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.
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.
Over the past decade, electric vehicles (EVs) have been considered in a growing number of models and methods for vehicle routing problems (VRPs). This study presents a comprehensive survey of EV routing problems and their many variants. We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip. The related literature can be roughly divided into nine classes: Electric traveling salesman problem, green VRP, electric VRP, mixed electric VRP, electric location routing problem, hybrid electric VRP, electric dial-a-ride problem, electric two-echelon VRP, and electric pickup and delivery problem. For each of these nine classes, we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.
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.
The construction of megaprojects has always resulted in extensive and long-term impacts on the society. However, the performance of megaproject management is poor, and improving it remains an urgent and necessary issue. Although many studies on megaproject success have been conducted, existing studies on the driving factors of successful megaproject construction are rather limited. Therefore, this study aims to systematically explore the key factors that can lead to successful megaproject construction management based on three cases: The Beijing–Shanghai High-Speed Railway, the Three Gorges Dam, and the Hong Kong–Zhuhai–Macao Bridge. Mixed research methods, such as literature review, case studies, and expert interviews, were used in this study. Consequently, 11 driving factors, namely, government support, public support, accumulation and application of technology and experience, development and innovation of technology, innovation and application of management system, organizational mode and structure, top management support, project culture, megaproject citizenship behavior, corporate reputation, and fulfillment of social responsibilities, were identified and grouped into five categories, namely, project environment, construction capabilities, organization, positive culture and behavior, and requirements for sustainable development. The contributions of this study lie in two aspects. First, the driving factors of successful megaproject construction are identified to deepen the understanding of industrial practitioners, assist them in focusing on key factors, and aid them in effectively managing megaprojects. Second, researchers could use the identified driving factors in conducting further empirical studies and apply them in future projects to enhance their chances of success.
The integration of building information modeling (BIM) and lean construction (LC) provides a solution for the management of megaprojects. Previous studies have generally focused on the theoretical or empirical adoption of BIM and LC. Moreover, only a few studies have examined the approach of simultaneously using BIM and LC in megaprojects. Therefore, an intensive study on the application of BIM and LC in megaprojects, particularly to explore considerably effective integrated application modes of BIM and LC in megaprojects, will substantially promote the management efficiency of megaprojects. The current study describes a method that integrates owner-dominated BIM and LC that was developed in a case study. The proposed method provides a framework for all stakeholders to use BIM and LC in a megaproject dominated by the owner. The interactional relations among the owner, BIM, and LC were analyzed and positive interactions were identified. These positive interactions served as a basis for the implementation of this integrated approach in a case study and could be applied to other megaprojects. The megaproject (i.e., airport construction project) was examined to verify the performance of the developed method. Results showed that the integration of BIM and LC dominated by the owner can improve management performance and achieve high quality standard.
Innovation and knowledge diffusion in megaprojects is one of the most complicated issues in project management. Compared with conventional projects, megaprojects typically entail large-scale investments, long construction periods, and conflicting stakeholder interests, which result in a distinctive pattern of innovation diffusion. However, traditional investigation of innovation diffusion relies on subjective feedback from experts and frequently neglects inter-organizational knowledge creation, which frequently emerges in megaprojects. Therefore, this study adopted project network theory and modeled innovation diffusion in megaprojects as intra- and inter-organizational learning processes. In addition, system dynamics and fuzzy systems were combined to interpret experts’ subject options as quantitative coefficients of the project network model. This integrated model will assist in developing an insightful understanding of the mechanisms of innovation diffusion in megaprojects. Three typical network structures, namely, a traditional megaproject procurement organization (TMO), the environ megaproject organization (EMO), and an integrated megaproject organization (IMO), were examined under six management scenarios to verify the proposed analytic paradigm. Assessment of project network productivity suggested that the projectivity of the TMO was insensitive to technical and administrative innovations, the EMO could achieve substantial improvement from technical innovations, and the IMO trended incompatibly with administrative innovations. Thus, industry practitioners and project managers can design and reform agile project coordination by using the proposed quantitative model to encourage innovation adoption and reduce productivity loss at the start of newly established collaborations.
