Repositioning fertilizer manufacturing subsidies for improving food security and reducing greenhouse gas emissions in China

China removed fertilizer manufacturing subsidies from 2015 to 2018 to bolster market-oriented reforms and foster environmentally sustainable practices.However,the impact of this policy reform on food security and the environment remains inadequately evaluated.Moreover,although green and low-carbon technologies offer environmental advantages,their widespread adoption is hindered by prohibitively high costs.This study analyzes the impact of removing fertilizer manufacturing subsidies and explores the potential feasibility of redirecting fertilizer manufacturing subsidies to invest in the diffusion of these technologies.Utilizing the China Agricultural University Agri-food Systems model,we analyzed the potential for achieving mutually beneficial outcomes regarding food security and environmental sustainability.The findings indicate that removing fertilizer manufacturing subsidies has reduced greenhouse gas(GHG)emissions from agricultural activities by 3.88 million metric tons,with minimal impact on food production.Redirecting fertilizer manufacturing subsidies to invest in green and low-carbon technologies,including slow and controlled-release fertilizer,organic-inorganic compound fertilizers,and machine deep placement of fertilizer,emerges as a strategy to concurrently curtail GHG emissions,ensure food security,and secure robust economic returns.Finally,we propose a comprehensive set of government interventions,including subsidies,field guidance,and improved extension systems,to promote the widespread adoption of these technologies.

Ballistic performance of additive manufacturing 316l stainless steel projectiles based on topology optimization method

Material and structure made by additive manufacturing(AM)have received much attention lately due to their flexibility and ability to customize complex structures.This study first implements multiple objective topology optimization simulations based on a projectile perforation model,and a new topologic projectile is obtained.Then two types of 316L stainless steel projectiles(the solid and the topology)are printed in a selective laser melt(SLM)machine to evaluate the penetration performance of the projectiles by the ballistic test.The experiment results show that the dimensionless specific kinetic energy value of topologic projectiles is higher than that of solid projectiles,indicating the better penetration ability of the topologic projectiles.Finally,microscopic studies(scanning electron microscope and X-ray micro-CT)are performed on the remaining projectiles to investigate the failure mechanism of the internal structure of the topologic projectiles.An explicit dynamics simulation was also performed,and the failure locations of the residual topologic projectiles were in good agreement with the experimental results,which can better guide the design of new projectiles combining AM and topology optimization in the future.

Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.

Influence of manufacturing process-induced geometrical defects on the energy absorption capacity of polymer lattice structures

Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this work.The numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice structure.Four geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are investigated.Specifically,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is investigated.The main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.

Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

A survey of composite robot for aviation intelligent manufacturing application

With the rapid development of the aviation industry,the development of intelligent manufacturing equipment represented by composite robots has been paid close attention by the aviation industry.Based on the analysis of the background and main structure function of composite robots,this paper focuses on the analysis of key technologies such as composite robot hardware design,visual sensing and planning system,integrated control of‘hands,feet,and eyes',multi-robot collaborative operation,and safety.The typical applications of composite robots in aviation intelligent manufacturing such as automatic drilling and connection of aircraft,aircraft surface spraying and finishing,parts handling,aircraft measurement,and inspection are presented.The development trends such as standardization of composite robots,integration of‘5G+cloud computing+AI',and fusion of intelligent sensors are proposed.

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

A review on the multi-scaled structures and mechanical/thermal properties of tool steels fabricated by laser powder bed fusion additive manufacturing

The laser powder bed fusion(LPBF) process can integrally form geometrically complex and high-performance metallic parts that have attracted much interest,especially in the molds industry.The appearance of the LPBF makes it possible to design and produce complex conformal cooling channel systems in molds.Thus,LPBF-processed tool steels have attracted more and more attention.The complex thermal history in the LPBF process makes the microstructural characteristics and properties different from those of conventional manufactured tool steels.This paper provides an overview of LPBF-processed tool steels by describing the physical phenomena,the microstructural characteristics,and the mechanical/thermal properties,including tensile properties,wear resistance,and thermal properties.The microstructural characteristics are presented through a multiscale perspective,ranging from densification,meso-structure,microstructure,substructure in grains,to nanoprecipitates.Finally,a summary of tool steels and their challenges and outlooks are introduced.

