Search results for: Gunji Balamurali

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Balamurali</title> <meta name="description" content="Search results for: Gunji Balamurali"> <meta name="keywords" content="Gunji Balamurali"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Gunji Balamurali"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Gunji Balamurali</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Parallel Gripper Modelling and Design Optimization Using Multi-Objective Grey Wolf Optimizer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Golak%20Bihari%20Mahanta">Golak Bihari Mahanta</a>, <a href="https://publications.waset.org/abstracts/search?q=Bibhuti%20Bhusan%20%20Biswal"> Bibhuti Bhusan Biswal</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20B.%20V.%20L.%20Deepak"> B. B. V. L. Deepak</a>, <a href="https://publications.waset.org/abstracts/search?q=Amruta%20Rout"> Amruta Rout</a>, <a href="https://publications.waset.org/abstracts/search?q=Gunji%20Balamurali"> Gunji Balamurali </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Robots are widely used in the manufacturing industry for rapid production with higher accuracy and precision. With the help of End-of-Arm Tools (EOATs), robots are interacting with the environment. Robotic grippers are such EOATs which help to grasp the object in an automation system for improving the efficiency. As the robotic gripper directly influence the quality of the product due to the contact between the gripper surface and the object to be grasped, it is necessary to design and optimize the gripper mechanism configuration. In this study, geometric and kinematic modeling of the parallel gripper is proposed. Grey wolf optimizer algorithm is introduced for solving the proposed multiobjective gripper optimization problem. Two objective functions developed from the geometric and kinematic modeling along with several nonlinear constraints of the proposed gripper mechanism is used to optimize the design variables of the systems. Finally, the proposed methodology compared with a previously proposed method such as Teaching Learning Based Optimization (TLBO) algorithm, NSGA II, MODE and it was seen that the proposed method is more efficient compared to the earlier proposed methodology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gripper%20optimization" title="gripper optimization">gripper optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristics" title=" metaheuristics"> metaheuristics</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=""></a>, <a href="https://publications.waset.org/abstracts/search?q=teaching%20learning%20based%20algorithm" title=" teaching learning based algorithm"> teaching learning based algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20gripper%20design" title=" optimal gripper design"> optimal gripper design</a> </p> <a href="https://publications.waset.org/abstracts/86971/parallel-gripper-modelling-and-design-optimization-using-multi-objective-grey-wolf-optimizer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/86971.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> An Automated Optimal Robotic Assembly Sequence Planning Using Artificial Bee Colony Algorithm </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Balamurali%20Gunji">Balamurali Gunji</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20B.%20V.%20L.%20Deepak"> B. B. V. L. Deepak</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20B.%20Biswal"> B. B. Biswal</a>, <a href="https://publications.waset.org/abstracts/search?q=Amrutha%20Rout"> Amrutha Rout</a>, <a href="https://publications.waset.org/abstracts/search?q=Golak%20Bihari%20Mohanta"> Golak Bihari Mohanta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assembly%20sequence%20planning" title="assembly sequence planning">assembly sequence planning</a>, <a href="https://publications.waset.org/abstracts/search?q=CAD" title=" CAD"> CAD</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20Bee%20colony%20algorithm" title=" artificial Bee colony algorithm"> artificial Bee colony algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=assembly%20predicates" title=" assembly predicates"> assembly predicates</a> </p> <a href="https://publications.waset.org/abstracts/87239/an-automated-optimal-robotic-assembly-sequence-planning-using-artificial-bee-colony-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87239.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">237</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Parametric Appraisal of Robotic Arc Welding of Mild Steel Material by Principal Component Analysis-Fuzzy with Taguchi Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amruta%20Rout">Amruta Rout</a>, <a href="https://publications.waset.org/abstracts/search?q=Golak%20Bihari%20Mahanta"> Golak Bihari Mahanta</a>, <a href="https://publications.waset.org/abstracts/search?q=Gunji%20Bala%20Murali"> Gunji Bala Murali</a>, <a href="https://publications.waset.org/abstracts/search?q=Bibhuti%20Bhusan%20Biswal"> Bibhuti Bhusan Biswal</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20B.%20V.%20L.%20Deepak"> B. B. V. L. Deepak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=robotic%20arc%20welding" title="robotic arc welding">robotic arc welding</a>, <a href="https://publications.waset.org/abstracts/search?q=weld%20process%20parameters" title=" weld process parameters"> weld process parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=weld%20joint%20parameters" title=" weld joint parameters"> weld joint parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=Taguchi%20method" title=" Taguchi method"> Taguchi method</a> </p> <a href="https://publications.waset.org/abstracts/87646/parametric-appraisal-of-robotic-arc-welding-of-mild-steel-material-by-principal-component-analysis-fuzzy-with-taguchi-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87646.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">179</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" 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Search results for: Gunji Balamurali