In this paper, we briefly review the development of ranking and selection (R&S) in the past 70 years, especially the theoretical achievements and practical applications in the past 20 years. Different from the frequentist and Bayesian classifications adopted by Kim and Nelson (2006b) and Chick (2006) in their review articles, we categorize existing R&S procedures into fixed-precision and fixed-budget procedures, as in Hunter and Nelson (2017). We show that these two categories of procedures essentially differ in the underlying methodological formulations, i.e., they are built on hypothesis testing and dynamic programming, respectively. In light of this variation, we review in detail some well-known procedures in the literature and show how they fit into these two formulations. In addition, we discuss the use of R&S procedures in solving various practical problems and propose what we think are the important research questions in the field.
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.
Strong aftershocks generally occur following a significant earthquake. Aftershocks further damage buildings weakened by mainshocks. Thus, the accurate and efficient prediction of aftershock-induced damage to buildings on a regional scale is crucial for decision making for post-earthquake rescue and emergency response. A framework to predict regional seismic damage of buildings under a mainshock–aftershock (MS–AS) sequence is proposed in this study based on city-scale nonlinear time-history analysis (THA). Specifically, an MS–AS sequence-generation method is proposed to generate a potential MS–AS sequence that can account for the amplification, spectrum, duration, magnitude, and site condition of a target area. Moreover, city-scale nonlinear THA is adopted to predict building seismic damage subjected to MS–AS sequences. The accuracy and reliability of city-scale nonlinear THA for an MS–AS sequence are validated by as-recorded seismic responses of buildings and simulation results in published literature. The town of Longtoushan, which was damaged during the Ludian earthquake, is used as a case study to illustrate the detailed procedure and advantages of the proposed framework. The primary conclusions are as follows. (1) Regional seismic damage of buildings under an MS–AS sequence can be predicted reasonably and accurately by city-scale nonlinear THA. (2) An MS–AS sequence can be generated reasonably by the proposed MS–AS sequence-generation method. (3) Regional seismic damage of buildings under different MS–AS scenarios can be provided efficiently by the proposed framework, which in turn can provide a useful reference for earthquake emergency response and scientific decision making for earthquake disaster relief.
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.
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.
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.
This multiple case study of a contracting firm contributes to understanding the barriers that organizations face during the implementation of building information modeling (BIM) by providing insights into the impact of these barriers across different organizational levels (i.e., from top management to project teams) and by relating these barriers to different degrees of BIM maturity. First, we observe the dominance of barriers related to the motivation, competence, and time capacity of people across all levels of an organization. Second, the cluster of barriers at the middle-management level highlights the important role of this level in reducing these barriers. Third, only those cases with a low level of BIM maturity have struggled with lack of top management support, thereby highlighting the importance of such support in achieving BIM maturity growth. High BIM maturity situations are more prone to externally oriented barriers in attempting to further leverage the benefits of BIM. Our study provides insights on where to focus BIM implementation measures and how to enhance organizational BIM maturity.
Servitization of manufacturing has become one of the main pathways for transition and upgrade in the manufacturing industry. New information and communication technologies (ICTs), such as the Internet of Things, Big Data, and Cloud Computing have enabled the servitization of manufacturing in terms of value creation, resource management, and supply chain management. This study presents a comprehensive review on the servitization in operations management in the era of new ICTs. A new value chain framework is proposed under the business model that revolves around servitization, which showcases the new activities and ways of implementation in the era of new ICTs. The virtualization, configuration, and evaluation of integrated manufacturing and service resources are analyzed. In particular, the methods used in new ICT-supported resource management platforms are surveyed. Problems in the supply chain management in manufacturing services (including the selection of partners, as well as the coordination, planning, and scheduling among members) are presented. This study concludes with a discussion on state-of-the-art servitization in operations management in the era of new ICTs.
