A knowledge-based approach for the extraction of machining features from solid models

Computer understanding of machining features such as holes and pockets is essential for bridging the communication gap between Computer Aided Design and Computer Aided Manufacture. This thesis describes a prototype machining feature extraction system that is implemented by integrating the VAX-OPS5 rule-based artificial intelligence environment with the PADL-2 solid modeller. Specification of original stock and finished part geometry within the solid modeller is followed by determination of the nominal surface boundary of the corresponding cavity volume model by means of Boolean subtraction and boundary evaluation. The boundary model of the cavity volume is managed by using winged-edge and frame-based data structures. Machining features are extracted using two methods : (1) automatic feature recognition, and (2) machine learning of features for subsequent recognition. [Continues.

Development of Feature Recognition Algorithm for Automated Identification of Duplicate Geometries in CAD Models

This research presents a feature recognition algorithm for the automated identification of duplicate geometries in the CAD assembly. The duplicate geometry is one of the seven indicators of the lazy parts mass reduction method. The lazy parts method is a light weight engineering method that is used for analyzing parts with the mass reduction potential. The duplicate geometry is defined as any geometries lying equal to or within the threshold distance with the user-defined orientation between them and have the percentage similarity that is equal to or greater than the threshold value. The feature recognition system developed in this research for the identification of duplicate geometries is also extended to retrieve the weighted bipartite graph of part connections for the assembly time estimation. The weighted bipartite graph is used as input for the part connectivity based assembly time estimation method. The SolidWorks API software development kit is used in this research to develop a feature recognition system in SolidWorks CAD software package using C++ programming language. The feature recognition system built in the SolidWorks CAD software uses a combination of topology and geometric data for the evaluation of duplicate geometry. The measurement of distances between the sampling points strategy is used for the duplicate geometry feature recognition. The feature recognition algorithm has three phases of evaluation: first, is the evaluation for threshold distance condition of parts in the CAD assembly. Second, the part pairs that have satisfied the threshold distance condition are evaluated for the orientation condition. The threshold distance and orientation are the necessary but not the sufficient conditions for duplicate geometries. In the third phase, the geometries that have satisfied orientation condition are evaluated for the percentage similarity condition. The geometries that satisfy the percentage similarity condition are highlighted in order to help designers review the results of the duplicate geometry analysis. The test cases are used to validate the algorithm against the requirements list. The test cases are designed to check the performance of the algorithm for the evaluation of the threshold distance, orientation, and percentage similarity condition. The results indicate that the duplicate geometry algorithm is able to successfully conduct all the three phases of evaluation. The algorithm is independent of the geometric type and is able to analyze planar, cylindrical, conical, spherical, freeform, and toroidal shapes. The number of sampling points generated on the faces of parts for the orientation and percentage similarity evaluation has the significant effect on the analysis time. The worst case complexity of the algorithm is the big O (nC2x m12 x m22x p4), where n = the number of parts in the assembly m1 = the number of faces in the parts that meet the threshold distance condition m2 = the number of faces that meet the orientation condition p = the number of sampling points on the face The duplicate geometry feature recognition approach is used to demonstrate the applicability in the extraction of assembly relations for the part connectivity based assembly time estimation method. The algorithm is also able to extract part connectivity information for the patterns. Further research is required to automate the identification of other laziness indicators in order to make the lazy parts method a completely automated tool. With regards to the complete automation of part connectivity based assembly time estimation method, the duplicate geometry feature recognition system needs integration with the algorithm for the computation of bipartite graph of part connections for the prediction of assembly time

