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1 – 10 of 235Yuanqiang Tan, Rong Deng, Y T Feng, Hao Zhang and Shengqiang Jiang
The purpose of this paper is to establish a new two-phase Discrete Element Method (DEM) model to investigate the movement of fresh concrete which consists of mortar and aggregate…
Abstract
Purpose
The purpose of this paper is to establish a new two-phase Discrete Element Method (DEM) model to investigate the movement of fresh concrete which consists of mortar and aggregate. The established DEM model was adopted to simulate the mixing process of fresh concrete based on the commercial software package PFC3D. The trajectories of particles and particle clusters were recorded to analyze the mixing behavior from different scales. On one hand, the macro-scale movement was obtained to make the mixing process visualization. On the other hand, the relative micro movement of the single particle and particle clusters was also monitored to further study the mixing mechanism of the fresh concrete.
Design/methodology/approach
A new two-phase DEM model was designed to simulate the movement of fresh concrete which consists of mortar and aggregate. The linear-spring dashpot model was used to model all the contacts between particle and particle/wall to characterize the viscidity of fresh concrete. Moreover, two sets of parallel bond models were employed to characterize the contact between the mortar particles and mortar/coarse aggregate particles, namely the pbond1 and pbond2. The hybrid treatment enables the current DEM model to handle the yield behavior.
Findings
The mixing process of fresh concrete is mainly composed by the transportation in the x-direction and the overturn and fall off in the y- and z-directions. With these movements in different directions, the concrete particles can be fully mixed in the mixing drum.
Originality/value
A new two-phase DEM model was proposed and used to simulate the mixing process of fresh concrete. The outcomes of the simulation would be helpful for making the transporting truck visualization and the movement behavior of fresh concrete observable. The model can provide dynamic information of particles to reveal the interaction mechanism of fresh concrete in the truck mixer which is extremely difficult to obtain on-line in physical experiments or building site.
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Zahra Sadat Moussavi Nadoushani, Ali Akbarnezhad and David Rey
Due to considerable contributions of the construction industry to the global carbon emissions, a great deal of attention is placed on possible incorporation of carbon footprint…
Abstract
Purpose
Due to considerable contributions of the construction industry to the global carbon emissions, a great deal of attention is placed on possible incorporation of carbon footprint minimization as an important objective in the planning of construction operations. The purpose of this paper is to present a framework to estimate and minimize the carbon emissions of the concrete placing operation through identifying the optimal number of pumps and the inter-arrival time of truck mixers.
Design/methodology/approach
The proposed framework integrates discrete event simulation and multi-objective optimization to estimate and minimize the carbon emission, costs and production rate of the concrete placing operation. An actual construction project is used to demonstrate the application of the proposed framework. Furthermore, a sensitivity analysis is performed to investigate the sensitivity of the results to variations in modeling parameters including the ratio of idle to non-idle emission rates of equipment and the activity duration distributions.
Findings
The results of the case study highlight that variations in the number of pumps and inter-arrival time of truck mixers significantly affect the carbon emissions, cost and production rate of the concrete placing operation. Furthermore, the results of the sensitivity analysis show that variations in the ratio of idle to non-idle emission rates for pumps and truck mixers have little effects on the selected setting for the project. This is contrary to the effect of uncertainty in the activity duration distributions, which was found to be significant.
Originality/value
Results of this study provide an insight into the trade-off between carbon emissions, cost and production rate of the concrete placing operation.
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Ning Huang, Qiang Du, Libiao Bai and Qian Chen
In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has…
Abstract
Purpose
In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.
Design/methodology/approach
The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.
Findings
Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.
Research limitations/implications
While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.
Practical implications
Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.
Social implications
Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.
Originality/value
The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.
