Additive Design and Manufacturing of Jet Engine Parts

The additive design (AD) and additive manufacturing (AM) of jet engine parts will revolutionize the traditional aerospace industry. The unique characteristics of AM, such as gradient materials and micro-structures, have opened up a new direction in jet engine design and manufacturing. Engineers have been liberated from many constraints associated with traditional methodologies and technologies. One of the most significant features of the AM process is that it can ensure the consistency of parts because it starts from point(s), continues to line(s) and layer(s), and ends with the competed part. Collaboration between design and manufacturing is the key to success in fields including aerodynamics, thermodynamics, structural integration, heat transfer, material development, and machining. Engineers must change the way they design a part, as they shift from the traditional method of “subtracting material” to the new method of “adding material” in order to manufacture a part. AD is not the same as designing for AM. A new method and new tools are required to assist with this new way of designing and manufacturing. This paper discusses in detail what is required in AD and AM, and how current problems can be solved.     

Energy consumption model of Binder-jetting additive manufacturing processes

Considering the potential for new product design possibilities and the reduction of environmental impacts, Additive Manufacturing (AM) processes are considered to possess significant advantages for automotive, aerospace and medical equipment industries. One of the commercial AM techniques is Binder-jetting (BJ). This technique can be used to process a variety of materials including stainless steel, ceramic, polymer and glass. However, there is very limited research about this AM technology on energy consumption aspect. This paper presents a method to build an energy consumption model for printing stage of BJ process. Mathematical analyses are performed to find out the correlation between the energy consumption and geometry of the manufactured part. Based on the analyses, total energy consumption is calculated as a function of part geometry and printing parameters. Finally, test printing is performed to check the accuracy of the model. This process model provides a tool to optimise part geometry design with respect to energy consumption.     

A novel approach to include sustainability concepts in classical DFMA methodology for sheet metal enclosure devices

Nowadays sustainable design is a mandatory requirement in the product development process. For this reason, design methodologies are addressed to establish a close relationship between environmental, social and economic impact indicators and product features from early design stages, especially in those features related to its manufacturing. In this paper, the design for manufacturing and assembly—DFMA methodology is adapted to sheet metal enclosure devices, integrating functional and component relationships to minimize particular sustainability indicators such as energy consumption, carbon footprint, number of parts, required amount of material, assembly time and manufacturing costs. Savings with the proposed method are achieved following specific sub-tasks oriented to define new simplified product components, considering changes in manufacturing processes and re-defining mechanical connections between parts. Traditional DFMA approaches consider manufacturing and assembly issues related to a reduction of product complexity and economic savings. The proposed method aims to examine the benefits in life cycle stages such as raw material consumption, service, maintenance, upgrading and end of life—EOL. The methodology is validated through a redesign of a sheet metal industrial clock, in which the sustainability impacts are calculated from a comparison of an existent product vs. a new product development. The implementation of the method in the case study demonstrate reductions of more than 25% in product mass, consumed energy and CO₂ footprint, and more than 50% in theoretical assembly time and product complexity. Sustainability indicators of the proposed method are selected from literature analysis and taking into account attributes of sheet metal enclosure devices.     

轴类零件二维工程图的特征识别方法

提出了轴类零件特征识别的方法.首先对特征进行了分类,接着建立了轴类零件的特征树模型,并且给出了实现该特征树模型的类结构;然后确定了主特征、辅助特征的识别原则和特征识别过程中的图形调整方法;最后描述了建立特征树的算法.在AutoCAD 2006环境下,以ObjectARX为开发工具,开发出了特征浏览器,实现了文中提出的原理和方法,以某典型轴类零件图为例进行了特征识别,识别效果良好.     

基于响应面法的楔横轧非对称轴类件轴向平衡研究

楔横轧非对称轴类件时由于存在较大不平衡的轴向力,会产生轴向窜动并导致台阶缺损和表面重皮等质量缺陷.为了减小不平衡的轴向力,目前一般采取的方法是结合工艺参数对楔横轧力能参数的影响规律,利用数值模拟手段,通过多次预设计工艺参数并反复试算以获得能使左右两端轴向力相等或近似相等的最佳工艺参数.该试算方法计算量大、繁琐、不直观,且需逐个零件进行,通用性差.本文通过利用中心组合实验设计并结合响应面法获得轴向力的响应曲面图,利用轴向力等值线选取工艺参数以保证非对称轴类件楔横轧的轴向平衡,本方法简单、直观,极大地节省了工艺参数选择所需时间,缩短了非对称轴类件楔横轧的模具设计周期.     

