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.

Flexible Fixture Design for the Top and End Surface Processing of NP2_NP4 Cylinder Heads

This paper focuses on the design of fixtures for NP2 and NP4 cylinder heads on a horizontal machining center of flexible machining automatic lines.It began with an analysis of the diagrams of part processing and working procedure which formed the basis for the design of the processing technology scheme,a selection of suitable machine tools,and the setting of processing parameters.Fixtures tailored to the chosen machine tools were then designed to meet the processing requirements.Additional aspects of the project included the design of part drawings,calculation of working time quota,design of auxiliary guides,support clamping,and hydraulic circuits,all aimed at fulfilling practical production requirements.

Design of high-performance ion-doped CoP systems for hydrogen evolution:From multi-level screening calculations to experiment

Rational design of high-performance electrocatalysts for hydrogen evolution reaction(HER)is vital for future renewable energy systems.The incorporation of foreign metal ions into catalysts can be an effective approach to optimize its performance.However,there is a lack of systematic theoretical studies to reveal the quantitative relationships at the electronic level.Here,we develop a multi-level screening methodology to search for highly stable and active dopants for CoP catalysts.The density functional theory(DFT)calculations and symbolic regression(SR)were performed to investigate the relationship between the adsorption free energy(ΔG_(H^(*)))and 10 electronic parameters.The mathematic formulas derived from SR indicate that the difference of work function(ΔΦ)between doped metal and the acceptor plays the most important role in regulatingΔG_(H^(*)),followed by the d-band center(d-BC)of doped system.The descriptor of HER can be expressed asΔG_(H^(*))=1.59×√|0.188ΔΦ+d BC+0.120|1/2-0.166 with a high determination coefficient(R^(2)=0.807).Consistent with the theoretical prediction,experimental results show that the Al-CoP delivers superior electrocatalytic HER activity with a low overpotential of75 m V to drive a current density of 10 mA cm^(-2),while the overpotentials for undoped CoP,Mo-CoP,and V-CoP are 206,134,and 83 m V,respectively.The current work proves that theΔΦis the most significant regulatory parameter ofΔG_(H^(*))for ion-doped electrocatalysts.This finding can drive the discovery of high-performance ion-doped electrocatalysts,which is crucial for electrocatalytic water splitting.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Design of Traditional Chinese Medicine Extraction Workshop Process and Automation System

Objective: This paper takes the example of a Panax notoginseng extraction workshop and designs an automated production workshop with advanced domestic capabilities. Methods: 1) Based on the small-scale Panax notoginseng extraction process, the feasibility of the workshop production process is demonstrated. 2) The workshop process design for Panax Notoginseng saponin extraction is completed, including production organization plans and the selection of key equipment. 3) For the Panax notoginseng extraction workshop process, an automated production control system is designed. Conclusion: Through optimized design of the production process and automation system, continuous and automated production of traditional Chinese medicine extraction is achieved, leading to improvements in drug quality and production efficiency.

MULTI-WORLD MECHANISM FOR MODELING EVOLUTIONARY DESIGN PROCESS FROM CONCEPTUAL DESIGN TO DETAILED DESIGN

A multi-world mechanism is developed for modeling evolutionary design process from conceptual design to detailed design. In this mechanism, the evolutionary design database is represented by a sequence of worlds corresponding to the design descriptions at different design stages. In each world, only the differences with its ancestor world are recorded. When the design descriptions in one world are changed, these changes are then propagated to its descendant worlds automatically. Case study is conducted to show the effectiveness of this evolutionary design database model.

On Software Application Database Constraint-driven Design and Development

This paper presents a methodology driven by database constraints for designing and developing(database)software applications.Much needed and with excellent results,this paradigm guarantees the highest possible quality of the managed data.The proposed methodology is illustrated with an easy to understand,yet complex medium-sized genealogy software application driven by more than 200 database constraints,which fully meets such expectations.

基于Process Designer的白车身数字化工厂数据检查软件开发和应用

为提高规划员检查供应商Process Designer(PD)数据的效率,同时规范供应商的数据设计行为,运用创新思维模式,自主开发了基于PD的白车身数字化工厂数据检查软件。该软件采用.NET环境下的C#语言编程,同时支持数据节点属性和树结构的检查、支持检查规则的可配置功能,增强了软件的可扩展性,软件可以100%检查节点属性和树结构与技术规范的符合性,并提供了良好的报错视图,方便问题的查找和更正。目前该检查软件已经在公司各车型项目上应用,可有效地执行检查工作,极大地提高了数据检查的效率和准确性,一个全新车型项目PD数字化工厂数据总检查时间可从原来的45天缩短到20天左右,是一个降本增效的优秀数字化应用案例。

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Automatic relational database compression scheme design based on swarm evolution

Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the re- duction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have im- plemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.

