Recognition of machining features for cast then machined parts

Mechanical parts are typically manufactured using multiple manufacturing processes. Primary processes such as casting realize the primary shape of the part, while secondary processes such as machining generate more detailed shape of the part. This paper presents a feature recognition method to support machining process planning for cast-then-machined parts. From the part model including the specification of machined faces, we generate the starting workpiece for machining, which represents the casting output in sufficient detail to support machining process planning. The starting workpiece is generated by identifying faces to be made by casting followed by machining, then offsetting the part through these faces by a uniform machining thickness to obtain cast faces, and combining the halfspaces induced by machined faces and the halfspaces induced by their bounding cast faces to enclose removal volumes. Machining features are then recognized from the removal volumes using a volume decomposition method called Alternating Sum of Volumes with Partitioning.     

Concurrent evaluation of machinability during product design

An approach to evaluating the machinability of a part during the design stage, which performs systematic generation and evaluation of machining alternatives, is discussed. The results of the analysis provide feedback to the designer about problems that might arise with the machining and information to the manufacturing engineer about which machining processes and process parameters are most desirable     

Geometric reasoning for mill-turn machining process planning

An integrated system to support both product and manufacturing process design should be such that (1) the part design can be evaluated and redesigned based on manufacturability analysis and (2) the manufacturing processes can be selected efficiently and flexibly exploiting product information provided by part design representations.

In this paper, we describe the feature-based geometric reasoning system for part modeling and process planning as applied to mill-turn machined parts. The feature recognition system based on convex decomposition and the mapping method to relate the negative feature volumes to machining process classes are applied to mill-turn parts. Also, the geometry-based machining precedence relations have been generated for various alternative machining feature decompositions. The above geometric information is input to mill-turn machining process planning to determine machining process sequences and assignment to multiple spindles and turrets.     

High speed pocket milling planning by feature-based machining area partitioning

Pocket milling operations are involved in two and a half-dimensional (2.5D) machining. The machining area of a pocket has to be divided into several sub machining regions (SMRs) to effectively select the machining parameters for ordinary or high speed milling. A SMR of a pocket has its own characteristic geometry, which implicitly provides machining features used for the generation of strategies for high speed machining. This paper presents a methodology to partition a pocket machining area, as well as to identify machining features used for planning of high speed pocket machining. To generate the machining strategy, the attributes of machining features are defined, and evaluated through a machining volume slicing method. SMR-based partitioning rules are developed based on the geometric features of a pocket. The proposed partitioning algorithm is applied to both simple and complex shaped pockets. A case pocket volume is divided into several SMRs, represented by a tree structure containing associated information for pocket milling planning.     

特征的自动识别规则与提取

在对箱体类零件的加工特征及特征参数进行了分析,归纳和总结,在特征实体造型进行了研究的基础上,制定了各类特征的合理的识别规则和 识别算法,及提取的信息模型,实现了对复杂箱体类零件的加要特征信息自动提取,及CAD／CAPP系统的信息自动传递。     

A research on the cutting database system based on machining features and TOPSIS

Cutting parameters play a significant role in machining processes. The traditional cutting database usually neither include all information about part machining nor provide the best alternative of cutting parameters automatically when several alternatives meet the requirements for retrieval. The paper presents a cutting database system based on machining features and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for selecting the best alternative of cutting parameters. Following the object-oriented idea, machining features are organized by part feature, geometric information, material information, precision information and manufacturing resources information, which is very convenient for the database to store and manage the necessary machining information. The multiple criteria decision making matrix D is constructed by spindle speed, feed rate, cutting depth and cutting width. And the best alternative of cutting parameters is selected according to the closeness coefficient by TOPSIS. In addition, a prototype system based on Web browsing mode has been developed. Finally, an example is used to validate that the proposed system is feasible and effective.     

