Feature-based Technology Research Articles

EasyGaze: Hybrid eye tracking approach for handheld mobile devices

BackgroundEye-tracking technology for mobile devices has made significant progress. However, owing to limited computing capacity and the complexity of context, the conventional image feature-based technology cannot extract features accurately, thus affecting the performance. MethodsThis study proposes a novel approach by combining appearance- and feature-based eye-tracking methods. Face and eye region detections were conducted to obtain features that were used as inputs to the appearance model to detect the feature points. The feature points were used to generate feature vectors, such as corner center-pupil center, by which the gaze fixation coordinates were calculated. ResultsTo obtain feature vectors with the best performance, we compared different vectors under different image resolution and illumination conditions, and the results indicated that the average gaze fixation accuracy was achieved at a visual angle of 1.93° when the image resolution was 96 × 48 pixels, with light sources illuminating from the front of the eye. ConclusionsCompared with the current methods, our method improved the accuracy of gaze fixation and it was more usable.

Systematic review of STEP-NC-based inspection

Closed-loop inspection manufacturing (CLIM) and computer-aided inspection planning (CAIP) have increasingly been evolved into a size method that can be used to look at fashions in the industrial area with a number of methods. CAIP is hastily carried out in the gadget and will become an indispensable phase of the production system. Numerous scientific findings that tackle the theme from exclusive perspectives are accompanied by CLIM and CAIP in the measuring process. A systematic overview of these heterogeneous methods can be considered vital for CLIM to become aware of the ways in which CAIP can be used in your personal context. Thus, this systematic review of literature aims to analyze current inspection article and use of CLIM in CNC machines, assess heritage research to create a steady taxonomy, and provide a framework for forthcoming CLIM lookup in accordance with CAIP in the desktop gadget to enhance product quality. The consequences of this study provide a comprehensive taxonomy and a define in terms of the advanced features of this emerging technology. Articles on CAIP and CLIM, system-based technology, implementation of STEP/STEP-NC, and feature-based technology were discussed. As a result, various CLIM lookup findings regarding the machining machine tended to the center of attention rather on the VISION/aspects of the ISO14649-based computing device and further on inspection process planning perspectives, as well as factors indicating CLIM in technologies. This review paper will strengthen this study by supplying a deep analysis of the present facts to shut down the hole and lengthen the current literature.

Auto-recognition and part model complexity quantification of regular-freeform revolved surfaces through delta volume generations

Vast research works implementing feature-based technology have successfully been devoted. However, work on recognition of revolved regular-freeform surfaces is still inadequate due to its complex geometrical properties and topologies resulting lack of its physical significance. This paper presents a new method for recognising both regular and freeform revolved surfaces part model and generates its sub-delta volume using the volume decomposition method. To map the recognised sub-delta volume and respective machining process, part model complexity (PMC) is introduced. Generated sub-delta volumes are classified into three types of revolved surfaces excluding internal features. Sub-delta volumes are generated based on the machining process of roughing and finishing by offsetting the recognised faces. Internal features are de-featured by revolving respective sectioned faces. Differences of the overall delta volume ($$\Delta {\text{ODV}}$$) were calculated and verifications of the proposed PMC were done and presented.

Energy-efficient cyber-physical production network: Architecture and technologies

Energy efficiency has become an integral aspect of today's manufacturing. As manufacturing activities become increasingly distributed while connected in the new era of manufacturing – Industry 4.0, energy-efficient manufacturing strategies and methodologies should be implemented in a global production network. The research work reported in this paper endeavors to develop a feasible solution to implementing energy-efficient manufacturing in such an environment by proposing a technical architecture, integrated with the developed platform, MCloud. The overall technical architecture is discussed in detail, particularly, the proposed Energy-efficient Manufacturing (E2M) module and two-round communication procedure. Feature-based technology was adopted in process planning to assess the technical capability and energy consumption of connected virtual factories. MCloud allows each party in this production network to use local energy consumption models for energy assessment with great flexitity and privacy protection. A case study was presented to demonstrate the way distributed manufacturers collaboratively work on a manufacturing job, proving that the enhanced MCloud can coordinate customized production activities based on energy-saving needs in an Industry 4.0 environment.

Combining Dynamic Machining Feature With Function Blocks for Adaptive Machining

Feature-based technologies are widely researched for manufacturing automation. However, in current feature models, features once defined remain constant throughout the whole manufacturing lifecycle. This static feature model is inflexible to support adaptive machining when facing frequent changes to manufacturing resources. This paper presents a new machining feature concept that facilitates responsive changes to the dynamics of machining features in 2.5/3D machining. Basic geometry information for feature construction of complex parts with various intersecting features is represented as a set of meta machining features (MMF). Optimum feature definition is generated adaptively by choosing optimum merging strategies of MMFs according to the capabilities of the selected machine tool, cutter, and cutting parameters. A composite function block for dynamic machining feature modelling is designed with Basic Machining Feature Function Block, Meta Machining Feature Extraction Function Block and Feature Interpreter Function Block. Once changes of the selected machining resources occur, they are informed as input events and machining features are then updated automatically and adaptively based on the event-driven model of function blocks. An example is provided to demonstrate the feasibility and benefits of the developed methodology.

