Current construction engineering management suffers numerous challenges in terms of the trust, information sharing, and process automation. Blockchain which is a decentralised transaction and data management technology, has attracted increasing interests from both academic and industrial aspects since 2008. However, most of the existing research and practices are focused on the blockchain itself (i.e. technical challenges and limitations) or its applications in the finance service sector (i.e. Bitcoin). This paper aims to investigate the potential of applying blockchain technology in the construction sector. Three types of blockchain-enabled applications are proposed to improve the current processes of contract management, supply chain management, and equipment leasing, respectively. Challenges of blockchain implementation are also discussed in this paper.
Safety is one of the most critical themes in any large-scale railway construction project. Recognizing the importance of safety in railway engineering, practitioners and researchers have proposed various standards and procedures to ensure safety in construction activities. In this study, we first review four critical research areas of risk warning technologies and emergency response mechanisms in railway construction, namely, (i) risk identification methods of large-scale railway construction projects, (ii) risk management of large-scale railway construction, (iii) emergency response planning and management, and (iv) emergency response and rescue mechanisms. After reviewing the existing studies, we present four corresponding research areas and recommendations on the Sichuan–Tibet Railway construction. This study aims to inject new significant theoretical elements into the decision-making process and construction of this railway project in China.
The high-end equipment intelligent manufacturing (HEIM) industry is of strategic importance to national and economic security. Engineering management (EM) for HEIM is a complex, innovative process that integrates natural science, technology, management science, social science, and the human spirit. New-generation information technology (IT), including the internet, cloud computing, big data, and artificial intelligence, have made a remarkable influence on HEIM and its engineering management activities, such as product system construction, product life cycle management, manufacturing resources organization, manufacturing model innovation, and reconstruction of the enterprise ecosystem. Engineering management for HEIM is a key topic at the frontier of international academic research. This study systematically reviews the current research on issues pertaining to engineering management for HEIM under the new-generation IT environment. These issues include cross-lifecycle management, network collaboration management, task integration management of innovative development, operation optimization of smart factories, quality and reliability management, information management, and intelligent decision making. The challenges presented by these issues and potential research opportunities are also summarized and discussed.
This article analyses the recent progressive increase in resourcequantity and production quantity of unconventional natural gas in China, describes its natural properties and the concepts, strategies and approaches of its development, summarizes the special techniques, management concepts and development modes formed in the process of its development, and puts forward proposals to accelerate the development of unconventional natural gas of China. The technically recoverable reserve of unconventional natural gas is 1.7 times that of conventional natural gas and its output in 2012 accounted for 41.8% of the total output in China. Chinese tight gas development has gained success, coal-bed methane development and shale gas production pilots have made important progresses. As the key feature of unconventional natural gas is "low grade", for the effective scale development, developers must build up the engineering concept of low-grade resources development, adhere to the low cost strategy, take the development route of "a step backward and then a step forward", apply such ideas and methods of engineering management as low cost dualistic integrative innovation, full control network management, economic limit theory, integrated operation and "four orientations" engineering management, establish a "two lows" engineering management system, and take reference of the successful development mode of the tight gas in Sulige and the coal-bed methane in the Qinshui basin. In order to achieve the objective of rapid development of nonconventional natural gas in China and to accelerate the development pace, the government should continue to increase support, to speed up the reform of natural gas price adjustment, to set up national comprehensive development and utilization demonstration areas, to input in sustainable technological research and to promote engineering management innovation.?
China is now in an era of large-scale metro construction. This paper reviews the nature of Chinese metro engineering with a specific focus on its organization and market mode, cost structure, safety control and schedule management. Then, an examination on recent research in metro engineering of the National Natural Science Foundation of China (NSFC) is also conducted, which indicates that information and automation based technologies are increasingly used in practice.
This study explores the influence of social media on stock volatility and builds a feature model with an intelligence algorithm using social media data from Xueqiu.com in China, Sina Finance and Economics, Sina Microblog, and Oriental Fortune. We find that the effect of social factors, such as increased attention to a stock’s volatility, is more significant than public sentiment. A prediction model is introduced based on social factors and public sentiment to predict stock volatility. Our findings indicate that the influence of social media data on the next day’s volatility is more significant but declines over time.
