• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.73-81
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• 1993

In recent years, mould industry in machining requires to increase machining productivity and to reduce costs, To adapt this trend it is necessary to optimize machine condition, Even though many researches in this area introduced various way to set the optimal condition, still there are not enough. Therefore this research was done to select the optimal cutting condition for industry, and to develop the computer program to select the optimal cutting condition automatically. The result of this research will contribute to increase machining productivity of various mould companies with the automatic selection of optimal cutting condition.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.31-40
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• 2003

In this paper, optimal cutting condition to minimize the form error in side wall machining with a flat end mill is studied. Cutting forces and tool deflection are calculated considering surface shape generated by the previous cutting such as roughing. Using the form error prediction method from tool deflection, optimal cutting condition considering form accuracy is investigated. Also, the effects of tool teeth number, tool geometry and cutting conditions on form error are analyzed. The characteristics and the difference of generated surface shape in up and down milling are discussed and over-cut free condition in up milling is presented. Form error reduction method through successive up and down milling is also suggested. The effectiveness and usefulness of the presented method are verified from a series of cutting experiments under various cutting conditions. It is confirmed that form error prediction from tool deflection in side wall machining can be used in optimal cutting condition selection and real time surface error simulation for CAD/CAM systems. This study also contributes to cutting process optimization for the improvement of form accuracy especially in precision die and mold manufacturing.

• Proceedings of the Optical Society of Korea Conference
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• 1990.02a
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• pp.37-41
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• 1990

The quality of cutting surface such as surface roughness, heat affected zone, serf width can be improved by controlling the parameters of cuting process. These parameters includes cutting velocity, laser beam power, material depth and assistant gas. Thermodynamic analysis and systematical experiments are attempted to pedict and determine the optimal cutting condition. There exists the optimal cutting condition to ensure high quality surface. Under this operation, the minimum surface roughness of the mild steel, the stainless steel and the titanium becomes 3.8${\mu}{\textrm}{m}$ 13${\mu}{\textrm}{m}$ and 10${\mu}{\textrm}{m}$ respectively.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.13-19
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• 2017

In modern industry, the machining process is very important for manufacturing various products. More than 80% of machining processes apply rough cutting. The target of this study is to establish the optimal condition of rough cutting using trochoidal motion for improving productivity. For research, the range of cutting conditions is defined by trochoidal motion. The cutting time and tolerance are measured and evaluated according to the cutting conditions of machining. Experimental data are utilized for comparing trochoidal motion and contouring. It is found that the cutting time of trochoidal motion is two times less than that of contouring with optimal cutting conditions. To conclude, trochoidal motion for rough cutting under appropriate cutting conditions improves productivity and shortens processing time significantly.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.6
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• pp.113-126
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• 1992

Recently the multi-kind, small-amount manufacturing system has been replacing the mass manufacturing system, and domestic machining inustry also is eager to absorb the new technology because of its high productivity and cost reduction. The optimization of the cutting condition has been a vital problem in the machining industry, which would help increase the productivity and raise the international competitiveness. It is intended in this study to investigate the machining costs per unit time which is essential to the analysis of the optimal cutting condition, to computer the cutting speed that lead to the minimum machining costs and the maximum production to suggest the cutting speed range that enables efficient speed cutting, and to review the machining economy in relation to cutting depth and feed. Also considered are the optimal cutting speed and prodution rated in rrelation with feed. It is found that the minimum-cost cutting speed increases and the efficient cutting speed range is reduced as machining cost per unit time increases since the cutting speed for maximum production remains almost constant. The machining cost is also lowered and the production rate increases as the feed increases, and the feed should be selected to satisfy the required surface roughness. The machining cost and production rate are hardly affected by the cutting depth if the cutting speed stays below 100m/min, however, they are subject to change at larger cutting depth and the high-efficient speed range also is restricted. It can be established an adaptive optimal cutting conditions can be established in workshop by the auto-selection progam for optimal operation. It is expected that this method for choosing the optimal cutting conditions might contribute to the improvement of the productivity and reduced the cost. It is highly recommended to prepare the optimal cutting conditionthus obtained for future use in the programing of G-function of CNC machines. If proper programs that automatically select the optimal cutting conditions should be developed, it would be helpful to the works being done in the machine shops and would result in noticeable production raise and cost reduction.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.4
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• pp.59-64
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• 2006

High Speed Machining(HSM) reduces machining time and improves surface accuracy because of the high cutting speed and feedrate. Development of HSM makes it allowable to machine difficult-to-cut material and use small-size-endmill. It is however limited to cutting condition and tool material. In the machining operation, it is important to check main parameter of tool life and select optimal cutting condition because tool breakage can interrupt progression of operation. In this study, cutting parameters are determined to 3 factors and 3 levels which are a spindle speed, a feedrate and a width of cut. Experiment is designed to orthogonal array table for L9 with 3 outer array using Taguchi method. Also, it is proposed to inspect significance of the optimal factors and levels by ANOVA using average of SN ratio for tool life. Finally, estimated value of SN ratio in the optimal cutting condition is compared with measured one in the floor shop and reduction of loss is predicted.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.965-969
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• 1997

Due to the high feed rate,high speed machining (HSM) provide a great potential of rationalization for the machining Dies and Moulds. But determination of cutting condition is very difficult, because cutting mechanism of high speed machining is very complicated,especially using ball end-mill. This paoer gives a report on selection of the optimal cutting condition to improve the machining efficiency, And optimal machining condition is determined through the cutting force, FFT analysis of cutting force and surface roughness according to the cutting condition. Based on this experiment result,wear process and machining characteristics are evaluated.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2225-2233
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• 1994

In order to improve the cutting ability of face mill, a model for optimal cutter shape was developed to minimize resultant cutting force by combing cutting force model and optimal technique. Wear test and surface roughness test for optimized and conventional cutter were performed. The new optimized cutter shows longer tool life of 2.29 times than conventional cutter in light cutting condition and 2.52 times in heavy cutting condition. The surface roughness of workpiece by optimized cutter is improved in heavy cutting condition, but deteriorated in light cutting condition in comparison with conventional cutter. The surface profiles of workpiece were analyzed by Fourier transformation. The distribution of cut lay left on workpiece by optimized cutter is more regular than that by the conventional cutter.