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.
Basins with various mineral resources coexisting and enriching often occupy an important strategic position. The exploration of various mineral resources is repetitive at present due to unshared data and imperfect management mechanism. This situation greatly increases the cost of energy exploitation in the country. Traditional data-sharing mode has several disadvantages, such as high cost, difficulty in confirming the right of data, and lack of incentive mechanism, which make achieving real data sharing difficult. In this paper, we propose a data-sharing mechanism based on blockchain and provide implementation suggestions and technical key points. Compared with traditional data-sharing methods, the proposed data-sharing mechanism can realize data sharing, ensure data quality, and protect intellectual property. Moreover, key points in the construction are stated in the case study section to verify the feasibility of the data-sharing system based on blockchain proposed in this paper.
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.
Residents’ concerns and feelings play pivotal roles in smoothly promoting urban redevelopment. Anxiety, as an intuitive feeling toward uncertainties, generally exists among residents who are confronted with redevelopment, and this feeling has gradually attracted scholars’ attention. However, relatively few studies have focused on the multidimensional view of this concept and its influencing factors. Drawing upon a large-scale questionnaire survey conducted in 13 pilot areas in China, this study refines and verifies five prominent dimensions of anxiety, namely, housing conditions, monetary compensation, public services, life adaptation, and public participation level, through factor analysis and one-sample t-test. The finding contributes to achieving a complete understanding of anxiety, and the scales developed for measuring these dimensions lay the foundation for further empirical studies on anxiety. The individual and collective effects of age, job, and region variables on anxiety dimensions are demonstrated via independent-sample t-test and analysis of variance, which clarifies the formation process of anxiety and highlights the importance of these contextual variables. Tailored strategies for policymaking and engineering management, including establishing reasonable compensation standards, providing equal public services, and delivering high-quality housing, are proposed to relieve residents’ anxiety. These strategies are expected to consider further the sensitive group, such as the elderly, farmers, and casual workers.
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 technologies 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.
The construction industry has long faced the challenge of introducing collaborative systems among multiple stakeholders. This challenge creates a high level of rigidity in terms of processing shared information related to different processes, robust holistic regulations, payment actualizations, and resource utilization across different nodes. The need for a digital platform to cross-connect all stakeholders is necessary. A blockchain-based platform is a prime candidate to improve the industry in general and the construction supply chain (CSC) in particular. In this paper, a literature review is presented to establish the main challenges that CSC faces in terms of its effects on productivity and efficiency. In addition, the effect of applying blockchain platforms on a case study is presented and analyzed from performance and security level. The analysis aims to emphasize that blockchain, as presented in this paper, is a viable solution to the challenges in the CSC regardless of the risks associated with the security and robustness of the flow of information and data protection. Moreover, a threat analysis of applying a blockchain model on the CSC industry is introduced. This model indicates potential attacks and possible countermeasures to prevent the attacks. Future work is needed to expand, quantify, and optimize the threat model and conduct simulations considering proposed countermeasures for the different blockchain attacks outlined in this study.
Vertical ship lifts (VSLs) are widely used in navigation facilities worldwide because of their efficiency and low cost. Although several researchers have investigated fire evacuation strategies for reducing potential safety hazards in VSLs, an effective and integrated application of stairs and elevators when a fire occurs in a VSL is necessary. Several evacuation routes were analyzed according to VSL structure and evacuation times in this study. Objective function corresponding to the minimum vertical evacuation time and related simulation model was subsequently developed to obtain a cooperative evacuation plan considering different numbers of evacuees. The Three Gorges ship lift was used as an example, and simulation results indicate that number of evacuees and exit selection are the main influencing factors of the total evacuation time in the stair- and elevator-coordinated evacuation mode. Furthermore, the distance between people trapped in ship reception chamber and evacuation exits affects evacuees’ choice of exits. The proposed model can provide a theoretical reference for evacuation research during initial fire events in VSLs.
The quality traceability of precast components has largely affected the widespread adoption of prefabricated buildings. Blockchain technology provides an effective solution to change the centralized storage mode of traditional traceability system and its related disadvantages. In this paper, we propose a framework of quality traceability system for precast components based on blockchain technology. The system framework adopts a hybrid blockchain architecture and dual storage mode, defines three types of smart contracts, and creates an interactive and efficient source tracing query method, which could effectively achieve the goals of decentralization, openness, and non-tamperability, as well as efficient traceability.
Lack of trust has been an ongoing issue for decades in construction quality management, hindering the improvement of quality performance. The development of mutual trust depends on immutable, traceable, and transparent construction quality information records. However, current information technologies cannot meet the requirements. To address the challenge, this study explores a blockchain-based framework for construction quality information management, which extends applications of blockchain in the domain of construction quality management. A consortium blockchain system is designed to support construction quality management in which participants’ information permissions and lifecycle are discussed. Additionally, this study presents in detail the consensus process that aims to address the problem of information fraud. The automated compliance checking based on smart contracts is presented as well, aiming to assure that construction products meet regulation requirements. Finally, an example of the consortium blockchain network is visualized to validate the feasibility of blockchain-based construction quality information management. The research shows that blockchain can facilitate mutual trust in construction quality management by providing distributed, encrypted, and secure information records and supporting automated compliance checking of construction quality.
The new mode for managing construction projects with information technology (IT) has attracted worldwide attention because it can help managers and workers perform tasks and bring potential benefits, such as high-quality products and accident-free production, effectively. However, the application of IT in site have not achieved expected results because it is faced with many constraints caused by internal factors from enterprises and projects and external factors from the government and environment. Although many relevant studies have discussed the constraints of implementing different IT and devices in the construction industry or site, few articles have specifically focused on identifying and analyzing the indicator system. In this work, we took China as the background, scientifically identified 23 influential factors that affect the implementation of IT in construction management through literature review and expert interviews. Subsequently, questionnaires were issued, and Delphi method was used to obtain empirical data that aimed at four different management fields. Then, an efficient and convenient method called DEMATEL was used to deal with these data. Afterward, the factors were divided into four categories, namely, core, diving, independent, and impact factors. Finally, the similarities and differences of the analysis results from the four fields were compared, and the key factors were identified. Results show that the cross-domain talent ability, concept and value cognition, and organization structure are core factors in all management fields that should be managed first along with the IT innovation ability in the enterprise. The formulation of technical standards and related device and training input are also critical in specific fields. Strategic planning plays a role in macro control and promotion. Data management and application, platform construction, solution, and collaboration have direct impacts on information management. The research results provide suggestions not only for the government to formulate effective policies for IT application and promotion in construction industry, but also for enterprises to take measures in improving management efficiency in the construction site and realizing its substantial benefits.