost management problems of construction projects and promote the development of the construction industry. This article mainly analyzes the influencing factors and current situation of construction project cost budget settlement review, and based on this, it explores the project cost budget settlement review strategy to promote the healthy development of construction project cost work.

A model for the application of big data analytics in cost prediction and control in construction projects

Abstract Construction project cost control is an important aspect of project management. This paper aims to provide an effective cost control management mode for the construction industry by studying the application of big data technology in cost prediction and control management of construction projects. The standard particle swarm algorithm is optimized by establishing a particle object element model, performing iterative and hierarchical updating of particles, and introducing the Tent mapping strategy. Then it is used in the optimization of the Extreme Learning Machine algorithm to design a construction project cost prediction and control model based on APSO-LLM. The index system of the construction project cost prediction and control model is constructed, and the convergence effect, prediction effect, and case application of the model are analyzed. The APSO-LLM model enhances the convergence speed and search accuracy, boosts the optimal fitness by 0.037, and maintains a construction cost prediction error below 3%. The study proves the APSO-LLM model’s applicability, accuracy, and good prediction effect in cost prediction and construction project control.

Research on the Path of Cost Control and Economic Benefit Enhancement in Construction Engineering Projects

Abstract The increasingly competitive market situation in the construction industry requires that construction enterprises strengthen the cost control of construction projects in order to improve the economic efficiency of enterprises. This paper is based on the improved genetic algorithm to realize the optimization of the cost control strategy of the construction project and effectively overcome the problems of weak cost control consciousness and high material procurement cost in the previous cost control. A construction company is selected as the object for the case study, and the genetic algorithm is used to calculate and analyze the cost control of the construction company. The return on investment, net present value, and internal rate of return are used as indicators to measure the economic benefits before and after optimizing cost control strategies. The improved genetic algorithm calculates that among the cost control factors of the construction company, procurement management, and field operation have a high probability of being selected in the genetic calculation, and the final project cost is 36.7849 million yuan through the genetic algorithm, which achieves the goal of project cost control. At the same time, this paper finds that cost control has a significant positive effect on the improvement of economic efficiency, and the economic efficiency of this construction company before and after the optimization of the cost control strategy is significantly improved.

Study on the application of construction project cost control in China

Project cost control is a hot issue in construction enterprise management and a key factor to determine the return on project investment. With the continuous summary of modern project management experience, systematic, comprehensive and dynamic management methods and ideas gradually began to be adopted. As a controllable system, cost system is the key to determine the market competitiveness of construction enterprises. This paper combines qualitative research with quantitative research, normative research with empirical research, theoretical research with practical research, and makes comprehensive use of previous research results to provide guidance for the practical operation of cost control in construction enterprises. Firstly, it introduces the important factors affecting the cost and the background and purpose of the project cost control, and then analyzes the object and content of the project cost control and analysis. Finally, the phenomenon of "three super" and the deviation of the project cost are analyzedd and discussed. It is of great practical significance to study project cost control for promoting the reform of investment system and improving market competitiveness of construction enterprises.

The Importance of Cost Control of Construction Projects

The Importance of Cost Control of Construction Projects

Research on Construction Cost Control Technology of Construction Project Based on Big Data Analysis Theory

The current methods proposed in construction cost control of construction projects have problems such as applicability and low accuracy. Therefore, this paper proposes a method for evaluating engineering cost control based on the big data Analytic Hierarchy Process (AHP) method. Based on the big data technology, the construction cost control index of the construction project is selected, and the construction cost control index model of the construction project is constructed according to the selection results, and the evaluation set is constructed. The corresponding weights of the construction cost control indicators of each construction project are obtained through the analytic hierarchy process, and a weight set is constructed. The membership relationship between the index set and the evaluation set is determined, a fuzzy relationship matrix is constructed, and the construction cost control result of the construction project is obtained according to the calculated weight and the constructed fuzzy relationship matrix. The test results of examples show that the risk assessment accuracy of the proposed method is higher than that of ordinary methods, and the quantitative processing of audit risk assessment is realized.

