基于自适应蚁群算法的工艺路线优化

针对计算机辅助工艺设计中最优方案选择,提出一种以制造资源更换率最低为目标的自适应蚁群优化方法(Adaptive ant colony algorithm,AACA)。通过分析零件特征,根据精度要求对制造特征进行分解,提出加工元概念。加工元被定义为特定的制造特征、加工阶段、加工方法、制造资源、装夹位置的集合,工艺路线的确定被转换为对加工元的优化顺序安排问题。以制造特征之间的几何位置约束,各加工阶段的先后顺序约束为基本元素,构造加工元优选约束矩阵,给出基于优选约束矩阵的加工元优选原则。在加工元优先顺序约束和可用制造资源的共同约束下,将缩短加工周期、提高加工质量和降低加工成本的综合目标表达为制造资源更换率最低,进行优化目标函数的数学建模。指出加工元优化排序可类比旅行商问题,并选择AACA进行优化求解。实例分析表明提出的方法可以可靠和有效地得到符合生产实际的工艺路线。     

Generating Alternative Interpretations of Machining Features

One of the major difficulties in extracting machining features is the lack of a systematic methodology to generate alternative ways of manufacturing a machined part. Most of the early research in feature extraction and process planning has not considered this aspect, and has focused on the generation of a single interpretation. In this paper, we propose a feature-based approach to generating alternative interpretations of machining features from a feature-based design model. The proposed approach simplifies the generation of alternative machining feature models by using information on feature which is captured and maintained during feature-based model-ling and machining feature extraction. A set of machining features is incrementally extracted during the feature-based design process of a machined part. A feature conversion process converts each design feature into a machining feature or a set of machining features by using information on the geometry and the feature. Using reorientation, reduction, and/or splitting operations, alternative models are generated from the sets of extracted machining features. During the execution of each operation, unpromising models are pruned by using criteria such as minimising the number of accessibility directions. The machining features and their precedence relationships are represented in a STEP-based machining feature graph for the purpose of data exchange.     

Energy-efficient machining systems: a critical review

Sustainable machining as a critical part in sustainable manufacturing has been valued by manufacturing enterprises of all sizes. The traditional short-term financial considerations are substituted by longer-term sustainable strategies to ensure the competitiveness, and ultimately, the survival of the company. Energy-efficient machining system, which promotes sustainable machining, is the focus of this paper. The energy-efficient machining system requires a comprehensive understanding as well as optimisation of energy consumption. Literature in this field is carefully reviewed and summarised. Energy consumption models, which are regarded as the core of the energy-efficient machining systems, are grouped into four categories, i.e. theoretical, empirical, discrete event-based, and hybrid models. Then, energy optimisation methodologies and strategies are discussed for energy-efficient process planning and production scheduling. The applications such as tool condition monitoring can employ energy information as useful input. Research inspired by energy-efficient machining studies is briefly introduced. The main elements of an individual energy-efficient machining system are then summarised. Discussions, research suggestions, and future directions are given at the end.     

Retrieval of machining information from feature patterns using artificial neural networks

The integration of design and manufacturing has been the subject of much debate and discussion over a long period of time. Recognition of feature patterns and the retrieval of necessary machining information from those patterns play vital roles in this process of integration, as they facilitate the selection of the necessary manufacturing parameters required to transform the designed product into a final physical entity. Although the problem of recognising features from a solid model has been exclusively studied, most existing product models are expressed as engineering drawings. Moreover, the solid model can only provide complete 3D topological and geometrical data and some of the essential machining information cannot be retrieved. In this paper, an approach for defining engineering features, like slots, steps and circular pockets is proposed using binary strings. Two artificial neural networks, one for slots and steps and the other for circular pockets, are designed and developed. These neural networks take the binary strings as inputs and give the relevant machining information as outputs. The networks are trained with non-interacting features and after training, those will become capable of providing the necessary machining information for both non-interacting and interacting features in the domains of slots, steps and circular pockets. This novel approach can further be extended to other features for retrieving relevant machining information and thus facilitating the effective integration of design and manufacturing.     

