• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.675-682
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• 2020

Multi-wire sawing is the prominent technology employed to cut hard material ingots into wafers. This paper aimed to research the effect of diamond toughness index on the cutting performance of electroplated diamond wire. Three different toughness index of diamond abrasives were used to manufacture electroplated diamond wires. The cutting performance of electroplated diamond wire is verified through experiments, in which sapphire ingot are cut using single wire sawing machine. A single wire saw for constant load slicing is developed for the cutting performance evaluation of electroplated diamond wire. Choosing the cutting depth, total cutting depth, cutting force and wear of electroplated diamond wires as evaluation parameters, the performance of electroplated diamond wire is evaluated. The results of this study showed that there was a significant direct relationship between the toughness index of diamond abrasives and the cutting performance. Results demonstrated that diamond abrasive with a high toughness index showed higher cutting performance. However, all diamond abrasives showed similar cutting performance under low load conditions. The results of this paper are useful for the development of cutting large diameter ingots and cutting high hardness ingots at high speed.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.81-87
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• 2000

A variable cutting speed control model was developed to be implemented for the flexible disk grinding process Control algorithm was based on the error referred by the discrepancy between current disk angle and intended one that are pro-posed to produce desired resulting depth of cut. Controller was implemented in two different aspect One was to initiate the control law from the beginning while the other was to activate as soon as the disk start to produce ground surface i.e. The beginning of the between edges stage. Several performance analysis were conducted comparing various process parameters such as cutting force disk angle depth of cut and disk speed with respect to process transition time Tentative results revealed that controller implemented from the earlier stages of the process showed better performance than the other revealed that controller implemented from the earlier stages of the process showed better performance that the other.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.95-103
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• 1995

Recently the trends toward reduction in size of industrial products have increased the application of micro drilling. But micro drilling has still much difficulty so that the needs for active control which give adaptation to controller are expanding. In this paper initial cutting condition was determined for some sorkpieces by experiment and GA-based Fuzzy controller was devised by genetic algorithms and fuzzy inference. The fuzzy inference has been applied to the various prob- lems. However the determination of the membership function is one of the difficult problem. So we introduce a genetic algorithms and propose a self-tuning method of fuzzy membership function. Based on this intelligent control, automation of micro drilling was carried out like the cutting process of skilled machinist.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.25-31
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• 2022

Recently, investment in the aerospace industry has increased, and titanium alloys have been widely adopted for manufacturing parts in the aerospace industry. The Ti-6Al-4V alloy has high strength in high-temperature and high-pressure environments and is evaluated as a material with excellent heat, corrosion, and abrasion. However, titanium alloys are expensive, difficult to cut, and possess a large cutting load during the drilling process. In this study, the cutting force generated in the drilling process of Ti-6Al-4V alloy was verified via finite element analysis (FEM) and cutting force measurement experiments. A structural analysis was performed based on the cutting analysis data to verify the plastic deformation occurring during the drilling process of cylindrical Ti-6Al-4V alloy aircraft parts. Methods were proposed to predict the amount of deformation that occur during the manufacturing process of titanium-alloy aircraft parts and control the external environment, to minimize the amount of deformation.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.47-52
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• 2015

In this paper, the performance of uncoated- and Titanium nitride aluminium TiAlN-PVD coated- carbide twist drills were investigated when drilling aluminium alloy, Al 6061. This research focuses on the optimization of drilling parameters using the Taguchi technique to obtain minimum surface roughness and thrust force. A number of drilling experiments were conducted using the L9 orthogonal array on a CNC vertical machining center. The experiments were performed on Al 6061 material l blocks using uncoated and coated HSS twist drills under dry cutting conditions. Analysis of variance(ANOVA) was employed to determine the most significant control factors. The main objective is to find the important factors and combination of factors influence the machining process to achieve low surface roughness and low cutting thrust force. From the analysis of the Taguchi method indicates that among the all-significant parameters, feed rate are more significant influence on surface roughness and cutting thrust than spindle speed.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.1-13
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• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1382-1385
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• 1993

In order to improve productivity, an intelligent control system is presented in the pater. In this intelligent control system, a feedforward neural network and a fuzzy feedback mechanism are adopted to achieve a constant milling force with an adjustable feedrate under a variety of cutting conditions in milling operations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.329-334
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• 2002

High-speed machining is one of the most effective technology to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut, feed rate, spindle revolution and cutting force are control factors. The effect of the control factors on machining accuracy is discussed for the results of surface roughness and machining error in Z-direction for the high speed machining of STD11.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.713-723
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• 1995

In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the technology for adaptively optimizing the cutting conditions to maximize the material removal rate in face milling operations is proposed using the exterior penalty function method combined with multilayered neural networks. Two neural networks are introduced ; one for estimating tool were length, the other for mapping input and output relations from experimental data. Then, the optimization of cutting conditions is adaptively implemented using tool were information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine and finish cutting.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.63-72
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• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.