• Journal of Welding and Joining
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• v.18 no.5
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.05a
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• pp.391-394
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• 2008

Durability of product is an important technical parameter of a current interception device (CID) filter. This parameter is influenced by several factors, such as: environment condition, external force, shape of device, heat and so on. In this study, the effect of the geometry of the device on durability was carried out. The effect of shape on durability of device is presented by force-carrying capacity that a device can sustain a maximum external force. Studied parameters of the CID filter's geometry include clearance, thickness, and corner radius. Fracture criterion of Cockcroft and Latham was also used to predict the maximum force-carrying capacity of device.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.414-424
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• 2023

In this study, a total of 326 data on a variety of geometric parameters of pick cutters and the corresponding cuttable rock conditions were collected and built as a database. Statistical analysis of the database showed that there is a significant positive correlation between the parameters that define the geometry of a pick cutter, especially between the parameters related to the length of a pick cutter and the geometry of a tungsten carbide insert. The diameter of a pick cutter shaft was also strongly correlated with the geometry of the inserts. On the other hand, it was difficult to find a clear correlation between the parameters for the rock conditions defined by the four conditions and the geometric parameters of pick cutters, which may be due to the uncertainty of the rock mass and the fact that the application of a pick cutter is presented as a range rather than a numerical single value. However, the mean values of geometric parameters of pick cutters tend to increase as a rock mass becomes harder. However, the pick length parameters are found to decrease as a rock mass becomes harder, which may be a way to reduce the moments that can occur when using long pick cutters in a hard rock condition.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.274-280
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• 1998

The welding technology and qualities are developed significantly, in recent years, in the use of automated processing technology and welding robot systems. But these automated welding technologies have many difficulties for finding the optimal welding parameter conditions. Because of the lack of mathematical model for determination of optimal welding process parameters. In this study, the sensitivity analysis of the empirical equations for finding weld bead width, height and penetration depth by using the published formulae. The selected major welding process parameters effected to weld bead geometries are the welding speed, current, voltage and weld wire diameter.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.768-776
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• 1994

This paper describes computer-aided forging design for rib/web shaped parts. In manufacturing a part by means of forging process, the first step is to design the forging. This is done by modifying the given machined part geometry according to the requirements of the forging process. Traditionally, this is done by experienced forging designers using empirical forging design guidelines. Generally, it would be neither possible nor practical to develop a system which encompasses the design of all types of forgings. Accordingly, forging design can be simplified by considering critical two dimensional cross sections of the machined part geometry. This system is composed of three modules(process variable decision module, forging design module and redesign module) and each module is carried out in regular sequence. In the process variable decision module, first of all, the undercut is checked and modified, and then deep recesses and holes difficult to forge are eliminated. Also parting line, forging plane, forging plan view area, forging weight and maximum size(maximum height or width)are determined. In the forging design module, the magnitude of various allowances, draft angle, minimum web thickness, corner and fillet radius are determined and then geometry modification is performed. Finally, since the design rules and databases used in this system are based on parameters of the forging geometry, such as the trimmed forging plan area, forging weight, forging maxmum size, plausible estimates need to be made for these parameters. Therefore, in the re-design module, the design process is iterated until a satisfactory forging is obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.871-877
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• 2008

It is important to investigate the relationship between weld process parameters and weld bead geometry for adaptive arc robot welding. Howeve, it is difficult to predict an exact back-bead owing to gap in process of butt welding. In this paper, the quantitative prediction system to specify the relationship external weld conditions and weld bead geometry was developed to get suitable back-bead in butt welding which is widely applied on industrial field. Multiple regression analysis for the prediction of process parameters was used as the research method. And, the results of the prediction method were compared and analyzed.

• Transactions of Materials Processing
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• v.20 no.6
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• pp.450-455
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• 2011

This paper presents an inverse design methodology for the cross section geometry of mold spring with a rectangular cross section as the starting material for a coiling process. The cross-sections of mold springs are universally rectangular, as the parallel sides minimize the possibility of failure under high service loads. Pre-coiled wires are initially designed to have a trapezoidal cross section, which becomes a rectangle by the coiling process. This study demonstrates a numerical exercise to predict changes in the sectional geometry in spring manufacture and to obtain the initial cross section which becomes the exact rectangle desired from the manufacturing process. Finite element analysis was carried out to calculate the sectional changes for various mold springs. Geometrical parameters were the widths at inner and outer radii, the inner and the outer corner radii, and the height. A partial least square regression analysis was carried out to find the main contributing factors for deciding initial design values. The height and the width mainly affected various initial parameters. The initial width at the inner radius was mostly affected by various specification parameters.

• Computers and Concrete
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• v.13 no.6
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• pp.765-780
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• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. In the present study, ANN models are developed in three categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is demonstrated through developed ANN models that geometry of the building and the sizes of the columns are significant parameters in the dynamic analysis of building frames. The testing dataset of these three models is used to obtain the empirical relationship between the height of the building and fundamental period of vibration and compared with the similar equations proposed by other researchers. Experiments are conducted on Mild Steel frames using uniaxial shake table. It is seen that the values obtained through the ANN models are close to the experimental values. The validity of ANN technique is verified by experimental values.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.