• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.84-87
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• 1999

This paper presents a preform design method that combines the analytic method and inference of known knowledge with neural network. The analytic method is a finite element method that is used to simulate backward extrusion with pre-defined process parameters. The multi-layer network and back-propagation algorithm are utilized to learn the training examples from the simulation results. The design procedures are utilized to learn the training examples from the simulation results. The design procedures are two methods the first the neural network infer the deformed shape from the pre-defined processes parameters. The other the network infer the processes parameters from deformed shape. Especially the latest method is very useful to design the preform From the desired feature it is possible to determine the processes parameters such as friction stroke and tooling geometry. The proposed method is useful for shop floor to decide the processes parameters and preform shapes for producing sound product.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.4
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• pp.39-45
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• 2012

In this paper, process conditions are investigated for elimination of the grain coarsening and improved material flow during forging process by both of experiments and FEM analysis. Particular interest has been given to understand role of preform shape on the grain coarsening behavior and magnitude of the hammer forging load. As the results of FEM simulation by using DEFORM-3D, the simulated forging loads were 2,200ton in the case of a machined bar which is machined from 65mm to 60mm diameter, and below 1,900ton in the case of machined preform, respectively. The use of preform has been beneficial for reduction of the forging load and elimination of the grain coarsening. However, in the case of as received bar and the round bar, which was machined to 2.5mm thickness in surface layer, some degree of local grain coarsening behavior has been observed. The optimized preform shape could be properly designed by applying the FEM simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.678-685
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• 1999

A UBET program is developed for determining flash the optimum sizes of preform and initial billet in plane-strain closed-die forging. The program consists of forward and backward tracing processes. In the forward program, flash, die filling and forging load are predicted. In backward tracing process the optimum dimensions of initial billet and preform are determined from the final-shape data based on flash design. Experiments are carried out with pure plasticine billets ar room temperature. The theoretical predictions of forging load and flow pattern are in good agree-ment with the experimental results.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03a
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• pp.26-29
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• 1999

Process design for elliptically shaped deep drawing products is various according to size shape and specification of products. This study presents two approaches to design the preform that is a key process for elliptically shaped products, One of these is that cross-section of punch is circular. Another is that for the improvement of characteristics for final products the cross-section of the punch is similar to rectangular shape. After forming the preform process design of top-part drawing is the same. In the study blank shape and dimension are obtained by applying a numerical formula and surface area constancy.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.29-35
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• 2007

The main objective of this paper is to propose the optimal design method of forging process using genetic algorithm. Design optimization of forging process was doing about one stage and multi stage. The objective function is considered the filling of die. The chosen design variables are die geometry in multi stage and initial billet shape in one stage. We performed FE analysis to simulated forging process. The optimized preform and initial billet shape was obtained by genetic algorithm and FE analysis. To show the efficiency of GA method in forging problem are solved and compared with published results.

• Journal of computational fluids engineering
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• v.16 no.1
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• pp.22-29
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• 2011

In this study, the glass fiber drawing from a silica preform in the furnace for the optical fiber manufacturing process is numerically simulated by considering the radiative heating of cylindrically shaped preform. The one-dimensional governing equations of the mass, momentum, and energy conservation for the heated and softened preform are solved as a set of the boundary value problems along with the radiative transfer approximation between the muffle tube and the deformed preform shape, while the furnace heating is modeled by prescribing the temperature distribution of muffle tube. The temperature-dependent viscosity of silica plays an important role in formation of preform neck-down profile when the glass fiber is drawn at high speed. The calculated neck-down profile of preform and the draw tension are found to be reasonable and comparable to the actual results observed in the optical fiber industry. This paper also presents the effects of key operating parameters such as the muffle tube temperature distribution and the fiber drawing speed on the preform neck-down profile and the draw tension. Draw tension varies drastically even with the small change of furnace heating conditions such as maximum heating temperature and heating width, and the fine adjustment of furnace heating is required in order to maintain the appropriate draw tension of 100~200 g.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.113-116
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• 1995

In this experimental study,aluminum hotforging was conduct to get superior pistion to cast piston. Cast structure of billet is destroyed, harmful defects is removed by forging process. We proposed the direction od die design by observing formability of product according to die shape. The microstructure of forged products with different preform was investigated to determine inital billet shape. We proposed appropriate heat treatment condition for improvement of mechanical properties.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.527-528
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• 2007

• Transactions of Materials Processing
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• v.11 no.2
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• pp.165-170
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• 2002

The preform design of forging processes plays a key role in improving product qualities, such as defect prevention, dimensional accuracy and mechanical strengths. In the industry, preforms are generally designed by the iterative trial-and-error approach, but it results in significant tooling cost and time. It is thus necessary to minimize lead-time and human intervention through an effective preform design method. In this paper, the equi-potential lines designed in the electric field are introduced to find the preform shape, and then the optimization process is used to choose the equi-potential lines that will keep the die wear to a minimum Because, in the forging process, the die wear is a function of various important factors, such as forming stress and strain, microstructure and mechanical properties of a Product.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.118-124
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• 1998

The die wear is one of the main factors affecting die accuracy and tool lifetime. It is desired to reduce die wear by developing simulation method to predict wear based on process variables, and then optimizing the process. Therefore, this paper describes methodology of preform design for minimizing wear of finisher die in multi-stage cold forging processes. The finite element method is combined with the routine of wear prediction. The cold forging process is analyzed using developed simulation method. In order to obtain preform to minimize die wear, the Flexible Polyhedron Search(FPS) algorithm is used. The optimal preform shape is found from iterative deformation analysis and wear calculation.