基于制造特征的火炮零件工艺决策技术研究

为简化结构复杂的火炮零件工艺设计流程,有效地提高工艺设计效率和可靠性,提出了一种基于制造特征的火炮零件工艺加工决策方法.采用参数化建模方法建立火炮零件模型,运用遗传算法对火炮零件工艺决策逻辑机制进行推理,并对制造特征进行识别与提取,从而快速确定火炮零件的工艺决策.以火炮炮尾为例进行了验证,结果表明,火炮零件模型可快速生成零件工艺流程,为火炮零件的加工制造提供条件.     

Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.     

基于瞬时频率估计阶比法的电机振动信号分析

电机转轴是电机中至关重要的精密零部件,运用信号分析的方法,可对电机转轴进行预估评价。为提高电机转轴的安全性,降低事故率,利用瞬时频率估计法与阶比法计算分析电机的振动信号,并进行电机实际缺陷情况下的验证试验。结果表明,基于瞬时频率估计阶比法能对信号进行有效降噪处理,准确地预测故障缺陷的具体位置。     

System for early cost estimation of die-cast parts

Early cost estimate of a part is important information and forms a basis for preparing quotations, which are competitive from a market point of view. It is seen that a commonly adopted approach of variant cost estimation based only on geometric information of the component is not always accurate. This is also true in the case of die-cast parts. The geometric complexity of the part, tooling complexity, part and tool material, processing cost, and manufacturing resources for producing the part all need to be considered for accurate cost estimation. This paper deals with a comprehensive system developed to estimate and analyze the manufacturing cost of die-cast parts. A computer-aided cost-estimation system has been developed that applies manufacturing process as well as manufacturing resource considerations in addition to part feature complexity. Use of the proposed system is demonstrated in selecting the optimum number of cavities and the appropriate manufacturing resources under machine-related constraints. Further, the cost-estimation system developed herein is used for carrying out feature sensitivity analysis to identify design features that add significant cost to the part. The use of this system for optimal machine loading in multiple parts situation is also demonstrated.     

Integration and application of feature recognition and mould manufacturing planning navigating process

Plastic injection mould manufacturing is diverse and complex. Traditional mould manufacturing planning often relied on experience and techniques. Therefore, in order not to affect the operation or even cause some loss of the enterprises, geometry information of computer-aided design (CAD) should be converted into manufacturing information of computer-aided process planning (CAPP) and CAM for automatic feature recognition to shorten the lead time. This study is the secondary development in a CAD environment creating a network plastic injection mould manufacturing navigating system and CAD/CAPP for integration and application. As part design is feature-based, each processing step can be regarded as a feature. By applying the hybrid recognition technology of the graph-based approach, the rule-based approach and hint-based approach in the analysis of part feature appearances, it can automatically categorise all the manufacturing features of the part and convert them into corresponding processes. The CAPP developed in this study can convert the part manufacturing features into corresponding processes and plan the part process sequence according to the process priority constraint relations. As proved by the case studies, the use of CAPP in this study can reduce planning time by 87%. It can provide users with a reference regarding process sequence, and speed up the part planning progress. Coupled with the mould manufacturing navigating process, it can achieve automatic design and manufacturing.     

并行特征转换

针对设计和制造在特征信息处理中的相似和不同点,指出面向产品零件的并行集成ＣＡＤ／ＣＡＭ不是通过一个模型来实现的,而是借助于功能超结构的全局性,建立了设计与制造特征模型间的有效通讯．     

Methods for the capture of manufacture best practice in product lifecycle management

The capture of manufacturing best practice knowledge in product lifecycle management systems has significant potential to improve the quality of design decisions and minimise manufacturing problems during new product development. However, providing a reusable source of manufacturing best practice is difficult due to the complexity of the viewpoint relationships between products and the manufacturing processes and resources used to produce them. This paper discusses how best to organise manufacturing best practice knowledge, the relationships between elements of this knowledge plus their relationship to product information. The paper also explores the application of UML-2 as a system design tool which can model these relationships and hence support the reuse of system design models over time. The paper identifies a set of part family and feature libraries and, most significantly, the relationships between them, as a means of capturing best practice manufacturing knowledge and illustrates how these can be linked to manufacturing resource models and product information. Design for manufacture and machining best practice views are used in the paper to illustrate the concepts developed. An experimental knowledge based system has been developed and results generated using a power transmission shaft example.     

