Cellular manufacturing layout on adding/removing machines

In order to rapidly respond to the complex and mutational market, a new facility layout plan based on cellular manufacturing is proposed, which gives consideration to high efficiency and flexibility. The plan designs two phases of integrated cell layout, i.e., cell construction and cell system layout, on the condition of adding/removing machines. First, in view of the costs of logics and machine-relocation, the cell construction based on the alternative processing routes and intra-cell layout are integrated as a whole, which achieves cell formation, process planning and the intra-cell layout in a single step. Secondly, an approach of a continuous optimized multi-line layout for solving the cell system layout problem is proposed, which eliminates the coupling relationship from the machine-relocation and realizes an integrated design of the two phases of the cell layout. An application based on real factory data is optimally solved by the Matlab 7.0 software to validate and verify the models.

Field-assisted machining of difficult-to-machine materials

Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation,semiconductor,biomedicine,and other key fields due to their excellent material properties.However,traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency.In recent years,field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating,tool vibration,magnetic magnetization,and plasma modification,providing a new solution for improving the machinability of DMMs.This technology not only addresses these limitations of traditional machining methods,but also has become a hot topic of research in the domain of ultra-precision machining of DMMs.Many new methods and principles have been introduced and investigated one after another,yet few studies have presented a comprehensive analysis and summarization.To fill this gap and understand the development trend of FAM,this study provides an important overview of FAM,covering different assisted machining methods,application effects,mechanism analysis,and equipment design.The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.

Prediction and interpretation of photocatalytic NO removal on g-C_(3)N_(4)-based catalysts using machine learning

Predictive modeling of photocatalytic NO removal is highly desirable for efficient air pollution abatement.However,great challenges remain in precisely predicting photocatalytic performance and understanding interactions of diverse features in the catalytic systems.Herein,a dataset of g-C_(3) N_(4)-based catalysts with 255 data points was collected from peer-reviewed publications and machine learning(ML)model was proposed to predict the NO removal rate.The result shows that the Gradient Boosting Decision Tree(GBDT)demonstrated the greatest prediction accuracy with R 2 of 0.999 and 0.907 on the training and test data,respectively.The SHAP value and feature importance analysis revealed that the empirical categories for NO removal rate,in the order of importance,were catalyst characteristics>reaction process>preparation conditions.Moreover,the partial dependence plots broke the ML black box to further quantify the marginal contributions of the input features(e.g.,doping ratio,flow rate,and pore volume)to the model output outcomes.This ML approach presents a pure data-driven,interpretable framework,which provides new insights into the influence of catalyst characteristics,reaction process,and preparation conditions on NO removal.

Effect of tool geometry on ultraprecision machining of soft-brittle materials:a comprehensive review

Brittle materials are widely used for producing important components in the industry of optics,optoelectronics,and semiconductors.Ultraprecision machining of brittle materials with high surface quality and surface integrity helps improve the functional performance and lifespan of the components.According to their hardness,brittle materials can be roughly divided into hard-brittle and soft-brittle.Although there have been some literature reviews for ultraprecision machining of hard-brittle materials,up to date,very few review papers are available that focus on the processing of soft-brittle materials.Due to the‘soft’and‘brittle’properties,this group of materials has unique machining characteristics.This paper presents a comprehensive overview of recent advances in ultraprecision machining of soft-brittle materials.Critical aspects of machining mechanisms,such as chip formation,surface topography,and subsurface damage for different machining methods,including diamond turning,micro end milling,ultraprecision grinding,and micro/nano burnishing,are compared in terms of tool-workpiece interaction.The effects of tool geometries on the machining characteristics of soft-brittle materials are systematically analyzed,and dominating factors are sorted out.Problems and challenges in the engineering applications are identified,and solutions/guidelines for future R&D are provided.