The construction industry is facing a gradual but important transformation toward more productivity and collaboration. In this framework, two major approaches are often cited in the literature as having the potential to improve the practices in the industry: Building Information Modeling (BIM) and Lean Construction. Several scientific studies have demonstrated the synergy of these two approaches and very recent research has reported positive results from the use of software applications as support for their implementation on construction sites. However, the stakes of such integration have been very little studied. This article presents the results of a research project conducted within a general contractor firm that decided to implement BIM and Last Planner System (LPS) on its construction sites. The research uses a four-stage action research approach, including the characterization of the research issue, the establishment of an action plan, its implementation and its evaluation. Compared to recent related studies, the research is less enthusiastic. While it highlights the need for new tools to improve production planning and control, it also points to a strong resistance to change by practitioners at the site. They emphasize the necessity for adequate pre-service training and the need for new resources that can work full-time on the ongoing training of site teams. In addition, some limitations of the tool lead workers to believe that it can quickly become a factor that slows down their daily work rather than improving it. Based on the advice of professionals, the paper formulates some recommendations to the industry, the researchers and the software developers.
Liquid Air Energy Storage (LAES) is at pilot scale. Air cooling and liquefaction stores energy; reheating revaporises the air at pressure, powering a turbine or engine (Ameel et al., 2013). Liquefaction requires water & CO2 removal, preventing ice fouling. This paper proposes subsequent geological storage of this CO2– offering a novel Carbon Dioxide Removal (CDR) by-product, for the energy storage industry. It additionally assesses the scale constraint and economic opportunity offered by implementing this CDR approach. Similarly, established Compressed Air Energy Storage (CAES) uses air compression and subsequent expansion. CAES could also add CO2 scrubbing and subsequent storage, at extra cost. CAES stores fewer joules per kilogram of air than LAES – potentially scrubbing more CO2 per joule stored. Operational LAES/CAES technologies cannot offer full-scale CDR this century (Stocker et al., 2014), yet they could offer around 4% of projected CO2 disposals for LAES and<25% for current-technology CAES. LAES CDR could reach trillion-dollar scale this century (20 billion USD/year, to first order). A larger, less certain commercial CDR opportunity exists for modified conventional CAES, due to additional equipment requirements. CDR may be commercially critical for LAES/CAES usage growth, and the necessary infrastructure may influence plant scaling and placement. A suggested design for low-pressure CAES theoretically offers global-scale CDR potential within a century (ignoring siting constraints) – but this must be costed against competing CDR and energy storage technologies.
Distributed photovoltaic (PV) systems have constantly been the key to achieve a low-carbon economy in China. However, the development of Chinese distributed PV systems has failed to meet expectations because of their irrational profit and cost allocations. In this study, the methodology for calculating the levelized cost of energy (LCOE) for PV is thoroughly discussed to address this issue. A mixed-integer linear programming model is built to determine the optimal system operation strategy with a benefit analysis. An externality-corrected mathematical model based on Shapley value is established to allocate the cost of distributed PV systems in 15 Chinese cities between the government, utility grid and residents. Results show that (i) an inverse relationship exists between the LCOEs and solar radiation levels; (ii) the government and residents gain extra benefits from the utility grid through net metering policies, and the utility grid should be the highly subsidized participant; (iii) the percentage of cost assigned to the utility grid and government should increase with the expansion of battery bank to weaken the impact of demand response on increasing theoretical subsidies; and (iv) apart from the LCOE, the local residential electricity prices remarkably impact the subsidy calculation results.
