The Experts below are selected from a list of 3441 Experts worldwide ranked by ideXlab platform

N. Murugan - One of the best experts on this subject based on the ideXlab platform.

  • Effect of FCAW Process Parameters on Weld Bead Geometry in Stainless Steel Cladding
    Journal of Minerals and Materials Characterization and Engineering, 2011
    Co-Authors: V. Vasantha Kumar, N. Murugan
    Abstract:

    Recently automated and / or robotic welding systems have received a great deal of attention because they are highly suitable not only to enhance production rate and quality, but also to decrease cost and time to manufacture for a given product. To get the desired quality welds it is essential to have complete control over the relevant process parameters in order to obtain the required Bead Geometry. Mathematical models need to be developed to have such control and to make effective use of automated and / or robotic arc welding process.

  • Optimization of weld Bead Geometry in plasma transferred arc hardfaced austenitic stainless steel plates using genetic algorithm
    The International Journal of Advanced Manufacturing Technology, 2009
    Co-Authors: K. Siva, N. Murugan, R. Logesh
    Abstract:

    Plasma transferred arc hardfacing has attracted increasing attention for its effective protection against corrosion, thermal shock, and abrasion. The quality of hardfaced components depends on the weld Bead Geometry and dilution, which have to be properly controlled and optimized to ensure better economy and desirable mechanical characteristics of the weld. These objectives can be fulfilled by developing mathematical equations to predict the dimensions of the weld Bead. This paper highlights the development of such mathematical equations using multiple regression analysis, correlating various process parameters to weld Bead Geometry in PTA hardfacing of Colmonoy 5, a nickel-based alloy over stainless steel 316 L plates. The experiments were conducted based on a five factor, five level central composite rotatable design matrix. A genetic algorithm (GA) was developed to optimize the process parameters for achieving the desired Bead Geometry variables.

  • Optimization of weld Bead Geometry for stainless steel claddings deposited by FCAW
    Journal of Materials Processing Technology, 2007
    Co-Authors: P. K. Palani, N. Murugan
    Abstract:

    Abstract The quality of cladded components depends on the weld Bead Geometry, coefficients of shape of welds and dilution, which have to be controlled. Optimum range of Bead parameters and dilution are required for better economy and to ensure the desired mechanical and corrosion resistant properties of the overlay. The above objectives can easily be achieved by developing mathematical equations to predict the weld Bead Geometry. This paper presents the development of such equations using the data obtained by conducting three factor five level factorial experiments. The experiments were conducted by depositing Type AISI 317L flux cored stainless steel wire onto IS: 2062 structural steel base plate. The results of the confirmation experiments showed that the models developed are able to predict the Bead geometries and dilution with reasonable accuracy. The studies have indicated that both main and interaction effects of the process variables play a major role in determining the Bead dimensions and dilution, and the effect of interaction between the process variables cannot be neglected. The process parameters were also optimized using response surface methodology (RSM) which will help the plant engineers to select and control the process variables effectively, to achieve the desired clad qualities.

  • Development of mathematical models for prediction of weld Bead Geometry in cladding by flux cored arc welding
    The International Journal of Advanced Manufacturing Technology, 2006
    Co-Authors: P. K. Palani, N. Murugan
    Abstract:

    The mechanical and corrosion resistant properties of cladded components depend on the clad Bead geometries, which in turn are controlled by the process parameters. Therefore it is essential to study the effect of process parameters on the Bead Geometry to enable effective control of these parameters. The above objective can easily be achieved by developing equations to predict the weld Bead dimensions in terms of process parameters. Experiments were conducted to develop models, using a three factor, five level factorial design for 317L flux cored stainless steel wire with IS:2062 structural steel as base plate. The models so developed were checked for their adequacy. Confirmation experiments were also conducted and the results show that the models developed can predict the Bead geometries and dilution with reasonable accuracy. It was observed from the investigation that the interactive effect of the process parameters on the Bead Geometry is significant and cannot be neglected.

  • prediction and control of weld Bead Geometry and shape relationships in submerged arc welding of pipes
    Journal of Materials Processing Technology, 2005
    Co-Authors: N. Murugan, V Gunaraj
    Abstract:

    Abstract To automate a welding process, which is the present trend in fabrication industry, it is essential that mathematical models have to be developed to relate the process variables to the weld Bead parameters. Because of its high reliability, deep penetration, smooth finish and high productivity, submerged arc welding (SAW) has become a natural choice in industries for fabrication, especially for welding of pipes. Mathematical models have been developed for SAW of pipes using five level factorial techniques to predict three critical dimensions of the weld Bead Geometry and shape relationships. The models developed have been checked for their adequacy and significance by using the F -test and the t -test, respectively. Main and interaction effects of the process variables on Bead Geometry and shape factors are presented in graphical form and using which not only the prediction of important weld Bead dimensions and shape relationships but also the controlling of the weld Bead quality by selecting appropriate process parameter values are possible.