采用Process Designer的白车身焊装生产线工艺规划研究

白车身焊装生产线工艺规划是决定汽车整车生产周期的重要环节。以先进的数字化工厂技术软件——ProcessDesigner为平台,通过创建制造信息模型和工艺过程模型,实现对白车身焊装生产线的生产信息管理和工艺过程规划,构建了白车身焊装生产线工艺规划系统,并详细描述了其工艺规划实现的具体方法和步骤,最后以某型白车身底板焊装线为例,生成了基于规划系统的数字化三维工厂,对规划结果进行了验证。结果表明,利用该系统进行焊装工艺规划能显著缩短工艺规划时间,提高工艺规划的准确性。

Designing Oxide Catalysts for Oxygen Electrocatalysis: Insights from Mechanism to Application

The electrochemical oxygen reduction reaction(ORR) and oxygen evolution reaction(OER) are fundamental processes in a range of energy conversion devices such as fuel cells and metal–air batteries. ORR and OER both have significant activation barriers, which severely limit the overall performance of energy conversion devices that utilize ORR/OER. Meanwhile, ORR is another very important electrochemical reaction involving oxygen that has been widely investigated. ORR occurs in aqueous solutions via two pathways: the direct 4-electron reduction or 2-electron reduction pathways from O_(2) to water(H_2O) or from O_(2) to hydrogen peroxide(H_2O_(2)). Noble metal electrocatalysts are often used to catalyze OER and ORR, despite the fact that noble metal electrocatalysts have certain intrinsic limitations, such as low storage. Thus, it is urgent to develop more active and stable low-cost electrocatalysts, especially for severe environments(e.g., acidic media). Theoretically, an ideal oxygen electrocatalyst should provide adequate binding to oxygen species. Transition metals not belonging to the platinum group metal-based oxides are a low-cost substance that could give a d orbital for oxygen species binding. As a result, transition metal oxides are regarded as a substitute for typical precious metal oxygen electrocatalysts. However, the development of oxide catalysts for oxygen reduction and oxygen evolution reactions still faces significant challenges, e.g., catalytic activity, stability, cost, and reaction mechanism. We discuss the fundamental principles underlying the design of oxide catalysts, including the influence of crystal structure, and electronic structure on their performance. We also discuss the challenges associated with developing oxide catalysts and the potential strategies to overcome these challenges.

A Feature Definition Hierarchy for Supporting Design Process

特征定义的适应性是特征技术在设计过程成功应用的关键和核心问题．本文基于提出了面向设计过程的特征定义层次结构及特征定义方法，将特征定义用应用特征、形状特征和几何表示３个相对独立的层次来表示，并分别利用特征语义解释器和改进的几何关联图实现层次间的有效连接和相互转换，这不仅消弱了特征定义对应用的依赖性而更具广泛性，也为基于特征的并行设计过程模型的建立提供了基础．

基于MATLAB App Designer的数字信号处理教学辅助系统设计

针对“数字信号处理”课程概念抽象、公式繁琐的特点,利用MATLAB App Designer控件多、界面友好、交互性强等特点设计了一款教学辅助系统。包含了数字信号处理课程内容中的常见信号及其运算、傅里叶变换及分析、滤波器设计、综合应用等方面。通过输入参数或修改参数,就能显示相应的响应结果,从而将数字信号处理抽象的数学运算,变成直观的、可视过程,有利于学生增强对理论的理解。设计的程序可添加在MATLAB App中随时调用,也可形成脱离MATLAB环境的可执行文件,经过2年在教学演示、实验辅助等方面的应用,取得了良好的效果。

A machine learning approach for accelerated design of magnesium alloys. Part A:Alloy data and property space