Machining feature-based similarity assessment algorithms for prismatic machined parts

This paper presents algorithms for identifying machined parts in a database that are similar to a given query part based on machining features. In this paper we only consider parts that are machined on 3-axis machining centers. We utilize reduced feature vectors consisting of machining feature access directions, feature types, feature volumes, feature dimensional tolerances and feature group cardinality as a basis for assessing shape similarity. We have defined a distance function between two sets of reduced feature vectors to assess the similarity between them from the machining effort point of view. To assess the similarity between the two parts, one set of reduced feature vectors is transformed in space using rigid body transformations with respect to the other set such that the distance between them is minimized. The distance between the two sets of aligned reduced feature vectors is used as a measure of similarity between the two parts. The existing machined parts are rank ordered based on the value of the distance with respect to the query part. The cost of previously machined parts that have a very small distance from the query part can be used as a basis for estimating the cost of machining the new part.     

Digital-twin-driven geometric optimization of centrifugal impeller with free-form blades for five-axis flank milling

Centrifugal impeller (CI) manufacturing is moving toward a new paradigm, with the objective to improve efficiency and competitiveness through Industry 4.0 and smart manufacturing. Making a CI developable and ruled has become a crucial technology to obviously improve machining efficiency and save costs although it may bring negative effects on aerodynamic performance accordingly. Hence, it is extremely challenging to consider and balance both machinability and aerodynamic performance in the process of CI geometric optimization. Digital Twin (DT) provides an attractive option for the integrated design and manufacturing due to multi-dimension and real-time. This paper breaks traditional procedures and presents a DT-based optimization strategy on the consideration of both machining efficiency and aerodynamic performance, as well as builds a reified 5-dimensional DT model. The virtual model consists of three sub-functional modules, including geometric modeling, machining optimization and aerodynamic performance evaluation. A tool-path generation method for CI five-axis flank milling is proposed to improve machining efficiency. The negative influences on aerodynamic performance and internal flow field are simulated and analyzed. Reinforce Learning is introduced to determine the optimization decision-making. Machining experiment and performance test with respect to various CI workpieces are conducted to provide immediate feedback to DT model. Real world and virtual world are combined to make CI geometry dynamically updated and iteratively optimized, which is desirable and significative to effectively shorten cycles and save costs in CI development.     

CAD/CAPP集成的关键技术

该文提出了基于特征实体模型上的截面轮廓造型自动特征识别方法。这种方法探索了一条实现自动特征识别的新途径。还提出了基于特征名、形面名的多层次多方位的零件信息描述方法。实现了对复杂箱体类零件的加工特征自动识别与信息自动提取,从而实现了CAD/CAPP系统的信息自动传递。     

并行工程下基于特征的零件可制造性及其评价方法研究*

结合并行工程的思想,对零件可制造性进行较详细的分析,提出并行工程环境下基于特征的可制造性分析方法,研究建立基于特征的可制造性零件定义模型及评价体系。阐述了基于特征的可制造性的评价方法,认为可制造性评价是一个多层次的决策问题,建立了基于制造约束规则的加工可行性定性评价和基于模糊综合评判的加工可行性定量评价两种评价方法,并给出了解法。利用上述研究方法,全面合理地对零件的可制造性进行评价和反馈,从而指导产品设计。最后以涡轮叶片榫头特征的可制造性分析为应用实例,说明了该方法的有效性和实用性。     

Inspection of the machined surfaces using manufacturing data

Accuracy of complex machined parts is usually estimated using coordinate measurement machines. The inspection results can be used to control or monitor a production system. Traditional inspection process of a machined surface commonly compares the resulting manufactured surface with the CAD-model or the nominal designed surface. Although, the result of this CAD-based inspection can be used to accept or reject the machined part, it does not provide the correct information required to study the machining errors and their behaviour. This paper presents a methodology to inspect a machined surface directly based on its actual CAM geometric model. The presented CAM-based inspection methodology can be used to model and understand the real machining errors, which can be utilized for process control, design for manufacturing or closed-loop machining.     

