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 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.
The paper empirically studies the engineering practices of the national currency circulation information system-China Union Pay’s Bankcard Information Exchange System. By integrating the meta-synthesis methodology and the financial information system engineering, the paper proposes basic principles and processes of the giant and complex financial information system engineering management, and further explores its paradigm and toolkit.
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.
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.
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
It is necessary for subsequent resource distribution planning that get expected relief time considering secondary disasters after natural disaster. The goal of this research is to develop a two-echelon emergency resource distribution model under condition of secondary disasters. Taking minimal maximize relief time as criterion of relief performance, we developed response strategies and simulation model to get the expected value. Numerical studies of this paper presented the result of response strategies.
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.
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.
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.
The NP-hard scheduling problems of semiconductor manufacturing systems (SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance (such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule (SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.
This study combines multi-regional input–output (MRIO) model with linear programming (LP) model to explore economic structure adjustment strategies for the reduction of carbon dioxide (CO2) emissions. A particular feature of this study is the identification of the optimal regulation sequence of final products in various regions to reduce CO2 emissions with the minimum loss in gross domestic product (GDP). By using China’s MRIO tables 2017 with 28 regions and 42 economic sectors, results show that reduction in final demand leads to simultaneous reductions in GDP and CO2 emissions. Nevertheless, certain demand side regulation strategy can be adopted to lower CO2 emissions at the smallest loss of economic growth. Several key final products, such as metallurgy, nonmetal, metal, and chemical products, should first be regulated to reduce CO2 emissions at the minimum loss in GDP. Most of these key products concentrate in the coastal developed regions in China. The proposed MRIO–LP model considers the inter-relationship among various sectors and regions, and can aid policy makers in designing effective policy for industrial structure adjustment at the regional level to achieve the national environmental and economic targets.
Despite the increasing dissemination of the Building Information Modeling (BIM) approach, many firms are still far from BIM and are only starting to adopt information technologies. We conducted an ethnographic action research with an industrial partner that implements information technologies on its construction sites, with a strong preference for home-made applications. Results show that the development of such applications faces difficulties and that multiple iterations and versions are necessary before achieving the expected goals because the required competencies are lacking among internal development teams. Moreover, initial needs evolve considerably throughout the application’s development and evaluation process. However, notwithstanding the difficulties encountered during the different application development phases, the industrial partner believes the decision to be worthwhile because of the desire to have internal control over the project data and the need to consider certain specificities related to business processes.
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.
Shanxi, Shaanxi, Inner Mongolia, Ningxia, and Gansu (hereafter generally referred as “the Western Area”) are major coal-producing areas in China due to rich coal resources and good mining conditions. However, the Western Area has a serious water shortage. The surface evaporation is huge and a great amount of mine water generated in coal mining is evaporated and lost after discharging to surface. In order to protect and utilize the water resources during large-scale coal mining in the Western Area, Shenhua Group has put forward a technological idea to store mine water in underground mined areas and successfully researched and developed the coal mine underground reservoir technology by solving the technical difficulties of water source prediction, reservoir site selection, reservoir capacity design, dam construction, safety guarantee, water quality control and so on through 20 years of exploration. Now Shenhua Group has successfully established a batch of reservoir in the Shendong Mining Area, obtaining great economic and social benefits. The technology is also extended to other western mining areas, providing an effective path for harmonic mining of coal and water resources in western China.
This paper proposes an economic growth model based on the Six Basic Factors of Production and Xu Growth Rate Equation for the first time, which fills-in the deficits of the New Classical Economic Growth Model based on the Solow Model. The empirical analysis indicates that over the past three decades, the consumption of six basic factors of production had complicated relations with economic growth. In some years, the consumption rate of the basic factors of production was meager, but the economy witnessed relatively rocketing growth rate; in some years, the factors of production consumption rate was very high, but the economy growth rate slowed down. In general, economy grows at the expenses of huge consumption of four factors. There is an obvious characteristic of huge input and low efficiency. The average contribution rate of technological advance peaks in the middle, while it drops down at two ends. Noticeably, since 2004, the technology contribution rate generally shows a downward trend, reasons of which should be explored systematically in aspects like economic policy and industry structure with a view to boost further transformation of the macro-economy scientific growth model.
