• KSTLE International Journal
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• 제3권1호
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• pp.17-22
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• 2002

Roughing of tool steel in its hardened state represents a real challenge in the die and meld industry and process improvement depends on research of tool material, coating technique, and lubrication. However, roughing of hardened steels generates extreme heat and without coolant flooding, tool material cannot withstand the high temperature without choosing the right tools with proper coating. This research conducted milling tests using coated ball end mills to study effects of cutting conditions and geometric parameters of ball end mills on the machinability of hardened tool steel. KP4 steel and STD 11 heat treated steels were used in the dry cutting as the workpiece and TiAIN coated ball end mills with side relief angle of 12$^{\circ}$ was utilized in the cutting tests. Cutting forces, tool wear, and surface roughness were measured in the cutting tests. Results from the experiments showed that 85 m/min of cutting speed and 0.32 mm/rev of feed rate were optimum conditions for better surface finish during rough cutting and 0.26mm/rev with the same cutting speed are optimum conditions in the finish cutting.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.643-648
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• 2002

In the cutting of plate steel, the quality of the cut surfaces is strongly dependent on the cutting conditions such as cutting speed, kerf width, plate thickness, length of tip-specimen and oxygen pressure etc. the cutting tests of plate steel were carried out using CNC gas cutting machine. this paper deals with cutting characteristics of plate steel using CNC cutting machine. the width of cutting entrance and exit, the surface roughness of cutting surfaces and the cutting surface are examined at various cutting conditions.

• International Journal of Safety
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• 제5권2호
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• pp.34-37
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• 2006

As part of an effort to systematize the operation planning for cutting processes, the neural network method has been applied to model the process of selecting cutting conditions and subsequently to arrive at effective and safe cutting conditions through learning during training of the model. New cutting conditions that are more effective and safer for the given circumstance are obtained. The proposed algorithm deletes the old information previously learned, and then makes the network make at improvement by learning. As a result, the new algorithm provides useful cutting conditions for safer manufacturing environments. A variety of simulation cases illustrate the performance of the proposed methodology. The simulation results are provided and discussed.

• 한국기계가공학회지
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• 제20권10호
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• pp.9-18
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• 2021

The cutting force in a cutting simulation is determined by the cutting conditions, such as cutting speed, feed rate, and depth of cut. The cutting force changes, depending on the material and cutting conditions, and is affected by the heat generated during cutting. The physical properties for predicting the cutting force use constitutive equations as functions of the hardening term, rate-hardening term, and thermal-softening term. To accurately predict the thermal properties, it is necessary to accurately predict the thermal-softening coefficient. In this study, the thermal-softening coefficient was determined, and the cutting force was predicted, using the response-surface method with the cutting conditions and the thermal-softening coefficient as factors.

• 한국기계가공학회지
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• 제8권3호
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• pp.74-81
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• 2009

At present, industries and researchers are looking for ways to reduce the use of lubricants because of ecological and economical reasons. Therefore, metal cutting is to move toward dry cutting or semi-dry cutting. One of the technologies is known as MQL machining. This paper presents an investigation into MQL machining with the objective of evaluating cylindricity and cooling effect for the turning process of SM45C. To reach this goal, cylindrical-outer-diameter turning experiments are carried out according to cutting conditions with fluid, MQL and dry machining methods. A cutting force, tool-shank temperature and cylindricity of workpiece are measured and analyzed. The correlation between cutting conditions and cylindricity are evaluated according to cooling lubricant environments.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.144-149
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• 2008

This study presents the selection of cutting conditions in high speed pipe cutting machine for the better quality. A high speed pipe cutting machine which uses a rotary knife can make good quality products in short time. But, the machine is much sensitive by cutting conditions because of the complicated mechanism. In this reason, many experiments for cutting condition selection are necessary to improve quality of production. This study carried out cutting experiments with the three factors that are cutting RPM, cutting force and pooling force. 2-dimensional profile measuring instrument is used to measure which is represented by ${\Delta}h$, a sum of burr and collapse height. The effects of factors are analyzed by using MINITAB, the commercial software.

• 한국정밀공학회지
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• 제14권2호
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• pp.169-177
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• 1997

In this study, investigated are the effects of tool rake angles and the change of cutting conditions on the specific cutting pressure in face milling. The cutting force in face milling is predicted from the double cutting edge model in3-dimensional cutting. Conventional specific cutting pressure model is modified by considering the variation of tool rake angles. Effectiveness of the modified cutting force model is verified by the experiments using special face milling cutters with different cutter pockets and various rake angles. From the comparison of the presented model and the specific cutting pressure, it is shown that the axial force can be predicted by the tangential force, radial force and geometric conditions. Also, the rela- tionship between specific cutting pressure and cutting conditions including feedrate, cutting velocity and depth of cut is studied.

• 한국정밀공학회지
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• 제21권10호
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• pp.20-25
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• 2004

Using the multiple regression analysis cutting forces of turning processes have been predicted based on the cutting conditions such as feed rate(f), depth of cut(d), and cutting velocity(v). The statistical inference of the equation was checked by ANOVA test. The validity of the proposed regression analysis was verified by two sets of cutting tests of 27 cutting conditions and the additional cutting tests of 18 cutting conditions. From the results of analytical and experimental studies, it was found that there was no significant difference between the measured and predicted cutting forces. Also, the shear and friction characteristics of turning processes were analyzed with predicted cutting forces.

• Journal of Welding and Joining
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• 제12권3호
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• pp.71-81
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• 1994

Laser cutting is experiencing a rising worldwide acceptance in the industry. Expert systems are necessary for the systematic arrangement and searching of experimental data existing in journal papers, job handbooks, etc.. This paper proposes an expert system for the selection of the appropriate laser cutting variables from the available database. Optimum cutting conditions according to the given cutting velocity were searched and qualitative comments which are difficult to be used as database variables were shown at each velocity using the binary and fuzzy inference. These comments could be informative to unskilled operators of the laser cutting process. Typical cutting conditions of the mild steel and stainless steel were included and the working range and quality variations were displayed graphically. The proposed algorithm was implemented in an IBM compatible personal computer as an expert system for CO$_{2}$ laser cutting to derive the optimum cutting conditions by using the turbo prolog.

• 한국정밀공학회지
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• 제15권6호
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• pp.79-89
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• 1998

In determining optimal cutting condition for face milling operation, tool wear is an important factor. For the purpose of establishing the relationship between various machining factors and tool wear, cutting tests have been performed. As a result, hardness and chemical composition of workpiece material, chemical composition and grain size of cutting tool and cutting speed have been selected as machining factors. In addition, relationship between feed rate and workpiece hardness has been observed. Prior to utilizing cutting conditions recommended by ‘Machining Data Handbook(MDH)’ as a knowledge base, an analysis for the validity of the MDH has been provided. Based on this analysis, tool life criteria applied by MDH has been modified. Finally, using MDH recommended data for neural network trainning, the results from the trained neural network for optimal cutting condition for some given workpiece and cutting tool can be used as reference cutting conditions.