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Computer simulation in construction planning has been the subject of research for the last few decades. The present paper describes simulation models geared toward improving the…
Abstract
Computer simulation in construction planning has been the subject of research for the last few decades. The present paper describes simulation models geared toward improving the productivity of concreting operations. It is primarily concerned with a study of the sensitivity of concreting operations to a set of possible resource combinations. Thirteen models are examined by the two well‐known methods of concreting: (1) crane and bucket; and (2) the pump. Concreting into slabs, beams and columns are considered. The simulation software Micro‐CYCLONE is used for the actual generation of models. Sensitivity parameters considered in resource combinations include the number of truck‐mixers, buckets and labourers in concrete placing crews. The simulation models developed are compared and the results are discussed. The results enable planners to realize how the resource quantities and capacities in one cycle affect the ones in another period for cyclic operations like concreting. It can be concluded that the maximum number of resources, the interaction of work crews caused by work space limitations and the interaction of equipment because of sharing with other activities of the project may bring limitations.
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Cristina Toca Pérez and Dayana Bastos Costa
This paper proposes to apply the lean philosophy principle of minimizing or eliminating non-value adding activities combined with 4D building information modeling (BIM…
Abstract
Purpose
This paper proposes to apply the lean philosophy principle of minimizing or eliminating non-value adding activities combined with 4D building information modeling (BIM) simulations to reduce transportation waste in construction production processes.
Design/methodology/approach
This study adopts design science research (DSR) because of its prescriptive character to produce innovative constructions (artifacts) to solve real-world problems. The artifact proposed is a set of constructs for evaluating the utility of 4D BIM simulations for transportation waste reduction. The authors performed two learning cycles using empirical studies in projects A, B and C. The construction process of cast-in-place (CIP) reinforcement concrete (RC) was selected to demonstrate and evaluate 4D BIM's utility. The empirical studies focused on understanding the current transportation waste, collecting actual performance data during job site visits and demonstrating the usage of 4D BIM.
Findings
In the first cycle, 4D BIM successfully allowed users to understand the CIP-RC process's transportation activities, which were modeled. In the second cycle, 4D BIM enabled better decision-making processes concerning the definitions of strategies for placing reusable formworks for CIP concrete walls by planning transportation activities.
Practical implications
In Cycle 2, three different scenarios were simulated to identify the most suitable formwork assembly planning, and the results were compared to the real situations identified during the job site visits. The scenario chosen demonstrated that the 4D BIM simulation yielded an 18.75% cycle time reduction. In addition, the simulation contributed to a decrease in transportation waste that was previously identified.
Originality/value
The original contribution of this paper is the use of 4D BIM simulation for managing non-value adding activities to reduce transportation waste. The utility of 4D BIM for the reduction of those conflicts considered three constructs: (1) the capacity to improve transportation activity efficiency, (2) the capacity to improve construction production efficiency and (3) the capacity to reduce transportation waste consequences.
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Vu Hong Son Pham, Nguyen Thi Nha Trang and Chau Quang Dat
The paper aims to provide an efficient dispatching schedule for ready-mix concrete (RMC) trucks and create a balance between batch plants and construction sites.
Abstract
Purpose
The paper aims to provide an efficient dispatching schedule for ready-mix concrete (RMC) trucks and create a balance between batch plants and construction sites.
Design/methodology/approach
The paper focused on developing a new metaheuristic swarm intelligence algorithm using Java code. The paper used statistical criterion: mean, standard deviation, running time to verify the effectiveness of the proposed optimization method and compared its derivatives with other algorithms, such as genetic algorithm (GA), Tabu search (TS), bee colony optimization (BCO), ant lion optimizer (ALO), grey wolf optimizer (GWO), dragonfly algorithm (DA) and particle swarm optimization (PSO).
Findings
The paper proved that integrating GWO and DA yields better results than independent algorithms and some selected algorithms in the literature. It also suggests that multi-independent batch plants could effectively cooperate in a system to deliver RMC to various construction sites.
Originality/value
The paper provides a compelling new hybrid swarm intelligence algorithm and a model allowing multi-independent batch plants to work in a system to deliver RMC. It fulfills an identified need to study how batch plant managers can expand their dispatching network, increase their competitiveness and improve their supply chain operations.
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Paul Dunlop and Simon D. Smith
With an increasingly competitive global market, the UK construction industry finally realised that in order to survive, a marked increase in efficiency and effectiveness have to…
Abstract
With an increasingly competitive global market, the UK construction industry finally realised that in order to survive, a marked increase in efficiency and effectiveness have to be achieved in all areas. This paper will describe the UK's approach to planning and designing the concrete operations that form a major part of many civil engineering construction projects. A productivity study has been carried out on three different construction projects and over 200 concrete pours have been observed. The data and knowledge collected on site have been subjected to lean construction philosophies, producing a “lean” measure of productivity, and it has been shown that major productivity increases could be achieved by implementing several relatively simple principles.
