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.
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.
This paper describes the combinational surface kinetics enhancement and surface states passivation of nickel-borate (Ni-Bi) co-catalyst for a hematite (Fe2O3) photoanode. The Ni-Bi-modified Fe2O3 photoanode exhibits a cathodic onset potential shift of 230 mV and a 2.3-fold enhancement of the photocurrent at 1.23 V, versus the reversible hydrogen electrode (RHE). The borate (Bi) in the Ni-Bi film promotes the release of protons for the oxygen evolution reaction (OER).
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.
Crystallization is one of the oldest separation and purification unit operations, and has recently contributed to significant improvements in producing higher-value products with specific properties and in building efficient manufacturing processes. In this paper, we review recent developments in crystal engineering and crystallization process design and control in the pharmaceutical industry. We systematically summarize recent methods for understanding and developing new types of crystals such as co-crystals, polymorphs, and solvates, and include several milestones such as the launch of the first co-crystal drug, Entresto (Novartis), and the continuous manufacture of Orkambi (Vertex). Conventional batch and continuous processes, which are becoming increasingly mature, are being coupled with various control strategies and the recently developed crystallizers are thus adapting to the needs of the pharmaceutical industry. The development of crystallization process design and control has led to the appearance of several new and innovative crystallizer geometries for continuous operation and improved performance. This paper also reviews major recent progress in the area of process analytical technology.
Increasing demand for weight reduction and greater fuel efficiency continues to spur the use of composite materials in commercial aircraft structures. Subsequently, as composite aerostructures become larger and more complex, traditional autoclave manufacturing methods are becoming prohibitively expensive. This has prompted renewed interest in out-of-autoclave processing techniques in which resins are introduced into a reinforcing preform. However, the success of these resin infusion methods is highly dependent upon operator skill and experience, particularly in the development of new manufacturing strategies for complex parts. Process modeling, as a predictive computational tool, aims to address the issues of reliability and waste that result from traditional trial-and-error approaches. Basic modeling attempts, many of which are still used in industry, generally focus on simulating fluid flow through an isotropic porous reinforcement material. However, recent efforts are beginning to account for the multiscale and multidisciplinary complexity of woven materials, in simulations that can provide greater fidelity. In particular, new multi-physics process models are able to better predict the infusion behavior through textiles by considering the effect of fabric deformation on permeability and porosity properties within the reinforcing material. In addition to reviewing previous research related to process modeling and the current state of the art, this paper highlights the recent validation of a multi-physics process model against the experimental infusion of a complex double dome component. By accounting for deformation-dependent flow behavior, the multi-physics process model was able to predict realistic flow behavior, demonstrating considerable improvement over basic isotropic permeability models.
Photosynthetic microorganisms are important bioresources for producing desirable and environmentally benign products, and photobioreactors (PBRs) play important roles in these processes. Designing PBRs for photocatalysis is still challenging at present, and most reactors are designed and scaled up using semi-empirical approaches. No appropriate types of PBRs are available for mass cultivation due to the reactors’ high capital and operating costs and short lifespan, which are mainly due to a current lack of deep understanding of the coupling of light, hydrodynamics, mass transfer, and cell growth in efficient reactor design. This review provides a critical overview of the key parameters that influence the performance of the PBRs, including light, mixing, mass transfer, temperature, pH, and capital and operating costs. The lifespan and the costs of cleaning and temperature control are also emphasized for commercial exploitation. Four types of PBRs—tubular, plastic bag, column airlift, and flat-panel airlift reactors are recommended for large-scale operations. In addition, this paper elaborates the modeling of PBRs using the tools of computational fluid dynamics for rational design. It also analyzes the difficulties in the numerical simulation, and presents the prospect for mechanism-based models.
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.
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.
