Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and newgeneration intelligent manufacturing. New-generation intelligent manufacturing represents an indepth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for ‘‘parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China.
With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.
Our next generation of industry—Industry 4.0—holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the IoT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.
With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership (AMP) in 2011 and the National Network for Manufacturing Innovation (NNMI) in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further “leverage existing resources… to nurture manufacturing innovation and accelerate commercialization” by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10-year plan and roadmap toward manufacturing: Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features: integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing (i2M) systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Internet of Things and Services (IoTS), cyber-physical systems (CPSs), and cloud computing are discussed. Challenges are addressed with applications that are based on commercially available platforms such as General Electric (GE)’s Predix and PTC’s ThingWorx.
Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.
An increased global supply of minerals is essential to meet the needs and expectations of a rapidly rising world population. This implies extraction from greater depths. Autonomous mining systems, developed through sustained R&D by equipment suppliers, reduce miner exposure to hostile work environments and increase safety. This places increased focus on “ground control” and on rock mechanics to define the depth to which minerals may be extracted economically. Although significant efforts have been made since the end of World War II to apply mechanics to mine design, there have been both technological and organizational obstacles. Rock in situ is a more complex engineering material than is typically encountered in most other engineering disciplines. Mining engineering has relied heavily on empirical procedures in design for thousands of years. These are no longer adequate to address the challenges of the 21st century, as mines venture to increasingly greater depths. The development of the synthetic rock mass (SRM) in 2008 provides researchers with the ability to analyze the deformational behavior of rock masses that are anisotropic and discontinuous—attributes that were described as the defining characteristics of in situ rock by Leopold Müller, the president and founder of the International Society for Rock Mechanics (ISRM), in 1966. Recent developments in the numerical modeling of large-scale mining operations (e.g., caving) using the SRM reveal unanticipated deformational behavior of the rock. The application of massive parallelization and cloud computational techniques offers major opportunities: for example, to assess uncertainties in numerical predictions; to establish the mechanics basis for the empirical rules now used in rock engineering and their validity for the prediction of rock mass behavior beyond current experience; and to use the discrete element method (DEM) in the optimization of deep mine design. For the first time, mining—and rock engineering—will have its own mechanics-based “laboratory.” This promises to be a major tool in future planning for effective mining at depth. The paper concludes with a discussion of an opportunity to demonstrate the application of DEM and SRM procedures as a laboratory, by back-analysis of mining methods used over the 80-year history of the Mount Lyell Copper Mine in Tasmania.
The possible mitigation of floods by dams and the risk to dams from floods are key problems. The People’s Republic of China is now leading world dam construction with great success and efficiency. This paper is devoted to relevant experiences from other countries, with a particular focus on lessons from accidents over the past two centuries and on new solutions. Accidents from floods are analyzed according to the dam’s height, storage, dam material, and spillway data. Most of the huge accidents that have been reported occurred for embankments storing over 10 hm3. New solutions appear promising for both dam safety and flood mitigation.
Municipal wastewater treatment has long been known as a high-cost and energy-intensive process that destroys most of the energy-containing molecules by spending energy and that leaves little energy and few nutrients available for reuse. Over the past few years, some wastewater treatment plants have tried to revamp themselves as “resource factories,” enabled by new technologies and the upgrading of old technologies. In particular, there is an renewed interest in anaerobic biotechnologies, which can convert organic matter into usable energy and preserve nutrients for potential reuse. However, considerable technological and economic limitations still exist. Here, we provide an overview of recent advances in several cutting-edge anaerobic biotechnologies for wastewater treatment, including enhanced side-stream anaerobic sludge digestion, anaerobic membrane bioreactors, and microbial electrochemical systems, and discuss future challenges and opportunities for their applications. This review is intended to provide useful information to guide the future design and optimization of municipal wastewater treatment processes.