Handoff processes during civil infrastructure operations are transitions between sequential tasks. Typical handoffs constantly involve cognitive and communication activities among operations personnel, as well as traveling activities. Large civil infrastructures, such as nuclear power plants (NPPs), provide critical services to modern cities but require regular or unexpected shutdowns (i.e., outage) for maintenance. Handoffs during such an outage contain interwoven workflows and communication activities that pose challenges to the cognitive and communication skills of handoff participants and constantly result in delays. Traveling time and changing field conditions bring additional challenges to effective coordination among multiple groups of people. Historical NPP records studied in this research indicate that even meticulous planning that takes six months before each outage could hardly guarantee sufficient back-up plans for handling various unexpected events. Consequently, delays frequently occur in NPP outages and bring significant socioeconomic losses. A synthesis of previous studies on the delay analysis of accelerated maintenance schedules revealed the importance and challenges of handoff modeling. However, existing schedule representation methods could hardly represent the interwoven communication, cognitive, traveling, and working processes of multiple participants collaborating on completing scheduled tasks. Moreover, the lack of formal models that capture how cognitive, waiting, traveling, and communication issues affect outage workflows force managers to rely on personal experiences in diagnosing delays and coordinating multiple teams involved in outages. This study aims to establish formal models through agent-based simulation to support the analytical assessment of outage schedules with full consideration of cognitive and communication factors involved in handoffs within the NPP outage workflows. Simulation results indicate that the proposed handoff modeling can help predict the impact of cognitive and communication issues on delays propagating throughout outage schedules. Moreover, various activities are fully considered, including traveling between workspaces and waiting. Such delay prediction capability paves the path toward predictive and resilience outage control of NPPs.
This study provides a systematic overview of the advent and evolution of reliability systems engineering (RSE) in China, and the latest RSE development, that is, model-based RSE (MBRSE), is emphatically introduced. The establishment of the system architecture and conceptual models of MBRSE is first described. The fundamental theory and methodology of MBRSE are then elaborated, with a V-model as the core of this approach. The development of various MBRSE platforms and the effectiveness of their implementation over the past 30 years are presented. The prospective trends in the development of RSE in China are outlined.
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 Sichuan–Tibet Railway is facing extraordinary challenges in terms of construction, operation, and maintenance because of its extremely complicated natural environment and geological conditions. Consequently, countermeasures are necessary and urgent to ensure its safety and reliability in the whole life cycle. This study proposes a novel reliability framework to guarantee the ideal operation state of the Sichuan–Tibet Railway. Reliability application in many fields are summarized, including military equipment, rail locomotive, and railway engineering. Given the fact that the Sichuan–Tibet Railway is a complex giant system, Nine-Connotation was summarized (i.e., safety, inherent reliability, testability, maintainability, supportability, environmental adaptability, predictability, resilience, and durability) under the goal of optimizing the operational efficiency. On the basis of the concept of the Nine-Connotation and the understanding of reliability transmission mechanism, the framework of reliability for the Sichuan–Tibet Railway was established, which can facilitate a comprehensive and real-time evaluation of all situations with a clear hierarchy. The proposed framework is composed of a resilience management system, an integrated technology system, and a dynamic reliability assessment system. The pathway for its application on railway construction was developed in this study. The proposed framework can assist in well-informed decisions for the construction, as well as the operation of the Sichuan–Tibet Railway. On the basis of a top–down design concept for the first time, this study emphasizes the railway’s availability and validity to complete the assigned tasks as a whole, that is, operational efficiency. It also shows the reliability transmission and control mechanism of the railway’s giant complex system, innovating and establishing the management principle of great safety and great reliability over the life cycle.
As part of general construction management, production planning and control is vital for successful project delivery. Numerous approaches supporting production planning and control exist in practice and research. However, the different approaches focus on distinct areas such as workflow stabilization or cost control, and no single system combines all the requirements of a holistic production management system. Varying production management systems can be explained by the unique characteristics of many construction projects. As an approach for the digital twinning in the construction industry, building information modeling (BIM) can help standardize production management through shifting the management system design toward the digital prototype. Previous scientific work has acknowledged this approach, thereby generating numerous concepts for using building information models within construction management approaches. However, BIM is often merely used as a parallel support rather than as an integral part of production management systems. To address this gap and in terms of research methodology, we follow a Design Science Research approach. Thus, we propose a new BIM-based production management system, which is characterized by a theoretical integration model for BIM and existing construction management techniques, and a methodology for applying these concepts in practice.
