Octree based assembly sequence generation

Unique definition and classification of assembly feature are presented. Assembly feature's definition is provided using the concept of assembly intents. Assembly features classification is done based on useful assembly-specific information. Assembly features provide information that result in a smaller number of assembly sequences that have to be checked in assembly sequence optimisation. Due to the reduction in assembly sequences, AND/OR graph not only reduces considerably but also becomes very simple. This can result in a significant reduction in the computation time for assembly sequence planning. Real-life examples are given to demonstrate how assembly features are useful in sequence planning.

Tolerance allocation is important aspect in designing as well as manufacturing. Mating features in an assembly are important from the tolerance point of view and govern the tolerance schema. Presence of patterns within these features also plays an important role in the allocation of different tolerance classes. Identification of these assembly features and patterns are previously done manually. This research is aimed at automating these processes. The automation starts with the recognition of the assembly features in the assembly. The algorithms for feature recognition are designed such that they can handle any user defined assembly feature. The input for feature recognition is a STEP file containing information of the assembly. And the output file contains information of the recognized assembly features. Then patterns are identified from these assembly features. This paper discusses these two processes in detail. Also to facilitate the user, define new assembly features an alternate system called assembly feature tutor is developed. This paper also explains the working of this tutor.

Assembly features encode geometric and functional relationships between parts in an assembly. They can be used in assembly design by features, kinematic and structural analyses, assembly planning and assemblability evaluation. Explicit definition of assembly features and archival in libraries can be used to assist in design and analysis of mechanical assemblies. This paper builds on our past work in neutral definition of generic assembly features to provide a mechanism for user-defined custom assembly features using an interactive system, called the assembly feature tutor. The user teaches the system interactively by examples and the tutor outputs an assembly definition file that is written in EXPRESS like language. Central to the definition are pairs of mating part faces and includes algebraic, geometric and parametric relations. Twist and wrench matrices can be extracted from face pair relations. The definition is implementation independent and provides a uniform way to define assembly features....

Interfacing CAD to CAPP (computer-aided process planning) is crucial to the eventual success of a fully-automated computer-integrated manufacturing (CIM) environment. Current CAD and CAPP systems are separated by a “semantic gap” that represents a fundamental difference in the ways in which they represent information. This semantic gap makes the interfacing of CAD to CAPP a non-trivial task. This paper argues that automatic feature recognition is an indispensable technique in interfacing CAD to CAPP. It then surveys the current literature on automatic feature recognition methods and systems, and analyzes their suitability as CAD/CAPP interfaces. It also describes a relatively recent automatic feature recognition method based on volumetric decomposition, using Kim’s alternating sum of volumes with partitioning (ASVP) algorithm. The paper’s main theses are: (1) that most previous automatic feature recognition approaches are ultimately based on pattern-matching; (2) that pattern-matching approaches are unlikely to scale up to the real world; and (3) that volumetric decomposition is an alternative to pattern-matching that avoids its shortcomings. The paper concludes that automatic feature recognition by volumetric decomposition is a promising approach to the interfacing of CAD to CAPP.

The topological and geometric information in B-rep models is essential for various applications, including feature recognition, design verification, and automatic tool path generation. In particular, representing surfaces using an analytic format offers advantages for utilizing geometric information such as surface type, axis of rotation, and radius. Models composed solely of NURBS surfaces often have limitations in extracting this type of information. To address this issue, this study proposes a method for identifying and replacing NURBS surfaces that can be represented analytically. In the first step, the feasibility of substituting a NURBS surface with an analytic surface is determined by examining the characteristics of its isocurves. In the second step, an equivalent analytic surface is created and used to replace the existing NURBS surface. To validate the proposed method, surface replacement experiments were conducted on multiple test cases. The results showed that, among 10 176 NURBS surfaces identified for possible analytic replacement across 37 B-rep models, 9 163 surfaces were successfully substituted in a stable manner. In addition, an experiment comparing feature recognition in the pre- and post-replacement models was conducted. As a result, none of the 12 design features were recognized in the pre-replacement model, whereas all were correctly detected afterward, confirming that the replacement process significantly enhances feature recognition accuracy.

The recognition and suppression of small features from B-rep models play an important role in effectively generating the qualified mesh for analysis. This paper presents a new algorithm for recognizing small blends automatically for the purpose of mesh generation. The algorithm first transforms the input B-rep model into an aggregation of faces. Then, each face is judged to be a blend or not based on matching conditions. At last, the blends with larger physical sizes than a threshold value are excluded. The innovations lie in the recognition conditions and the unique calculating procedure of the blend physical size. Several examples are given to demonstrate the validity and applicability of the algorithm.

The design of a mould, which is manually performed, is time-consuming and quite complicated. This research presents a study on the procedures for automatic feature recognition to help in mould design. A hybrid representation approach is used in automatic feature recognition to extract geometric information from a feature to identify undercut features. Boundary representation is applied in the shape representation using topology and geometry. The proposed approach uses a face adjacency hypergraph to describe the shape of the undercut features by representing the relationships amongst the feature faces. Face-to-face composition is applied to represent the relationship between the main and the undercut features. Parts A, B, and C are created, and automatic feature recognition is used to classify the depression and protrusion features. Algorithms based on a heuristic rule are adopted to determine the optimal parting line and direction of the parts by comparing their feature’s geometric information. The automatic feature recognition approach identifies the shape of concave and convex features in accordance with the depression or protrusion of faces and the face adjacency relationship. This approach can be helpful in automatically creating the core and cavity. The proposed approach will help simplify the process and reduce the time for mould design. Therefore, this approach will significantly affect the increase in productivity in the manufacturing industry.

