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.
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.
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.
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.
Decisions in supply chains are hierarchically organized. Strategic decisions involve the long-term planning of the structure of the supply chain network. Tactical decisions are mid-term plans to allocate the production and distribution of materials, while operational decisions are related to the daily planning of the execution of manufacturing operations. These planning processes are conducted independently with minimal exchange of information between them. Achieving a better coordination between these processes allows companies to capture benefits that are currently out of their reach and improve the communication among their functional areas. We propose a network representation for the multilevel decision structure and analyze the components that are involved in finding integrated solutions that maximize the sum of the benefits of all nodes of the decision network. Although such task is very challenging, significant research progress has been made in each component of this structure. An overview of strategic models, mid-term planning models, and scheduling models is presented to address the solution of each node in the decision network. Coordination mechanisms for converging the integrated solutions are also analyzed, including solving large-scale models, multiobjective optimization, bi-level programming, and decomposition. We conclude by summarizing the challenges that hinder the full integration of multilevel decision making in supply chain management.
While in the EU alone 80 million citizens are suffering from excessive environmental noise, the conventional approach, i.e., reduction of ‘sound level’, does not always deliver the required improvements in quality of life. The growing field of ‘soundscape studies’ is addressing this gap by considering the sound environment as perceived, in context, with an interdisciplinary approach. However, soundscapes are hugely complex, and measuring them as a basis for environmental design requires a step change to the discipline. This paper explores the need for developing ‘soundscape indices’, in the movement from noise control to soundscape creation, adequately reflecting levels of human comfort, the impact of which will be reminiscent of that of the Decibel scale created by Bell Systems a century ago. By analysing the soundscape design of urban open public spaces, the coherent steps for achieving this are also discussed, including characterising soundscapes by capturing soundscapes and establishing a comprehensive database; determining key factors and their influence on soundscape quality based on the database; developing, testing and validating soundscape indices; and demonstrating the applicability of the soundscape indices in the management of our sound environment.
A wide range of industrial Internet of Things (IoT) applications have been developed and deployed in recent years. IoT has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of RFID, wireless, mobile and sensor devices. In an effort to understand the development of IoT in industries, this paper reviews the current research of IoT, key enabling technologies, major IoT applications in industries, and identifies research trends and challenges. As IoT has received support from governments and businesses across the globe, IoT will also greatly impact One Belt One Road (OBOR) in foreseeable future.
Boosting the resilience of power systems is a core requirement of smart grids. In fact, resilience enhancement is crucial to all critical infrastructure systems. In this study, we review the current research on system resilience enhancement within and beyond smart grids. In addition, we elaborate on resilience definition and resilience quantification and discuss several challenges and opportunities for system resilience enhancement. This study aims to deepen our understanding of the concept of resilience and develop a wide perspective on enhancing the system resilience for critical infrastructures.
Engineering informatics is an emerging engineering discipline integrating information technology or informatics with a variety of engineering disciplines. It is an interdisciplinary scientific subject focusing on applying advanced information and communications technology (ICT) to a variety of engineering disciplines. Rapid advances in industrial information integration methods have spurred the growth of new techniques that can be used for probing industrial information integration including engineering informatics. These techniques include business process management (BPM), enterprise architecture (EA), enterprise application integration (EAI), service-oriented architecture (SOA), and others. Practical applications may require a combination of these techniques that have originated from different disciplines. These techniques have the potential to contribute to engineering informatics. For integrating complex engineering systems, both formal methods and systems methods are crucial. In this paper, we briefl review the state of the art of engineering informatics as it interfacing with industrial information integration.
In large cities with heavily congested metro lines, unexpected disturbances often occur, which may cause severe delay of multiple trains, blockage of partial lines, and reduction of passenger service. Metro dispatchers have taken a practical strategy of rescheduling the timetable and adding several backup trains in storage tracks to alleviate waiting passengers from crowding the platforms and recover from such disruptions. In this study, we first develop a mixed integer programming model to determine the optimal train rescheduling plan with considerations of in-service and backup trains. The aim of train rescheduling is to frequently dispatch trains to evacuate delayed passengers after the disruption. Given the nonlinearity of the model, several linearization techniques are adapted to reformulate the model into an equivalent linear model that can be easily handled by the optimization software. Numerical experiments are implemented to verify the effectiveness of the proposed train rescheduling approach.
Train speed trajectory optimization is a significant issue in railway traffic systems, and it plays a key role in determining energy consumption and travel time of trains. Due to the complexity of real-world operational environments, a variety of factors can lead to the uncertainty in energy-consumption. To appropriately characterize the uncertainties and generate a robust speed trajectory, this study specifically proposes distance-speed networks over the inter-station and treats the uncertainty with respect to energy consumption as discrete sample-based random variables with correlation. The problem of interest is formulated as a stochastic constrained shortest path problem with travel time threshold constraints in which the expected total energy consumption is treated as the evaluation index. To generate an approximate optimal solution, a Lagrangian relaxation algorithm combined with dynamic programming algorithm is proposed to solve the optimal solutions. Numerical examples are implemented and analyzed to demonstrate the performance of proposed approaches.