复杂零件三维机加工艺网络化发布方法研究

针对三维机加工艺在制造端轻量化的需求,文中研究了一种复杂零件三维机加工艺网络化发布方法。首先,以工序特征模型作为信息载体代替二维工序图纸。针对机加工艺模型的多工序的加工特性,给出了多工序模型的输出方式,并采用中间转换法对工序模型进行轻量化处理以满足Web端可视化需求,让工艺制造端显示更加直观可靠。其次,为了更好地体现复杂零件的加工面,分析了机加工艺工序模型加工特征轮廓的提取应用方法,包含边界曲线的格式定义以及网络显示方式。最后通过实例验证了文中所述机加工艺模型发布方法的可行性和有效性。     

Tolerance chart balancing with a complete inspection plan taking account of manufacturing and quality costs

This paper introduces a mathematical model of tolerance chart balancing for machining process planning under complete inspection. The criteria considered in this study are based on the combined effects of manufacturing cost and quality loss, under constraints such as process capability limits, product design specifications, and product quality requirements. Manufacturing costs include the machining cost, part cost, inspection cost, reworking cost, and replacement cost. The machining cost is expressed in geometrical decreasing functions, which represent tolerances to be assigned. Process variability is expressed in quadratic loss functions, which represent the deviation between the part measurement and the target value. An example is presented to demonstrate the proposed model. A comparison made with previous methods shows that the proposed model minimizes the total cost of manufacturing activities and quality-related issues in machining process planning, particularly in the early stages. Moreover, the applications are not be limited to machining process planning but can also be used in other forms of production planning.     

一种基于加工特征的数控工艺设计方法

将数控工艺的设计分成了两大模块,即加工特征级的智能工艺决策过程和加工方法级的派生式数控代码生成。对加工特征进行数控加工工步设计时,辅以加工特征数控工艺决策知识库、机床特征映射库和刀具特征映射库的智能支持,提高了工艺决策的准确性和智能化水平。同时以加工特征为单元,采用参数化编程技术实现数控程序的派生式生成,提高了数控程序设计效率和质量,并有利于数控程序设计的自动化、智能化、模块化。     

Integrated manufacturing process planning and control based on intelligent agents and multi-dimension features

Dynamic manufacturing environments require a flexible process planning and control system in response to changing manufacturing resource availability, production uncertainty, and dynamic machining conditions. To address these issues, this paper proposes a novel integrated process planning and control method based on intelligent software agents and multi-dimension manufacturing features. An integration framework with three modules including generic process planning, shop floor process planning, and online process control is developed. An intelligent agent-based approach is adopted for achieving intelligence and autonomy of individual software modules and components. An ontology-based multi-dimension manufacturing feature model is proposed to facilitate the communication and collaboration between process planning and control, as well as to speed up the decision-making of intelligent agents. The feasibility and flexibility of the proposed method are validated through a proof-of-concept implementation.     

基于特征的制造工艺资源建模与检索方法研究

为表达制造工艺资源特征层次结构、分类结构及资源对象关系,采用面向对象与特征建模技术构建了制造工艺资源特征模型,用特征映射技术描述零件结构特征与加工特征、加工特征与加工方法特征、加工方法与制造工艺资源特征的映射关系和模糊决策方法。研究了用工序特征描述工艺设计过程所对应的资源特征的集,并以形式化表示,提出了从制造工艺资源数据库中检索工序资源特征,以特征参数的相似性计算来检索与工序匹配的资源特征的检索算法。最后,将该方法应用于工艺设计中制造工艺资源特征与工序特征的匹配。     

Representation and similarity assessment in case-based process planning and die design for manufacturing automotive panels

This work improves process planning and die design in automotive panel manufacturing using a novel case-based reasoning (CBR) methodology. An innovative indexing representation and retrieval approach are also addressed. The flat-bend graph, which is utilized to represent a panel model with a B-rep structure, retains geometric and topological data in the Standard for the Exchange of Product model data format. Flat-type faces collected into several groups are represented by graph nodes, and bend-type faces are represented by graph arcs. Based on the topological information between bend-type faces and flat-type faces, a graph is constructed. Additionally, the holes detected are considered another graph node types. Geometric information and stamping parameters are utilized as graph attributes. To retrieve an appropriate case for a potentially huge search space, independent maximal cliques detection is applied. All independent maximal cliques that represent the maximum number of features shared by models are identified. Based on the retrieval result, previous process plans and die sets can be acquired for use by new cases. Experimental results obtained using the CBR system integrated with the product data management system demonstrate the practicality of reusing previous designs to accelerate stamping process planning and die design.     

