Search results

The purpose of this study is to develop an integrated model for the stochastic multiproject scheduling and material ordering problems, where some of the prominent features of offshore projects and their environmental-degrading effects have been embraced as well. The durations of activities are uncertain in this model. The developed formulation is tri-objective that seeks to minimize the expected time, total cost and CO₂ emission of all projects.

A new version of the multiobjective multiagent optimization (MOMAO) algorithm has been proposed to solve the amalgamated model. To empower the MOMAO, various procedures of this algorithm have been modified based on the multiattribute utility theory (MAUT) technique. Along with the MOMAO, this study has employed four other meta-heuristic methodologies to solve the model as well.

The outputs of the MOMAO have been put to test against four other optimizers in terms of convergence, diversity, uniformity and computation times. The results of the Mean Ideal Distance (MID) metric have revealed that the MOMAO has strongly prevailed its rival optimizers. In terms of diversity of the acquired solutions, the MOMAO has ranked the first among all employed optimizers since this algorithm has offered the best solutions in 56.66 and 63.33% of the test problems regarding the diversification metric and hyper-volume metrics. Regarding the uniformity of results, which is measured through the spacing metric (SP), the MOMAO has presented the best SP values in more than 96% of the test problems. The MOMAO has needed more computation times in comparison to its rivals.

A real case study comprising two concurrent offshore projects has been offered. The proposed formulation and the MOMAO have been implemented for this case study, and their effectiveness has been appraised.

Very few studies have focused on presenting an integrated formulation for the stochastic multiproject scheduling and material ordering problems. The model embraces some of the characteristics of the offshore projects which have not been adequately studied in the literature. Limited capacities of the offshore platforms and cargo vessels have been embedded in the proposed model. The offshore platforms have spatial limitations in storing the required materials. The vessels are also capacitated and they also have limited shipment capacities. Some of the required materials need to be transported from the base to the offshore platform via a fleet of cargo vessels. The workforces and equipment can become idle on the offshore platform due to material shortage. Various offshore-related costs have been integrated as a minimization objective function in the model. The cargo vessels release CO₂ detrimental emissions to the environment which are sought to be minimized in the developed formulation. To the best of the authors' knowledge, the MOMAO has not been sufficiently employed as a solution methodology for the stochastic multiproject scheduling and material ordering problems.

Construction material management plays a significant role in achieving successful project delivery of a construction project. However, ineffective material management is a critical issue in the construction industry, especially in developing economies, of which Sri Lanka is not an exception. Therefore, this study aims to focus on exploring the causes of ineffective material management practices in civil engineering construction projects in Sri Lanka and their impact on successful project delivery.

Furthermore, the literature findings were validated through the preliminary survey. Subsequently, a quantitative research approach was adopted to pursue the research aim. Questionnaire responses were obtained from 215 construction professionals in civil engineering projects who were selected using the judgemental and snowball sampling techniques. Collected data were analysed through Statistical Package for the Social Sciences (SPSS) V26 and Microsoft Excel 2016.

Moreover, the study revealed that material price fluctuation, shortage of material in the market, delay in material procurement, inadequate planning and delays in material delivery are the most frequent causes of ineffective material management in civil engineering projects. In addition, it was evidenced that most ineffective material management practices cause both time and cost overruns in civil engineering construction projects. Most respondents emphasized inadequate planning, inadequate qualified and experienced staff, lack of supervision and lack of leadership as the causes for both time and cost overruns.

The study was concluded by proposing strategies for effective material management. Education/training/enlightenment of staff in charge of materials management, use of software like Microsoft Project, Primavera and similar software to eliminate manual errors in material management, and providing clear specifications to suppliers were the most agreed strategies for effective material management in civil engineering construction projects.

The unstable labor productivity and periodic planning method cause barriers to improving construction logistics management. This paper aims to explore a demand-driven mechanism for efficient construction logistics planning to record the material consumption, report the real-time demand and trigger material replenishment from off-site to on-site, which is aided by Building Information Modeling (BIM) and the Kanban technique.

This paper follows the design science research (DSR) principles to propose a system of designing and applying Kanban batch with 4D BIM for construction logistics planning and monitoring. Prototype development with comparative simulation experiments of a river remediation project is conducted to analyze the conventional and Kanban-triggered supply. Two-staged industrial interviews are conducted to guide and evaluate the system design.

The proposed BIM-enabled Kanban system enables construction managers and suppliers to better set integrated on- and off-site targets, report real-time demands and conduct collaborative planning and monitoring. The simulation results present significant site storage and schedule savings applying the BIM-enabled Kanban system. Feedback and constructive suggestions from practitioners are collected via interviews and analyzed for further development.

This paper brings to the limelight the benefits of implementing BIM-enabled demand-driven replenishment to remove waste from the material flow. This paper combines lean production theory with advanced information technology to solve construction logistics management problems.

