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.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

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.

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。

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。

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．

FIXED-DESIGN REGRESSION FOR LINEARTIME SERIES

This paper obtains asymptotic normality for double array sum of linear time series zeta(t), and gives its application in the regression model. This generalizes the main results in [1].

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.

QUALITY FUNCTION DEPLOYMENT IN BOTTOM-UP PROCESS FOR DESIGN REUSE

To deal with a bottom up process model for design reuses a specific extended house of quality(EHOQ)is proposed Two kinds of supported functions,basic supported functions and new supported functions,are defined.Two processes to determine two kinds of functions are presented A kind of EHOQ matrix for a company is given and its management steps are studied.

ON DESIGN METHOD OF THE PRECISION CAM PROFILE WITH RANDOM PROCESSING ERRORS

Based on probability and statistic, a design method of precision cam profileconcerning the influence of random processing errors is advanced. Combining the design with theprocess, which can be used to predict that cam profiles will be successfully processed or not in thedesign stage, design of the cam can be done by balancing the economization and reliability. Inaddition, an fuzzy deduction method based on Bayers formula is advanced to estimate processingreasonable of the designed precision cam profile, and it take few samples.

Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design

The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this challenge.Traditionally,new advanced materials are found empirically or through trial-and-error approaches.As theoretical methods and associated tools are being continuously improved and computer power has reached a high level,it is now efficient and popular to use computational methods to guide material selection and design.Due to the strong interaction between material selection and the operation of the process in which the material is used,it is essential to perform material and process design simultaneously.Despite this significant connection,the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required.Hybrid modeling provides a promising option to tackle such complex design problems.In hybrid modeling,the material properties,which are computationally expensive to obtain,are described by data-driven models,while the well-known process-related principles are represented by mechanistic models.This article highlights the significance of hybrid modeling in multiscale material and process design.The generic design methodology is first introduced.Six important application areas are then selected:four from the chemical engineering field and two from the energy systems engineering domain.For each selected area,state-ofthe-art work using hybrid modeling for multiscale material and process design is discussed.Concluding remarks are provided at the end,and current limitations and future opportunities are pointed out.

Review on biomass metallurgy:Pretreatment technology,metallurgical mechanism and process design

The metallurgy industry consumes a considerable amount of coal and fossil fuels,and its carbon dioxide emissions are increasing every year.Replacing coal with renewable,carbon-neutral biomass for metallurgical production is of great significance in reducing global carbon consumption.This study describes the current state of research in biomass metallurgy in recent years and analyzes the concept and scientific principles of biomass metallurgy.The fundamentals of biomass pretreatment technology and biomass metallurgy technology were discussed,and the industrial application framework of biomass metallurgy was proposed.Furthermore,the economic and social advantages of biomass metallurgy were analyzed to serve as a reference for the advancement of fundamental theory and industrial application of biomass metallurgy.

Integrated Building Envelope Design Process Combining Parametric Modelling and Multi-Objective Optimization

As an important element in sustainable building design, the building envelope has been witnessing a constant shift in the design approach. Integrating multi-objective optimization(MOO) into the building envelope design process is very promising, but not easy to realize in an actual project due to several factors, including the complexity of optimization model construction, lack of a dynamic-visualization capacity in the simulation tools and consideration of how to match the optimization with the actual design process. To overcome these difficulties, this study constructed an integrated building envelope design process(IBEDP) based on parametric modelling, which was implemented using Grasshopper platform and interfaces to control the simulation software and optimization algorithm. A railway station was selected as a case study for applying the proposed IBEDP, which also utilized a grid-based variable design approach to achieve flexible optimum fenestrations. To facilitate the stepwise design process, a novel strategy was proposed with a two-step optimization, which optimized various categories of variables separately. Compared with a one-step optimization,though the proposed strategy performed poorly in the diversity of solutions, the quantitative assessment of the qualities of Pareto-optimum solution sets illustrates that it is superior.

Research on Flexible Transfer Line Schematic Design Using Hierarchical Process Planning