基于特征匹配检索与区间数优势度多属性排序方法的工艺规划研究

为满足现代制造企业产品品种多样性、制造过程离散性、生产环境复杂性要求,提出将工艺规划分为两个阶段,第一阶段采用特征匹配的实例检索制定出加工零件所需的各种数据及多条加工路线;第二阶段采用基于区间数优势度多属性排序方法选择最优的加工路线,实现设备能力导航及加工时间与成本最低。最后,用实例验证了该方法的可行性。     

Research into integrated design and manufacturing based on STEP

This paper discusses a typical STEP-compliant manufacturing environment, which effectively integrates two systems. The first generates native data that retain the information needed to machine a part on a particular machine tool, whereas the second carries out optimization for machining parameters using the dispatched information from the first system. The related research work is divided into four areas, feature generation, macro process planning, micro process planning, and machining execution. The main part of the paper is devoted to reviewing the most recent research publications. The publications have been organized into the four areas as mentioned above. The discussion section that follows looks at the STEP-compliant research from the perspectives of industrial adoption, feature recognition for process planning, challenges in STEP-enabled inspection and STEP-NC controllers.     

基于PDM的工艺分工规划系统

为了在企业广泛应用PDM系统条件下,快速构建工艺分工规划系统,提出了一种基于PDM系统的工艺分工规划设计与管理解决办法。在引入物理制造单元、逻辑制造单元、逻辑加工路线和可执行加工路线等概念基础上,介绍了系统的总体框架和工作流程,分析了产品零组件信息模型建立、系统数据组织和基于知识的逻辑加工路线设计等关键技术。通过依据论文提出方法实现的应用系统的介绍,说明通过该方法可以有效解决通过集成方式的工艺分工规划解决办法所引起的数据冗余、一致性差、信息共享度低、效率低下等问题。     

基于图像深度学习的零件加工特征信息提取方法

针对各类基于模型定义(MBD)的零件模型加工特征的信息集成问题,提出一种多层次提取架构的加工特征全息信息提取方法.通过对零件的结构特点进行分析,以具有制造语义且无法拆分的最简化特征实现加工特征的分类;在阐述提取策略的基础上,构建了基于深度学习图像识别技术的加工特征分类器;依据MBD模型信息标注的特点快速定位、抽取加工特...     

Planning and Sequencing Heuristics for Feature-Based Control of Holonic Machining Equipment

The intelligent manufacturing system program was proposed by Japan in 1989. Five participating regions—Australia, Canada, the European Community, Japan, and the United States—currently are involved in developing 21st century manufacturing technology through an investment of US $1.2 billion over 10 years. Korea joined the program and will start work on one of the six ongoing projects, holonic manufacturing systems (HMSs). The objective of the paper is to develop the control architecture of the holonic machining unit (HMU) for construction of the HMSs and to present some planning and sequencing heuristics for feature-based control of the HMU. Further, the paper provides the HMU's functionality using the IDEF0 function modeling method. The basic operation of the decision maker among the HMU's functions is to determine an efficient feature sequence in real time from the nonlinear feature graph used to represent a process plan. To this end, two methodologies are applied sequentially to managing a nonlinear process plan: removal of the OR nodes and then grouping and sequencing the features in the feature graph. Markov chain theory is used to compute the path preference indicator for removing the OR nodes, that is, for selecting the best path among those surrounded by OR nodes. The resulting graph is the AND graph, from which the feature type nodes are formed into sequenced groups. The CNC codes associated with the features in each group are combined and downloaded to the CNC machine. The development of the methodologies can help manufacturers efficiently cope with unexpected failures encountered during computer-automated machining.     

Neutral representation of tolerance information for process planning using STEP AP 224

The focus of CIM is on information as it is the crucial element for integrating all the manufacturing activities. CAPP, as one of the key elements in CIM, needs to extract the manufacturing information such as machining features and precision specifications like surface roughness and tolerances from a geometric model in order to link CAD and CAM. However, these data are not real attributes of the geometric model in most of the current CAD systems. Therefore, human interpretation is inevitable for further processing of CAD model for downstream application like process planning or inspection. This paper proposes a scheme to represent the manufacturing information in a neutral format using STEP technology in order to enable downstream users such as process planner and inspection planner to make correct decisions on process selection, processing conditions, etc. It is shown that by using STEP AP224 manufacturing information encompassing machining features, surface roughness, dimensional and geometric tolerances can be completely represented together with part geometry, which certainly contributes to successful implementation of CIM.     