The current irrational use of fossil fuels and the impact of greenhouse gases on the environment are driving research into renewable energy production from organic resources and waste. The global energy demand is high, and most of this energy is produced from fossil resources. Recent studies report that anaerobic digestion (AD) is an efficient alternative technology that combines biofuel production with sustainable waste management, and various technological trends exist in the biogas industry that enhance the production and quality of biogas. Further investments in AD are expected to meet with increasing success due to the low cost of available feedstocks and the wide range of uses for biogas (i.e., for heating, electricity, and fuel). Biogas production is growing in the European energy market and offers an economical alternative for bioenergy production. The objective of this work is to provide an overview of biogas production from lignocellulosic waste, thus providing information toward crucial issues in the biogas economy.
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.
Fischer-Tropsch synthesis (FTS) is an increasingly important approach for producing liquid fuels and chemicals via syngas—that is, synthesis gas, a mixture of carbon monoxide and hydrogen—generated from coal, natural gas, or biomass. In FTS, dispersed transition metal nanoparticles are used to catalyze the reactions underlying the formation of carbon-carbon bonds. Catalytic activity and selectivity are strongly correlated with the electronic and geometric structure of the nanoparticles, which depend on the particle size, morphology, and crystallographic phase of the nanoparticles. In this article, we review recent works dealing with the aspects of bulk and surface sensitivity of the FTS reaction. Understanding the different catalytic behavior in more detail as a function of these parameters may guide the design of more active, selective, and stable FTS catalysts.
The synthesis of fluorescent nanomaterials has received considerable attention due to the great potential of these materials for a wide range of applications, from chemical sensing through bioimaging to optoelectronics. Herein, we report a facile and scalable approach to prepare fluorescent carbon dots (FCDs) via a one-pot reaction of citric acid with ethylenediamine at 150 °C under ambient air pressure. The resultant FCDs possess an optical bandgap of 3.4 eV and exhibit strong excitation-wavelength-independent blue emission (λEm= 450 nm) under either one- or two-photon excitation. Owing to their low cytotoxicity and long fluorescence lifetime, these FCDs were successfully used as internalized fluorescent probes in human cancer cell lines (HeLa cells) for two-photon excited imaging of cells by fluorescence lifetime imaging microscopy with high-contrast resolution. They were also homogenously mixed with commercial inks and used to draw fluorescent patterns on normal papers and on many other substrates (e.g., certain flexible plastic films, textiles, and clothes). Thus, these nanomaterials are promising for use in solid-state fluorescent sensing, security labeling, and wearable optoelectronics.
Photocatalytic water splitting, which directly converts solar energy into hydrogen, is one of the most desirable solar-energy-conversion approaches. The ultimate target of photocatalysis is to explore efficient and stable photocatalysts for solar water splitting. Tantalum (oxy)nitride-based materials are a class of the most promising photocatalysts for solar water splitting because of their narrow bandgaps and sufficient band energy potentials for water splitting. Tantalum (oxy)nitride-based photocatalysts have experienced intensive exploration, and encouraging progress has been achieved over the past years. However, the solar-to-hydrogen (STH) conversion efficiency is still very far from its theoretical value. The question of how to better design these materials in order to further improve their water-splitting capability is of interest and importance. This review summarizes the development of tantalum (oxy)nitride-based photocatalysts for solar water spitting. Special interest is paid to important strategies for improving photocatalytic water-splitting efficiency. This paper also proposes future trends to explore in the research area of tantalum-based narrow bandgap photocatalysts for solar water splitting.
Cadaverine, a natural polyamine with multiple bioactivities that is widely distributed in prokaryotes and eukaryotes, is becoming an important industrial chemical. Cadaverine exhibits broad prospects for various applications, especially as an important monomer for bio-based polyamides. Cadaverine-based polyamide PA 5X has broad application prospects owing to its environmentally friendly characteristics and exceptional performance in water absorption and dimensional stability. In this review, we summarize recent findings on the biosynthesis, metabolism, and physiological function of cadaverine in bacteria, with a focus on the regulatory mechanism of cadaverine synthesis in Escherichia coli (E. coli). We also describe recent developments in bacterial production of cadaverine by direct fermentation and whole-cell bioconversion, and recent approaches for the separation and purification of cadaverine. In addition, we present an overview of the application of cadaverine in the synthesis of completely bio-based polyamides. Finally, we provide an outlook and suggest future developments to advance the production of cadaverine from renewable resources.