The era of big data brings unprecedented opportunities and challenges to management research. As one of the important functions of management decision-making, evaluation has been given more functions and application space. Exploring the applicable evaluation methods in the big data environment has become an important subject of research. The purpose of this paper is to provide an overview and discussion of systematic evaluation and improvement in the big data environment. We first review the evaluation methods based on the main analytic techniques of big data such as data mining, statistical methods, optimization and simulation, and deep learning. Focused on the characteristics of big data (association feature, data loss, data noise, and visualization), the relevant evaluation methods are given. Furthermore, we explore the systematic improvement studies and application fields. Finally, we analyze the new application areas of evaluation methods and give the future directions of evaluation method research in a big data environment from six aspects. We hope our research could provide meaningful insights for subsequent research.
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.
Ecological compensation plays an important role in implementing the social responsibility of infrastructure mega-projects. Based on the results of a field study, an in-depth interview, and archive data, this paper introduces the ecological compensation for Sousa chinensis (the Indo-Pacific humpbacked dolphin) during the construction of the Hong Kong-Zhuhai-Macao Bridge. It studies the concrete measures, decision-making processes, and organizational collaboration of the ecological compensation, using the method of a case study. The present study not only enriches our understanding of the ecological compensation practice during the construction of infrastructure mega-projects, but also extends the literature on the social responsibility of infrastructure mega-projects. This sheds light on the protection of the environment as well as biodiversity in the construction of future infrastructure mega-projects.
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.
In Ethiopian construction projects, schedule delay risk is a predominant issue because it is not properly addressed. Although several studies have been focused on the various effects of risk in construction projects, limited efforts have been made to investigate the typical and the overall schedule delay risk. In this study, our aim is to detect the typical and overall schedule delay risk throughout the construction project lifecycle, which consists of the pre-construction, construction, and post-construction stages, and compare the stages with each other. Common criteria, sub-criteria, and attributes were developed for all alternatives for the purpose of making a risk decision. The methodology that was followed integrated the multiple-criteria decision-making (MCDM) model of fuzzy analytic hierarchy process comprehensive evaluation (FAHPCE) and the relative important index (RII). Data were collected from 77 participants, who were selected through purposive sampling from different contracting organizations in Ethiopian construction projects by means of questionnaires that were distributed to experienced experts. The findings showed that there is a typical delay risk either in the type or in the level of the different construction activities. Consequently, the most influenced alternative is the construction stage because of the high-risk responsibility, resource, and contract condition related criteria. The post-construction stage was the second most influenced stage because of the high-risk responsibility-related criteria. The pre-constructed stage was the least influenced stage that consist high-risk criteria of responsibility, resource, and contract condition related. These differences provided noteworthy information about risk mitigation in construction projects by identifying the exact risk level on specific activity to make appropriate decision.
Due to the characteristics of hesitant fuzzy sets (HFSs), one hesitant fuzzy element (HFE), which is the basic component of HFSs, can express the evaluation values of multiple decision makers (DMs) on the same alternative under a certain attribute. Thus, the HFS has its unique advantages in group decision making (GDM). Based on which, many scholars have conducted in-depth research on the applications of HFSs in GDM. We have viewed lots of relevant literature and divided the existing studies into three categories: theory, support and methods. In this paper, we elaborate on hesitant fuzzy GDM from these three aspects. The first aspect is mainly about the introduction of HFSs, HFPRs and some hesitant fuzzy aggregation operators. The second aspect describes the consensus process under hesitant fuzzy environment, which is an important support for a complete decision-making process. In the third aspect, we introduce seven hesitant fuzzy GDM approaches, which can be applied in GDM under different decision-making conditions. Finally, we summarize the research status of hesitant fuzzy GDM and put forward some directions of future research.
Decomposition analysis has been widely used to assess the determinants of energy and CO2 emissions in academic research and policy studies. Both the methodology and application of decomposition analysis have been largely improved in the past decades. After more than 50 years’ developments, decomposition studies have become increasingly sophisticated and diversified, and tend to converge internally and integrate with other analytical approaches externally. A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda. To this end, this study presents a literature survey for decomposition analysis applied to energy and emission issues, with a focus on the period of 2016–2021. A review for three individual decomposition techniques is first conducted, followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole. The findings are expected to direct future research in decomposition analysis.
