• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.36-43
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• 2019

Turning, a main machining process, is a widespread process in metal cutting industries. Many researchers have investigated the effects of process parameters on the machining process. In the turning process, input variables including cutting speed, feed, and depth of cut are generally used. Surface roughness and electric current consumption are used as output variables in this study. We construct a simulation model for the turning process using a neural network, which predicts the output values based on input values. In the neural network, obtaining the appropriate set of weights, which is called training, is crucial. In general, back propagation (BP) is widely used for training. In this study, techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) as well as BP were used to obtain the weights in the neural network. Particularly, two combined techniques of ACO_BP and PSO_BP were utilized for training the neural network. Finally, the performances of the two techniques are compared with each other.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.28-31
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• 2001

Recently, in order to satisfy the consumer's demand the life cycle and the lead-time of a product is to be shortened. It is thus important to reduce the time and cost in manufacturing trial products. Several techniques have been developed and successfully commercialized in the market RPM(Rapid Prototyping and Manufacturing). However, most commercial systems currently use resins or waxes as the raw materials. So, the limited mechanical strength for functional testing is regarded as an obstacle towards broader application of rapid prototyping techniques. To overcome this problems, high-speed machining technology is being investigated worldwide for rapid manufacturing and even for direct rapid tooling application. In this paper, some fundamental experiments and analyses are carried out to obtain the filling time, materials, method, and process parameters for HisRP process. HisRP is a combination process using high-speed machining technology with automatic filling. In filling process, Bi58-Sn alloy is chosen because of the properties of los-melting point, low coefficient of thermal expansion and enviromental friendship. Also the use of filling wire is of advantage in term of simple and flexible mechanism. Then the rapid manufacturing product, for example a skull, is machined for aluminum material by HisRP process with an automatic set-up device of 4-faces machining.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.88-94
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• 2002

Recently, the life cycle and the lead-time of a product are to be shortened in order to satisfy consumer's demand. It is thus important to reduce the time and cost in manufacturing trial products. Several technique have been developed and successfully commercialized in the market of RPM(Rapid Prototyping and Manufacturing). However, most commercial systems currently use resins or waxes as the raw materials. So, the limited mechanical strength for functional testing is regarded as an obstacle towards broader application of rapid prototyping techniques. To overcome these problems, high-speed machining technology is being investigated worldwide for rapid manufacturing and even for direct rapid tooling application. In this paper, some fundamental experiments and analyses are carried out to obtain the filling time, materials, method, and process parameters for HisRP(High-Speed RP) process. HisRP is a new RP process that is combined high-speed machining with automatic filling. In filling process, Bi58-Sn alloy is chosen as filling material because of the properties of low-melting point, low coefficient of thermal expansion and no harm to environment. Also the use of filling wire it if advantage since it needs simple and flexible mechanism. Then the rapid product, for example a skull, is manufactured for aluminum material by HisRP process with an automatic set-up device thor 4-faces machining.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.73-81
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• 1996

This paper presents a general procedure for the selection of the machining parameters for a given machine which provides the maximum material removal rate using a Genetic Algorithms(GAs). Some constraints were given in order to achieve desired surface integrity and cutting tool life conditions as wel as to protect machine tool. Such a constrained problem can be transformaed to unconstrained problem by associating a penalty with all constraint violations and the penalties are included in the function evaluation. Genetic Algorithms can be used for finding global optimum cutting conditions with respect to the above cost function transformed by pennalty function method. From the demonstration of the numerical results, it was found that the near optimal conditions could be obtained regardless of complex solution space such as cutting environment.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.74-78
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• 2008

High-speed tool steels are extensively used in tooling industries for manufacturing cutting tools, forming tools, and rolls. Electrical discharge machining (EDM) has been found to be an effective process for machining these extremely hard and difficult-to-cut materials. Extensive research has been conducted to identify the optimum machining parameters for EDM with different tool steels. This paper presents a fundamental study of the surface characteristics of SKH-51 tool steel machined by micro-EDM, with particular focus on obtaining a better surface finish. An RC pulse generator was used to obtain a better surface finish as it produces fine discharge craters. The main operating parameters studied were the gap voltage and the capacitance while the resistance and other gap control parameters were kept constant. A negative tungsten electrode was used in this study. The micro-EDM performance was analyzed by atomic force microscopy to determine the average surface roughness and the distance between the highest peak and lowest valley. The topography of the machined surface was observed using a scanning electron microscope and a digital optical microscope.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.778-781
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• 2004

As the technique of high-speed end-milling is widely adopted to in machining field. The investigation for microscopic precision of workpiece is necessary for machinability evolution. In this study, cutting force, cutting temperature and microhardness were investigated to evaluate damaged layer in conventional machining and high-speed machining. Damaged layer was measured using optical microscope. The thickness of damaged layer depends on cutting process parameters, specially feed per tooth and radial depth. It is obtained that the characteristics of damaged layer is high-speed machining better than conventional machining.