In the last five years, China has seen the technological development of intelligent mining and the application of the longwall automation technology developed by the Longwall Automation Steering Committee. This paper summarizes this great achievement, which occurred during the 12th Five-Year Plan (2011–2015), and which included the development of a set of intelligent equipment for hydraulic-powered supports, information transfers, dynamic decision-making, performance coordination, and the achievement of a high level of reliability despite difficult conditions. Within China, the intelligent system of a set of hydraulic-powered supports was completed, with our own intellectual property rights. An intelligent mining model was developed that permitted unmanned operation and single-person inspection on the work face. With these technologies, the number of miners on the work face can now be significantly reduced. Miners are only required to monitor mining machines on the roadway or at the surface control center, since intelligent mining can be applied to extract middle-thick or thick coal seams. As a result, miners’ safety has been improved. Finally, this paper discusses the prospects and challenges of intelligent mining over the next ten years.
Nitrogen-doped carbon nanotubes (NCNTs) were used as a support for iron (Fe) nanoparticles applied in carbon dioxide (CO2) hydrogenation at 633 K and 25 bar (1 bar= 105 Pa). The Fe/NCNT catalyst promoted with both potassium (K) and manganese (Mn) showed high performance in CO2 hydrogenation, reaching 34.9% conversion with a gas hourly space velocity (GHSV) of 3.1 L·(g·h)−1. Product selectivities were high for olefin products and low for short-chain alkanes for the K-promoted catalysts. When Fe/NCNT catalyst was promoted with both K and Mn, the catalytic activity was stable for 60 h of reaction time. The structural effect of the Mn promoter was demonstrated by X-ray diffraction (XRD), temperature-programmed reduction (TPR) with molecular hydrogen (H2), and in situ X-ray absorption near-edge structure (XANES) analysis. The Mn promoter stabilized wüstite (FeO) as an intermediate and lowered the TPR onset temperature. Catalytic ammonia (NH3) decomposition was used as an additional probe reaction for characterizing the promoter effects. The Fe/NCNT catalyst promoted with both K and Mn had the highest catalytic activity, and the Mn-promoted Fe/NCNT catalysts had the highest thermal stability under reducing conditions.
Crystallization is an important unit operation in the pharmaceutical industry. At present, most pharmaceutical crystallization processes are performed in batches. However, due to product variability from batch to batch and to the low productivity of batch crystallization, continuous crystallization is gaining increasing attention. In the past few years, progress has been made to allow the products of continuous crystallization to meet different requirements. This review summarizes the progress in pharmaceutical continuous crystallization from a product engineering perspective. The advantages and disadvantages of different types of continuous crystallization are compared, with the main difference between the two main types of crystallizers being their difference in residence time distribution. Approaches that use continuous crystallization to meet different quality requirements are summarized. Continuous crystallization has advantages in terms of size and morphology control. However, it also has the problem of a process yield that may be lower than that of a batch process, especially in the production of chirality crystals. Finally, different control strategies are compared.
The development of technologies such as big data and cyber-physical systems (CPSs) has increased the demand for product design. Product digital design involves completing the product design process using advanced digital technologies such as geometry modeling, kinematic and dynamic simulation, multi-disciplinary coupling, virtual assembly, virtual reality (VR), multi-objective optimization (MOO), and human-computer interaction. The key technologies of intelligent design for customized products include: a description and analysis of customer requirements (CRs), product family design (PFD) for the customer base, configuration and modular design for customized products, variant design for customized products, and a knowledge push for product intelligent design. The development trends in intelligent design for customized products include big-data-driven intelligent design technology for customized products and customized design tools and applications. The proposed method is verified by the design of precision computer numerical control (CNC) machine tools.