The popularization of the mobile internet has given rise to demand for flexible and convenient payment methods. For China, it is necessary to keep pace with or even lead the trend of innovation and development in the age of mobile payment. From the perspective of systems engineering, this paper introduces research and implementation of China UnionPay’s mobile payment project. The general requirements and core engineering problems of the mobile payment project are summarized based on analyses of the characteristics and engineering difficulties of this project. Integration of innovative technologies is introduced to resolve the contradiction between ease-of-use and security. A rapid iterative development process is adopted to improve the product release efficiency as well as the users' experience. The launch of the mobile payment project also opens the window to coordinating and upgrading the whole payment industry chains.
Logistics resource planning is an integration model of materials requirement planning and distribution resource planning which is a resource allocation technology. It is a technology of satisfying both production material supply and resource allocation optimization which is based on inventory management. For the remanufacturing supply chain, recycling and rebuilding of products form a reverse materials movement loop which challenges the traditional logistics resource planning system. For the characteristics of reverse logistics of remanufacturing supply chain, we propose a closed-loop supply chain resource allocation model based on autonomous multi-entity. We focus on integration resource allocation model of materials requirement planning and distribution resource planning considering remanufacturing.
Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber–physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.
Under the huge challenges of global energy conservation, emission reduction and energy security, distributed solar photovoltaic industry has become the key means to achieve economic restructuring and low carbon economy. Based on System Advisor Model software, the authors choose Baoji as the sample plot. Household load, unit investment, loan interest rate and loan fraction are used as influence factors to analyze the economic benefits of distributed solar photovoltaic in China. The result demonstrates that government incentives help to increase the profitability of distributed solar photovoltaic by a large extent; other factors that influence the profitability includes household load, unit investment cost, loan interest rate and loan fraction.
Owing to the heterogeneity between functional units and resource scarcity, manufacturing firms have been struggling with intra-organizational coordination for productivity and innovation. Traditional organizational structures, such as linear-functional and matrix, may cause responsibility division and independent goals (
The flue gas pollutants deep-removal technology (DRT) focusing on PM2.5 removal is the prime method of further reducing pollutants emission from coal-fired power plants. In view of the four key technological challenges in developing the DRT, studies were conducted on a series of purification technologies and the DRT was developed and successfully applied in 660 MW and 1000 MW coal-fired units. This paper analyzes the application results of the demonstration project, and proposes a roadmap for the follow-up researches and optimizations.
At present, the research on circular economy has made a lot of substantive results both at home and abroad. But for the papermaking enterprise, which is the representative of the light industry, few studies have analyzed the evaluation index system of circular economy. Since the current material flow analyses have limitations that the researchers cannot calculate materials with different units. The authors take advantage of the intrinsic correlation between the basic principle of value flow analysis and circular economy, and then analyze the dynamic changes of material flow and value flow through enterprises internal production process. Considering the resource output, the authors set up the layered structure of the evaluation index system, and then preliminarily determine the index form. Next, the authors use the frequency statistics analysis method to adjust indicators, forming a preliminary index system. After that, the principal component analysis and independent analysis are applied for screening. Finally, the authors build a circular economy evaluation index system for papermaking enterprise to provide scientific guidance for the process of circular economy.
Active exploration has been carried out to determine a pattern for developing green eco-urban areas in the Starting Area of Guangzhou International Financial City with an emphasis on the core role of comprehensive green arrangement. By comparing and analyzing existing research, development of green technologies at home and abroad, and indicator systems of green urban areas of similar sizes, the builders developed a green ecological indicator system. They proposed a new concept called “district-level indicator” in order to emphasize the importance of classifying indicators according to different project situations. By verifying the indicators for all land parcels and assessing future costs and efficiency, experience accumulated in this project can be beneficial for future green eco-urban area development projects.
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.
Electricity consumption is one of the major contributors to greenhouse gas emissions. In this study, we build a power consumption carbon emission measurement model based on the operating margin factor. We use the decomposition and decoupling technology of logarithmic mean Divisia index method to quantify six effects (i.e., emission intensity, power generation structure, consumption electricity intensity, economic scale, population structure, and population scale) and comprehensively reflect the degree of dependence of electricity consumption carbon emissions on China’s economic development and population changes. Moreover, we utilize the decoupling model to analyze the decoupling state between carbon emissions and economic growth and identify corresponding energy efficiency policies. The results of this study provide a new perspective to understand carbon emission reduction potentials in the electricity use of China.