The construction sites of mega construction projects (MCP) often have numerous participants with interfacing work within a highly complex system. It is critical how to realize collaborative work and information sharing among such participants. The information and communication technologies (ICTs) provides a technical guarantee for solving this problem. Existing research has been achieved the partial processes digitization of construction site, but certain problems still exist: 1)information perception of the construction site is passive. 2) common collaboration and coordination problems in the construction industry have not been addressed. The emerging trends of ICTs have resulted in the integration of various computer technologies such as CPS, BIM, big data, and cloud computing into construction process, which would changes behavioral and management mode of construction sites. These new ICTs have been applied successfully in MCP, in particular, Hong Kong-Zhuhai-Macao Bridge project. A new management mode of construction sites is inspired by these case. In this paper, a new management mode of construction site for MCP has been proposed, namely, smart construction site. The ultimate goal of smart construction site is to accomplish safe, efficient and high-quality construction. This study put forward the conceptual framework for smart construction site, and have identified three key elements of smart construction site, including information support platform, collaboration work, and intelligent construction management. A case study on Hong Kong-Zhuhai-Macao Bridge project work as an evidence to support the practicability of the proposed mode. Significant contributions of this study is to propose a new management mode for MCP in construction industry, which would enrich the body of knowledge or the construction management community. Future research should be dedicated to further explore the potential of smart construction site in MCP management.
The low carbon energy transition has attracted worldwide attention to mitigate climate change. Renewable energy (RE) is the key to this transition, with significant developments to date, especially in China. This study systematically reviews the literature on RE development to identify a general context from many studies. The goal is to clarify key questions related to RE development from the current academic community. We first identify the forces driving RE development. Thereafter, we analyze methods for modeling RE developments considering the systematic and multiple complexity characteristics of RE. The study concludes with insights into the target selection and RE development roadmap in China.
The global production of bio-based chemical products, particularly biofuel products, has tremendously increased over the last decade. Driven largely by a new legislation, this increase has generated the commercialization of new products and processes. Unfortunately, alongside these developments were a significant number of accidents and explosions at biofuel facilities, entailing property damage, injury, and even deaths. The aim of this current study is to draw attention to incidents that occurred in biofuel facilities and clarify the misconceptions that cause people to ignore safety in bio-refineries. A process hazard analysis (PHA) method, namely the hazard and operability study (HAZOP), is first used in biofuel production. This method is an ethanol distillation and dehydration process. Through the HAZOP analysis, 36 recommended action items are proposed, and all recommendations are accepted. The case study reveals that potential high-level risks exist in the current biofuel process design and operating procedures, and these risks can be better controlled if they can be previously identified.
With the accelerated urbanization in China, passenger demand has dramatically increased in large cities, and traffic congestion has become serious in recent years. Developing public urban rail transit systems is an indispensable approach to overcome these problems. However, the high energy consumption of daily operations is an emerging issue due to increased rail transit networks and passenger demands. Thus, reducing the energy consumption and operational cost by using advanced optimization methodologies is an urgent task for operation managers. This work systematically introduces energy-saving approaches for urban rail transit systems in three aspects, namely, train speed profile optimization, utilization of regenerative energy, and integrated optimization of train timetable and speed profile. Future research directions in this field are also proposed to meet increasing passenger demands and network-based urban rail transit systems.
The mechanism of risk allocation is designed to protect all stakeholders, and it is vital to project success. Qualitative and quantitative ways of optimizing risk allocation have been well documented in extant literature (e.g., allocation principles, models, and solutions), and the foci of existing research are usually the maximization of rational utility. Few research has focused on partners’ social preferences affecting the output of risk allocation. This study presents a quantitative approach based on modeling alliance member (AM)’s inequity aversion (IA) to analyze risk-sharing arrangements in an alliance project. Fehr and Schmidt’s inequity-aversion model is integrated into modeling partner’s utility. This paper derives results for an alliance leader (AL)’s optimal risk-sharing ratio and AM’s optimal risk-management effort simultaneously. The derivation is based on solving a restrained optimization problem using the conception and methods from Stackelberg game theory. Results show that an AM’s IA significantly affects risk allocation between AL and AM. Specifically, envious preference is positively related to AL’s optimal risk-sharing ratio, whereas guilty preference negatively affects AL’s optimal risk-sharing ratio. These findings will be of interest to academics and practitioners involved in designing alliance negotiations.