Guangjun Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Bead Geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis
    Journal of Intelligent Manufacturing, 2014
    Co-Authors: Jun Xiong, Guangjun Zhang, Jianwen Hu, Lin Wu
    Abstract:

    The single weld Bead Geometry has critical effects on the layer thickness, surface quality, and dimensional accuracy of metallic parts in layered deposition process. The present study highlights application of a neural network and a second-order regression analysis for predicting Bead Geometry in robotic gas metal arc welding for rapid manufacturing. A series of experiments were carried out by applying a central composite rotatable design. The results demonstrate that not only the proposed models can predict the Bead width and height with reasonable accuracy, but also the neural network model has a better performance than the second-order regression model due to its great capacity of approximating any nonlinear processes. The neural network model can efficiently be used to predict the desired Bead Geometry with high precision for the adaptive slicing principle in layer additive manufacturing.

  • Online measurement of Bead Geometry in GMAW-based additive manufacturing using passive vision
    Measurement Science and Technology, 2013
    Co-Authors: Jun Xiong, Guangjun Zhang
    Abstract:

    Additive manufacturing based on gas metal arc welding is an advanced technique for depositing fully dense components with low cost. Despite this fact, techniques to achieve accurate control and automation of the process have not yet been perfectly developed. The online measurement of the deposited Bead Geometry is a key problem for reliable control. In this work a passive vision-sensing system, comprising two cameras and composite filtering techniques, was proposed for real-time detection of the Bead height and width through deposition of thin walls. The nozzle to the top surface distance was monitored for eliminating accumulated height errors during the multi-layer deposition process. Various image processing algorithms were applied and discussed for extracting feature parameters. A calibration procedure was presented for the monitoring system. Validation experiments confirmed the effectiveness of the online measurement system for Bead Geometry in layered additive manufacturing.

  • Prediction of Weld Bead Geometry for Robotic GMAW Rapid Prototyping & Manufacturing
    Advanced Materials Research, 2012
    Co-Authors: Zi Qiang Yin, Guangjun Zhang, Hui Hui Zhao, Ning Guo, Chuan Bao Jia
    Abstract:

    This paper concentrates on direct rapid prototyping and manufacturing (RP&M) of functional metallic parts. Robotic gas metal arc welding (GMAW) is employed in this “Slicing & Stack” principle RP&M system. It is indicated that surface smoothness is a critical factor to affects the performance of RP & M products. In order to improve surface smoothness of product, the RP & M system must decrease stack error during stacking in each layer. This investigation establishes relationships between welding parameters and weld Bead Geometry. First, a rational welding parameters range is determined according to preliminary experiments. Then, quadric orthogonal regression rotational combination experiments scheme is proposed to predict width and height of weld Bead. The width and height in regression results are expressed in the form of quadratic equations by welding parameters. Significance test results show that the two quadratic equations are both significant. According to the established relationships, users can easily predict width and height of weld Bead when welding parameters are given. Whereas when the given condition is weld Bead Geometry, optimum welding parameters can also be determined by importing boundary condition according to users’ requirement or the service environment of parts. Experiment results indicate that prediction errors of width and height are both less than 3%.

Jun Xiong - One of the best experts on this subject based on the ideXlab platform.

  • Modeling of weld Bead Geometry for rapid manufacturing by robotic GMAW
    International Journal of Modern Physics B, 2015
    Co-Authors: Tao Yang, Jun Xiong, Hui Chen, Yong Chen
    Abstract:

    Weld-based rapid prototyping (RP) has shown great promises for fabricating 3D complex parts. During the layered deposition of forming metallic parts with robotic gas metal arc welding, the Geometry of a single weld Bead has an important influence on surface finish quality, layer thickness and dimensional accuracy of the deposited layer. In order to obtain accurate, predictable and controllable Bead Geometry, it is essential to understand the relationships between the process variables with the Bead Geometry (Bead width, Bead height and ratio of Bead width to Bead height). This paper highlights an experimental study carried out to develop mathematical models to predict deposited Bead Geometry through the quadratic general rotary unitized design. The adequacy and significance of the models were verified via the analysis of variance. Complicated cause–effect relationships between the process parameters and the Bead Geometry were revealed. Results show that the developed models can be applied to predict the desired Bead Geometry with great accuracy in layered deposition with accordance to the slicing process of RP.

  • Bead Geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis
    Journal of Intelligent Manufacturing, 2014
    Co-Authors: Jun Xiong, Guangjun Zhang, Jianwen Hu, Lin Wu
    Abstract:

    The single weld Bead Geometry has critical effects on the layer thickness, surface quality, and dimensional accuracy of metallic parts in layered deposition process. The present study highlights application of a neural network and a second-order regression analysis for predicting Bead Geometry in robotic gas metal arc welding for rapid manufacturing. A series of experiments were carried out by applying a central composite rotatable design. The results demonstrate that not only the proposed models can predict the Bead width and height with reasonable accuracy, but also the neural network model has a better performance than the second-order regression model due to its great capacity of approximating any nonlinear processes. The neural network model can efficiently be used to predict the desired Bead Geometry with high precision for the adaptive slicing principle in layer additive manufacturing.

