• KSTLE International Journal
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• v.3 no.2
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• pp.95-100
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• 2002

Electrochemical discharge machining is a very recent technique for non-conducting materials such as ceramics and glasses. ECDM is conducted in the NaOH solution and the cathode electrode is separated from the solution by H$_2$ gas bubble. Then the discharge is appeared and the non-conductive material is removed by spark and some chemical reactions. In the ECDM technology, the H$_2$ bubble control is the most important factor to stabilize the discharging condition. In this paper we proposed the discharge peak monitoring/discharging duty feedback algorithms fur the discharge stabilization and the feasibility of this algorithm is verified by various pattern machining in the constant preload conditions for the cathode electrode.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.29-34
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• 2012

This study describes the selection of optimum machining conditions for a high-hardness resin by using a large 5-axis machine. The experiments were conducted to examine the main factors that affect the surface roughness, such as the spindle speed, axial and radial depths of the cut, and pattern of the cutter path. To analyze the experiment results, the factor with the biggest impact on machining was determined using the smaller-the-better characteristic of the Taguchi method; the effectiveness of the experiment was then confirmed by verifying the selected optimum machining condition.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.62-67
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• 2003

The grinding force generated during the grinding process causes an elastic deformation of the workpiece, grinding wheel, and machine system. Thus, the true depth of cut is always smaller than the apparent depth of cut. This is known as machining elasticity phenomenon. The machining elasticity parameter is defined as a ratio between the true depth of cut and the apparent depth of cut. It is an important factor to understand the material removal mechanism of the grinding process. To increase productivity, the value of this machining elasticity parameter must be large. Therefore, it is essential to know the characteristics of this parameter. The objective of this research is to study the effect of the major grinding conditions, such as table speed, depth of cut, on this parameter experimentally, Through this research, it is found that this parameter value is increasing when the table speed is decreasing or the depth of cut is increasing. Also, this parameter value depends on the grinding mode (up grinding, down grinding).

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.17-22
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• 2019

The method of electrical discharge machining (EDM), one of the processing methods based on non-traditional manufacturing procedures, is gaining increased popularity, since it does not require cutting tools and allows machining involving hard, brittle, thin and complex geometry. This present investigation details the determination of optimum process parameter to attain the better machining performance in EDM of AISI 4340 steel with graphite as a tool electrode. The experimental combinations are planned and analyzed by Taguchi's design of experiments approach. To predict the optimal condition, the experiments are conducted by using Taguchi's L27 orthogonal array. The influence of process variables such as discharge current, pulse on and pulse off time, voltage and spark speed were investigated to control the various desired performance measures such as surface roughness. Analysis of Variance (ANOVA) has to be performed to know the magnitude of each factor. Investigations indicate that the surface roughness is strongly depend on pulsed current.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.11-18
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• 2008

Surface roughness is an important factor to evaluate machined parts in precision machining. This is the major measure of surface quality. This research sets up experiments to select the factors which affect surface roughness in the machining of inclined planes of aluminum. The levels of the selected experimental factors are chosen to evaluate the relationship between the surface roughness of the machined parts and machining parameters. This is to find out the optimal machining condition in the inclined planes. The objective of this research is to improve the surface roughness of the machined products by using the ANOVA analysis. The factors for the experiments are cutting speed, feed rate, cutting depth, and cutting width. The experimental levels of the factors are two for the cutting depth and width. For the cutting speed and feed rate, their levels are three because they are more sensitive for the surface roughness than the other two. The inclined planes are machined by 5-axis machining equipment.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.9-16
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• 2015

The machining-chatter stands for a sudden relative vibration appeared between a material and a tool while processing with a machine. This chatter is key factor that seriously affects the quality of processed materials as well as being a factor which causes serious damages to the tool and the machine. This study is related to the monitoring and smart control of chatter problem that can compensate machining-chatter faster and produce processed goods with more precision by autonomous compensation. The above-mentioned machining-chatter compensator includes the chatter vibration sensor and the chatter compensator that estimates the compensation value according to the sensor detecting the chatter vibration of machine-tool and the chatter vibration detected from the sensor while having a feature of being organized by interlocking with the machine-tool controller.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.1
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• pp.54-61
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• 2011

Ball screw systems are largely used in industry for motion control and motor applications. But the problem of noise, which really perplexes us, is highly correlated with the quality in ball screw systems all the way. In this paper, machining process parameters were evaluated in respects of technique, business, produce and quality to verify which impact influences the noise most. In order to adjust and compare, two comparison groups were set with the present parameters bench mark. Different ball screws were produced as specimens for the noise tests. Through comparing the noise performance of different parameters in the machining process respectively, a group of optimized machining process parameters were obtained. Another noise test was proceeded to know how noise performance was improved by optimizing the machining process parameters. At last, surface roughness tests have been done to know how surface roughness improved by optimization. The improvement of surface roughness is the main factor influences the noise performances.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.1
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• pp.26-32
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• 2012

Polishing is one of the important methods in manufacturing of Si wafers and in thinning of completed device wafers. This study will report the characteristic of wafer according to processing time, machining speed and pressure which have major influence on the abrasion of Si wafer polishing. It is possible to evaluation of wafer abrasion by load cell and infrared temperature sensor. The characteristic of wafer surface according to processing condition is selected to use a result data that measure a pressure, machining speed, and the processing time. This result is appeared by the characteristic of wafer surface in machining condition. Through that, the study cans evaluation a wafer characteristic in variable machining condition. It is important to obtain optimal condition. Thus the optimum condition selection of ultra precision Si wafer polishing using load cell and infrared temperature sensor. To evaluate each machining factor, use a data through each sensor. That evaluation of abrasion according to variety condition is selected to use a result data that measure a pressure, machining speed, and the processing time. And optimum condition is selected by this result.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.125-130
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• 2017

In this study, the influence of various factors on surface roughness was investigated using the Taguchi experimental method through high-speed machining processing. Feed rate, pitch, tool diameter, and depth of cut are widely applied to high-speed machining conditions for mold production. Each of these factors was implemented and classified into three levels; then, after high speed machining, surface roughness was measured, the S/N ratio was analyzed, and the influence on the surface roughness of control factors was analyzed quantitatively by ANOVA. Using this information, a mathematical model for predicting surface roughness was derived from multiple regression analysis. This mathematical model enables the surface roughness value after high-speed machining to be predicted at the production stage, before machining, for a wide range of machining conditions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.551-557
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• 2009

A development of smart materials is becoming a prominent issue on present industries. A smart material, included in functions, is needed for micro fabrication. A shape memory alloy(SMA) in a smart material is best known material. Ni-Ti alloy, composed of nikel and titanium is one of the best shape memory alloy(SMA). Nitinol SMA is used for a lot of high tech industry such as aero space, medical device, micro actuator, sensor system. However, Ni-Ti SMA is difficult to process to make a shape and fabrications as traditional machining process. Because nitinol SMA, that is contained nikel content more than titanium content, has similar physical characteristics of titanium. In this paper, the characteristics of ECM grooving process for nitinol SMA are investigated by experiments. The experiments in this study are progressed for power, gap distance and machining time. The characteristics are found each part. Fine shape in work piece can be found on conditions; current 6A, duty factor 50%, gap distance 15%, gap distance $15{\mu}m$, machining time 10min.