Reduce Project Costs Research Articles

Level of Awareness of Industrialised Building Systems (IBS) in The Ghanaian Construction Industry

Purpose: Adopting Industrialised Building Systems (IBS) in the developed world has proven beneficial for raising and enhancing project value and productivity while reducing project costs and duration. This study assessed the prevalence of IBS implementation among Ghanaian construction firms, focusing on those in the Bono region. Design/Methodology/Approach: The study employed a cross-sectional survey research design to elicit responses from construction contractors with a construction firm in the Bono region of Ghana. The study used a structured questionnaire with a 4-point Likert scale for data collection. Purposive sampling was used to sample 42 active firms out of the 61 construction firms registered in the Bono region. Data was analysed using a statistical package for social scientists (SPSS) using descriptive statistical tools such as mean and standard deviation. Findings: The study identified high awareness of IBS in the construction industry and critical IBS adoption challenges. The industry favours traditional techniques over modern IBS techniques. Financial constraints and a lack of financing are the significant obstacles to the widespread adoption of IBS. Research Limitation: The Bono Region in Ghana was the study's exclusive focus, particularly on contractors and construction firms. The contractors are classified in the D2K2 and D3K3 categories. Practical Implications: This will ensure that professionals can manipulate advanced and sophisticated technologies to improve project performance. Social Implication: Adopting IBS can enhance efficiency, quality, safety, productivity of skilled labour, innovation, and economic growth. IBS can also help improve the housing stock, reduce informal settlements, and improve the quality of life. Originality/Value: The study contributes significantly to the literature on industrialised building systems (IBS) by exclusively focusing on the prevalence of IBS implementation among Ghanaian construction firms.

A joint work package sizing and scheduling problem considering resource constraints with a look-ahead heterogeneous reinforcement learning method

Effective work package sizing and project scheduling are crucial for construction project management. However, existing studies often address them as separate optimisation problems, neglecting the interactive nature of these processes. In practical scenarios with limited resources, there is an increasing demand for integrating work package sizing and project scheduling to enhance project management efficiency. This research aims to bridge this gap by developing an integer non-linear programming model that incorporates work package sizing and project scheduling while considering their interaction within a resource-constrained environment. Moreover, we introduce a novel look-ahead heterogeneous reinforcement learning approach that dynamically adjusts work package sizes and project schedules based on observed information at each decision step. A look-ahead sequential decision mechanism is proposed to effectively address the interdependencies and constraints inherent in the joint model. We extend the heterogeneous agent mirror learning technique to our problem to improve sample efficiency and ensure progressive enhancement of the joint policy. To evaluate our approach's effectiveness, we conduct experiments using datasets of 15, 30, 60, 90, and 120 tasks from Rangen and PSPLIB and validate our method in a real-world modular integrated construction project. The experimental results reveal that a joint model integrating work package sizing and project scheduling offers a more comprehensive understanding of their interplay, leading to better resource utilisation and improved project schedules. A comparative analysis against existing state-of-the-art reinforcement learning and priority rule-based methods further substantiates the superior effectiveness of our proposed approach, yielding an approximate 5% reduction in total project cost.

Key factors affecting project delivery system selection in the Chinese construction industry

This study aims to investigate the key factors owners consider when selecting a PDS, the importance degree of these factors, and the perception differences among owners, consultants, and contractors regarding these factors. Interviews and questionnaire surveys were used to determine the importance degree of each influencing factor. And perception differences of the influencing factors on PDS among the three subjects were calculated through SPSS 15.0. The findings show that the three subjects' perceptions of the importance degree of the economic attributes of the engineering project, engineering project complexity, sub-project construction interference degree, and delivery system preference were significantly different, while the perceptions of engineering project scale, investment control requirements, schedule requirements, quality requirements, risk preference, construction management capability, land acquisition, demolition and migration, construction site conditions, local policies and regulations, and construction market development level were insignificantly different. This research can help owners understand influencing factors on PDS selection from different dimensions. Valuable information was provided for owners to select an accurate and reasonable PDS, ultimately reducing project costs and facilitating project management. Additionally, this research complements previous research on PDS selection and proposes a new influencing factors framework by exploring the key factors affecting PDS selection and the perception differences between the three subjects.