A knowledge base model for complex forging die machining

Recent evolutions on forging process induce more complex shape on forging die. These evolutions, combined with High Speed Machining (HSM) process of forging die lead to important increase in time for machining preparation. In this context, an original approach for generating machining process based on machining knowledge is proposed in this paper. The core of this approach is to decompose a CAD model of complex forging die in geometrical features. Technological data and topological relations are aggregated to a geometrical feature in order to create machining features. Technological data, such as material, surface roughness and form tolerance are defined during forging process and dies design. These data are used to choose cutting tools and machining strategies. Topological relations define relative positions between the surfaces of the die CAD model. After machining features identification cutting tools and machining strategies currently used in HSM of forging die, are associated to them in order to generate machining sequences. A machining process model is proposed to formalize the links between information imbedded in the machining features and the parameters of cutting tools and machining strategies. At last machining sequences are grouped and ordered to generate the complete die machining process. In this paper the identification of geometrical features is detailed. Geometrical features identification is based on machining knowledge formalization which is translated in the generation of maps from STL models. A map based on the contact area between cutting tools and die shape gives basic geometrical features which are connected or not according to the continuity maps. The proposed approach is illustrated by an application on an industrial study case which was accomplished as part of collaboration.     

An integrated form-feature-based design system for manufacturing

Much of the knowledge that is applied in or communicated between design and manufacturing activities is primarily shape based or shape indexed. Previous attempts to acquire and organize shape knowledge have been mostly concentrated on feature recognition from solid models, group technology (GT) coding schemes, and feature-based modeling. This paper presents the development of an efficient form-feature-based modeling system, and addresses the important issue of utilizing feature information for manufacturing, which has not been extensively discussed by previous work. In this paper we first present a Euler operator-based approach for efficient and effective form-feature encoding and manipulation in a feature-based design environment. Subsequently, a hybrid representation scheme called enhanced CSG tree of feature (ECTOF), which integrates feature model with solid model in a tree structure, is discussed. A feature interference resolution methodology to maintain the correct and consistent feature information in an ECTOF is also deliberated. Finally, we present a machinability-checking module, which employs global accessibility criteria to analyze a feature's machinability on a three-axis machining center. By developing feature interference resolving and machinability testing techniques and integrating with an efficient feature-based design system, this research makes the development of an integrated feature-based design and manufacturing system possible.     

Multi-layer integration framework for low carbon design based on design features

Global warming has currently become the most discussed environmental issue. The major portion of the carbon emission for a product is determined at the design stage of its life cycle. Given that products are made of parts, one of the major difficulties is that existing carbon emission assessment methods are machining process-oriented and lack association with design information, which makes it difficult to support low-carbon design. To address this problem, this paper develops a multi-layer integration framework for part low-carbon design based on the association mechanism among five layers, i.e., design feature, machining process, machining feature, operation feature, and carbon emission feature. The carbon emission assessment model of the part could be obtained by the method of top-down expansion and bottom-up assessment in terms of the design features through the developed framework. To obtain a low carbon design scheme, an improved differential evolution algorithm (IDE) with the multi-layer encoding method is proposed based on the hierarchical relationship of the framework, which aims to minimize the potential carbon emissions of parts and makespan of its machining processes. The proposed methodology is verified by the low carbon design of a flange plate.     

A flexible quantitative method for NC machining verification using a space-division based solid model

A geometric-modeling method called Graftree and a system design of an NC (numerical control) machining verifier based on Graftree are proposed. Graftree is constructed by combining Oct-tree and constructive solid geometry (CSG) so as to simulate machining processes precisely in three-dimensional space. Using Graftree, the Boolean operation produces no risk of yielding topological conflicts, which often cause the simulation to stop abnormally. Based on the properties of Graftree, an NC machining verifier is designed to consist of three individual subsystems: data-input operations, geometric simulation, and interactive verification, i.e., visuluatzation of machining scenes and evaluation of the machined product using models of the measuring instruments. This design lets the users watch selectively only the machining steps they want to check precisely, and verify the machining according to dimensional tolerance.     