China is an early user of geothermal energy, and its direct use ranks first in the world. Recent national strategies and policies have enabled China’s geothermal energy industry to enter a new era with important development opportunities. This paper investigates the strengths, weaknesses, opportunities, and threats (SWOT) to China’s geothermal energy industry from political, economic, social, and technological (PEST) perspectives. SWOT–PEST analysis indicates that the resources, market, and technological foundation exist for the large-scale development of China’s geothermal energy industry. However, it experiences constraints, such as unclear resource distributions, incomplete development of government regulations, incomplete implementation of national policies, unclear authority between governmental administrative systems, and lack of uniform technical standards and codes. Therefore, future development strategies have been proposed to provide technical support and policy tools for geothermal energy development. The recommendations to ensure its healthy and sustainable development include improving resource exploration, rationalizing administration systems, enhancing policy guidance and financial support, and cultivating geothermal talent.
The Cyber–Physical Power System (CPPS) is one of the most critical infrastructure systems in a country because a stable and secure power supply is a key foundation for national and social development. In recent years, resilience has become a major topic in preventing and mitigating the risks caused by large-scale blackouts of CPPSs. Accordingly, the concept and significance of CPPS resilience are at first explained from the engineering perspective in this study. Then, a review of representative quantitative assessment measures of CPPS resilience applied in the existing literature is provided. On the basis of these assessment measures, the optimization methods of CPPS resilience are reviewed from three perspectives, which are mainly focused on the current research, namely, optimizing the recovery sequence of components, identifying and protecting critical nodes, and enhancing the coupling patterns between physical and cyber networks. The recent advances in modeling methods for cascading failures within the CPPS, which is the theoretical foundation for the resilience assessment and optimization research of CPPSs, are also presented. Lastly, the challenges and future research directions for resilience optimizing of CPPSs are discussed.
The use of engineering procurement construction (EPC) mode is currently a trend in hydropower engineering construction. The clarification of the internal relationship between hydropower EPC projects and the realization of synergy has great significance in improving management efficiency and implementation effect. In this work, a three-dimensional system and a system model of hydropower EPC project management synergy are constructed. The mechanism and factors that influence the degree of management synergy are analyzed on the basis of management synergy theory. Furthermore, the evaluation index system and the degree of synergy model are established, and grey relational analysis is utilized to identify the key factors that affect the synergy degree. Thus, this study aims to facilitate the hydropower EPC project management synergy, provide a quantitative method for synergy degree evaluation, and propose corresponding promotion strategies. Results show that the order degree of each subsystem presents a steady upward trend. Specifically, the order degree of the subsystem at the trial operation stage is low, which is the major restriction on the further improvement of the synergy degree of EPC project management. The key factors in improving the synergy level of hydropower EPC project management are mainly concentrated in the information and organization synergy subsystems, including the construction degree of information platform, the performance of functions, the timeliness of information transfer, and the functions of the information platform.
Power grids deliver energy, and telecommunication networks transmit information. These two facilities are critical to human society. In this study, we conduct a comprehensive overview of the development of reliability metrics for power grids and telecommunication networks. The main purpose of this review is to promote and support the formulation of communication network reliability metrics with reference to the development of power grid reliability. We classify the metrics of power grid into the reliability of power distribution and generation/transmission and the metrics of telecommunication network into connectivity-based, performance-based, and state-based metrics. Then, we exhibit and discuss the difference between the situations of the reliability metrics of the two systems. To conclude this study, we conceive a few topics for future research and development for telecommunication network reliability metrics.