Flexible transfer line(FTL)is now widely used in ma ny manufacturing domains to realize efficiently,high quantity and economic prod uction.These manufacturing domains include automobile,tractor,internal-combu stion engine,and so on.In today’s competitive business environment,it is vit ally important for machine tool manufacturers to design flexible transfer line m ore effectively and efficiently according to a wider variety of customer demand s.This paper proposes an approach to a bidding-based flexible transfer line sc hematic design system.By analyzing manual FTL design process,the architecture o f flexible transfer line schematic design system(FTLSDS)is established.The syst em consists:of four processes:part feature modeling,process planning,FTL fac i lity layout and FTL evaluation. For FTL schematic design.a five-level proces s planning strategy named hierarchical process planning method is proposed.This method includes selection of manufacturing feature machining operation;part se t-up planning,feature sequencing,operation sequencing and process plan genera ting.The major decision relies on setup planning.According to the proceeding o f the hierarchical process planning,the structure of reasoning is proposed base d on blackboard.Under this paradigm,a cooperative effort between a hybrid coll ection of knowledge sources is possible.Total reasoning task can be divided int o some subtasks,and recursive-reasoning system is formed.It is convenient for process planning with step-by-step solution.Meanwhile,the blackboard is use d as the global data exchange area during all reasoning process.By using modula r technology,special purpose machine tools can be designed more efficiently and rapidly.The framework of machine modular design system to support machine requ irement design for FTL is established.By synthesizing the FTL evaluation criter ia.five evaluation criteria of flexible transfer 1ine schematic design are take n into account.An exampie is supplied to demonstrate and verify the validity an d feasibility of flexible transfer line schematic design approach.

The “Static” and “Dynamic” Design Verification Stages of the Lean Development Process: Automotive Industry

he design verification steps that take place in today’s automotive industry, which constitute the values of each successive or simultaneous phase in the new product development process, create a complex structure with the inclusion of each new technology and discipline. Therefore, step by step, each design verification phase definition in the flow contains important phase transition measurements or approval tolerances that ensure the simplicity and continuity of vehicle development processes. In addition, classification of design verification stages within the framework of this study or evaluation in two classes (static and dynamic) is a new approach, but it is a synthesis with the analysis of the new product development process. The vehicle’s basic structure, which constitutes the ergonomic and functional requirements of the vehicle in a static environment, takes into account the dynamic environment variables with crash or accident tests. Increasing new technology adaptations in the automotive industry have changed the new product development process that performs this function structurally and created the concept of design verification under consecutive or simultaneous process simplicity. From the autonomous driving to the use of alternative energy, possible accident scenarios and design verification phase transitions in the integration of parts and systems of the newly developed vehicle create a new structure that models and directs the lean product development process especially in the automotive industry in the coming days. In the lean product development process that takes place in the automotive industry, the design verification transition steps or the approval-control analysis of the development stages, which form a new and effective approach, are re-modeling the entire flow. Therefore, successful execution of design verification steps used in the control of new interdisciplinary product development phase transitions provides value creation.?Within the scope of this study, the effectiveness of the static and dynamic design verification steps, which are carried out in 5 global automotive companies included in the research, which constitute the stage transitions of the new product development process, has been measured. Apart from the design verification transition stages, the process variables that differ among the automotive companies involved in the research are excluded from the scope of this study. In other words, in field researches in the automotive industry, new vehicle design steps or basic engineering steps in the new product development process steps, while creating independent fixed variables, interdisciplinary collaborations, static and dynamic design verification transition stages they perform, or their sequence in the basic flow, is accepted as a dependent variable. Therefore, in the study, the positive effect of the automotive companies that included the static and dynamic design verification phase transition approvals in the lean product development process was investigated. Under the comparative analysis structure of the research, the effect of automotive companies, which accept international vehicle specifications as static design verification input, on market performance has been examined in depth. The detailed depth in the comparison analysis conducted under the second field studies of the study is due to the prediction of dynamic design verification stages to provide a high impact on the market performance, according to the static verification analysis. The new product development stages of the dependent variables were fixed and the flow-oriented?“effect”?of the independent variables in the basic process influenced by the design verification activities was analyzed under the new automotive industry company comparisons. In addition, the impact of the automotive design activities that make up the comparison analysis of the research on the scope of the lean product development stage and its effect on the basic process flow has been demonstrated competition-oriented. Therefore, sub-variables, options, criteria, results, which form a defined comparison problem, create basic test values that affect the problem.

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。

Process design for gas condensate desulfurization and synthesis of nano-13X zeolite adsorbent: equilibrium and dynamic studies

This paper summarizes the results of a study of adsorption of sulfur compounds from a high-sulfur feed on improved spherical-shaped nano-AgX zeolite. For this purpose, the nano-AgX zeolite was initially synthesized and improved with silver compounds such as silver nitrate, and then it was utilized in the adsorption process. In order to investigate the equilibrium and dynamics of the adsorption process, adsorptive desulfurization of real feed(i.e., sour gas condensate from the South Pars gas field) was carried out in batch and continuous processes under several operating conditions; a temperature-dependent Langmuir isotherm model was used to fit the equilibrium data. The value of monolayer adsorption capacity(q_m) and adsorption enthalpy(ΔH) were calculated to be 1.044 mmol/g and 16.8 kJ/mol, respectively. Furthermore, a detailed theoretical model was employed in order to model the breakthrough experiments. The results revealed that an increase in the feed flow rate and 1/T values will cause linear and exponential increase in the total mass transfer coefficient(ks). Isotherm and dynamic breakthrough models were found to be in agreement with the experimental data.