复杂零件数控加工的仿真与优化研究

复杂零件数控代码繁多,采用人工检测、试切和机床运行的代码检测方法将造成极大的资源浪费。为了减小这方面的浪费及提高复杂零件加工的质量,本文以减速器中的典型零件产品为例,在Vericut里面建立三轴加工环境及方针模型,对数控代码进行仿真。通过仿真,优化了数控代码,精确模拟出实际的加工过程,直观地观察到刀具的轨迹和工艺的可加工性,为复杂零件的高效数控加工提供了借鉴。     

Improving machining accuracy in precision line boring

There is an ever-growing demand for high precision machining to obtain increased accuracy and surface finish, as they are key factors in product quality and performance. Machining operations, in general, are associated with errors of varying magnitude originating from different sources. As a result, the sizes of the machined features usually deviate from their desired, nominal values. Identification of error sources, techniques of measurements (on/off line), and efficient strategies for their compensation are the steps required to minimize, and, in some cases eliminate process errors. This paper focuses on modeling and compensation of geometric errors in machining operations specific to the line boring process. It is part of an undergoing research project focused on design and development of an agile precision line boring station for machining of long bores. After a brief overview of sources of geometric errors and their components, a methodology for their calculation is introduced. In this regard, error equations reflecting the effects of machine tool geometric errors at the tool tip are derived. It is shown that these equations can be further simplified without significantly affecting computational accuracy of the results. This makes the approach more attractive for real-time applications. A set of experimental data obtained from a prototype of the machine is used to study the effectiveness of the proposed approach and the results are reported. The paper concludes with discussions and presentation of different methods and available tools for real time compensation of these errors.     

An application-independent methodology of feature recognition with explicit representation of feature interaction

The existing feature-based design and feature recognition methods cannot fulfil the requirements of automated process planning. It is now recognized that satisfactory modelling of interactions between features is necessary for developing an automated process planning system. The selection of an optimum manufacturing process for a part needs to be considered at the conceptual design phase to incorporate the capabilities and constraints of the process in design. This paper describes a methodology of feature recognition that is independent of manufacturing process and explicitly generates geometric feature interactions in a part. The paper illustrates generation of feature sets for shape-forming processes, and describes a method to convert the process-independent features into machinable volumes and tool paths for material removal processes.     

An accurate and efficient approach to geometric modeling of undeformed chips in five-axis CNC milling

Many important and complex parts, such as aero-engine compressors and automotive punch dies, are often machined in five-axis computer numerically controlled (CNC) milling. To machine the parts with accurate dimensions and shapes and low machining costs it is necessary to construct 3D models of the finished parts in the geometric simulation and in-process workpiece models of the parts in the physical simulation of their five-axis milling. A kernel technique of the geometric and the physical simulations is to accurately and efficiently model the geometry of the workpiece material removed at every moment of the machining, which is the instantaneous, undeformed chip geometry. Although in the past decades much research has been conducted on modeling cutter swept volumes in CNC milling to represent the finished part geometry in the geometric simulation, it is very time consuming to calculate the instantaneous, undeformed chip geometries using the cutter swept volumes. Besides, the existing method of modeling undeformed chip geometry in three-axis milling cannot be used for that in five-axis milling. To address this problem, our work proposes an accurate and efficient approach. In this article, a generic theory about the boundary of the area covered by the instantaneous cutting edges on a workpiece layer at any moment is established, which is called the boundary theory. A simple diagram of determining the boundary is invented, which is called boundary construction diagram. This approach lays a theoretical foundation for the geometric and the physical simulations of five-axis milling and will significantly promote them for high performance machining in industry.     

On-line robust identification of tool-wear via multi-sensor neural-network fusion

Real-time identification and monitoring of tool-wear in shop-floor environments is essential for the optimization of machining processes and the implementation of automated manufacturing systems. This paper analyzes the signals from an acoustic emission sensor and a power sensor during machining processes, and extracts a set of feature parameters that characterize the tool-wear conditions. In order to realize real-time and robust tool-wear monitoring for different cutting conditions, a sensor-integration strategy that combines the information obtained from multiple sensors (acoustic emission sensor and power sensor) with machining parameters is proposed. A neural network based on an improved backpropagation algorithm is developed, and a prototype scheme for the real-time identification of tool-wear is implemented. Experiments under different conditions have proved that a higher rate of tool-wear identification can be achieved by using the sensor integration model with a neural network. The results also indicate that neural networks provide a very effective method of implementing sensor integration for the on-line monitoring of tool abnormalities.