Deterministic design of binary phase-only blazed grating with subwavelength features under limitation on spatial resolution of fabrication technique

We propose a deterministic design method of a blazed grating consisting of a binary grating with subwavelength structures for a multilevel phase modulation. The feasible shapes of binary subwavelength microstructures are restricted to a few kinds of surface profiles by constraints in an actual fabrication technique. The relationship between the feasible shapes of binary subwavelength microstructures and their phase modulations can be calculated by an electromagnetic analysis and tabulated. Using the relationship, a deterministic design of a binary grating with subwavelength structures is simply realized. We have designed the binary blazed grating with subwavelength structures and investigated its performance. Its diffraction efficiency is in good agreement with that by a conventional statistical design method.     

Variant design for mechanical parts based on extensible logic theory

A new variant design method of mechanical part is proposed based on extensible logic theory, to support design knowledge reuse more efficiently in computer aided conceptual design. In this method, matter-element, event-element and relation-element are used to characterize the feature information, connection constraint relations and topology variant operations of mechanical conceptual structures respectively. Extensible composite-element model of product part is established sequentially based on the above three basic-element models (matter-element, event-element and relation-element). Moreover, five types of variant operations are defined in order to realize structure variations and shape design of mechanical parts. Finally, an example of shaft housing part in grinder component is taken to explain the part variant design process in details, in which the efficiency and effectiveness of this method are illustrated simultaneously.     

基于多触点定位和状态校验的虚拟装配技术

目的提供一种具有通用性的虚拟装配零部件设计方法,能够实现多位置、多旋转状态判定的装配方式与灵活的装配序列规划。方法首先使用多个定位触点进行碰撞检测来确定零件的位置和旋转状态,然后使用二进制整数作为零件状态码表达零件间的装配依赖关系,最后通过二进制运算表达式的校验算法限制零件状态码的取值决定零件是否可以装配,从而达到装配序列的约束规划。结果在装配方式上使得所有零件具有通用的设计方案,针对特殊零件只需要设置特殊定位触点,在装配序列规划上实现了多种灵活的装配顺序设计,装配逻辑关系表达更加清晰。结论通过多触点定位和状态校验可以实现具有很好通用性和扩展性的虚拟装配技术。     

Energy and material flow modelling of additive manufacturing processes

Additive manufacturing (AM) processes allow fabrication of three-dimensional complex parts. Due to the exact amount of material used during the manufacturing step, these new manufacturing processes offer great opportunities for sustainable manufacturing. However, existing studies on these processes focus mainly on energy consumption and information about resources consumptions and waste flows are still lacking. This study aims to quantify with accuracy inventory data of AM processes during the manufacturing step of the life cycle of products. In order to accurately assess the environmental impact of a product, a generic method for acquisitions and characterisation of inventory data for parts made by AM processes is proposed. This methodology focuses not only on the electrical energy consumption but also on material consumption. This paper also describes the development of a parametric process model, which provides to an operator, an accurate estimation of the environmental performances of the fused deposition modelling process.     

