• Steel and Composite Structures
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• 제36권4호
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• pp.417-426
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• 2020

Drilling processes in fiber-reinforced polymer composites are essential for the assembly and fabrication of composite structural parts. The economic impact of rejecting the drilled part is significant considering the associated loss when it reaches the assembly stage. Therefore, this article tends to illustrate the effect of cutting conditions (feed and speed), and laminate thickness on thrust force, torque, and delamination in drilling woven E-glass fiber reinforced epoxy (GFRE) composites. Four feeds (0.025, 0.05, 0.1, and 0.2 mm/r) and three speeds (400, 800, and 1600 RPM) are exploited to drill square specimens of 36.6×36.6 mm, by using CNC machine model "Deckel Maho DMG DMC 1035 V, ecoline". The composite laminates with thicknesses of 2.6 mm, 5.3 mm, and 7.7 mm are constructed respectively from 8, 16, and 24 glass fiber layers with a fiber volume fraction of about 40%. The drilled specimen is scanned using a high-resolution flatbed color scanner, then, the image is analyzed using CorelDraw software to evaluate the delamination factor. Multi-variable regression analysis is performed to present the significant coefficients and contribution of each variable on the thrust force and delamination. Results illustrate that the drilling parameters and laminate thickness have significant effects on thrust force, torque, and delamination factor.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.49-52
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• 1996

The control of diamond turning is usually achieved through a laser-interferometer feedback of slide position. The limitation of this control scheme is that the feedback signal does not account for additional dynamics of the tool post and the material removal process. If the tool post is rigid and the material removal process is relatively static, then such a non-collocated position feedback control scheme may surfice. However, as the accuracy requirement gets tighter and desired surface contours become more complex, the need for a direct tool-tip sensing becomes inevitable. The physical constraints of the machining processprohibit any reasonable implementation of a tool-tip motion measurement. It is proposed that the measured force normalto the face of the workpice can be filterd through an appropriate admittance transfer function to result in the estimated depth of cut. This can be compared to the desired depth of cut to generate the adjustment cotnrol action in addition to position feedback control. In this work, the design methodology on the admittance model-based control with a conventional controller is presented. Based on the empirical data of the cutting dynamics, simulation results are shown.

• 한국정밀공학회지
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• 제11권1호
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• 한국기계가공학회지
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• 제14권6호
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• pp.1-6
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• 2015

Tool condition monitoring plays one of the most important roles in the improvement of both machining quality and productivity. In this regard, various process signals and monitoring methods have been developed. However, most of the existing studies used cutting force or acoustic emission signals, which posed risks of interference with the machining system in dynamics, fixturing, and machining configuration. In this study, a feed motor current signal is used as a process signal representing process and tool states in tool breakage monitoring based on an adaptive autoregressive model and unsupervised neural network. From the experimental results using various cases of tool breakage, it is shown that the developed system can successfully detect tool breakage before two revolutions of the spindle after tool breakage.

• 소성∙가공
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• 제15권4호
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• pp.319-325
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• 2006

The laser forming process is a new flexible forming process without forming tools and external force, which is applied to various fields of industry. Especially, applications of the laser forming process focused on cutting, welding and marking process. In this paper, the laser bending process of sheet metal which is heated by laser beam and formed by internal stress is simulated by using thermo elastic-plastic analysis model. Based on the result of FE-analysis, the laser bending machine is made to obtain reliable data for sheet bending. Under the same condition as FE-analysis, the laser bending experiment has been performed to ver 펴 the result of FE-analysis and good agreement has been obtained between FE-analysis and experiments. Additional laser bending experiments have been performed to evaluate the laser bending machine.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.329-329
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• 2000

In this paper, a spindle system using an electromagnetic exciter is proposed to compensate a spindle disturbance such as unbalance and machining force etc A spindle compliance can be readily varied with a disturbance which is generated by the interact ion between the spindle / workpiece structure and the cutting process dynamics. The varied compliance is one of the major constraints that deteriorates the surface quality of workpiece. This paper suggests a compliance compensation by using the EME in the proposed spindle system. To compensate the varied compliance, firstly a spindle system modeling was conducted by using the bond graph. Then the model is simulated by numerical analysis method and an optimal EME position is determined to compensate a disturbance effectively through simulation, which makes the bearing load to be minimized

• 한국정밀공학회지
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• 제13권7호
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• pp.158-166
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• 1996

In this study, a flexible disk grinding process is applied in order to produce high precision product. A new model was developed considering feed motion along horizontal and vertical direction. Different types of feed speed variation was tested with respect to distinct process stages in order to achieve flat surface. It was observed that highest order polynomial form for both horizontal and vertical feed speed variation among the proposed categories produced surface close to flat one. Disk deflection trend during the process was visualized confirming the proposed scheme. Cutting force and VRR(volume removal rate) was observed as an aid to process planning.

• 대한기계학회논문집A
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• 제21권6호
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• pp.988-994
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• 1997

The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, digital image of time series sequence was acquired by taking advantage of optical technique. Mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR(auto regressive) model was selected for system model and fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, it was found that there was a system stability.

• 기술혁신연구
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• 제15권2호
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• pp.123-152
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• 2007

The striking characteristic of the contemporary global security environment is that the nature of threats has become diverse and complex. For example, transnational and non-military threats including terrorism and proliferation of weapon of mass destruction has increased. In this security environment, Advanced countries funnel their investments for defense budgets into the assurance of key force capability and R&D of cutting-edge core technologies, in consideration of future battlefield environments so as to get an edge on not only defense science and technology but also intelligence capabilities. As shown by past practices of the korea's defense acquisition, the ministry of national defense has tried to enhance its force capabilities in the short-term by purchasing foreign weapon systems rather than by investing in domestic R&D. Accordingly, the technological gaps between the korea and advanced countries were widened due to both insufficient investment in development of domestic technologies and avoidance of technological transfer by advanced countries. Thus, for the effective execution of the R&D budget and the successful performance of the projects, the importance of selection, management and evaluation of the R&D projects is emphasized. So, The objective of this study is that the analysis of the proposal-selection evaluation system for the realization of the successful defense core technology R&D projects. This study focused on the improvement of the proposal-selection evaluation model which can be applicable to the national defense core R&D projects. Using the improved proposal-selection evaluation system, we propose a model to enhance the reliability of the national defense core technology R&D project evaluation system.

• Steel and Composite Structures
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• 제34권5호
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.