A Meta-analysis of the Profit-Sharing Practices among Engineering, Construction, and Related Firms: Strategy to Increase Company Revenue

This paper explores the impact of profit sharing on employee motivation, productivity, and company performance in the engineering and construction industry. Through a meta-analysis of recent studies, it identifies key factors that influence the effectiveness of profit-sharing programs. The findings reveal that profit sharing significantly boosts employee motivation and productivity, with increases of 15% and 12% respectively. Moreover, job satisfaction rates are 20% higher among employees participating in profit-sharing programs. However, there is a notable preference split, with 60% of employees favoring profit sharing for its potential higher earnings, while 40% prefer fixed salary increases for stability. The research further indicates that frequent and actively managed profit-sharing distributions, such as quarterly payouts, lead to better financial performance, with a 10% increase in overall performance and a 5% improvement in profitability. Project-based profit sharing in the construction sector is particularly effective, resulting in a 25% increase in project completion rates and a 15% reduction in project costs. Additionally, profit sharing is more effective in unionized organizations, with an 18% increase in effectiveness, and mandatory profit-sharing frameworks enhance worker satisfaction and productivity. Based on these findings, the paper recommends developing tailored profit-sharing strategies that cater to different employee preferences, implementing frequent and active management of profit-sharing distributions, adopting project-based profit sharing in project-centric industries, engaging with unions for fair terms, advocating for supportive regulatory frameworks, and continuously monitoring and evaluating the effectiveness of these programs. By adopting these strategies, engineering and construction firms can enhance employee motivation, improve productivity, and achieve better financial performance, driving organizational success.

Design and application of a prefabricated structure for large-span arch open-cut highway tunnels

To enhance construction efficiency, improve lining quality, and reduce project costs, this study proposes a prefabricated arch structure scheme for large-span open-cut highway tunnels, specifically targeting the ongoing construction of an eight-lane open-cut tunnel on Chongqing’s Xinsen Avenue. By establishing a finite element “load-structure” integrated calculation model and adopting an iterative analysis method, the impact of joint stiffness variations on internal force distribution was determined. Combined with long-term field monitoring and measurements, a thorough analysis was conducted on the performance of the prefabricated arch structure during different construction stages. The results indicate that after assembly into a ring, the structure undergoes a self-adaptive adjustment phase, during which the joints experience significant stress and deformation. Following top-layer backfilling and water level restoration, the axial force on the joints increases, while stress and deformation decrease, exerting a positive effect on the joint bearing capacity. From the construction period to post-opening operations, the stress variation experienced by the joints remains within a controllable range, demonstrating substantial safety margins. This fully validates the safety and reliability of the prefabricated arch structure scheme.

Multi-mode resource-constrained project scheduling problem with multiple shifts and dynamic energy prices

Considering the characteristics of time-of-use tariffs and multi-shifts in real-life project execution scenarios, we present a multi-mode resource-constrained project scheduling problem with multi-shift and time-of-use tariffs (MRCPSP-MS-TOU). The MRCPSP-MS-TOU is a bi-objective scheduling problem that aims to simultaneously minimise both project duration and energy costs. In this problem, renewable resources are the critical equipment that consumes the most energy and can work continuously for multiple shifts. Activities that require critical equipment with high energy consumption are given priority for shifts with lower electricity prices under time-of-use tariffs. We construct a mixed integer linear programming model for the MRCPSP-MS-TOU. For small-scale projects, the ε-constraint method is implemented to solve the MRCPSP-MS-TOU using the Gurobi optimiser. For large-scale projects, this paper develops meta-heuristic algorithms in the framework of the two non-dominated sorting genetic algorithm versions. The MRCPSP-MS-TOU enables manufacturers and the construction industry to schedule projects using time-of-use tariffs and multi-shifts in a more efficient manner since it can control the intensity of energy consumption, reduce project costs, make full use of energy-intensive equipment, and effectively reduce order delivery time.