Material Removal Rate Prediction of Electrical Discharge Machining Process Using Artificial Neural Network

This article presents an Artificial Neural Network （ANN） architecture to model the Electrical Discharge Machining （EDM） process. It is aimed to develop the ANN model using an input-output pattern of raw data collected from an experimental of EDM process, whereas several research objectives have been outlined such as experimenting machining material for selected gap current, identifying machining parameters for ANN variables and selecting appropriate size of data selection. The experimental data （input variables） of copper-electrode and steel-workpiece is based on a selected gap current where pulse on time, pulse off time and sparking frequency have been chosen at optimum value of Material Removal Rate （MRR）. In this paper, the result has significantly demonstrated that the ANN model is capable of predicting the MRR with low percentage prediction error when compared with the experimental result.

Thermal-Mechanical Efect and Removal Mechanism of Ti-6Al-4V During Laser-Assisted Grinding

The low density and high corrosion resistance of titanium alloy make it a material with various applications in the aerospace industry. However, because of its high specifc strength and poor thermal conductivity, there are problems such as high cutting force, poor surface integrity, and high cutting temperature during conventional machining. As an advanced processing method with high efciency and low damage, laser-assisted machining can improve the machinability of titanium alloy. In this study, a picosecond pulse laser-assisted scratching (PPLAS) method considering both the temperature-dependent material properties and ultrashort pulse laser’s characteristics is frst proposed. Then, the efects of laser power, scratching depth, and scratching speed on the distribution of stress and temperature feld are investigated by simulation. Next, PPLAS experiments are conducted to verify the correctness of the simulation and reveal the removal behavior at various combinations of laser power and scratching depths. Finally, combined with simulated and experimental results, the removal mechanism under the two machining methods is illustrated. Compared with conventional scratching (CS), the tangential grinding force is reduced by more than 60% and the material removal degree is up to 0.948 during PPLAS, while the material removal is still primarily in the form of plastic removal. Grinding debris in CS takes the form of stacked fakes with a “fsh scale” surface, whereas it takes the form of broken serrations in PPLAS. This research can provide important guidance for titanium alloy grinding with high surface quality and low surface damage.

Powder mixed electrochemical discharge process for micro machining of C103 niobium alloy

This work demonstrates the viability of the powder-mixed micro-electrochemical discharge machining(PMECDM) process to fabricate micro-holes on C103 niobium-based alloy for high temperature applications.Three processes are involved simultaneously i.e.spark erosion,chemical etching,and abrasive grinding for removal of material while the classical electrochemical discharge machining process involves double actions i.e.spark erosion,and chemical etching.The powder-mixed electrolyte process resulted in rapid material removal along with a better surface finish as compared to the classical microelectrochemical discharge machining(MECDM).Further,the results are optimized through a multiobjective optimization approach and study of the surface topography of the hole wall surface obtained at optimized parameters.In the selected range of experimental parameters,PMECDM shows a higher material removal rate(MRR) and lower surface roughness(R_(a))(MRR:2.8 mg/min and R_(a) of 0.61 μm) as compared to the MECDM process(MRR:2.01 mg/min and corresponding Raof 1.11 μm).A detailed analysis of the results is presented in this paper.

Influence of Input Factors on Surface Roughness and Material Removal Speed when Wire-EDM a Hardened SKD11 Steel Curve Profile

The goal of this research is to identify the best set of process machining parameters for wire-EDM(Electrical Discharge Machining)cutting of hardened SKD11 steel when machining a curve profile.The multi-objective function includes reducing surface roughness and increasing MRR(Material Removal Rate).The optimization process is prepared by using Taguchi method coupled Grey Relational Analysis.The obtained results revealed that Toff has the greatest influence on the average grey value(48.30%),followed by the influence of WF(Wire Feed,15.99%),VM(Cutting Voltage,9.33%),SV(Server Voltage,5.05%),Ton(Pulse on Time,1.81%),while SPD(Cutting Speed)has a negligible effect(0.89%).Moreover,using the optimal set of machining parameters generates in surface roughness of 1.25399mm and MRR of 26.5562 mm^(2)/min.The verification experiment and Anderson-Darling method demonstrate the validity of the proposed model,which can be utilized for estimating surface roughness and MRR.