Research Progress of Additive Manufacturing Technology in Energetic Material Field at Home and Abroad

As a subversive manufacturing technology, additive manufacturing technology has many technical advantages such as high freedom of design and not limited by complex structure of parts. The application of additive manufacturing technology to the charge molding of energetic materials will subvert the traditional manufacturing concept of energetic materials, realize the advanced charge design concept, shorten the research and development time of weapons and equipment, and improve the comprehensive performance of weapons and equipment, which is of great significance for the rapid development of high-tech weapons and equipment. This paper analyzes the research progress of additive manufacturing technology in the field of energetic materials at home and abroad and puts forward some suggestions for future research of this technology. .

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Research on the Design and Application of Virtual and Real Integrated Training Platform Based on Intelligent Manufacturing

In this paper,we built a robot training platform using virtual simulation software,and the robot assembly,handling,and palletizing were realized.The workstation includes an industrial robot,gas control unit,track function module,assembly function module,palletizing function module,vision module,etc.,and robot movement is achieved through language programming.The platform provides conditions for the practical ability training of application-oriented talents.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

Exploration and Application Practice of Energy Conservation Theory and Method in Steel Manufacturing Process System

This article briefly discusses the theoretical basis and overall goals of energy conservation in the steel manufacturing process system.It is proposed that in the process of implementing system energy conservation,it is necessary to fully recognize and utilize the characteristics and functional advantages of the steel manufacturing process,pay more attention to energy quality,firmly grasp the overall goal of system optimization,focus on the integrated optimization of gas,steam,and waste heat systems,and propose the idea of constructing a"steel chemi-cal gas electricity heating cooling multi generation system".Based on practice,the main principles,models,and effects of implementing systematic energy conservation in steel enterprises have been proposed.

Minimizing Products Rates Variation in Just-in-Time Mixed-Model Manufacturing

Mixed-Model assembly lines are often used in manufacturing based on just-in-time techniques. The effective utilization of these lines requires a schedule for assembling the different models be determined. The objective is to minimize the total deviation of actual production rates from the desired production rates. Mathematical method with the optimization algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the proposed algorithm is an efficient and effective algorithm which gives better results with the large problem sizes. This paper presents a practical procedure to minimize total product variation rates, and easy to use by practitioner.

Additive manufacturing of magnesium matrix composites: Comprehensive review of recent progress and research perspectives

The magnesium matrix composites(MMCs) formed by introducing reinforcements to magnesium alloys overcome the limitations of the mechanical properties to a certain extent, presenting unique and excellent properties that any component does not have, such as high specific stiffness and specific strength, good dimensional stability, outstanding shock absorption performance, excellent electromagnetic shielding and hydrogen storage characteristics, etc. As an emerging manufacturing technology, additive manufacturing(AM) is based on the design of threedimensional(3D) data model to obtain 3D objects through layer-by-layer processing, which possesses the advantages of short manufacturing cycle, high material utilization rate, high degree of design freedom, excellent mechanical properties and the ability to fabricate complex structural components. Combining the high stiffness and high strength properties of MMCs and the technical advantages of AM forming complex structural parts with high performance, the prepared AM MMCs have huge potential advantages and broad application prospects in new high-tech industries such as automobile, aerospace, consumer electronics and biomedicine, etc. This paper reviews the research progress in the field of AM MMCs, mainly introduces the main AM technologies, including selective laser melting(SLM), electron beam selective melting(EBSM), laser engineered net shaping(LENS) and wire and arc additive manufacturing(WAAM). The formation mechanism and control methods of the typical defects including balling effect, porosity, poor fusion, loss of alloy elements and cracks produced during AM are discussed. The main challenges of AM MMCs are proposed from the aspects of composition design and the preparation of powder raw material. The relationship between the microstructure and mechanical properties, corrosion performance and biocompatibility of AM MMCs are elaborated in detail. The application potential of AM MMCs in various fields at present and in the future is introduced. Finally, the development direction and urgent problems to be solved in the AM MMCs are prospected.