Computer-aided process planning – A critical review of recent developments and future trends

For the past three decades, computer-aided process planning (CAPP) has attracted a large amount of research interest. A huge volume of literature has been published on this subject. Today, CAPP research faces new challenges owing to the dynamic markets and business globalisation. Thus, there is an urgent need to ascertain the current status and identify future trends of CAPP. Covering articles published on the subjects of CAPP in the past 10 years or so, this article aims to provide an up-to-date review of the CAPP research works, a critical analysis of journals that publish CAPP research works, and an understanding of the future direction in the field. First, general information is provided on CAPP. The past reviews are summarised. Discussions about the recent CAPP research are presented in a number of categories, i.e. feature-based technologies, knowledge-based systems, artificial neural networks, genetic algorithms, fuzzy set theory and fuzzy logic, Petri nets, agent-based technology, Internet-based technology, STEP-compliant CAPP and other emerging technologies. Research on some specific aspects of CAPP is also provided. Discussions and analysis of the methods are then presented based on the data gathered from the Elsevier's Scopus abstract and citation database. The concepts of ‘Subject Strength’ of a journal and ‘technology impact factor’ are introduced and used for discussions based on the publication data. The former is used to gauge the level of focus of a journal on a particular research subject/domain, whereas the latter is used to assess the level of impact of a particular technology, in terms of citation counts. Finally, a discussion on the future development is presented.

A generative process planning system for cold extrusion

In this paper, a CAPP system GIFTEP (Generative, Interactive, Feature-based Technology for Extruded Products) based on a generative approach is proposed for forward cold extrusion of complex-shape solid components to be extruded through single-hole dies. This is an attempt, using the previous efforts of Kumar et al. 1999 and 2002), made by the authors to bridge the gap between CAD and CAM practices related to cold extrusion. A feature recognition methodology, an upper bound model, an optimum die profile, a defect prediction criteria, criteria to choose a die arrangement and a simple adiabatic model to account for the temperature of extrudate proposed in the previous work of Kumar are taken as the foundation modules for the purpose. Based on the component layout, a recognition module provides necessary data to carry out the die design process. The input parameter selection module first selects the input parameters provided by the user (material, reduction, billet condition, production type, etc.) or the default values from a database (die material, profile, die arrangement, accessories, etc.). The process parameter determination module carries out the optimization and calculates the optimal process parameters for two different criteria. Finally, an optimal process plan corresponding to both criteria are generated. The methodology is implemented in C through examples.

Multi-model technology and its application in the integration of CAD/CAM/CAE

The globalization and the intensive competition of the automotive market require shortening of the product development cycle, improvement of the quality and reduction of the cost. A new product modeling technology, multi-model technology (MMT), is provided in this paper to meet the needs of the challenge for automotive power-train product development. MMT introduces object-oriented technology (OT) into the product modeling process and combine OT with feature-based modeling technology. With the help of OT, MMT builds a product object model to support system level management in product development. The object model of the product is a multi-model structure (MMS). The MMS consists of a finish part model level (assembly model level), a rough part model level (part model level), a function model level and a basic model level. Every model in the MMS is created by feature-based technology in the design process. In this case, models in the MMS of the product can be shared by a casting mould, a sand core and a sand core mould. Therefore, CAD engineers, CAE engineers and CAM engineers can work concurrently and the integration of CAD/CAM/CAE can be realized. Then, MMT is applied in cylinder head development. The practice shows that the modeling technology in this paper can optimize the development process, and realize data sharing and concurrent engineering in the product development process.

Features extraction with the consideration of manufacturing processes

Computers are being used increasingly in the process planning function. The starting point of this function involves interpreting design data from a CAD model of the designed component. Feature-based technology is becoming an important tool for this. Automatic recognition of features and extraction of feature information from CAD data can be used to drive a process planning system. In this paper a new approach to automatic feature extraction called the 'blank-surface concave-edge' (BS-CE) approach is illustrated. This approach attempts to remove as much of the blank material within a given machine setup as possible. Hence intuitively one can say that the manufacturing cost of material removal may be minimized if this technique is employed. This feature extraction method is explained along with examples of its implementation. An analysis of alternate feature extraction results is performed and the cost of manufacture is compared to demonstrate the near optimal performance of this technique. Then a rule-based technique for feature recognition is presented.

Concurrent intelligent rapid prototyping environment

Rapid prototyping technology enables rapid production of complex objects directly from a computer-aided design model without involving any tooling or conventional part programming. This has created a new set of problems associated with part design, process planning, support design and value engineering analysis of rapid prototyping parts. In this paper, a methodology for resolving these problems is described, which uses concurrent engineering, distributed blackboard, value engineering, knowledge-based and feature-based technologies. The functionality, design methodology and knowledge representation techniques of a concurrent intelligent rapid prototyping system for stereolithography form the main focus of this paper.