基于胡麻油工作液电火花成形加工可行性研究

传统的电火花工作液煤油或碳氢矿物油等,存在加工效率低、表面质量差且环境污染和资源消耗等问题。而绿色可持续制造也是当今发展的主要趋势。因此文章提出利用植物油胡麻油为工作液在电火花成形加工中的实验研究,旨在实现绿色可持续电火花加工。研究响应参数电流、脉冲宽度和间隙电压对材料去除率,表面粗糙度值,表面质量的影响规律。实验结果表明,胡麻油在电火花加工过程中表现出显著的性能优势。胡麻油为工作液时,材料去除率显著提高,可获得更好的加工表面,表面裂纹明显减少,重铸层厚度更薄。说明胡麻油具有代替传统工作液的潜质,有望进一步促进绿色电火花加工技术的发展和应用。

金属钼圆基片平面研磨及其表面创成机理研究

目的实现金属钼圆基片高效平坦化加工,获得超光滑表面。方法采用游离磨料对钼圆基片进行平面研磨加工,研究磨料种类及研磨盘转速、研磨压力、研磨时间等工艺参数对研磨效果的影响规律,通过材料去除率(MRR)与表面粗糙度(Ra)的建模分析,对比钼材与高硬脆和高塑性材料,揭示其研磨工艺特性、探究其表面创成机理。结果钼圆基片材料去除快慢和表面形貌受各因素作用的综合影响。CeO_(2)磨料适合钼圆基片的研磨加工,材料去除方式为二体、三体摩擦塑性去除;在研磨过程中,MRR随研磨盘转速、研磨压力的递增而先增大后减小,在研磨盘转速为60 r/min、研磨压力为0.026 MPa条件下MRR达到最大;除磨料因素外,其他工艺因素对表面粗糙度的影响较小;MRR和Ra随加工时间的延长而趋于稳定;使用粒径W1 CeO_(2)磨料在研磨盘转速为60 r/min、研磨压力为0.026 MPa下研磨40 min后,表面粗糙度Ra由46 nm降至9.53 nm,MRR达1.16 mg/min。结论采用游离磨料研磨方法在优化工艺条件下可以有效降低表面粗糙度,获得良好表面。

液压抓料机阀控冷却系统设计

针对抓料机液压散热系统能耗高、散热器易积尘及海拔适应性差等问题,提出冷却风扇反转除尘及引入风扇转速修正系数的电液比例控制方案,基于MATLAB/Simulink建模仿真分析,通过试制产品开展可靠性试验。结果表明:采用新型控制策略的液压散热系统,能根据油温实时调节散热风扇转速,液压油温在55~80℃区间的风扇转速响应更快、能耗更低;风扇反转防尘除尘能力明显,节能效果显著,散热器散热能力明显提升,可为类似风扇系统的开发设计提供参考。

基于机器学习的烟叶除杂工序优化设计

传统的烟叶除杂主要依赖人工和机械分拣,导致产生了效率低和精度不足的问题。随着光谱技术和机器学习的发展,特别是深度学习在图像识别中的显著性能提升,文章引入了这些先进技术,以提高除杂工序的自动化水平和准确性。文章采用了卷积神经网络(CNN)与长短期记忆网络(LSTM)的组合模型进行特征提取和分类,从而提升烟叶的利用率和生产效率。该设计为烟草行业及其他工业除杂应用提供了新的可能性。未来的工作将专注于进一步优化数据处理和算法,以适应更广泛的工业场景。

基于YOLOv3的袋式除尘器滤袋破损自动检测方法

干式除尘装置中袋式除尘器的滤袋在长时间使用后会出现破损,造成能源消耗增加、除尘效率降低、污染环境等严重问题。为此,本文采用在除尘舱室处搭建粉尘烟雾检测摄像头,并基于YOLOv3算法检测袋口烟雾的泄漏情况。试验检测步骤:①根据真实除尘舱室尺寸设计袋式除尘器袋口烟雾泄漏实验室平台,采集不同洞口烟雾泄漏的图像数据;②使用软件标注这些图像数据;③搭建Darknet深度学习框架,采用YOLOv3算法对图像数据进行训练,并依据模型计算结果识别破袋情况。结果表明:模型对于批量图像的识别准确率能达到91%以上,对于连续视频的识别准确率可达95.65%。本文系统可以减少除尘器运行中的人工检测,降低工厂人力资源成本和工人劳动强度,可以避免生产中的安全隐患和损失,可以为工厂的生产安全及定期维护提供技术指导,也为全厂智能化生产提供了有效的方案。