A Digital Project Management Framework for Transnational Prefabricated Housing Projects

Compared with an ordinary prefabricated housing project (PHP), a transnational PHP tends to involve more uncertainties, with major stakeholders residing in different countries. This study proposes a novel digital project management framework that integrates building information modeling to enhance information utilization. This framework also incorporates innovative design concepts of modulor, modulus, module, model, durability, and recyclability for enhanced user comfort, housing industrialization, and extended lifespan. It was demonstrated how planning, design, manufacture, and transportation processes can be streamlined in transnational PHP delivery. A case study was performed in a typical transnational PHP between the Kingdom of Saudi Arabia and China for validation. By applying the framework, this PHP could install a single house within 24 h, improve precast level by about 20%, and reduce project cost per square meter by 5.2%, because of integrated design concept, reduced labor cost, effective material cost control, and enhanced information management.

Power and Interest Matrix Stakeholders of the Geothermal Development Project in Indonesia

Indonesia has 23 GW of geothermal reserves and is ranked second with the largest geothermal installed capacity in the world. Currently, the electricity generated from geothermal energy is 2,418 MW, that only 10% of geothermal energy utilization in Indonesia. This is because geothermal projects are capital-intensive, complex, and sensitive to uncertainty and risk thus make the investment less viable. Based on the literature review, simplifying the geothermal development process can reduce project costs and accelerate project completion to make it more attractive One of them is the effectiveness of coordination between stakeholders related to geothermal development. This research aims to identify key stakeholders and map them based on the power and interest of each key stakeholder involved in geothermal development using the Stakeholder Analysis approach. The Delphi method is employed in this study, a group of experts contributes insights, revealing a clear pattern in identifying and mapping stakeholders in geothermal development in Indonesia. The final round result of expert validation led to the inclusion of 14 stakeholders in the key stakeholder category from 30 identified stakeholders initially. Among the 14 key stakeholders, an assessment based on power and interest was conducted. The results showed that 11 stakeholders were categorized as players, while 3 key stakeholders were classified as context setters.

Combining Thermal Effect and Mobility Control Mechanism to Reduce Water Cut in a Sandstone Reservoir in Kazakhstan.

The application of polymer flooding is currently under investigation to control water cut and recover residual oil from a giant sandstone reservoir in Kazakhstan, where the water cut in most producers exceeds 90%, leaving substantial untouched oil in the porous media. The primary objective of this research is to explore the feasibility of a novel approach that combines the mechanisms of mobility control by polymer injection and the thermal effects, such as oil viscosity reduction, by utilizing hot water to prepare the polymer solution. This innovative hybrid method's impact on parameters like oil recovery, resistance factor, and mobility was measured and analyzed. The research involved an oil displacement study conducted by injecting a hot polymer at a temperature of 85 °C, which is higher than the reservoir temperature. Incremental recovery achieved through hot polymer injection was then compared to the recovery by conventional polymer flooding and the conventional surfactant-polymer-enhanced oil recovery techniques. The governing mechanisms behind recovery, including reductions in oil viscosity, alterations in polymer rheology, and effective mobility control, were systematically studied to comprehend the influence of this proposed approach on sweep efficiency. Given the substantial volume of residual oil within the studied reservoir, the primary objective is to improve the sweep efficiency as much as possible. Conventional polymer flooding demonstrated a moderate incremental oil recovery rate of approximately 48%. However, with the implementation of the new hybrid method, the recovery rate increased to more than 52%, reflecting a 4% improvement. Despite the polymer's lower viscosity during hot polymer flooding, which was observed by the lower pressure drop in contrast to the conventional polymer flooding scenario, the recovery factor was higher. This discrepancy indicates that while polymer viscosity decreases, the activation of other oil displacement mechanisms contributes to higher oil production. Applying hybrid enhanced oil recovery mechanisms presents an opportunity to reduce project costs. For instance, achieving comparable results with lower chemical concentrations is of practical significance. The potential impact of this work on enhancing the profitability of chemically enhanced oil recovery within the sandstone reservoir under study is critical.

Implementation of an Automated Code Checking Algorithm Based on Site Analysis

To date, BIM has been primarily utilized in cost and schedule management, an interference check between architectural and structural models and systems based on geometric data in the process of the construction life cycle. However, there is a lack of research that utilizes the information contained in the BIM model to review whether the proposed architectural model is appropriately designed in accordance with each country’s building regulations or building codes or that proposes a model optimized for laws and standards. ‘Building code checking’ is the step of reviewing whether a building designed based on the building codes is suitable for being constructed as a building. However, this process consumes significant time and money and leads to human errors due to the manual review process. This study included implementation of an algorithm based on the Korean building code. In this study, there was the process of selection of codes when architects interpret building codes in common and implementation based on the codes selected. Next, modeling based on DXF files from NGII (National Geographic Information Institute) was applied to the algorithm developed in this study. Last, it includes case studies that compare the outputs of the algorithm with the real buildings, which had received real code checking, to make sure the algorithm in this paper is working properly. The implementation of such an automated system has the potential to significantly improve the efficiency and effectiveness of the building design and construction process. It can help architects to quickly and accurately identify potential legal issues and provide alternative solutions that meet regulatory requirements. This, in turn, can lead to reduced project costs, improved quality of designs, and faster project delivery times.