A project-oriented organization is a hybrid form of organization where a functional hierarchy is augmented with structures to manage projects strategically across the organization. Six project-oriented organizations from diverse industries that emphasize innovation in their strategies were selected for this study. We use the three pillars of institutional theory — regulative, normative and cultural-cognitive — and institutional entrepreneurship to analyze interview data from executive and project, program and portfolio management personnel in the project-oriented organizations to investigate how innovation is facilitated through external influences and internal responses. Our findings indicate that processes and new structures provide effective ways for innovation and, while individuals are important, processes are more effective than individuals at enabling innovation. We put forward some lessons for practice that emerge directly from the findings, including suggestions on improving allocation of resources, a need to focus on processes, reconceptualization of “failure”, and dedicated investment in market knowledge, customer knowledge, performance metrics and flexible governance structures.
With the acceleration of supply-side renewable energy penetration rate and the increasingly diversified and complex demand-side loads, how to maintain the stable, reliable, and efficient operation of the power system has become a challenging issue requiring investigation. One of the feasible solutions is deploying the energy storage system (ESS) to integrate with the energy system to stabilize it. However, considering the costs and the input/output characteristics of ESS, both the initial configuration process and the actual operation process require efficient management. This study presents a comprehensive review of managing ESS from the perspectives of planning, operation, and business model. First of all, in terms of planning and configuration, it is investigated from capacity planning, location planning, as well as capacity and location combined planning. This process is generally the first step in deploying ESS. Then, it explores operation management of ESS from the perspectives of state assessment and operation optimization. The so-called state assessment refers to the assessment of three aspects: The state of charge (SOC), the state of health (SOH), and the remaining useful life (RUL). The operation optimization includes ESS operation strategy optimization and joint operation optimization. Finally, it discusses the business models of ESS. Traditional business models involve ancillary services and load transfer, while emerging business models include electric vehicle (EV) as energy storage and shared energy storage.
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.
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.
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.?
Intelligent construction technology has been widely used in the field of railway engineering. This work first analyzes the connotation, function, and characteristics of intelligent construction of railway engineering (ICRE) and establishes its system structure from three dimensions, namely, life cycle, layers of management, and intelligent function, to deeply understand the development situation of intelligent railway construction in China. Second, seven key technical support systems of ICRE, which include building information modeling (BIM) standard system for China’s railway sector, technology management platform and life cycle management based on BIM+GIS (geography information system), ubiquitous intelligent perception system, intelligent Internet-of-Things (IoT) commu-nication system based on mobile interconnection, construction management platform based on cloud computing and big data, unmanned operation system based on artificial intelligence, intelligent machinery and robot, and intelligent operation and maintenance system based on BIM and PHM (prediction and health management), are established. Third, ICRE is divided into three development stages: primary (perception), intermediate (substitution), and advanced (intelligence). The evaluation index system of each stage is provided from the aspects of technology and function. Finally, this work summarizes and analyzes the application situation of ICRE in the entire railway sector of China, represented by Beijing–Zhangjiakou and Beijing–Xiong’an high-speed railways. Result shows that the technical support systems of the ICRE have emerged in China and are still in the process of deepening basic technology research and preliminary application. In the future, the ICRE of China’s railway sector will develop toward a higher stage.
Although China’s construction machinery thrives to meet the needs of construction, a number of challenges still remain to be overcome, such as lack of thorough knowledge of regional disparities and several limitations in terms of carbon emissions and economic development. Meanwhile, a low-carbon economy was proposed and implemented in China. This research aims to investigate the differences in industrial agglomeration of construction machineries and further explore the relationship between industrial agglomeration and low-carbon economy. On this basis, spatiotemporal analysis was performed to evaluate the levels of industrial agglomeration in different regions based on the situations of China’s construction machinery industry. Furthermore, this study explored the interaction between industrial agglomeration and low-carbon economy utilizing the coupling coordination analysis method. Results showed that the coupling coordination of the two subsystems was extremely unbalanced in 2006, and it maintained an increasing trend, reaching a relatively high level in 2018. Finally, suggestions, such as establishing a policy guarantee system and implementing variable policies in different regions, were proposed to provide guidelines for the government decision-making and promote the sustainable development of China’s construction machinery industry.