材料去除过程中Rehbinder效应的研究进展

精密机械加工过程中,利用Rehbinder效应对工件表面特性的影响,可以更好地控制零件表面质量。不同工程材料的Rehbinder效应的微观表现形式有所差异,但宏观结果都是降低工件表面硬度,使材料去除过程更容易进行。回顾了Rehbinder效应概念的提出和发展过程并对其内涵和应用范围进行了阐述,为加工过程中的材料去除方法提供思路,对材料表面完整性的形成具有指导意义。列举了近年来科研人员对Rehbinder效应的相关研究成果,分析对比其在硬脆材料和塑性材料加工过程中的表现形式和微观作用机理,总结Rehbinder效应的影响因素,如极性分子的吸附活性、工件材料的晶粒尺寸等。揭示了Rehbinder效应中极性分子的吸附作用,以及吸附作用后的扩散、位错和间隙三种促进机制,并综述离散元法、有限元法和分子动力学等数值仿真方法对宏观尺度和微观尺度Rehbinder效应机理的研究。Rehbinder效应可以看作是一种对加工表面的改性机制,研究Rehbinder效应作用下的表面活性剂与被加工表面的匹配机制是提高材料表面完整性的关键,对推动精密制造工艺的发展有重要意义。

小孔内表面磁力研磨加工技术研究进展

磁力研磨加工是提高小孔内表面质量的一种重要光整技术,利用该技术能高效提升小孔类零部件在极端环境下的使役性能。针对小孔内表面的磁力研磨光整加工,按其发展历程对磁力研磨加工技术进行总结,归纳了磁性磨粒研磨、磁针磁力研磨、液体磁性磨具研磨、超声辅助磁力研磨和电解磁力复合研磨等加工方法的技术特点,并分析评述了其局限性。对磁力研磨加工过程中材料去除机理进行了研究,材料主要以微量切削与挤压、塑性变形磨损、腐蚀磨损、电化学磨损等方式去除,材料种类不同,去除机理也不同。其中,硬脆性材料主要以脆性断裂、塑性变形和粉末化的形式去除;塑性材料在经历滑擦阶段、耕犁阶段和材料去除阶段后主要以切屑的形式去除。此外,还对磁力研磨加工过程中的材料去除模型进行了研究,对单颗磁性磨粒材料去除模型和“磁力刷”材料去除模型进行了分析讨论。最后,对磁力研磨加工技术今后的研究发展给出了建议并进行了展望。

微磨料气射流加工技术研究现状与展望

微磨料射流加工技术是一种基于高能流体的磨粒冲蚀磨损加工技术,已广泛应用于难加工材料、复杂三维型面、光滑表面的加工。为进一步提高磨料射流加工过程中的精准控形控性能力,国内外学者开展了诸多基础加工理论与工艺探索等方面的研究工作。本文在概述磨料射流加工技术发展的基础上,全面总结了国内外学者在微磨料气射流加工(MAJM)技术中的微磨料气射流束发散效应及其抑制策略、材料力学性能对材料冲蚀去除模式的影响、材料冲蚀加工过程磨料嵌入抑制策略、微结构冲蚀加工几何特征等方面的主要研究成果,并对微磨料射流加工技术的难点与发展趋势进行了展望。

Optimization of micro milling electrical discharge machining of Inconel 718 by Grey-Taguchi method

The optimization of micro milling electrical discharge machining（EDM） process parameters of Inconel 718 alloy to achieve multiple performance characteristics such as low electrode wear,high material removal rate and low working gap was investigated by the Grey-Taguchi method.The influences of peak current,pulse on-time,pulse off-time and spark gap on electrode wear（EW）,material removal rate（MRR） and working gap（WG） in the micro milling electrical discharge machining of Inconel 718 were analyzed.The experimental results show that the electrode wear decreases from 5.6×10-9 to 5.2×10-9 mm3/min,the material removal rate increases from 0.47×10-8 to 1.68×10-8 mm3/min,and the working gap decreases from 1.27 to 1.19 μm under optimal micro milling electrical discharge machining process parameters.Hence,it is clearly shown that multiple performance characteristics can be improved by using the Grey-Taguchi method.

