1,043 research outputs found

    Integration of CAD/tool path data for 5-axis STEP-NC machining of free form/irrregular controured surfaces.

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    This research paper presents the work on feature recognition, tool path data generation and integration with STEP-NC (AP-238 format) for features having Free form/Irregular Contoured Surfaces(s) (FICS). Initially, the FICS features are modelled/imported in UG CAD package and a closeness index is generated. This is done by comparing the FICS features with basic B-Spines/Bezier curves/surfaces. Then blending functions are caculated by adopting convolution theorem. Based on the blending functions, contour offsett tool paths are generated and simulated for 5 axis milling environment. Finally, the tool path (CL) data is integrated with STEP-NC (AP-238) format. The tool path algorithm and STEP-NC data is tested with various industrial parts through an automated UFUNC plugin

    Toolpath algorithm for free form irregular contoured walls / surfaces with internal deflecting connections.

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    This paper presents a toolpath generation method to efficiently machine free form irregular contoured walls / surfaces (FIWS) containing internal deflecting connections (IDC’s). The toolpath generation method is based on a series of identifications and calculations, where initially a ‘Main Computable Zone (MCZ)’ in the Machinable Areas (Ma’s) of FIWS is identified based on the Tool track dimensions (Td). Then the MCZ’s are divided into Split Computable Zones (SCZ’s) and Split Computable Zones for Internal Connections (SCZI’s) which are subsequently sub divided as ‘Categorized Computable Zones’ (CCZ) with simple-medium-high complexity. The identification of CCZ’s is based on the 10 different types of FIWS representations developed for this study. From the CCZ’s categorization of complexity, they are further split into smaller ‘Machinable Zones (MZ’s)’ using a 4-step algorithm. In the algorithm, the first step calculates a common plane (CP) to cut the steep areas in the CCZ’s where the tool cannot have full access for machining. Once the CP is identified, the second step is to extend it by moving them along the CCZ’s and calculate the necessary ‘Machinable Zones (MZ’s)’ in the next stage. This is done by finding the intersection of CP with the FIWS through a point to point / line plane intersection concept. After this step, the MZ’s are re-iterated by including the open and closed surface criteria and is analyzed for the IDC’s to be combined in the fourth stage. This is achieved by adding up the IDC’s with the existing MZ’s computed by the algorithm. At every stage, the algorithm considers tool collision avoidance and tool rubbing in the CCZ’s and MZ’s . This is by an automatic computation based on the height to fixture clearance for safer neck length which avoids collision and rubbings in the final toolpaths. Finally, a combined tool path is generated for all the MZ’s and has been verified / tested for a sample part and impeller containing similar shapes using UG NX / STEP –NC software

    A Quaternionic Wavelet Transform-based Approach for Object Recognition

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    Recognizing the objects in complex natural scenes is the challenging task as the object may be occluded, may vary in shape, position and in size. In this paper a method to recognize objects from different categories of images using quaternionic wavelet transform (QWT) is presented. This transform separates the information contained in the image better than a traditional Discrete wavelet transform and provides a multiscale image analysis whose coefficients are 2D analytic, with one near-shift invariant magnitude and three phases. The two phases encode local image shifts and the third one contains texture information. In the domain of object recognition, it is often to classify objects from images that make only limited part of the image. Hence to identify local features and certain region of images, patches are extracted over the interest points detected from the original image using Wavelet based interest point detector. Here QWT magnitude and phase features are computed for every patch. Then these features are trained, tested and classified using SVM classifier in order to have supervised learning model. In order to compare the performance of local feature with global feature, the transform is applied to the entire image and the global features are derived. The performance of QWT is compared with discrete wavelet transform (DWT) and dual tree discrete wavelet transform (DTDWT). Observations revealed that QWT outperforms the DWT and shift invariant DTDWT with lesser equal error rate. The experimental evaluation is done using the complex Graz databases.Defence Science Journal, Vol. 64, No. 4, July 2014, pp. 350-357, DOI:http://dx.doi.org/10.14429/dsj.64.450

    IMPROVE THE PERFORMANCE OF AODV UNDER BLACKHOLE ATTACK IN MANET

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    The Mobile Ad-hoc Network is an infrastructure-less network in which each mobile node can communicate with other node without any fixed network. In view of this, the networks are vulnerable to various kind of attacks such as black hole attack, gray hole attack etc. The black hole attack is one of the cruel attacks in Mobile Ad-hoc NETwork (MANET). The simulation is carried out using MATLAB and analyzes the black hole attack in Ad-hoc On-demand Distance Vector (AODV) routing protocol and compared the performance of packet delivery ratio and delay with existing algorithm Hash_DSR. The result shows that the Hash_AODV is better than the Hash_DSR

    Automated design and STEP-NC machining of impellers

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    This paper presents the four stage approach followed for automated design and STEP-NC based machining of impellers. In the first stage, the design calculations are performed to construct the 'Meridional representation' of the radial impeller. Then 3D curves are projected from the 'Meridional representation' and 3D model is generated using UG-NX software. In the second stage, the process planning activities including tooling & setup plan are completed. Here, ball end mill cutters with suitable diameter and length are selected and appropriate process parameters as suited to 5 axis milling are considered. In the third stage, the tool path data based on contour area milling is generated and verified in the UG NX software. Finally, in the fourth stage, the model with the complete data is imported to STEP-NC software and the AP-238 format is generated. In this article the design procedure adopted for construction of 'Meridional Section' of a radial turbine is discussed with the general methdology to automate the process planning and tool path generation. A test case of radial impeller is presented with the results obtained by adopting STEP-NC format

    An IoT based industry 4.0 architecture for integration of design and manufacturing systems.

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    This paper proposes an Internet of Things (IoT) based 5-stage Industry 4.0 architecture to integrate the design and manufacturing systems in a Cyber Physical Environment (CPE). It considers the transfer of design and manufacturing systems data through the Cloud/Web-based (CW) services and discusses an effective way to integrate them. In the 1st stage, a Radio-Frequency IDentification (RFID) technology containing Computer Aided Design (CAD) data/models of the product with the ability to design / redesign is scanned and sent to a secure Internet/Cloud Server (CS). Here the CAD models are auto identified and displayed in the Graphical User Interface (GUI) developed for the purpose. From the scanned RFID CAD data/models, the 2nd stage adopts unique machine learning technique(s) and identifies the design & manufacturing features information required for product manufacture. Once identified, the 3rd stage handles the necessary modelling changes as required to manufacture the part by verifying the suitability of process-based product design through user input from the GUI. Then, it performs a Computer Aided Process Planning (CAPP) sequence in a secure design cloud server designed using web-based scripting language. After this, the 4th stage generates Computer Aided Manufacturing (CAM) toolpaths by continuous data retrieval of design and tooling database in the web server by updating the RFID technology with all the information. The various processes involved the 3rd and 4th stages are completed by using ‘Agents’ (a smart program) which uses various search and find algorithms with the ability to handle the changes to the process plan as required. Finally, the 5th stage, approves the product manufacture instructions by completing the production plan with the approved sheets sent to the Computer Numerical Control (CNC) machine. In this article, the proposed architecture is explained through the concept of IoT data transfer to help industries driving towards Industry 4.0 by improving productivity, reducing lead time, protecting security and by maintaining internationals standards / regulations applied in their workplace
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