This paper present a new method for automatic form feature recognition from boundary representation of a solid model. The proposed method is called the edge boundary classification technique. This technique uses the geometry, topology, and spatial information of a solid model for feature recognition patterns. Some aspects of edge boundary classification are discussed for recognising non-intersecting and intersecting form features.

A review of automated feature recognition with rule-based pattern recognition

Fillets, rounds, grooves and sharp edges segmentation from 3D scanned surfaces

Internet-based collaborative product design with assembly features and virtual design spaces

In the first part of the review, recent developments in medical imaging technology are described. Developments in transducer materials and matching, leading to improvements in band-width and sensitivity are discussed. Improvements in dynamic range due to increased transducer sensitivity, lower electronic noise levels and more efficient filtering are then considered. The benefits of the application of digital signal processing (DSP) techniques to radiofrequency (RF) echo signals are described, including more precise filtering and beam forming, synthetic aperture and parallel receive beam forming. Finally, the current situation in regard to 1.5 D arrays, 3 D scanning, ultrasound computed tomography (UCT), harmonic imaging with contrast agents and elastography are discussed. In the second part, some predictions for future developments are made. These will be possible largely due to the power of DSP. Parallel transmissions will make more efficient use of time, allowing greater spatial and temporal resolution, and greater accuracy in Doppler imaging. Adaptive transmission tailoring will be used, where the pulse characteristics to each part of the image field are independently optimized, as will adaptive receive processing in which echo sequences from each part of the image are independently and optimally processed. An important potential development will be automatic feature recognition, making possible accurate compound scanning with high spatial resolution, and quantitative information about the spatial distribution of acoustic speed. Compound scanning will provide more complete visualization of all structures and, particularly when incorporated into intravascular probes, should greatly aid the investigation of arterial plaque morphology. Feature recognition will also make it possible to have UCT systems (array based in future) which require less than 360 degrees access. Harmonic imaging without contrast agents, based simply on the inherent non-linearity of sound propagation in tissue, will become common. 2 D phased array transducer will permit symmetric beam focusing and scanning throughout a solid cone, greatly facilitating the development of 3 D scanning applications. Large 2 D arrays would have the potential to produce a five-fold increase in spatial resolution of a limited volume of tissue, or to measure the variation of backscatter with angle, as an aid to tissue characterization. Finally, ultrasound will be increasingly used to measure the elastic and dynamic properties of local regions of tissue.

Automatic feature recognition has been an active area of research in solid modeling for more than two decades. In fact it is considered to be the most critical component in the integration of CAD/CAM. One of the hard problems in automatic feature recognition is to recognize interacting features. The inherent complexity of this problem is due to the missing geometry/topology information in the solid model, whenever features interact. Till date, the most promising techniques have used geometric reasoning algorithms to supply the partially missing information. In this paper, we have taken a very practical approach to the feature interaction problem. Whenever our feature recognition algorithm fails to recognize interacting features correctly, we allow the user to define a new feature. This User Defined feature is then added to the existing list of features. The entire feature list is then sent to the process planning module for preparing a detailed manufacturing plan. We claim that a User Defined feature provides a novel way to address the feature interaction problem using a man-in-the-loop interface.

Automatic Feature Recognition (AFR) techniques provide the capabilities for translating the data of the part definition between Computer Aided Design (CAD) system and the feature needed to be determined; these techniques take a general CAD model, which is commercially available for providing an automated interface to extract and recognize the manufacturing features from the CAD model. Standard for Exchange of Product (STEP) format is an international standard for transporting geometric and non-geometric data between CAD and Computer Aided Manufacturing systems. Many researches have investigated the AFR in symmetrical features in rotational parts, but few studies have tried to recognize the cross-hole feature because of the recognition difficulty of such feature. A cross hole is recognized with existence of (B-spline Curve with Knots) string in (STEP AP203) neutral file. Cross holes might be perpendicular, offset or inclined to cylinder’s axis, it also can be blind or through. Extraction of the necessary information from (STEP) file for generating the parameters of the manufacturing operation becomes a significant task. In this paper, a new approach for automatic recognition of cross hole feature in hollow cylinders is developed, This approach has been built by connecting the Visual Basic programming language (VB) to the SolidWorks software. The drawing is sent to the VB after saving it as a (STEP AP203) file. VB extracts and recognizes the cross-hole feature according to the rule-based reasoning, some case studies for demonstrating the application of this method on different cases of the cross-hole are presented.

Automatic feature recognition (AFR) techniques represent an essential tool that links computer-aided design (CAD) and computer-aided process planning (CAPP) systems. This is by converting low-level geometric entities of part design models created in CAD systems to manufacturing features which are used in CAPP. Whilst different AFR systems have been developed for the purpose of recognising final manufacturing features of a part, most of them do not solve features intersecting issues. The features intersecting is an unavoidable matter that occurs during the rough cutting cycle and forms intermediate manufacturing features. This paper presents a “features subtraction” methodology for solving manufacturing features intersection issues of rotational parts. The system takes the recognised external and internal manufacturing features from a smart interactive AFR (SI-AFR) system as an input. After seven steps of processing, it provides geometrical and topological information of intermediate and final features that can be used to automatically generate CAPP outputs, such as selecting machining process, sequence of operations, cutting tools and cutting conditions, and generating the G-code for machining the part. This has been written using C# coding, and several examples have been processed for this paper to validate the system.