表面织构电解加工技术研究进展

表面织构在能源、光学、电子、信息技术、生物和摩擦学等领域具有重要应用,其加工工艺是制造技术研究的重要内容。由于所加工表面织构具有无毛刺、翻边等优点,电解加工成为表面织构的重要制造技术方法和技术研究热点,故详细介绍了五种典型表面织构电解加工技术在方法创新、材料去除机制、加工过程建模及加工工艺等方面的研究进展,给出了电解加工表面织构的典型结构和材料,指出提高加工效率和加工自动化程度是未来表面织构电解加工技术的发展趋势。

超声心动图联合膈肌超声对心脏瓣膜置换术机械通气患者撤机结局的预测研究

目的:分析超声心动图联合膈肌超声对心脏瓣膜置换术机械通气患者撤机结局的预测价值。方法:回顾性选择2022年1月至2023年3月宜宾市第一人民医院住院部收治并行心脏瓣膜置换术后机械通气的57例患者,根据撤机结果,拔管前30 min对患者行自主呼吸试验(SBT),将撤机48 h后再次插管或气道切开SBT失败的11例患者纳入撤机失败组;撤机48 h内存活且无需任何呼吸机支持SBT成功的46例患者纳入撤机成功组。所有患者均接受超声心动图联合膈肌超声检查,比较不同撤机结局组间左室射血分数(LVEF)、右室面积变化分数(RVFAC)及二尖瓣瓣环侧壁收缩速度(Sa)等超声心动图指标,以及记录二尖瓣环根部舒张早期峰值(e')计算二尖瓣舒张早期血流速度峰值(E)与e'比值(E/e')及超声心动图指标与膈肌超声指标,行logistic回归分析影响撤机失败因素,绘制受试者工作特征(ROC)曲线,预测超声心动图指标与膈肌超声指标在机械通气撤机失败中的预测价值。结果:撤机成功组LVEF差值、RVFAC差值及Sa差值与撤机失败组比较,差异均无统计学意义(P>0.05);撤机成功组E/e'为10.06±1.30,低于撤机失败组的12.69±2.86,组间比较差异有统计学意义(t=2.084,P<0.05);撤机成功组膈肌增厚率(DTF)和膈肌活动度(DE)值为(41.34±10.74)和(13.04±1.18),均显著高于撤机失败组的(19.67±5.37)和(11.27±0.94),组间比较差异有统计学意义(t=2.148、2.776,P<0.05);logistic回归分析结果显示,DTF、DE低水平表达,E/e'高水平表达均为心脏瓣膜置换术机械通气患者撤机失败的影响因素;DTF、DE及E/e'的ROC曲线结果显示,预测模型最佳临界值为0.0893,ROC曲线下面积(AUC)为0.713(95%CI:0.646~0.758)、0.710(95%CI:0.651~0.779)、0.752(95%CI:0.657~0.805)和0.886(0.782~0.991)。结论:超声心动图联合膈肌超声可较好地预测撤机结局,具有较高的临床应用价值。

横向旋转磁场辅助电火花铣削加工烧结钕铁硼的效果研究

为了更好地解决电火花铣削加工烧结钕铁硼过程中蚀除颗粒排出困难的问题,文章引入横向旋转磁场。通过无磁场加工、横向恒定磁场辅助加工、横向旋转磁场辅助加工的加工效果对比试验,分析加工参数对材料去除率、表面粗糙度和电极损耗率的影响。从正离子的受力角度,分析无磁场、横向恒定磁场辅助、横向旋转磁场辅助电火花铣削烧结钕铁硼方法的材料去除率、电极损耗率和表面粗糙度的差异。结果表明:横向旋转磁场辅助电火花铣削烧结钕铁硼的材料去除率更高,表面粗糙度更好,电极损耗率更低。