Analysis of the Practical Application of Project Budget in Construction Project Cost Control

Analysis of the Practical Application of Project Budget in Construction Project Cost Control

Research on Costing and Cost Control of Construction Projects Based on BIM Technology

Research on Costing and Cost Control of Construction Projects Based on BIM Technology

Cost Control Analysis of Construction Projects Based on Wireless Communication and Artificial Intelligence Decisions

In decades of development, the country has been vigorously developing infrastructure projects and providing a steady stream of help, so our infrastructure strength has always been world’s top part. But now, because of the vigorous development of environmental protection enterprises, a variety of raw materials and environmental treatment costs are getting higher and higher, in order to maintain the profitability of enterprises, so we need to carry out cost control of construction projects to ensure a certain profit. In recent years, various emerging terms such as artificial intelligence and big data have become more and more popular, so in order to ensure the stability of the industry, it is imperative for the construction industry to introduce new technologies for the technological revolution. Wireless communication is also widely used with artificial intelligence to build systems because of the fast speed of interaction. In order to ensure the steady development of the construction industry in the future, we need to control the cost of the project and the introduction of high-tech. The purpose of this paper is to control the cost of construction projects by means of wireless communication and artificial intelligence decision-making. After reviewing the history of the construction industry in recent decades, as well as the price fluctuations of building materials and the relevant laws and regulations on environmental protection and construction in recent years, this paper uses the emerging artificial intelligence and traditional wireless communication methods to carry out the traditional project cost control experiments. After a period of experiments, people found that the use of wireless communication with artificial intelligence decision-making ability can be very good control of construction project costs in a certain range, to ensure the profitability of the project and the maximum use of materials.

Research on optimization of construction project cost control in construction enterprises

As a pillar industry of the national economy, the construction industry plays an important role in promoting economic growth, social stability and improvement of quality of life of people. Influenced by the deepening reform of the market economy system and the normal prevention and control of the COVID-19 epidemic, the construction market has increasingly high requirements and the market competition is becoming increasingly fierce. The major enterprises compete with each other to obtain the project at a low price, which seriously disturbs the market order and further compresses the market profit space. In the limited market share, in order to improve their competitiveness, cost control has become the focus of construction enterprises. This paper analyzes the current situation of cost control of construction projects in construction enterprises, finds out the existing problems and puts forward countermeasures and suggestions in order to realize the dynamic cost control of the whole process of construction projects.

Discussion on Cost Control Strategy in the Process of Engineering Project Construction

Rapid socio-economic development, promoting the development of the construction industry. Companies want to stand out from the fierce market competition, must strengthen the cost control of construction projects. This paper elaborates the importance of cost control of engineering construction projects, and then proposes that the dilemmas faced by cost control management of engineering construction projects are: inadequate market research of raw materials, lack of high-quality cost management talents, imperfect cost management system, neglected cost management work, lack of supervision and regulation of cost management work, and finally proposes that the cost control strategies in the process of engineering project construction include clarifying the cost control objectives of engineering cost, cultivating professional cost control talents, deepening the innovative cost management system, increasing the supervision and regulation of cost of the whole process of engineering, and ensuring the reasonableness of the cost budget plan. We hope to further promote construction companies' attention to cost control of engineering price construction projects.

Research on cost management of engineering projects in state-owned construction enterprises: taking the red line cost budget management practice of a project of China Railway Group Co., Ltd. as an example

<p>Based on a systematic consideration of the development dilemmas and outlets faced by state-owned construction enterprises, this paper demonstrates the need for state-owned construction enterprises to carry out cost management during the transition from “incremental expansion” to “intensive development”, and systematically summarizes the main factors of impact of costs management. Combined with the practice of carrying out project red line cost budget management by a China Railway Bureau Group Co., Ltd., it gives suggestions for the implementation of key points and safeguard measures for cost control of construction projects carried out by state-owned construction enterprises.</p>

Application of Data Mining Technology in Field Verification of Project Cost

The traditional budget quota pricing model seems incompatible with the continuous development of the market economy. Low degree of visualization, extensive resource management, difficulty in collecting construction data, lagging control work, and separation of cost control from project management have become the main problems of current construction project cost control. This paper combines data mining technology to improve the project cost on-site verification network system, build a project cost verification system that can be used for on-site verification, and build a cost information platform. Moreover, this paper makes full use of computer information technology and uses the local area network and network as the basis to transform the vertical transmission of cost information into horizontal, so as to ensure the effective communication and exchange of cost information. According to the analysis of the case study, it can be seen that the project cost field verification method based on data mining proposed in this paper is very effective, and the system proposed in this paper can be used in actual projects.