In-situ deposition of apatite layer to protect Mg-based composite fabricated via laser additive manufacturing

Biodegradable magnesium(Mg) and its alloy show huge potential as temporary bone substitute due to the favorable biocompatibility and mechanical compatibility. However, one issue deserves attention is the too fast degradation. In this work, mesoporous bioglass(MBG)with high pore volume(0.59 cc/g) and huge specific surface area(110.78 m^(2)/g) was synthesized using improved sol-gel method, and introduced into Mg-based composite via laser additive manufacturing. Immersion tests showed that the incorporated MBG served as powerful adsorption sites, which promoted the in-situ deposition of apatite by successively adsorbing Ca2+and HPO42-. Such dense apatite film acted as an efficient protection layer and enhanced the corrosion resistance of Mg matrix, which was proved by the electrochemical impedance spectroscopy measurements. Thereby, Mg based composite showed a significantly decreased degradation rate of 0.31 mm/year. Furthermore,MBG also improved the mechanical properties as well as cell behavior. This work highlighted the advantages of MBG in the fabrication of Mg-based implant with enhanced overall performance for orthopedic application.

A review on stress determination and control in metal-based additive manufacturing

Metal additive manufacturing(MAM)is an emerging and disruptive technology that builds three-dimensional(3D)components by adding layer-upon-layer of metallic materials.The complex cyclic thermal history and highly localized energy can produce large temperature gradients,which will,in turn,lead to compressive and tensile stress during the MAM process and eventually result in residual stress.Being an issue of great concern,residual stress,which can cause distortion,delamination,cracking,etc.,is considered a key mechanical quantity that affects the manufacturing quality and service performance of MAM parts.In this review paper,the ongoing work in the field of residual stress determination and control for MAM is described with a particular emphasis on the experimental measurement/control methods and numerical models.We also provide insight on what still requires to be achieved and the research opportunities and challenges.

Laser additive manufacturing of zinc:formation quality,texture,and cell behavior

Laser powder bed fusion(LPBF)makes it possible for biodegradable zinc(Zn)to be used to produce customized orthopedic implants.In this research,we investigate the impact of laser power and scanning speed on the development of surface quality,relative densification,and texture during LPBF of Zn implants.Increasing laser power was able to decrease melt viscosity and surface tension,which improved the metallurgical bonding between adjacent tracks.Uneven and twisted tracks also became continuous and straight.Scanning speed could controlmolten-pool temperature to restrain grain natural orientation,achieving various crystal orientations and a weakened texture.Importantly,it further avoided the thermal expansion and contraction caused by excessive energy storage and accumulation in the matrix,thus reducing the generation of high-dislocation density.As a result,by selecting a reasonable laser power and scanning speed,the LPBF parts exhibited a flat surface morphology and a high density over 99.5%.Their average hardness,mechanical strength,and elongation reached 50.2 HV,127.8 MPa,and 7.6%,respectively.Additionally,the parts displayed a moderate degradation rate and excellent osteogenic properties.All these results provide a basis for selecting process parameters to optimize the comprehensive properties of LPBF-processed Zn parts for biodegradable applications.

Additive manufacturing of Ni-based superalloys: Residual stress, mechanisms of crack formation and strategies for crack inhibition

The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in high-end industrial systems.However,the intense temperature gradient induced by the rapid heating and cooling processes of AM can generate high levels of residual stress and metastable chemical and structural states,inevitably leading to severe metallurgical defects in Ni-based superalloys.Cracks are the greatest threat to these materials’integrity as they can rapidly propagate and thereby cause sudden and non-predictable failure.Consequently,there is a need for a deeper understanding of residual stress and cracking mechanisms in additively manufactured Ni-based superalloys and ways to potentially prevent cracking,as this knowledge will enable the wider application of these unique materials.To this end,this paper comprehensively reviews the residual stress and the various mechanisms of crack formation in Ni-based superalloys during AM.In addition,several common methods for inhibiting crack formation are presented to assist the research community to develop methods for the fabrication of crack-free additively manufactured components.

Review of functionally graded materials processed by additive manufacturing

Additive manufacturing(AM)technology makes parts through layer-by-layer deposition,which can regulate the microstructure and properties of different parts of a single part well.It provides a new idea for the preparation of functionally gradient materials(FGM),and has become a research hotspot at present.By referring to and analyzing the recent research achievements in the additive manufacturing tech-nology of FGM,the latest research progress at domestic and abroad from four aspects were summaried:selective laser melting additive man-ufacturing,electron beam additive manufacturing,arc additive manufacturing,path planning,and material texture.Moreover,the existing problems in the research are pointed out,and the future research direction and focus are prospected.