Electron beam selective melting (EBSM) is a promising additive manufacturing (AM) technology. The EBSM process consists of three major procedures: ① spreading a powder layer, ② preheating to slightly sinter the powder, and ③ selectively melting the powder bed. The highly transient multi-physics phenomena involved in these procedures pose a significant challenge for in situ experimental observation and measurement. To advance the understanding of the physical mechanisms in each procedure, we leverage high-fidelity modeling and post-process experiments. The models resemble the actual fabrication procedures, including ① a powder-spreading model using the discrete element method (DEM), ② a phase field (PF) model of powder sintering (solid-state sintering), and ③ a powder-melting (liquid-state sintering) model using the finite volume method (FVM). Comprehensive insights into all the major procedures are provided, which have rarely been reported. Preliminary simulation results (including powder particle packing within the powder bed, sintering neck formation between particles, and single-track defects) agree qualitatively with experiments, demonstrating the ability to understand the mechanisms and to guide the design and optimization of the experimental setup and manufacturing process.
After two decades’ endeavor, the Research Institute of Petroleum Processing (RIPP) has successfully developed a green caprolactam (CPL) production technology. This technology is based on the integration of titanium silicate (TS)-1 zeolite with the slurry-bed reactor for the ammoximation of cyclohexanone, the integration of silicalite-1 zeolite with the moving-bed reactor for the gas-phase rearrangement of cyclohexanone oxime, and the integration of an amorphous nickel (Ni) catalyst with the magnetically stabilized bed reactor for the purification of caprolactam. The world’s first industrial plant based on this green CPL production technology has been built and possesses a capacity of 200?kt·a−1. Compared with existing technologies, the plant investment is pronouncedly reduced, and the nitrogen (N) atom utilization is drastically improved. The waste emission is reduced significantly; for example, no ammonium sulfate byproduct is produced. As a result, the price difference between CPL and benzene drops. In 2015, the capacity of the green CPL production technology reached 3?×?106?t·a−1, making China the world’s largest CPL producer, with a global market share exceeding 50%.
Reactive oxygen species (ROS) can be caused by mechanical, thermal, infectious, and chemical stimuli, and their negative effects on the health of humans and other animals are of considerable concern. The nuclear factor (erythroid-derived 2)-like 2/Kelch-like ECH-associated protein 1 (Nrf2/Keap1) system plays a major role in maintaining the balance between the production and elimination of ROS via the regulation of a series of detoxifying and antioxidant enzyme gene expressions by means of the antioxidant response element (ARE). Dietary phytochemicals, which are generally found in vegetables, fruits, grains, and herbs, have been reported to have health benefits and to improve the growth performance and meat quality of farm animals through the regulation of Nrf2-mediated phase II enzymes in a variety of ways. However, the enormous quantity of somewhat chaotic data that is available on the effects of phytochemicals needs to be properly classified according to the functions or mechanisms of phytochemicals. In this review, we first introduce the antioxidant properties of phytochemicals and their relation to the Nrf2/Keap1 system. We then summarize the effects of phytochemicals on the growth performance, meat quality, and intestinal microbiota of farm animals via targeting the Nrf2/Keap1 system. These exhaustive data contribute to better illuminate the underlying biofunctional properties of phytochemicals in farm animals.
The ball-screw feed drive has varying high-order dynamic characteristics due to flexibilities of the slender screw spindle and joints between components, and an obvious feature of non-collocated control when a direct position measurement using a linear scale is employed. The dynamic characteristics and non-collocated situation have long been the source of difficulties in motion and vibration control, and deteriorate the achieved accuracy of the axis motion. In this study, a dynamic model using a frequency-based substructure approach is established, considering the flexibilities and their variation. The position-dependent variation of the dynamic characteristics is then fully investigated. A corresponding control strategy, which is composed of a modal characteristic modifier (MCM) and an intelligent adaptive tuning algorithm (ATA), is then developed. The MCM utilizes a combination of peak filters and notch filters, thereby shaping the plant dynamics into a virtual collocated system and avoiding control spillover. An ATA using an artificial neural network (ANN) as a smooth parameter interpolator updates the parameters of the filters in real time in order to cope with the feed drive’s dynamic variation. Numerical verification of the effectiveness and robustness of the proposed strategy is shown for a real feed drive.