Review of research in feature-based design

Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems do. The evolution of feature definitions is briefly discussed. Features and their role in the design process and as representatives of design-objects and design-object knowledge are discussed. The main research issues related to feature-based design are outlined. These are: feature representation, features and tolerances, feature validation, multiple viewpoints towards features, features and standardization, and features and languages. An overview of some academic feature-based design systems is provided. Future research issues in feature-based design are outlined. The conclusion is that feature-based design is still in its infancy, and that more research is needed for a better support of the design process and better integration with manufacturing, although major advances have already been made

3D Shape Segmentation with Projective Convolutional Networks

This paper introduces a deep architecture for segmenting 3D objects into their labeled semantic parts. Our architecture combines image-based Fully Convolutional Networks (FCNs) and surface-based Conditional Random Fields (CRFs) to yield coherent segmentations of 3D shapes. The image-based FCNs are used for efficient view-based reasoning about 3D object parts. Through a special projection layer, FCN outputs are effectively aggregated across multiple views and scales, then are projected onto the 3D object surfaces. Finally, a surface-based CRF combines the projected outputs with geometric consistency cues to yield coherent segmentations. The whole architecture (multi-view FCNs and CRF) is trained end-to-end. Our approach significantly outperforms the existing state-of-the-art methods in the currently largest segmentation benchmark (ShapeNet). Finally, we demonstrate promising segmentation results on noisy 3D shapes acquired from consumer-grade depth cameras.Comment: This is an updated version of our CVPR 2017 paper. We incorporated new experiments that demonstrate ShapePFCN performance under the case of consistent *upright* orientation and an additional input channel in our rendered images for encoding height from the ground plane (upright axis coordinate values). Performance is improved in this settin

Geometric and form feature recognition tools applied to a design for assembly methodology

The paper presents geometric tools for an automated Design for Assembly (DFA) assessment system. For each component in an assembly a two step features search is performed: firstly (using the minimal bounding box) mass, dimensions and symmetries are identified allowing the part to be classified, according to DFA convention, as either rotational or prismatic; secondly form features are extracted allowing an effective method of mechanised orientation to be determined. Together these algorithms support the fuzzy decision support system, of an assembly-orientated CAD system known as FuzzyDFA

3D point cloud video segmentation oriented to the analysis of interactions

Given the widespread availability of point cloud data from consumer depth sensors, 3D point cloud segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It benefits from the richer information contained in real world 3D data compared to 2D images. This also implies that the classical color segmentation challenges have shifted to RGBD data, and new challenges have also emerged as the depth information is usually noisy, sparse and unorganized. Meanwhile, the lack of 3D point cloud ground truth labeling also limits the development and comparison among methods in 3D point cloud segmentation. In this paper, we present two contributions: a novel graph based point cloud segmentation method for RGBD stream data with interacting objects and a new ground truth labeling for a previously published data set. This data set focuses on interaction (merge and split between ’object’ point clouds), which differentiates itself from the few existing labeled RGBD data sets which are more oriented to Simultaneous Localization And Mapping (SLAM) tasks. The proposed point cloud segmentation method is evaluated with the 3D point cloud ground truth labeling. Experiments show the promising result of our approach.Postprint (published version

Conceptual Graphs in CAD

This paper elaborates on the use of conceptual graphs in a prototype of a computer based support system for re-design. Re-design support involves the modelling of assemblies and components. The requirements of the components to be modelled are a compromise between the functioning of the assembly and the manufacturability of the individual components. Conceptual graphs provide for an elegant way of representing both functioning and manufacturing aspects. In the prototype system, conceptual graphs are used for representing and defining assemblies, components and features as well as the relations between these entities. Constraints, such as kinematic, tolerance and manufacturing constraints are also represented using conceptual graphs

Goods and services tax (GST) on construction capital cost and housing property price

Good and Service Tax (GST) an indirect broad-based conswnpti.on tax. Following with the implementation of GST in Malaysia on 1st April 2015, it is suspected that the construction capital cost and housing property price will increase accordingly. This study is aim to review the GST effect associated on construction capital cost and it influences towards housing developer and housing property price. Additionally, this study highlights what was the developer point of view on the GST given to them and also the housing price further proposes initiatives to the housing developers. Argument of GST effect is useful for the public administrators so that to re-consider the rate of GST and also beneficial to the construction parties to account with the GST implementation. As conclusion, this study review that GST do give an impact towards the construction capital cost, housing developer and housing property price in terms of knock-on effect

Effect of PAO-based γ-Fe2O3 and surfactant concentration on viscosity characteristic

This is a preliminary study on the viscosity characteristics of polyalphaolefin (PAO)- based γ-Fe2O3 under zero magnetic fields. By varying the concentration of magnetic nanoparticles (MNPs), PAO-based γ-Fe2O3 with different concentrations were synthesized by co-precipitation method. The effect of this factor on the viscosity characteristic of γ-Fe2O3 (< 30 nm) was investigated on the basic of a series of rheological measurement. The use of oleic acid (OA) as a coating agent and surfactant was also investigated by varying its concentration. The results show the concentration of MNPs and the amount of OA has obvious effect on viscosity characteristics of PAO-based γ-Fe2O3. In the case of comparison between the concentrations of MNPs, higher concentration of MNPs increased the viscosity of the PAO-based γ-Fe2O3 and exhibit nearly Newtonian behavior. The large amount of OA also exhibits the increment on viscosity characteristic of MNPs. The experimental data were compared with the Bingham and Casson model and the results revealed that the rheology of the polyalphaolefin (PAO)-based γ-Fe2O3 fitted the Casson model better