Drawing on resource dependence theory, this paper develops and empirically tests a model for understanding how the implementation of building information modeling (BIM) in construction projects impacts the performance of different project participating organizations through improving their interorganizational collaboration capabilities. Based on two sets of survey data collected from designers and general contractors in BIM-based construction projects in China, the results from partial least squares analysis and bootstrapping mediation test provide clear evidence that BIM-enabled capabilities of information sharing and collaborative decision-making as a whole play a significant role in determining BIM-enabled efficiency and effectiveness benefits for both designers and general contractors. The results further reveal that designers and general contractors benefit from project BIM implementation activities significantly non-equivalently, and that this non-equivalence closely relates to the different roles played by designers and general contractors in BIM-enabled interorganizational resource exchange processes. The findings validate the resource dependence theory perspective of BIM as a boundary spanning tool to manage interorganizational resource dependence in construction projects, and contribute to deepened understandings of how and why project participating organizations benefit differently from the implementation of interorganizational information technologies like BIM.
Through analysis of articles published from 2000 to March 2014 in Automaton in Construction (AUTCON), an international research journal published by Elsevier, this paper summarizes the topics of research and the institutions worldwide where research was conducted in construction safety engineering and management. Seventy-one articles published during this time focused on Information Technology (IT) applications in this field were selected for analysis. The underlying research topics and their related IT implementations are discussed, and research trends in allied specialties are identified.
Building and infrastructure construction projects can be viewed as a complex system consisting of many subsystems. Over the last two decades, considerable researches that use system dynamics (SD) as an analytical and modeling approach exist to address construction project management issues. However, only few critical reviews have been conducted to provide an in-depth understanding of SD application in construction project management. Moreover, many studies have failed to apply SD accurately. Therefore, the present study aims to gain an understanding of the current state of play and future directions in applying SD method in construction project management research, by undertaking a comprehensive review of 105 relevant articles published from 1994 to 2018. These articles are analyzed in terms of annual publication rate, key papers and their contribution, critical issues in SD application, and research topics. A significant increase in the number of publications in the last five years has been observed. When applying SD method to model construction system, the following aspects must be carefully considered: Model boundary, model development, model test, and model simulation. In addition, SD has been applied in a wide range of research topics, including (1) sustainable construction; (2) design error, rework, and change management; (3) risk management; (4) resource management; (5) decision making; (6) hybrid modeling; (7) safety management; (8) PPP project; and (9) organization performance. Based on the review findings, this study discusses three future research directions, namely, integration of SD with other methods, uncertainty analysis, and human factor analysis. This study can help researchers gain an in-depth understanding of the critical issues in the application of SD in construction management and the state-of-the-art of SD research.
Building information modeling (BIM) and project management are two major research topics that accommodate large volumes of research efforts. BIM has been interpreted as a process technology that aids in enhancing project management. Hence, the investigation from an interdisciplinary perspective of the two concepts may bring new insights to understanding related research. In this paper, a structural approach is adopted in reviewing BIM studies in project management from 2005 to 2017 within identified target journals. This review aims to classify the major research directions and topics for BIM research in project management. Moreover, given BIM’s potential for application in project management, this paper attempts to establish a fundamental research foundation for a new paradigm of project management that incorporates BIM, namely, BIM-based project management. The preliminary result suggests that BIM research in project management develops drastically in the examined duration. The research directions of BIM studies in project management include enabling BIM as a technology in project management; BIM application as a solution for specific project management scopes; integration issues of BIM that have been brought to project management; institutional environment and regulatory governance of BIM in realizing project management strategies; and analysis of effects and strategies of BIM adoption and implementation in projects. The directions and trends are then analyzed to develop a research route for BIM studies in project management. Finally, conclusions focus on the relations of the research directions, as well as the contributions and theoretical implications of this review. Future research areas are also recommended.
Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries. Motivated by the major development strategies and needs of industrial intellectualization in China, this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization, as well as their application to smart industrial engineering. First, this study describes a general methodology for the fusion of data analytics and optimization. Then, it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing. Finally, it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization. The framework uses data analytics to perceive and analyze industrial production and logistics processes. It also demonstrates the intelligent capability of planning, scheduling, operation optimization, and optimal control. Data analytics and system optimization tech-nologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing, resources and materials, energy, and logistics systems, such as high energy consumption, high costs, low energy efficiency, low resource utilization, and serious environmental pollution. The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency. Therefore, industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.
As the coal-dominated energy structure will remain unchanged in the short term, the sustainable development of the coal industry is still serving as one of the foundations for the sound development of the national economy. The construction of modernized mines based on "four orientations", that is, orientations of scale production, modern technology and equipment, informationized management and professional working team, has been rapidly enhancing its development in the recent decade. However, in the next decade or an even longer period, the industry, with the energy centre shifting to the West of China, will be exposed to new options and development in the layout, structure, model, technology, etc.
Cities are incorporating smart and green infrastructure components in their urban design policies, adapting existing and new infrastructure systems to integrate technological advances to mitigate extreme weather due to climate change. Research has illustrated that smart green infrastructure (SGI) provides not only climate change resilience but also many health and wellbeing benefits that improve the quality of life of citizens. With the growing demand for smart technology, a series of problems and challenges, including governance, privacy, and security, must be addressed. This paper explores the potential to transition from grey, green, or smart silos to work with nature-based solutions and smart technology to help change cities to achieve considerable environmental and socio-economic benefits. The concepts of grey, green, and smart infrastructure are presented, and the needs, benefits, and applications are investigated. Moreover, the advantages of using integrated smart, green nature-based solutions are discussed. A comprehensive literature review is undertaken with keyword searches, including journal papers, stakeholder and case study reports, and local authority action plans. The methodology adopts multimethod qualitative information review, including literature, case studies, expert interviews, and documentary analysis. Published data and information are analysed to capture the key concepts in implementing SGI systems, such as storm-water control, flood and coastal defense, urban waste management, transportation, recreation, and asset management. The paper investigates the elimination of silo approaches and the alleviation of the destructions caused by extreme weather events using these interdependent SGI systems supported by novel data-driven platforms to provide nature-based solutions to boost the health and wellbeing of the residents.
The field of engineering management usually involves evaluation issues, such as program selection, team performance evaluation, technology selection, and supplier evaluation. The traditional self-evaluation data envelopment analysis (DEA) method usually exaggerates the effects of several inputs or outputs of the evaluated decision-making unit (DMU), resulting in unrealistic results. To address this problem, scholars have proposed the cross-efficiency evaluation (CREE) method. Compared with the DEA method, CREE can rank DMUs more completely by using reasonable weights. With the extensive application of this technique, several problems, such as non-unique weights and non-Pareto optimal results, have arisen in CREE methods. Therefore, the improvement of CREE has attracted the attention of many scholars. This paper reviews the theory and applications of CREE, including the non-uniqueness problem, the aggregation of cross-efficiency data, and applications in engineering management. It also discusses the directions for future research on CREE.
System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.
The construction of new buildings represents a significant investment. The goal of new building construction is to maximize value and minimize cost while staying on time and within budget. Translating customer requirements into engineering terms for new construction design is vital for a construction project to be successful. Quality function deployment has been successfully used in product development to capture the voice of the customer and translate it into engineering characteristics. Quality function deployment then carries these parameters into production and service to ensure the voice of the customer is being met with the final product. The house of quality, a tool within quality function deployment, can provide a means for comparison of owner’s project requirements and the proposed design, along with identifying how the design decisions impact meeting customer requirements and green building requirements. Quality function deployment can effectively link the project phases through design and construction and into operations and maintenance to ensure the owner’s project requirements are met with the final building. This research identifies and categorizes studies of quality function deployment applications in construction. The research method used is a systematic literature review from databases related to quality function deployment in the construction industry published in the periodicals through 2016. The principal findings of implementations, practices, and integrated approaches are then summarized. This article intends to propel further research of quality function deployment in the construction sector.
The global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient functions into logistics operations. However, they also change the narrative of logistics management. Scholars in the areas of engineering, logistics, transportation, and management are attracted by this revolution. Operations management research on smart logistics mainly concerns the application of underlying technologies, business logic, operation framework, related management system, and optimization problems under specific scenarios. To explore these studies, the related literature has been systematically reviewed in this work. On the basis of the research gaps and the needs of industrial practices, future research directions in this field are also proposed.