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Odey Alshboul, Ali Shehadeh, Omer Tatari, Ghassan Almasabha and Eman Saleh
Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify…
Abstract
Purpose
Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify, select, manage and optimize the associated decision variables (e.g. capacity, number and speed) for trucks and loaders equipment to minimize cost and time objectives.
Design/methodology/approach
This paper addresses an innovative multiobjective and multivariable mathematical optimization model to generate a Pareto-optimality set of solutions that offers insights of optimal tradeoffs between minimizing earthmoving activity’s cost and time. The proposed model has three major stages: first, define all related decision variables for trucks and loaders and detect all related constraints that affect the optimization model; second, derive the mathematical optimization model and apply the multiobjective genetic algorithms and classify all inputs and outputs related to the mathematical model; and third, model validation.
Findings
The efficiency of the proposed optimization model has been validated using a case study of earthmoving activities based on data collected from the real-world construction site. The outputs of the conducted optimization process promise the model’s originality and efficiency in generating optimal solutions for optimal time and cost objectives.
Originality/value
This model provides the decision-maker with an efficient tool to select the optimal design variables to minimize the activity's time and cost.
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Marina Macedo de Abreu and Alberto Casado Lordsleem Jr
The purpose of this paper is to establish and evaluate the concrete loss and labor productivity (LP) indicators in the concreting step of aluminum formwork system (AFS) in…
Abstract
Purpose
The purpose of this paper is to establish and evaluate the concrete loss and labor productivity (LP) indicators in the concreting step of aluminum formwork system (AFS) in construction in Brazil. The loss and productivity indicators are directed to a regional database (Pernambuco, Brazil).
Design/methodology/approach
Case study was selected as the most appropriate approach. The methodology included data collection in the construction project with 10 residential towers of 320 apartments, in the city of Jaboatão dos Guararapes, Brazil, throughout 82 concrete pouring days using 415 concrete mixer trucks, with a total of 2,582.50 m3 of concrete.
Findings
The findings identified an average concrete loss of 2.6 percent and the LP indicator varying between 0.15 and 0.97 WH/m3. It could be verified that the loss indicators were influenced mainly by the learning effect associated to the qualification of the labor. In addition, the productivity indicators were strongly influenced by delays at the beginning of the concrete pouring and by problems coming from the sequence of concrete supply.
Originality/value
LP indicators are still literature restricted, especially considering only the concreting step. The direct observations of this study allow the identification of factors that inhibit productivity. The comparison of indicators for the concreting service between the ASF and the conventional system attests to the speed, low cost and efficiency of the system studied in this paper.
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S. Venkataraman, George (Yiorgos) Allayannis and Gerry Yemen
“Suitable for MBA, Executive MBA, GEMBA, and executive education programs, this case uses CEMEX, a global cement producer based in Mexico, to set the stage for unfolding an…
Abstract
“Suitable for MBA, Executive MBA, GEMBA, and executive education programs, this case uses CEMEX, a global cement producer based in Mexico, to set the stage for unfolding an analysis of a growth through acquisition strategy. It offers a discussion about the firm's overall strategy to acquire on a global scale instead of growing organically and provides an opportunity to introduce basic financial, marketing, and operational terms that can be explored in subsequent classes. The material includes a PMI process that further allows discussion on that technique.
The case opens with a conference call and another barrage of questions for CEO Lorenzo Zambrano about his bid to buy the Australia-based Rinker Group in October 2006. Until this point, CEMEX has had a long-standing habit of buying businesses in emerging markets; this acquisition would be a departure from that strategy. If the deal goes through, it would be the single largest acquisition in CEMEX's history, and it would be among its few forays into a developed market other than the neighboring United States. The company has grown exponentially and successfully. Why would this effort be any different? Was the acquisition a good idea or not? And if it was, how would Zambrano and his leadership team convince Wall Street and others of that?”
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