Extracting Alternative Machining Features: Al Algorithmic Approach

Automated recognition of features from CAD models has been attempted for a wide range of application domains. In this paper we address the problem of representing and recognizing the complete class of features in alternative interpretations for a given design. We present a formalism for representing feature- based design alternatives and a methodology for recognizing a class of machinable features. Our approach handles a class of volumetric features that describe material removal volumes made by operations on the three-axis vertical machining centers including: drilling, pocket-, slot-, and face-miling, chamfering, filleting, and blended surfaces. Our approach recognizes intersecting features, and is complete over all features in our class, i.e. for any given part, the algorithm produces a set containing all features in our class that correspond to possible operations for machining that part. This property is of particular significance in applications where consideration of different manufacturing alternatives is crucial. In addition, we have shown that the algorithms are, in the worst-case, euqdratic in the number solid modeling operations. This approach employs a class of machinable features expressible as MRSEVs ( a STEP- based library of machining features). An implementation of these algorithms has been done using the ACISsolid modeler and the NIH C++ class library

Feature-based interaction: an identification and classification methodology

Features are an established means of adding non-geometric information and extra geometric semantics to conventional computer aided design (CAD) systems. For some time it has been realized that, although feature-based modelling is necessary for the next generation of integrated design and manufacturing systems, the inherent feature interactions pose a difficulty in representing and manipulating geometric designs. This paper presents a structured geometric spatial feature interaction identification method based on a broad multilevel classification. Feature interaction definitions and classifications have been surveyed and it is evident that, although many feature interaction classifications have been proposed, there is a lack of a general framework. The classification presented here encompasses existing feature interference cases found in the literature and defines a singular framework that leads to a general classification structure. The framework is presented and applied at three different levels and each interaction case is defined by feature parameters rather than just geometric entities. The restrictions often found in other research concerning contact:non-contact and concave:convex situations are avoided. The resulting classification is easy to understand and implement because it uses simple rules based on commonly available Boolean operators. Finally, an example component is presented and the advantages, uses and applications of the classification scheme are discussed

Automated feature recognition system for supporting engineering activities downstream of conceptual design.

Transfer of information between CAD models and downstream manufacturing process planning software typically involves redundant user interaction. Many existing tools are process-centric and unsuited for selection of a "best process" in the context of existing concurrent engineering design tools. A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format. Existing hint-based feature recognition techniques have been extended to encompass a broader range of manufacturing domains than typical in the literature, by utilizing a combination of algorithms, each successful at a limited range of features. Use of wire-frame models simplifies product geometry and has the potential to support rapid manufacturing shape evaluation at the conceptual design stage. Native CAD files are converted to IGES neutral files to provide geometry data marshalling to remove variations in user modelling practice, and to provide a consistent starting point for FR operations. Wire-frame models are investigated to reduce computer resources compared to surface and solid models, and provide a means to recover intellectual property in terms of manufacturing design intent from legacy and contemporary product models. Geometric ambiguity in regard to what is ?solid? and what is not has plagued wire-frame FR development in the past. A new application of crossing number theory (CNT) has been developed to solve the wire-frame ambiguity problem for a range of test parts. The CNT approach works satisfactorily for products where all faces of the product can be recovered and is tested using a variety of mechanical engineering parts. Platform independent tools like Extensible Mark-up Language are used to capture data from the FR application and provide a means to separate FR and decision support applications. Separate applications are composed of reusable software modules that may be combined as required. Combining rule-based and case-based reasoning provides decision support to the manufacturing application as a means of rejecting unsuitable processes on functional and economic grounds while retaining verifiable decision pathways to satisfy industry regulators

Classroom Interactions, Instructional Activities And Learning Affordances Of An Undergraduate Technical Writing Classroom: A Sociocultural Study

This thesis is the result of an academic venture to explore writing practices in the Malaysian higher education. The study assumes a sociocultural view and approaches writing practices as the teaching, learning, and doing of writing. Tesis ini dihasilkan menerusi satu usaha akademik untuk menerokai amalan menulis di institusi pengajian tinggi di Malaysia. Kajian ini berdasarkan pandangan sosiobudaya dan mengambil pendekatan terhadap amalan menulis sebagai pengajaran, pembelajaran dan perlakuan penulisan