Construction organisations cannot underestimate the improvement in public–private partnership (PPP) projects’ implementation. At the same time, construction organisations cannot overlook the risk arising from engaging in PPP construction projects. Hence, this study aims to establish the influence of risk resource management (RRM) in managing PPP risk in the construction industry in Ghana.

The researchers adopted qualitative and quantitative research methods to achieve the aim of the study, in which Delphi questions and a close-ended questionnaire were developed. A total of 650 construction specialists, including procurement officers, consultants, project managers, quantity surveyors, site engineers and planning officers were chosen using random and purposive sampling techniques. Recovered data were analysed using descriptive statistics and confirmatory factor analysis (CFA). The CFA maximum likelihood estimation extractor compresses 19 variables into 3 pattern matrices.

The results of the study revealed three factors that measure RRM in Ghana’s PPP construction industry, including financial resource management which was influenced by communicating the budget to project team members and project partners understanding the budget, and material resource management which was influenced by the provision of materials transportation and provision of delivery programs and labour resource management which was impacted by a commitment to pay social security and taxes and provision of good salaries, to address RRM in PPP construction organisations.

To incessantly improve the PPP risk management (RM) in construction through RRM, there should be a strong liaison between the universities, government agencies and the construction industry, and such collaboration will assist the industry to obtain first-hand information regarding the study findings and how they can be implemented to help the development of RM in the construction industry. This study is limited to Ghana and CFA and further study should explore structural equation model to determine the structure and measurement model of the risk resource variables.

The study may be valuable to industry stakeholders looking for new approaches to improve RM in their construction activities, particularly in PPP projects. Also, to assist reduce PPP risk, construction companies should use RRM in their organisations.

Due to its longer length compared to other construction materials and distinctive stacking patterns, obtaining construction steel bars in congested construction sites with limited storage capacity becomes challenging. Lack of storage space in crowded places prompts the need for building steel bar storage choice optimization. Therefore, this study aims to optimize the construction steel bar procurement plan by providing when and how much rebar to order and how to stack different sizes of rebar considering limited storage capacity.

A novel approach has been presented in this paper by integrating 4D building information modelling (BIM) and mixed-integer linear programming (MILP). This technique uses BIM to retrieve material quantities, including rebar, during the design phase. Following that, activities are scheduled depending on the duration determined by crew productivity data and material quantity. Then, based on the prior price, the price of each unit of rebar is projected for the duration of construction using the exponential smoothing method. After that, the MILP approach is used to generate an optimal steel bar procurement plan for limited storage space following the scheduled rebar-related operations.

The developed strategy minimizes overall procurement costs and ensures the storage of rebar as per standard guidelines. An optimal rebar procurement and storage plan to construct a six-storied RC frame has been presented in this paper as a demonstrative example to show the effectiveness of the proposed method.

This work partially satisfies a long-sought research need for establishing a comprehensive construction steel bar procurement system, making it a very useful source of information for practitioners and researchers. The proposed method can be used to minimize a key performance limitation that the conventional rebar procurement practice for crowded building sites may experience.

Construction material management is an important process in supporting construction operations that affect project performance. Previous studies attempt to identify factors influencing material management in different stages such as procurement, transportation and utilization. However, they lack a model to explain the relationship between influential factors and the effectiveness of material management. Therefore, this study aims to validate the variables and key factors influencing the effectiveness of material management processes.

A total of 42 variables were reviewed from literature in different stages of material management process. Survey questionnaires were used to collect data about participants' perceptions on these variables. The respondents were 200 project engineers and project managers from construction sites and offices in Vietnam. Then factor analysis techniques were undertaken to validate the structure of factor groups. Two methods of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were, respectively, performed to evaluate and verify the model's fit.

Factors influencing the effectiveness of material management were grouped into nine main factors, which are procurement issues, site conditions, planning and handling on site, industrial environments, contractual issues, quality control, suppliers and manufacturers' issues, transportation in and out site and security on site.

The paper has several implications for theory and methodology related to material management. It features influential factors in association with the material management effectiveness. Therefore, senior managers can more fully understand the errors in their works and propose timely solutions to limit the unwanted risks.

This research contributes on theoretical development on factors influencing effectiveness of material management processes. The key findings on influential factors can be applied to measure the effectiveness of material management processes.

Lean production has been proved to be a cost-effective and efficient means of production that reduces non-valve added activities. Industry 4.0 (I4.0) is a technology-driven platform that allows machines to interact with other systems through artificial intelligence, machine learning, industrial Internet of Things (IoT), etc. that improve the production system with flexibility, quality and customization throughout the whole value chain. New approaches to digitization of lean production have recently been emerged and they are transforming the industry and increasing productivity throughout the value chain. Through this article, an effort has been made to review the research published in this field.

This paper reviews the literature published in various journals, the databases Web of science (WoS), ScienceDirect, Scopus, Emerald etc. were referred with a focus on lean concepts and tools and I4.0 technologies; it has been noticed that the integration of the lean tools with I4.0 technologies is a very effective tool for the industry.