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.
Burn-in has been proven effective in identifying and removing defective products before they are delivered to customers. Most existing burn-in models adopt a one-shot scheme, which may not be sufficient enough for identification. Borrowing the idea from sequential inspections for remaining useful life prediction and accelerated lifetime test, this study proposes a sequential degradation-based burn-in model with multiple periodic inspections. At each inspection epoch, the posterior probability that a product belongs to a normal one is updated with the inspected degradation level. Based on the degradation level and the updated posterior probability, a product can be disposed, put into field use, or kept in the test till the next inspection epoch. We cast the problem into a partially observed Markov decision process to minimize the expected total burn-in cost of a product, and derive some interesting structures of the optimal policy. Then, algorithms are provided to find the joint optimal inspection period and number of inspections in steps. A numerical study is also provided to illustrate the effectiveness of our proposed model.
Surface integrity is the major factor impacting on the operation quality, service life and reliability of the aeroengine components. The surface integrity of aeroengine component is damaged by the failures such as crack, deformation, oxidation, corrosion, erosion, and microstructural degeneration. It adopts advanced remanufacturing technologies to restore or improve the surface integrity and regenerate these high value parts. This paper firstly puts forward the concept, namely surface integrity remanufacturing for aeroengine components, and its connotation. The key remanufacturing technologies have been developed to repair the components with surface damages. Ultimately, some application examples of surface integrity remanufacturing technologies as well as their effects in aeroengine maintenance are introduced. The discarded components have been reused and their service lives have been extended and their reliability has been increased by implementing surface integrity remanufacturing. It has realized “The Repaired Components Outpacing the New Ones”, material saving, energy saving, and emission reduction.
Under the ambitious goal of carbon neutralization, photovoltaic (PV)-driven electrolytic hydrogen (PVEH) production is emerging as a promising approach to reduce carbon emission. Considering the intermittence and variability of PV power generation, the deployment of battery energy storage can smoothen the power output. However, the investment cost of battery energy storage is pertinent to non-negligible expenses. Thus, the installation of energy-storage equipment in a PVEH system is a complex trade-off problem. The primary goals of this study are to compare the engineering economics of PVEH systems with and without energy storage, and to explore time nodes when the cost of the former scenario can compete with the latter by factoring the technology learning curve. The levelized cost of hydrogen (LCOH) is a widely used economic indicator. Represented by seven areas in seven regions of China, results show that the LCOH with and without energy storage is approximately 22.23 and 20.59 yuan/kg in 2020, respectively. In addition, as technology costs drop, the LCOH of a PVEH system with energy storage will be less than that without energy storage in 2030.
This paper uses project organizational theories to draw lessons from a historic megaproject, the Ajaokuta Steel Plant (ASP). Archival reports on the ASP were explored to identify the unique attributes of the project; the political wrangling that underplayed its evolution, its economic significance and organizational impacts. Findings suggest the goals of the ASP project were, and still are, unambiguous. Failure occurred as socio-political forces aggravated the project’s complex milestones. Stakeholders were impatient with pre-project investigations. During planning, owners ignored opinions that were contrary to their expectations. While delays lingered, pressures from the global economy weakened the project’s motivation to succeed. These combined to turn the project’s outcomes into a chaotic situation that triggered dire implications. Despite about 1400% overrun in cost, the success achieved on the plant was 28% at commissioning. Contractors remained on site until eight years after commissioning. Six key elements of the 482 items in the ASP project contract were not delivered nearly 40 years on. A simplistic look at these suggests poor planning is the main problem. However, planning issues is not entirely strange in greenfield projects. The paper draws strength from project organization theories to explain what was poor about the planning. Socrates’ generic management theory was used to explain the role of leadership in the failure of the ASP project. McGregor’s Theory X and Theory Y explain the significance of stakeholders’ integration in megaprojects. Systems and chaos theories were used to explain the sensitivity of the ASP project to uncertainties. Narratives on these combine well to inspire stakeholders of megaprojects on where and how to seek courage in making effective plans that can help achieve success in complex projects. While normative literature only recognizes project success in a definitive perspective, this study provides insights from failure as an instrument to trigger sublime reflections.