一种零件综合质量评定方法研究

零件的质量评定是柔性智能制造中十分重要的环节。现有的自动化识别装置一般采用非人工接触的光学检测系统,但由于工况环境复杂,诸多干扰因素均会影响零件质量检测与评定的准确性。另外,工业现场的连续作业对工控机硬件的运行速度、光学检测系统的环境适应性以及质量评定算法的预测准确性都提出了更高的要求。基于此,提出一种基于机器视觉与机器学习的零件综合质量评定方法。首先,借助机器视觉技术完成被测零件图像的实时采集与处理,并利用灰度匹配算法与几何匹配算法对零件的图像与CAD（computer aided design,计算机辅助设计）机械加工图进行比较,求解得到灰度匹配分数与几何匹配分数这2个几何特征参数。然后,针对零件表面的缺陷（如划伤、磨损、边缘缺料及锈蚀等）,在图像预处理（灰度化、图像增强、高斯降噪和二值化）的基础上,求解得到图像灰度的均值和标准差这2个表面缺陷特征参数。最后,借助主成分分析（principal component analysis, PCA）对零件的四维特征数据集进行降维处理,并利用K最近邻（K-nearest neighbor, KNN）算法对降维后的数据集进行训练和预测,完成零件综合质量评定;在此基础上,比较KNN算法与其他机器学习算法的准确率、召回率和特异度等指标,以验证其可行性。实验结果表明,所搭建的光学检测与处理系统在不同光源条件下的识别准确率达到96.15%以上;当相机的快门时间设定为100 μs时,该系统的图像处理速度达到45.2 帧/s。所提出的零件综合质量评定方法具有较高的准确率与处理速度,适用于复杂工况下零件的综合质量评定。     

飞机铝合金深锥型面零件多道次充液拉深技术

目的随着新一代飞机在隐身和战斗性能方面的提高,飞机钣金零件的复杂程度和制造精度要求也越来越高。对于深型腔复杂型面零件,充液拉深是一种有效的精密制造方法。方法针对难成形、复杂型面的某型飞机铝合金深锥零件,利用理论分析、有限元模拟和工艺试验相结合的方法,设计了多道次充液拉深技术方案,并建立有限元分析模型。基于等裕量函数法和零件锥面特征,分配并优化了不同道次的材料变形量。结果对多道次充液拉深成形过程中出现的起皱和破裂的失效形式进行了研究,分析了预成形高度,液室压力和压边力等关键工艺参数对零件成形质量的影响,获得了优化的预成形高度和液室压力加载轨迹。结论结果表明,提出的多道次充液成形技术能够实现复杂型面,大拉深比的铝合金零件的整体精确成形,采用优化的工艺参数能够成形出壁厚均匀,表面质量好,锥面精度高的零件。     

An energy flow analysis in a paper-based industry

Industrial sector is the largest user of energy in India and many parts of the world. More than half of the total energy is used in industries to operate various energy-using machineries. Energy conservation is a cost-effective approach in any energy optimization program that can be implemented in industrial activities. Energy-intensive industries in developing economies offer significant energy-saving potential owing to the technology gap as well as lower operating efficiency. A detailed energy flow analysis was conducted in a paper carton manufacturing unit in India to quantify the energy-saving potential. The study revealed that the compressed air leakage is responsible for about 50% of the total energy loss. The specific electrical and thermal energy consumption was estimated and found to be 91.85?kWh/ton and 1,619?MJ/ton of biomass, respectively. Annual energy saving potential was found to be 5.9% of the total annual energy consumption. The cost of DG power is found to be 389% higher than the grid power. The share of self-generated DG power is estimated to be 41% of the total power consumed. Electrical energy intensity of the plant could be reduced by 6.36% implementing energy conservation measures proposed in this study.     

On-line strategic control of liquid composite mould filling process

Liquid composite moulding (LCM) processes are used to manufacture high quality and complex-shaped fibre reinforced polymeric composite parts in the aerospace, automotive, marine and civil industries. A thermoset resin is injected into a mould cavity filled with a reinforcing fibrous preform. The composite part is demoulded after the filling is completed and resin has cured. During prototype development, the design engineers may combine their manufacturing experience with simulations to decide which LCM process must be used for the selected part. For complicated mould shapes, the manufacturing engineer has to make decisions about injection pressure, flow rate, location of gates and vents, etc. to achieve a high-quality composite part which is free of dry spots. Inherent variability in the process and the possible errors in characterization of material properties, such as fibre volume fraction and permeability, challenge the manufacturing engineer to reduce the number of unacceptable parts. An on-line strategic controller with in situ sensor data can influence the flow front pattern during mould filling and drive the process towards successful completion. Some of these variabilities are considered in off-line mould filling simulations. By analysing the simulation results, the sensors are placed inside the mould to identify the variabilities and take corrective action(s) to eliminate voids. Sensor data and the control actions are cast in the form of a decision tree. Data acquisition software collects the in situ sensor data and implements the control actions from this decision tree. A case study was included in which various race-tracking and bulk permeability variations can be expected during manufacturing. The proposed controller is described in detail for this selected case study and its usefulness is verified with experiments.