Multi-objective optimization of construction management of expressway engineering based on improved particle swarm optimization algorithm

Engineering management is an extremely important aspect of construction engineering, and a better management approach can greatly enhance the production profits of enterprises. Traditional management optimization schemes cannot adapt to current technological needs due to their inability to effectively consider the impact of each factor. Therefore, a construction management optimization scheme combining improved particle algorithm and multi-objective optimization was proposed. The improved particle algorithm enhances its performance by introducing adaptive weight and multi-objective optimization ideas. These studies confirmed that the predicted direct cost savings for the project were around 1 million yuan. The total construction period of project was optimized to 380 days, saving 34 days. The optimization technology not only reduced construction costs, but also reflected the problems that could be improved during this construction process. This study contributes to achieving multi-objective balance in the construction management process, effectively improving project efficiency, reducing project costs and risks, and providing scientific support for construction decision-making.

Synchronizing production of precast elements with on-site erection

Offsite construction technologies are developed to reduce project cost and duration. To make the most of the potential offered by prefabrication the planner should consider the whole supply chain. A failure to coordinate the off-site production with on-site erection is a source of waste (waiting time of the construction crews or redundant handling activities on-site). Most of the research to date focused on optimizing operations of a prefabrication plant assuming a deterministic schedule of demand for its products. The purpose of this paper is to develop a mathematical model for integrated scheduling of offsite and on-site operations. Its solution is a schedule that minimizes the downtime of both the prefabrication plant and the on-site erection crews. In accordance with the Just-in-Time concept, the prefabrication schedule is set in a way to reduce the stocks of finished products, thus reducing the storage area and cost of funds tied up in inventory. The schedule’s robustness against the disturbance in the production and erection workflows is assumed to be assured allocating time buffers. The advantage of the proposed method is the ease of collecting the input: instead of detailed cost records, estimates of unit cost of lost time can be used.

Optimizing construction project outcomes through BIM and MEP system integration

The integration of Building Information Modeling (BIM) with Mechanical, Electrical, and Plumbing (MEP) systems represents a transformative approach to improving efficiency, coordination, and cost-effectiveness in construction projects. This paper explores a comprehensive methodology for BIM and MEP integration, encompassing framework development, data management, and collaboration mechanisms. It highlights the significant benefits such as enhanced project coordination, improved efficiency, and cost reduction while addressing key challenges including technical barriers, cultural and organizational changes, and data security concerns. Solutions such as the development of interoperability standards, middleware technologies, robust data management protocols, and collaborative platforms are discussed. The study underscores the necessity of a multifaceted strategy involving training, change management, and leadership commitment to drive successful implementation. Through detailed analysis and discussion, this paper demonstrates how BIM and MEP integration can lead to more streamlined, cost-effective, and high-quality construction projects.

A multi-period topology and design optimization approach for district heating networks

The transition to modern, low-carbon district heating creates a growing need for scalable, automated design tools that accurately capture the spatial and temporal details of heating network operations. This paper presents an automated design approach for the optimal design of district heating networks that combines scalable density-based topology optimization with a multi-period approach. In this way, temporal variations in demand, supply, and heat losses can be taken into account while optimizing the network design based on a nonlinear physics model. The transition of the automated design approach from worst-case to multi-period shows a design progression from separate branched networks to a single integrated meshed network topology connecting all producers. These integrated topologies emerge without imposing such structures a priori. They increase network connectivity, and allow for more flexible shifting of heat loads between different producers and heat consumers, resulting in more cost-effective use of heat. In a case study, this integrated design resulted in an increase in waste heat share of 42.8 % and a subsequent reduction in project cost of 17.9 %. We show how producer unavailability can be accounted for in the automated design at the cost of a 3.1 % increase in the cost of backup capacity. The resulting optimized network designs of this approach connect multiple low temperature heat sources in a single integrated network achieving high waste heat utilization and redundancy, highlighting the applicability of the approach to next-generation district heating networks.