Train speed profile optimization is an efficient approach to reducing energy consumption in urban rail transit systems. Different from most existing studies that assume deterministic parameters as model inputs, this paper proposes a robust energy-efficient train speed profile optimization approach by considering the uncertainty of train modeling parameters. Specifically, we first construct a scenario-based position–time–speed (PTS) network by considering resistance parameters as discrete scenario-based random variables. Then, a percentile reliability model is proposed to generate a robust train speed profile, by which the scenario-based energy consumption is less than the model objective value at
Production planning and scheduling are becoming the core of production management, which support the decision of a petrochemical company. The optimization of production planning and scheduling is attempted by every refinery because it gains additional profit and stabilizes the daily production. The optimization problem considered in industry and academic research is of different levels of realism and complexity, thus increasing the gap. Operation research with mathematical programming is a conventional approach used to address the planning and scheduling problem. Additionally, modeling the processes, objectives, and constraints and developing the optimization algorithms are significant for industry and research. This paper introduces the perspective of production planning and scheduling from the development viewpoint.
This research investigates recent developments in assessment methods of green buildings and compares the differences in rating systems among the United Kingdom, USA, and Germany. There are indications that the rating systems are moving from green buildings to sustainable buildings. In order to understand the recent research in academic areas, we survey the recent Ph.D. dissertations and literature related to green building assessment. Discussion is provided on the major research areas of green buildings, which cover accountability of life cycle cost, methodology for balancing the three pillars, and government vision and public policy.
Cyber–physical systems (CPS) are intended to facilitate the tight coupling of the cyber and physical worlds. Their potential for enhancing the delivery and management of constructed facilities is now becoming understood. In these systems, it is vital to ensure bi-directional consistency between construction components and their digital replicas. This paper introduces the key features of CPS and describes why they are ideally suited for addressing a number of problems in the delivery of construction projects. It draws on examples of research prototypes developed using surveys, field experiments, and prototyping methodologies, to outline the key features and benefits of CPS for construction applications and the approach to their development. In addition, it outlines the lessons learned from developing various systems for the design, construction and management of constructed facilities, which include building component placement and tracking, temporary structures monitoring, and mobile crane safety. The paper concludes that the construction industry stands to reap numerous benefits from the adoption of CPS. It states that the future direction of CPS in construction will be driven by technological developments and the extent to which CPS is deployed in new application areas.
Green Smart City (GSC), is one of the new types of cities which integrates eco-concepts and information technologies. As GSC construction is a resource intensive process, it requires a large amount of knowledge, information, talent and capital. Thus, setting up an innovation ecosystem is an astute way to promote the construction of a GSC. This paper, based on the case study by the Insigma Group, tries to explore the rules of innovation ecosystem building for the construction of GSCs in China.
This paper aims to overview Building Information Modeling (BIM) implementation and problems of BIM implementation in Japan. First, BIM implementation guidelines and pilot projects are introduced. Then, some popular BIM software together with typical implementation cases are provided. BIM implementation in Japan is not always encouraged via a top-down consensus in architectural firms and general contractors, as the client and architects can reduce the project risk inherent in design and drawings by transferring these tasks to a general contractor. The paper finally discusses the problems in project management to present a strategy to develop a new version of BIM that will provide value to all of the stakeholders of a project.
Blockchain has attracted much attention in recent years with the development of cryptocurrency and digital assets. As the underlying technology of cryptocurrency, blockchain has numerous benefits, such as de-centralization, collective maintenance, tamper-resistance, traceability, and anonymity. The potential of the blockchain technology (BT) is widely recognized in the financial field. Although some scholars have proposed the combination of blockchain and supply chain finance (SCF), the details of this combination is rarely mentioned. This study first analyzes the coupling between SCF and blockchain technology. Second, the conceptual framework of blockchain-driven SCF platform (BcSCFP) is presented. Third, the operation process of three SCF models on the BcSCFP is proposed. Finally, a case study combined with actual events is conducted. This paper has a positive practical significance in the operation and management of banks and loan enterprises.