It has been found in the literature published earlier in various journals that lean manufacturing (LM) is commonly acknowledged and considered a best practice to improve the productivity. It is concerned with the tight integration of people into the industrial process through continuous improvement which leads to value addition throughout the whole value chain by eliminating non vale added activities. The findings show that organizations can improve their productivity and flexibility with speed and accuracy by integrating I4.0 technologies with LM, which is foremost need of any industry across the world.

This article accentuates the connections between the principles and tools developed under the umbrella of I4.0 and those developed by the LM techniques, with a specific emphasis on how some of the principles and tools of I4.0 improve the implementation of lean principles dependent on the competence levels of the technology. Very few articles have been published in this area, and this paper is an original piece of research covering a review of extant research published in various journals.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

The purpose of this study is to utilize two types of gypsum mold wastes from two different factories as novel and economical reinforcing fillers for composites that may be useful for building materials and floors. Two types of gypsum mold wastes from two different factories as raw materials were incorporated into linear low density polyethylene (LLDPE) aiming to get rid of that waste in one hand and obtaining useful economical composites suitable for building materials and floors.

Composites were prepared from two types of gypsum mold wastes substituted with different ratios from raw gypsum and LLDPE throughout the melt blending technique. The physico-mechanical and electrical investigations in addition to the morphology of the composites were included.

The mechanical results illustrate that substituting commercial gypsum with gypsum mold waste positively affects tensile strength, flexural strength and hardness shore D for the LLDPE composites. The tensile strength increased from 5 MPa for LLDPE filled with commercial gypsum as blank samples to 11.2 and 13.2 MPa for LLDPE filled with D and S waste. Also, electrical properties which include both permittivity ɛ′ and dielectric loss ɛ″ increased with increasing the waste content in the LLDPE matrix. In addition to the electrical conductivity values, σ lies in the order of insulation materials. Consequently, it is possible to produce materials with a gypsum matrix by adding industrial waste, improving the behavior of the traditional gypsum and enabling those composites to be applied in various construction applications as eco-friendly tiles.

This study aims to prepare eco-friendly composites based on LLDPE and waste gypsum mold to preserve resources for the coming generations, other than lowering the environmental footprint and saving the costs of getting rid of it.

The purpose of the research was to evaluate the relationship between income and the recycled materials used in order to rate the business related to circular repair services under the burden of economic development in the countries of the European Union.

The analytical processes explore data from 2010 to 2020. The countries were divided into clusters according to economic maturity (Human Development Index (HDI), real Gross domestic product (GDP) per capita). Subsequently, the relationships were evaluated through the income indicators (for the 13 population groups), and the circular materials use rate indicator. The three indicators decomposed into five specific metrics were employed. The commonly applied characteristics of the descriptive analysis, Pearson's correlation coefficient and the panel regression analysis were engaged in the investigation.

The results demonstrated the vast disparities between income and circular materials use. In the more economically developed countries, their levels were twice higher as the less-developed countries. However, there is a meaningful positive relationship between them. The greatest attention was paid to the panel regression analysis applied to the relationship between income and circular economy (CE) use. The results showed that in a majority of the cases (different income categories), there is a significant positive relationship. When comparing the outcomes of the regression models between the groups of the countries according to their economic development, a closer relationship was clearly demonstrated in the countries with a lower level of development (Bulgaria, Romania, Croatia, Hungary).

Besides the specific strengths, the study also shows some limitations identified mainly on the data side. The latest data on the consumption of circular materials come from 2020, so they do not cover the period related to the pandemic crisis. It is believed that there may have been some changes in income during the pandemic, and they may have harmed CE. Furthermore, there is to note that some limitations occur in the analytical process. The incompleteness of the data can also be included here as certain data is not available; hence, it was estimated directly by the Eurostat statistical authority.

At the same time, the following are currently considered among the primary barriers: financial restrictions, insufficient infrastructure, weak government support and obstacles on the global market. Consumers, industry leaders and the government are the most influential stakeholder groups in overcoming barriers. Higher demand for repair services will also initiate further development of business activities in this area at various regional levels. Progress in the repair services economy will continue to require extensive efforts in the future. Systematic coordination of activities at multiple levels of government together with manufacturers, designers, educational institutions, community institutions and individuals will be essential.

Socioeconomic characteristics such as sex, age and education represent crucial predictors of consumer behavior. Therefore, the authors would like to focus future research on analyzing these characteristics and examine all the conceptual frameworks of consumer behavior and its positioning in detail within CE and the strategies related to the repair service. Discussing this issue through follow-up research will allow for solving complex transformational and political tasks related to the repair service strategies within CE. It will also inspire the discussion frameworks and multidisciplinary solutions to this issue affecting the fields of human geography, sociological, ethnographic and political sciences.

In less-developed countries, wage change can have a more substantial impact on the development of the CE. Also, a closer relationship between business in the field of repair services with income and the use of circular materials was manifested in the same way.