Method development has always been and will continue to be a core driving force of microbiome science. In this perspective, we argue that in the next decade, method development in microbiome analysis will be driven by three key changes in both ways of thinking and technological platforms: ① a shift from dissecting microbiota structureby sequencing to tracking microbiota state, function, and intercellular interaction via imaging; ② a shift from interrogating a consortium or population of cells to probing individual cells; and ③ a shift from microbiome data analysis to microbiome data science. Some of the recent method-development efforts by Chinese microbiome scientists and their international collaborators that underlie these technological trends are highlighted here. It is our belief that the China Microbiome Initiative has the opportunity to deliver outstanding “Made-in-China” tools to the international research community, by building an ambitious, competitive, and collaborative program at the forefront of method development for microbiome science.
Trillions of microbes have evolved with and continue to live on and within human beings. A variety of environmental factors can affect intestinal microbial imbalance, which has a close relationship with human health and disease. Here, we focus on the interactions between the human microbiota and the host in order to provide an overview of the microbial role in basic biological processes and in the development and progression of major human diseases such as infectious diseases, liver diseases, gastrointestinal cancers, metabolic diseases, respiratory diseases, mental or psychological diseases, and autoimmune diseases. We also review important advances in techniques associated with microbial research, such as DNA sequencing, metabonomics, and proteomics combined with computation-based bioinformatics. Current research on the human microbiota has become much more sophisticated and more comprehensive. Therefore, we propose that research should focus on the host-microbe interaction and on cause-effect mechanisms, which could pave the way to an understanding of the role of gut microbiota in health and disease. and provide new therapeutic targets and treatment approaches in clinical practice.
Tissue engineering is a relatively new but rapidly developing field in the medical sciences. Noncoding RNAs (ncRNAs) are functional RNA molecules without a protein-coding function; they can regulate cellular behavior and change the biological milieu of the tissue. The application of ncRNAs in tissue engineering is starting to attract increasing attention as a means of resolving a large number of unmet healthcare needs, although ncRNA-based approaches have not yet entered clinical practice. In-depth research on the regulation and delivery of ncRNAs may improve their application in tissue engineering. The aim of this review is: to outline essential ncRNAs that are related to tissue engineering for the repair and regeneration of nerve, skin, liver, vascular system, and muscle tissue; to discuss their regulation and delivery; and to anticipate their potential therapeutic applications.
The first author proposed the concept of the cemented material dam (CMD) in 2009. This concept was aimed at building an environmentally friendly dam in a safer and more economical way for both the dam and the area downstream. The concept covers the cemented sand, gravel, and rock dam (CSGRD), the rockfill concrete (RFC) dam (or the cemented rockfill dam, CRD), and the cemented soil dam (CSD). This paper summarizes the concept and principles of the CMD based on studies and practices in projects around the world. It also introduces new developments in the CSGRD, CRD, and CSD.
The rapid development of additive manufacturing and advances in shape memory materials have fueled the progress of four-dimensional (4D) printing. With the right external stimulus, the need for human interaction, sensors, and batteries will be eliminated, and by using additive manufacturing, more complex devices and parts can be produced. With the current understanding of shape memory mechanisms and with improved design for additive manufacturing, reversibility in 4D printing has recently been proven to be feasible. Conventional one-way 4D printing requires human interaction in the programming (or shape-setting) phase, but reversible 4D printing, or two-way 4D printing, will fully eliminate the need for human interference, as the programming stage is replaced with another stimulus. This allows reversible 4D printed parts to be fully dependent on external stimuli; parts can also be potentially reused after every recovery, or even used in continuous cycles—an aspect that carries industrial appeal. This paper presents a review on the mechanisms of shape memory materials that have led to 4D printing, current findings regarding 4D printing in alloys and polymers, and their respective limitations. The reversibility of shape memory materials and their feasibility to be fabricated using three-dimensional (3D) printing are summarized and critically analyzed. For reversible 4D printing, the methods of 3D printing, mechanisms used for actuation, and strategies to achieve reversibility are also highlighted. Finally, prospective future research directions in reversible 4D printing are suggested.
Coal is the dominant primary energy source in China and the major source of greenhouse gases and air pollutants. To facilitate the use of coal in an environmentally satisfactory and economically viable way, clean coal technologies (CCTs) are necessary. This paper presents a review of recent research and development of four kinds of CCTs: coal power generation; coal conversion; pollution control; and carbon capture, utilization, and storage. It also outlines future perspectives on directions for technology research and development (R&D). This review shows that China has made remarkable progress in the R&D of CCTs, and that a number of CCTs have now entered into the commercialization stage.