Analysis on Procurement Management and Procurement Cost Control of Construction Projects

Analysis on Procurement Management and Procurement Cost Control of Construction Projects

Optimal Mix Ratios of Green Building Materials and Construction Cost Control

Green concrete wall-building composite materials (namely GBMs, green building materials for short) have superior mechanical properties and good durability, thus they are now a high-profile topic in relevant research field. However, due to the existence of risk factors such as the high initial cost, and unclear policy direction, the promotion of GBMs has been greatly limited. In this context, it is a necessary work to study the cost control of construction projects, and figure out the relationship between the saving of building operating cost and the increase of initial construction cost. For this purpose, this study experimented on the optimal mix ratios of GBMs to control the construction budget of engineering projects. At first, this paper modeled the strain-hardening and steady-state cracking of GBMs, and constrained the models based on the bridging rule, the energy criterion, and the strength criterion. Then, this paper constructed a fractal model for the dense effect of powder particles in the aggregates of the GBMs, and analyzed its fractal features; after that, this paper designed the mix ratios of GBMs and experimented on the mechanical properties; at last, this paper constructed a production cost-use benefit model of the GBMs, completed the construction budget control of the engineering project, and gave experimental results of the performance of GBMs and the use cost calculation and analysis results.

Predicting Performance Measurement of Residential Buildings Using an Artificial Neural Network

Application Earned Value Management (EVM) as a construction project control technique is not very common in the Republic of Iraq, in spite of the benefit from EVA to the schedule control and cost control of construction projects. One of the goals of the present study is the employment machine intelligence techniques in the estimation of earned value; also this study contributes to extend the cognitive content of study fields associated with the earned value, and the results of this study are considered a robust incentive to try and do complementary studies, or to simulate a similar study in alternative new technologies. This paper is aiming at introducing a novel and alternative method of applying Artificial Intelligence Techniques (AIT) for earned value management of the construction projects through using Artificial Neural Networks (ANN) to build mathematical models to be used to estimate the Schedule Performance Index (SPI), Cost Performance Index (CPI) and to Complete Cost Performance Indicator (TCPI) in Iraqi residential buildings before and at execution stage through using web-based software to perform the calculations in the estimation quickly, accurately and without effort. ANN technique was utilized to produce new prediction models by applying the Backpropagation algorithm through Neuframe software. Finally, the results showed that the ANN technique shows excellent results of estimation when it is compared with MLR techniques. The results were interpreted in terms of Average Accuracy (AA%) equal to 83.09, 90.83, and 82.88%, also, correlation coefficient (R) equal to 90.95, 93.00, and 92.30% for SPI, CPI and TCPI respectively. Doi: 10.28991/cej-2021-03091666 Full Text: PDF

Towards a framework of automated resource model for post contract cost control of construction projects

Real-time control of on-site construction cost has been a major concern as every client demand value for the money invested in procuring a construction project. The design team and other stakeholders in the construction industry face the challenges posed by the ever-increasing complexity of construction facilities, and the demands of clients to meet their needs within a given budget. In addition, the trend of information technology in construction demands that all activities including cost optimization be automated and digitalized for better proficiency of the construction professionals and effectiveness of job delivery. This article presents a conceptual framework for the automated resource model (ARM) for on-site construction cost control. The concept of ARM is based on the use of mobile technology, integrating it with a back-office central system for real-time data capturing, monitoring, and control to keep expenditure within a predetermined budget. The scope covered includes Automated Real-Time Data (ARTiD) collection, Construction Progress Monitoring and Evaluation, and Construction Activity Monitoring. The ARM concept can enable the construction stakeholders to obtain information on cost implications of all activities simultaneously. It can also enable quick detection of any source of cost and time overrun and propose quick remedial action.

Management and Cost Control of Construction Projects in Jordan

The variations in time and quality are vital to the projects' success. Though the cost variation is the most impacting variation, the objective of this study is to recognise the significance of the cost controls in the construction projects in Jordan. Moreover, it aims to determine the factors that lead to reduce these costs. For the methodology, the study used the questionnaire instrument for the data collection. The study sample entailed 154 respondents who hold the responsibility in relevance positions with experiences in contracting and consultants engineering field in Jordan under first and second-grade classification. The study results revealed that there is a significant relationship between cost reduction and all investigated factors, namely, the demographic variables, the pre-execution conditions and specification, and managerial, technical, or financial dimensions. Further, the results showed a significant impact of proper resource planning. In summary, the key factors affecting the project cost during the pre-execution stage involves the appropriate resources planning (i.e., workforce, funds, data). In details, the most critical factors affecting the project cost from managerial dimension are the project manager assignment and integrity of consultant. For the technical dimension, the elements are the skilled workers, the applied methods, the statements and specifications. Lastly, for the fund allocation dimension, the most critical factors that affect the project cost from a financial point of view. Lastly, a set of recommendations are proposed to the project managers to reduce the cost.

Construction Project Cost Control Measures

The construction project cost control is a comprehensive discipline, focus on technology, economy and management. Through effective project cost budget control, can obtain greater benefits for the enterprise. This article from the influence factors of the construction project cost to the common problems of the construction project cost budget control, and how to enhance the project cost budget control level the strategy.