This study aims to find appropriate locations for wind farms that can maximize the overall energy output while controlling the effects of wind speed variability. High wind speeds are required to obtain the maximum possible power output of a wind farm. However, balancing the wind energy supplies over time by selecting diverse locations is necessary. These issues are addressed using network-based models. Hence, actual wind speed data are utilized to demonstrate the advantages of the proposed approach.
Travel time reliability is of increasing importance for travelers, shippers, and transportation managers because traffic congestion has become worse in major urban areas in recent years. To better evaluate the urban network-wide travel time reliability, five indices based on the emerging on-demand ride service data are proposed: network free flow time rate (NFFTR), network travel time rate (NTTR), network planning time rate (NPTR), network buffer time rate (NBTR), and network buffer time rate index (NBTRI). These indices take into account the probability distribution of the travel time rate (i.e., travel time spent for the unit distance, in min/km) of each origin-destination (OD) pair in the road network. We use real-world data extracted from DiDi-Chuxing, which is the largest on-demand ride service platform in China. For demonstrative purposes, the network-wide travel time reliability of Beijing is analyzed in detail from two dimensions of time and space. The results show that the road network is more unreliable in AM/PM peaks than other time periods, and the most reliable time period is the early morning. Additionally, we can find that the central region is more unreliable than other regions of the city based on the spatial analysis results. The proposed network travel time reliability indices provide insights for the comprehensive evaluation of the road network traffic dynamics and day-to-day travel time variations.
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.
The multi-wave algorithm (Glover, 2016) integrates tabu search and strategic oscillation utilizing repeated waves (nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers’ demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.
This paper takes an overview of the Hongshiyan landslide dam triggered by an earthquake near Ludian County in Zhaotong City, Yunnan Province, introduces how the danger removal plan is drafted and implemented, and analyzes the outcome of its implementation. The paper then explains the significance and effect of coordinated management in the event of natural disasters and other public safety emergencies, and discusses ways to improve coordinated management.
The author discusses the application of System Dynamics to high-level strategic simulation in construction. In particular, System Dynamics’ strength on representing feedback processes, aggregation, soft variables, and continuous simulation clock for high-level simulation are discussed using real modeling examples. From this exercise, it is concluded that System Dynamics offers a great potential for strategic simulation in construction. Further, the author proposes a comprehensive simulation framework that integrates System Dynamics and Discrete Event Simulation for a strategic decision making process in construction where operational details should be taken into account.
In the EU Horizon 2020 Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called “IN2CLOUD,” which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other (including domain knowledge and experience) but do not want to share their raw data or information. IN2CLOUD will help the movement of railway industry systems from “local” to “global” optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology (IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.
L♮-convexity, one of the central concepts in discrete convex analysis, receives significant attentions in the operations literature in recent years as it provides a powerful tool to derive structures of optimal policies and allows for efficient computational procedures. In this paper, we present a survey of key properties of L♮-convexity and some closely related results in lattice programming, several of which were developed recently and motivated by operations applications. As a new contribution to the literature, we establish the relationship between a notion called m-differential monotonicity and L♮-convexity. We then illustrate the techniques of applying L♮-convexity through a detailed analysis of a perishable inventory model and a joint inventory and transshipment control model with random capacities.
As part of China’s “the Belt and Road” strategy, China Railway Express provides alternative shipping routes and transportation modes from Asia to Europe and creates new opportunities for intermodal transportation in the shipping industry. A time–distance-based cost (time cost) function was proposed to compare China Railway Express with traditional transportation modes. Time cost was related to different types of cargoes, which exhibit distinct sensitivity to time. Using the proposed cost function as basis, we identified the cost indifference area where total costs are equal. Further analysis was performed for selecting the transportation mode and supply area for a specific cargo. This study provides various parties, such as business owners, the government, and the shipping industry, with many valuable insights.