Green process engineering, which is based on the principles of the process intensi?cation strategy, can provide an important contribution toward achieving industrial sustainable development. Green process engineering refers to innovative equipment and process methods that are expected to bring about substantial improvements in chemical and any other manufacturing and processing aspects. It includes decreasing production costs, equipment size, energy consumption, and waste generation, and improving remote control, information ?uxes, and process ?exibility. Membrane-based technology assists in the pursuit of these principles, and the potential of membrane operations has been widely recognized in the last few years. This work starts by presenting an overview of the membrane operations that are utilized in water treatment and in the production of energy and raw materials. Next, it describes the potential advantages of innovative membrane-based integrated systems. A case study on an integrated membrane system (IMS) for seawater desalination coupled with raw materials production is presented. The aim of this work is to show how membrane systems can contribute to the realization of the goals of zero liquid discharge (ZLD), total raw materials utilization, and low energy consumption.
Knee osteoarthritis (OA) is the most common form of arthritis worldwide. The incidence of this disease is rising and its treatment poses an economic burden. Two early targets of knee OA treatment include the predominant symptom of pain, and cartilage damage in the knee joint. Current treatments have been beneficial in treating the disease but none is as effective as total knee arthroplasty (TKA). However, while TKA is an end-stage solution of the disease, it is an invasive and expensive procedure. Therefore, innovative regenerative engineering strategies should be established as these could defer or annul the need for a TKA. Several biomaterial and cell-based therapies are currently in development and have shown early promise in both preclinical and clinical studies. The use of advanced biomaterials and stem cells independently or in conjunction to treat knee OA could potentially reduce pain and regenerate focal articular cartilage damage. In this review, we discuss the pathogenesis of pain and cartilage damage in knee OA and explore novel treatment options currently being studied, along with some of their limitations.
This paper introduces the high-speed electrical multiple unit (EMU) life cycle, including the design, manufacturing, testing, and maintenance stages. It also presents the train control and monitoring system (TCMS) software development platform, the TCMS testing and verification bench, the EMU driving simulation platform, and the EMU remote data transmittal and maintenance platform. All these platforms and benches combined together make up the EMU life cycle cost (LCC) system. Each platform facilitates EMU LCC management and is an important part of the system.
Solar-powered carbon dioxide (CO2)-to-fuel conversion presents itself as an ideal solution for both CO2 mitigation and the rapidly growing world energy demand. In this work, the heating effect of light irradiation onto a bed of supported nickel (Ni) catalyst was utilized to facilitate CO2 conversion. Ceria (CeO2)-titania (TiO2) oxide supports of different compositions were employed and their effects on photothermal CO2 conversion examined. Two factors are shown to be crucial for instigating photothermal CO2 methanation activity: ① Fine nickel deposits are required for both higher active catalyst area and greater light absorption capacity for the initial heating of the catalyst bed; and ② the presence of defect sites on the support are necessary to promote adsorption of CO2 for its subsequent activation. Titania inclusion within the support plays a crucial role in maintaining the oxygen vacancy defect sites on the (titanium-doped) cerium oxide. The combination of elevated light absorption and stabilized reduced states for CO2 adsorption subsequently invokes effective photothermal CO2 methanation when the ceria and titania are blended in the ideal ratio(s).
The Made in China 2025 initiative will require full automation in all sectors, from customers to production. This will result in great challenges to manufacturing systems in all sectors. In the future of manufacturing, all devices and systems should have sensing and basic intelligence capabilities for control and adaptation. In this study, after discussing multiscale dynamics of the modern manufacturing system, a five-layer functional structure is proposed for uncertainties processing. Multiscale dynamics include: multi-time scale, space-time scale, and multi-level dynamics. Control action will differ at different scales, with more design being required at both fast and slow time scales. More quantitative action is required in low-level operations, while more qualitative action is needed regarding high-level supervision. Intelligent manufacturing systems should have the capabilities of flexibility, adaptability, and intelligence. These capabilities will require the control action to be distributed and integrated with different approaches, including smart sensing, optimal design, and intelligent learning. Finally, a typical jet dispensing system is taken as a real-world example for multiscale modeling and control.