  • Online measurement of Bead Geometry in GMAW-based additive manufacturing using passive vision
    Measurement Science and Technology, 2013
    Co-Authors: Jun Xiong, Guangjun Zhang
    Abstract:

    Additive manufacturing based on gas metal arc welding is an advanced technique for depositing fully dense components with low cost. Despite this fact, techniques to achieve accurate control and automation of the process have not yet been perfectly developed. The online measurement of the deposited Bead Geometry is a key problem for reliable control. In this work a passive vision-sensing system, comprising two cameras and composite filtering techniques, was proposed for real-time detection of the Bead height and width through deposition of thin walls. The nozzle to the top surface distance was monitored for eliminating accumulated height errors during the multi-layer deposition process. Various image processing algorithms were applied and discussed for extracting feature parameters. A calibration procedure was presented for the monitoring system. Validation experiments confirmed the effectiveness of the online measurement system for Bead Geometry in layered additive manufacturing.

V Gunaraj - One of the best experts on this subject based on the ideXlab platform.

  • prediction and control of weld Bead Geometry and shape relationships in submerged arc welding of pipes
    Journal of Materials Processing Technology, 2005
    Co-Authors: N. Murugan, V Gunaraj
    Abstract:

    Abstract To automate a welding process, which is the present trend in fabrication industry, it is essential that mathematical models have to be developed to relate the process variables to the weld Bead parameters. Because of its high reliability, deep penetration, smooth finish and high productivity, submerged arc welding (SAW) has become a natural choice in industries for fabrication, especially for welding of pipes. Mathematical models have been developed for SAW of pipes using five level factorial techniques to predict three critical dimensions of the weld Bead Geometry and shape relationships. The models developed have been checked for their adequacy and significance by using the F -test and the t -test, respectively. Main and interaction effects of the process variables on Bead Geometry and shape factors are presented in graphical form and using which not only the prediction of important weld Bead dimensions and shape relationships but also the controlling of the weld Bead quality by selecting appropriate process parameter values are possible.

T Kannan - One of the best experts on this subject based on the ideXlab platform.

  • Influence of Welding Process Parameters on Bead Geometry-A Review
    2017
    Co-Authors: B. Senthilkumar, T Kannan, P. Surendran
    Abstract:

    Surfacing techniques are developed to impart desirable properties like corrosion and wear resistance to low cost substrates like low carbon steels. Weld surfacing is capable of processing prefabricated and worn-out components. The various welding parameters influence the heat input, Bead Geometry and occurrence of weld defects. This paper briefly looks into various methods adapted to model, regulate and control weld surfacing techniques. The knowledge on effects of welding process parameters, percentage of overlap, inter-pass temperature, pulse characteristics, oscillation methods and control techniques is helpful to tailor the properties of the deposits. This review is mainly focused on selected welding techniques that can be readily and economically adopted for surfacing process.

  • prediction and optimization of weld Bead Geometry in gas metal arc welding process using rsm and fmincon
    Mechanical Engineering Research, 2013
    Co-Authors: P Sreeraj, T Kannan, Subhasis Maji
    Abstract:

    Cladding is a surface modification process in which a specially designed alloy is surface welded in order to enhance corrosion resistant properties. Common cladding techniques include Gas Tungsten Arc Welding (GTAW), submerged arc welding (SAW) and gas metal arc welding (GMAW). Because of high reliability, easiness in operation, high penetration good surface finish and high productivity gas metal arc welding became a natural choice for fabrication industries. This paper presents central composite rotatable design with full replication techniques to predict four critical dimensions of Bead Geometry. The second order regression method was developed to study the correlations. The developed models have been checked for adequacy and significance. The main and interaction effects of process variables and Bead Geometry were presented in graphical form. Using fmincon function the process parameters were optimized.   Key words: Gas metal arc welding (GMAW), weld Bead Geometry, mathematical model.

  • Effect of process parameters on clad Bead Geometry and its shape relationships of stainless steel claddings deposited by GMAW
    The International Journal of Advanced Manufacturing Technology, 2009
    Co-Authors: T Kannan, J. Yoganandh
    Abstract:

    Weld cladding is a process of depositing a thick layer of a corrosion resistance material over carbon steel plate to improve the corrosion resistance properties. The main problem faced in stainless steel cladding is the selection of process parameters for achieving the required clad Bead Geometry and its shape relationships. This paper highlights an experimental study carried out to develop mathematical models to predict clad Bead Geometry and its shape relationships of austenitic stainless steel claddings deposited by gas metal arc welding process. The experiments were conducted based on four-factor, five-level central composite rotatable design with full replication technique. The mathematical models were developed using multiple regression method. The developed models have been checked for their adequacy and significance. The direct and interaction effects of process parameters on clad Bead Geometry and its shape relationships are presented in graphical form.