The procurement of public construction projects must walk a fine line between the corruption of state officials and collusion of contractors. The method of awarding projects to the lowest responsible tenderer was originally implemented to guard against corruption of state officials. However, an investigation of the construction industry in the Canadian province of Quebec showed that lowest-tender-offer procurement gave rise to collusion of companies tendering for the contracts. Alternatively, best-value procurement has been used for decades, but here problems arise owing to the necessity of subjective judging of measures other than price to compare bids, giving rise to time- and money-consuming protests. The paper proposes a compelling argument that the construction engineering management (CEM) culture should refocus its efforts on enhancing project cost certainty rather than merely searching for means to design a project in a manner that produces the lowest initial cost, and awards the construction to the lowest tender offer that focuses on cost savings during the project development and delivery process. The difference in the two approaches is subtle but extremely important. To make the transition, the engineering management tools must be advanced to the next level. This means that all project control tools for managing cost, schedule, and technical scope must be transformed from working in the deterministic mode to the stochastic mode, thus making the probability of completing the project within or below its official budget the primary decision criterion. To do so, CEMs must accept that there is a benefit in paying more for an alternative that increases cost certainty for the entire project. The authors of this paper hope that it will provide the grist for a more general dialog across all industry sectors where engineering management is practiced.
Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.
Using the theory of human blood circulation system, the authors explore the importance of remanufacturing in Industry 4.0. In this paper, they draw analogies between smart factory and human heart, between smart products and blood, and, between product function and nutrition and oxygen in the blood. Remanufacturing is analogous to the ingestion of oxygen and nutrition in lesser circulation or systemic circulation. Remanufacturing well supports recycling production, which is significant in realizing intelligent industry. Furthermore, this paper discusses the development direction of remanufacturing engineering in Industry 4.0 ages.
Based on a literature review and the context characteristics of construction megaprojects (CMPs), a multidimensional connotation model of CMP citizenship behavior was proposed, including definitions, actors, and dimensions. Organizational citizenship behavior includes Cooperation Behavior (CoB), Collaboration Behavior (ClB), Innovation Behavior (IB), Voice Behavior (VB),Conscientiousness & Dedication Behavior (CDB), Benefit Defense Behavior (BDB) and Guanxi (Relations) Maintenance Behavior (GMB). Actors were divided into three levels that were project managers (individual), participant agents (group) and project organization (network).
Engineering projects can be subject to significant complexity, which may result in a number of issues and challenges that need to be addressed throughout the project life-cycle. Traditionally projects have been viewed according to the so called “iron triangle,” i. e., achievement of project milestones according to schedule, cost and quality targets. While these targets are fundamentally important to the performance of engineering projects, it is possible to view projects on a systemic level in order to allow an adequate focus on all the underpinning factors that have the potential to influence the performance of projects. Consequently, a management framework has been developed that is based on an integrated systems perspective of engineering projects, where the performance of projects is a function of six contributing sub-systems that are: process, technology, resources, knowledge, culture and impact.
To develop a lean and green construction industry, Lean Construction (LC) is proposed as a new construction production method to improve the efficient use of resources and the value of construction supply chains, which has received increasing research concerns from scholars and practitioners. Based on related articles covered by the Web of Science and Scopus databases between 1995 and 2014, this study conducts a scientometric analysis. The analysis identifies four core topics in existing research, including: Last Planner System (LPS); production control theory; improvement and evaluation of productivity; and principle of value. Three major directions of LC research: greening LC; Building Information Modeling (BIM) based LC; and lean safety management, are also proposed. Lastly, several recommendations for future LC research and practice are provided in the literature review.
Throughout history mankind has sought to improve its economic and even its spiritual development through the creation of gargantuan and awe-inspiring infrastructure projects. The twenty-first century has seen the rapid growth of the use of this type of project in providing society’s needs: such projects are widely referred to as “mega-projects”. Mega-projects are extremely large-scale infrastructure projects typically costing more than $1 billion. Mega-projects include power-plant (conventional, nuclear or renewable), oil and gas extraction and processing projects and transport projects such as highways and tunnels, bridges, railways, seaports and even cultural events such as the Olympics. Mega-projects are united by their extreme complexity (both in technical and human terms) and by a long record of poor delivery. What to do in the face of this dilemma is a question that is still being asked by mega-project practitioners and academics alike.
This paper presents the unique work of the MEGAPROJECT COST Action which brings together a multi-disciplinary network of over 80 researchers from 24 countries to respond to this dilemma. Mega-project’s aim involves capturing the existing performance of large infrastructural mega-projects and understanding how their delivery can be improved. In order to do this, the investigation has gathered together the MEGAPROJECT Portfolio. The Portfolio contains meta-data on a wide range of mega-projects from across countries and sectors and acts as a firm empirical foundation for the investigation’s activities.
Having assembled the MEGAPROJECT Portfolio, this paper shows how analyzing the Portfolio shatters myths of mega-project management and identifies new areas of fruitful investigation. Mega-project’s findings downplay the importance of formal project management tools and techniques in insuring successful delivery. Instead mega-project highlights the need to concentrate on the impact of financing on project governance, the technical modularization of the project and the devastating roles that eternal stakeholders can have on mega-project delivery. Most importantly, it discusses how we can effectively learn across mega-projects in order to maximize their value to their stakeholders and to society as a whole.