基于几何与公差信息的加工特征识别方法

为实现计算机辅助设计与计算机辅助工艺规划系统的有效集成,提出了一种同时利用几何信息和公差信息的加工特征识别新方法。建立了加工资源、加工表面和加工方法三类信息模型。提出了切削模式的概念及以之为基础的表面加工方法生成原理和过程。建立了表面加工方法优化选择模型。采用多目标模糊优化结合蚁群算法求解该模型,为每个加工表面选择最优加工方法,并将在同次装夹中采用同一刀具类型和加工条件进行加工的表面聚为加工特征。最后,通过实例测试,验证了该方法的正确性和有效性。     

Extraction of manufacturing information from design-by-feature solid model through feature recognition

Feature recognition is the key to the computer-aided design (CAD) and computer-aided manufacturing (CAM) integration to build a computer-integrated manufacturing system. There are two approaches to CAD feature recognition: platform-dependent and platform-independent. In the platform-independent approach, the part’s geometrical data are extracted from a neutral file such as DXF, IGES, or STEP. In contrast, the platform-dependent approach extracts the information of the design features directly from a design-by-feature solid model through the object-oriented model of a part. This paper explains a platform-dependent approach which is implemented to translate design features into manufacturing information. This approach begins with simplification using the suppression of fillets, and clustering non-intersecting design features is done. Then, the rule-based method is employed in order to recognize machining features. Finally, the needed manufacturing information such as tool accessing direction, dimensions, material removal regions, and geometrical and topological data is recognized. The application of the proposed system would be exhibited in generating machine path code for rapid prototyping and CNC machines and providing a database for computer-aided process planning. The proposed system was implemented on Autodesk Inventor and successfully tested for many complex 3D models.     

A STEP AP 203–214-based machinable volume identifier for identifying the finish-cut machinable volumes from rough-machined parts

This paper presents a STEP AP203–214-based machinable volume identifier (MVI) to identify the finish-cut machinable volume in prismatic parts by deducting the rough-machined part from the final part. The MVI provides an intermediate link between rough and finish machining computer-aided process planning system for automatic generation of process plans while machining prismatic parts. To calculate the machinable volumes of manufacturing features, the MVI utilizes the output of the feature identifier which contains the information about the dimensional details, edge loops, edges, vertices, coordinate points, and location planes of the features. In this research, a total of 234 features have been considered; out of which, 32 are normal and 202 are tapered. To calculate the machinable volumes for these features, generalized methodologies are developed for 17 basic feature types, each having a varying number of specific features. Initially, the pattern strings are generated for the front and back face of the rough-machined feature and final feature. Then, MVI uses the predefined syntactic pattern strings stored in the strings database and checks with the generated strings of the feature to determine the shape of the machinable volume stored in the volumes database. After determining the shape, one relevant methodology or more (for features having combination of more than one taper) are selected from among the 17 “feature type” specific methodologies developed for finish-cut machinable volume identification. In this article, methodology is presented for one basic feature type which covers 14 features and explained through one case study. The final output from this module is stored as a text file with full dimensional details of machinable volumes for later use inside the machining planning module. The proposed MVI can be used in Computer Integrated Manufacturing Industries as an intermediate linker to achieve a robust manufacturing environment.     

基于制造资源能力的装夹工艺分层设计技术

为发展创成式的计算机辅助工艺设计,研究了计算机辅助工艺设计系统中工件装夹规划的自动生成算法.基于扩展有向图,建立了零件的公差信息和基准-加工特征关系的数学表示模型,基于公差分析和制造资源能力模型,建立了从单件层到多件层的工件装夹工艺生产算法.该数学模型和算法可自动识别工件的加工特征、装夹基准,并根据制造资源能力和公差分析对装夹进行优化分组,实现装夹分组对工件加工精度的影响最小化,进而生成装夹规程.最后以实例证明了该方法的可行性.