Study on the Properties of Waste Stone Powder-clay Slurry based on the Influence of Filter Press

A grouting material pressure effect simulation device (FSD) was used to study the performance of grout considering grouting pressure, slurry rheology, clay ash, slurry concentration and particle size composition of waste stone powder (FSD influencing factors). After the effect of filter pressing, the alkaline environment of the slurry became stronger, the number of active particles increased, and the CaCO3 and clay crystals were fully agglomerate, and the degree of crystallization increased. The cation exchange capacity increased, and the formation of calcium-silicon-aluminum matrix phase and aluminosilicate aggregates increased. The surface water between the matrix particles supports the crystal layer, and the plastic viscosity and yield stress are reduced. The free calcium oxide decreased, and the consolidation shrinkage rate after slurry hardening was less than 1%. The water-cement ratio is reduced, and the total time for slurry to be poured into the fracture to consolidate and form a mold and intermittent is shortened. The use of waste stone powder and clay in the coal mine grouting industry can not only reduce project costs, but also reduce soil erosion and soil pollution.

Geothermal power generation potential in the United States by 2050

Geothermal energy provides a dispatchable source of carbon-free electricity that can balance the output of variable resources. However, geothermal provides just 3.7 gigawatts (GW e ) ( < 1%) of electricity in the United States today, mostly from hydrothermal resources that are geographically constrained. Enhanced geothermal systems (EGS), which extract heat from deep rock, could be applicable in more locations. However, baseline levels and potential trends in EGS costs have been insufficiently characterized by previous studies. Here, we assess geothermal penetration potential by using as baseline the latest available data on drilling costs from three costing models to create updated estimates of costs and performance. We input those estimates along with various scenarios of cost trends, emissions policies, and electricity demand into the regional energy deployment system (ReEDS) capacity expansion model to simulate electricity generation in the United States through 2050. The scarcity of hydrothermal resources limits deployments to no more than 18 GW e across our scenarios. EGS is more costly than hydrothermal for now, but it has greater potential to scale nationwide. Thus, future deployments of EGS depend strongly on projected cost reductions and emissions policies. In scenarios with moderate ( < 50%) reductions in costs by 2050, very little EGS is likely to be built, since wind and solar with storage provide lower-cost electricity. However, over 70% cost reductions from our updated baseline would make geothermal the least-cost carbon-free dispatchable resource. Under those cost trends, we project that 3 GW e of EGS would be built by 2050 under existing policies, 11 GW e with a 95% decarbonization policy, and 152 GW e if full decarbonization of electricity is mandated. Most geothermal would likely first be built in western states with the steepest subsurface temperature gradients, although mandates for full decarbonization could drive it to be deployed in other states.

The Impact of Building Information Modeling Technology on Cost Management of Civil Engineering Projects: A Case Study of the Mombasa Port Area Development Project

Introduction: This study examines the impact of building information modeling on the cost management of engineering projects, focusing specifically on the Mombasa Port Area Development Project. The objective of this research is to determine the mechanisms through which building information modeling facilitates stakeholder collaboration, reduces construction-related expenses, and enhances the precision of cost estimation. Furthermore, this study investigates barriers to execution, assesses the impact on the project’s transparency, and suggests approaches to maximize resource utilization. Methodology: This study employed a mixed-method research design comprising document reviews and surveys. During the document review, credible databases including ScienceDirect and Institute of Electrical and Electronics Engineers Xplore were explored. The survey included 69 professionals, among which were project managers, cost estimators, and building information modeling administrators. The mixed-methods approach prioritized ethical considerations and the statistical Package for the Social Sciences and Microsoft Excel were used in the analysis. Results: The results show that building information modeling is a valuable system for organizations looking to reduce project costs. The results note that the technology improves cost estimation accuracy, facilitates the identification of cost-related risks, and promotes collaborative decision-making. Conclusions: Building information modeling is an effective cost-estimating technology that positively impacts additional project aspects such as decision-making, collaboration, performance, and delivery time. Therefore, the Mombasa Port Area Development Project should inspire other stakeholders in engineering and construction to embrace building information modeling.