Typically, magnesium alloys have been designed using a so-called hill-climbing approach, with rather incremental advances over the past century. Iterative and incremental alloy design is slow and expensive, but more importantly it does not harness all the data that exists in the field. In this work, a new approach is proposed that utilises data science and provides a detailed understanding of the data that exists in the field of Mg-alloy design to date. In this approach, first a consolidated alloy database that incorporates 916 datapoints was developed from the literature and experimental work. To analyse the characteristics of the database, alloying and thermomechanical processing effects on mechanical properties were explored via composition-process-property matrices. An unsupervised machine learning(ML) method of clustering was also implemented, using unlabelled data, with the aim of revealing potentially useful information for an alloy representation space of low dimensionality. In addition, the alloy database was correlated to thermodynamically stable secondary phases to further understand the relationships between microstructure and mechanical properties. This work not only introduces an invaluable open-source database, but it also provides, for the first-time data, insights that enable future accelerated digital Mg-alloy design.

The action mechanisms and structures designs of F-containing functional materials for high performance oxygen electrocatalysis

Non-renewable fossil fuels have led to serious problems such as global warming,environmental pollution,etc.Oxygen electrocatalysis including oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)plays a central role in clean energy conversion,enabling a number of sustainable processes for future air battery technologies.Fluorine,as the most electronegative element(4.0)not only can induce more efficient regulation for the electronic structure,but also can bring more abundant defects and other novel effects in materials selection and preparation for favorable catalysis with respect to the other nonmetal elements.However,an individual and comprehensive overview of fluorine-containing functional materials for oxygen electrocatalysis field is still blank.Therefore,it is very meaningful to review the recent progresses of fluorine-containing oxygen electrocatalysts.In this review,we first systematically summarize the controllable preparation methods and their possible development directions based on fluorine-containing materials from four preparation methods.Due to the strong electron-withdrawing properties of fluorine,its control of the electronic structure can effectively enhance the oxygen electrocatalytic activity of the materials.In addition,the catalytic enhancement effect of fluorine on carbonbased materials also includes the prevent oxidation and the layer peeling,and realizes the precise atomic control.And the catalytic improvement mechanism of fluorine containing metal-based compounds also includes the hydration of metal site,the crystal transformation,and the oxygen vacancy induction.Then,based on their various dimensions(0D–3D),we also have summarized the advantages of different morphologies on oxygen electrocatalytic performances.Finally,the prospects and possible future researching direction of F-containing oxygen electrocatalysts are presented(e.g.,novel pathways,advanced methods for measurement and simulation,field assistance and multi-functions).The review is considered valuable and helpful in exploring the novel designs and mechanism analyses of advanced fluorine-containing electrocatalysts.

Design Strategy of Digital Display Based on the Concept of Service Design

Based on the analysis of the concept,core,research content and method of service design,this paper explains the necessity of service design to participate in digital display,and further discusses how service design integrates with digital display,how to redesign the digital display system under the intervention of service design,and how to integrate user needs into it at all times.Finally,the design strategy of digital display under the concept of service design is proposed.

基于Geomagic Design X的复杂曲面产品逆向设计

随着科学技术的发展和市场需求的不断变化,人们对产品的要求越来越高,产品更新换代的速度越来越快,产品结构也更加复杂。逆向设计通过对产品实物样件结构进行数据采集、处理,并对生成的三维模型结构进行重构,实现了对实物结构的分析和再设计。逆向设计技术具有快速、高效和精确的特点,现已广泛应用于多个行业和领域。以蓝光雾化消毒枪为模型,详细介绍利用Geomagic Design X软件进行产品逆向设计的具体过程和流程。

Design Around Bundle Patent Portfolio Based on Technological Evolution

Product innovation can be achieved by analyzing leading products patents in the market.Different methods have been proposed for design around patent,commonly using the elimination or replacement of a single patent element However,the existing research fails to restore the position and function of the design around object in the original patent portfolio of enterprises,which often leads to the phenomenon of evading one patent and violating another.This paper proposes a method for design around patent through using the fusion of technologies of the evolution theory and bundle-type patent portfolio analysis in the initial stage of product development.The object system is analyzed to select technical opportunities through the evolutionary path of technologies and functional trimming methods to achieve circumvent barriers of bundle-type patents.The bundle patent portfolio is analyzed for the product evolution with a radar map.The technological evolution path is combined with the TRIZ innovation method to identify and solve the design problem.Patentability of the new design is evaluated using the patent system rules for innovative scheme difference from the original patent portfolio.The method is verified in a case study for the design of a glass-wiping robot.The design solution has been patented.