• Journal of Industrial Technology
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• v.16
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• pp.257-265
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• 1996

When machining of a free-form surface with a ball endmill it is very important to select proper cutting conditions considering the geometrical shape of a workpiece to make the production more effective and reduce the machining time. Even though the same cutting conditions and materials are used, the cutting system of different geometry part machining shows the different static/dynamic characteristics. In this study, through various cutting experiments, we can construct the data base of stable cutting conditions for the machining of a Zine Alloy. We can get some relational plots between the optimal feedrates and classified shape features and parameters. On the basis of these results, we can develop the feedrate optimization program OptiCode. The developed program make it possible to reduce the cutting time and increase the machining accuracies.

• Proceedings of the Materials Research Society of Korea Conference
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• 2012.05a
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• pp.81.2-81.2
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• 2012

To fabricate a metal mold for injection molding, hot-embossing and imprinting process, mechanical machining, electro discharge machining (EDM), electrochemical machining (ECM), laser process and wet etching ($FeCl_3$ process) have been widely used. However it is hard to get precise structure with these processes. Electrochemical etching has been also employed to fabricate a micro structure in metal mold. A through mask electrochemical micro machining (TMEMM) is one of the electrochemical etching processes which can obtain finely precise structure. In this process, many parameters such as current density, process time, temperature of electrolyte and distance between electrodes should be controlled. Therefore, it is difficult to predict the result because it has low reliability and reproducibility. To improve it, we investigated this process numerically and experimentally. To search the relation between processing parameters and the results, we used finite element simulation and the commercial finite element method (FEM) software ANSYS was used to analyze the electric field. In this study, it was supposed that the anodic dissolution process is predicted depending on the current density which is one of major parameters with finite element method. In experiment, we used stainless steel (SS304) substrate with various sized square and circular array patterns as an anode and copper (Cu) plate as a cathode. A mixture of $H_2SO_4$, $H_3PO_4$ and DIW was used as an electrolyte. After electrochemical etching process, we compared the results of experiment and simulation. As a result, we got the current distribution in the electrolyte and line profile of current density of the patterns from simulation. And etching profile and surface morphologies were characterized by 3D-profiler(${\mu}$-surf, Nanofocus, Germany) and FE-SEM(S-4800, Hitachi, Japan) measurement. From comparison of these data, it was confirmed that current distribution and line profile of the patterns from simulation are similar to surface morphology and etching profile of the sample from the process, respectively. Then we concluded that current density is more concentrated at the edge of pattern and the depth of etched area is proportional to current density.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.48-51
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• 2004

The estimation of NC machining time is of significance since it provides shop floor engineers with information for the determination of the productivity of the floor as well as process schedules. The NC machining time commonly depends on NC programs since they have various important information such as tool positions, feed rates, and other miscellaneous functions. Thus, nominal NC machining time can be easily acquired based on the programs. Actual machining time, however, cannot be simply obtained because of the dynamic characteristics of a NC machine controller such as acceleration and deceleration. Hence, this study presents a NC machine time estimation model for sculptured surfaces, considering the dynamic characteristics. The estimation model uses the distribution of NC blocks according to a factor influencing the machining time. Finally, machining time is estimated by a statistical machining time estimation model representing the relationship between the block distribution and the machining time. The parameters in the model are searched out by a genetic algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.291-295
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• 2002

Ceramics are very difficult-to-cut materials because of its high strength and hardness. Their machining process can be characterized by cracking and brittle fracture. Generally, ceramics are machined using traditional method such as grinding and polishing. However, such processes are generally costly and have low material removal rate. In this paper, to develop machinable ceramics those have good machinability without losing their material properties, machinability evaluations are performed by applying the experimental design method. In this paper, to evaluate the machinability of the developed ceramics, various workpieces are machined on the CNC machining center, and surface roughness are measured under predefined process parameters obtained using Taguchi method. And the experimental results are investigated to derive optimum cutting parameters for the given materials.