Design of Sustainable Construction Cost Estimation System Based on Grey Theory — BP Model

China’s construction industry is developing rapidly, and market investment is out of control. Therefore, accurate and rapid project cost estimation is the focus of the industry. The grey theory system is a method to study the uncertainty problem of little data and poor information. It can excavate different information hidden in the system observation data to achieve correct description and understanding. The research will improve the BP neural network based on grey theory, and verify the exactitude and advantage of the model from performance comparison and empirical analysis. This study can make the project cost forecast more reasonable. Results show that compared with the traditional model, the maximum error value decreased by 0.52, the research model’s maximum mean square error decreased by 0.09, and the variance decreased by 0.13. In the regression analysis, the [Formula: see text]-value of the model fitting was above 0.95, the [Formula: see text]-value of the verification fitting reached 0.9205. The [Formula: see text]-value of the overall fitting reached 0.9475, and the fitting effect was excellent. The convergence speed of the research model is faster than other models, and the fitness value is stable at 1.36. In the empirical analysis, this model can review project cost investment budgets in some areas and reduce project costs. This can improve work efficiency. The model also has certain practical significance for the sustainable development of construction project cost estimates.

The role of BIM as a lean tool in design phase

In the architectural, engineering, and construction industry, poor visualization of construction processes and lack of information exchange between different work teams can lead to poor performance. To address these challenges, lean construction methodologies aim to reduce and eliminate waste in construction processes, while BIM technology aims to enhance collaboration between project team members. In general, these technologies can be used together to improve project management and cost reduction. This can be achieved through improving workflow and coordination, enhancing interaction among project members, and using available tools to analyze and improve work. Many aspects of the integration between LC and BIM have been studied, and researchers have come up with some findings and recommendations. Most studies previously demonstrated theoretically that cost reductions using BIM techniques are significant compared to the traditional approach of project management. This is what this study proved practically by applying BIM in the design of a building which is quite successful in construction as it identifies the main causes of construction waste such as reducing waiting time and reducing non-value-added work by using Dynamo to develop these designs. So, the research problem comes, which is how to keep up with development in the field of construction by applying different BIM programs, which results in reducing the time and cost used in design. BIM is a technology that aims to enhance project management and cut costs. A digital representation of the project that contains all the data required for planning, managing, and carrying out the project is created using BIM.

Methodology for retrospectively developing a BIM model from point cloud scans using ongoing building project as case study

Purpose The purpose of this study is to explore the suggestions that construction processes could be considerably improved by integrating building information modelling (BIM) with 3D laser scanning technologies. This case study integrated 3D laser point cloud scans with BIM to explore the effects of BIM adoption on ongoing construction project, whilst evaluating the utility of 3D laser scanning technology for producing structural 3D models by converting point cloud data (PCD) into BIM. Design/methodology/approach The primary data acquisition adopted the use of Trimble X7 laser scanning process, which is a set of data points in the scanned space that represent the scanned structure. The implementation of BIM with the 3D PCD to explore the precision and effectiveness of the construction processes as well as the as-built condition of a structure was precisely captured using the 3D laser scanning technology to recreate accurate and exact 3D models capable of being used to find and fix problems during construction. Findings The findings indicate that the integration of BIM and 3D laser scanning technology has the tendency to mitigate issues such as building rework, improved project completion times, reduced project cost, enhanced interdisciplinary communication, cooperation and collaboration amongst the project duty holders, which ultimately enhances the overall efficiency of the construction project. Research limitations/implications The acquisition of data using 3D laser scanner is usually conducted from the ground. Therefore, certain aspects of the building could potentially disturb data acquisition; for example, the gable and sections of eaves (fascia and soffit) could be left in a blind spot. Data acquisition using 3D laser scanner technology takes time, and the processing of the vast amount of data acquired is laborious, and if not carefully analysed, could result in errors in generated models. Furthermore, because this was an ongoing construction project, material stockpiling and planned construction works obstructed and delayed the seamless capture of scanned data points. Originality/value These findings highlight the significance of integrating BIM and 3D laser scanning technology in the construction process and emphasise the value of advanced data collection methods for effectively managing construction projects and streamlined workflows.