• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.283-290
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• 2002

Two-level fractional factorial designs are widely used when many factors are considered. When two-level fractional factorial designs are used, some effects are confounded with each other. To break the confounding between effects, we can use fractional factorial designs, called fold-over designs, in which certain signs in the design generators are switched. In this paper, optimal fold-over designs with four-level quantitative and two-level factors are presented for (1) the initial designs without curvature effect and (2) those with curvature effect. Optimal fold-over design tables are provided for 8-run, 16-run, and 32-run experiments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.993-996
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• 2005

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, which has many advantages such as good quality, low cost and rapid machining time. but it also has problems like tool break, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is effected by the milling conditions whose evaluated parameters are spindle, feedrate, and width of cut. The experiments are carried out by full factorial design of experiments using and orthogonal array. This paper shows optimal combination and mathematical model for tool life, and the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.2 s.179
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• pp.73-80
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• 2006

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, because it has many advantages such as good quality, low cost and rapid machining time. But it also has problems such as tool breakage, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is affected by the milling conditions whose selected parameters are spindle speed, feedrate, and width of cut. The experiments were carried out by full factorial design of experiments using an orthogonal array. This paper shows optimal combination and mathematical model for tool life, Therefore, the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
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• v.18 no.5
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.121-129
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• 1999

Recently, the regulations from the govemment and the concems of the people give rise to the interest in exhaust noise of passenger car as much as other vehicles. The exact analysis of various mufflers is needed to reduce the level of exhaust noise. In this paper, we propose a design to improve the mufflers capacity by reducing noise of exhaust system combining Taguchi method and fractional factorial design. In order to measure the performance of a muffler, the performance prediction software which is developed by the Dept. of Automotive Engineering at Hanyang University is used. From the current muffler system we select control factors such as lenght and radius of each component that are thought to be effective on capacity of muffler. Factors are arranged using L18, L27 table of orthogonal array and the fractional factorial design for analysis. We find some significant interaction effects using 1/3 fractional factorial design and accomplish the reduction of noise from the muffler.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.4
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• pp.65-70
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• 2007

In this study, we analyzed about that after design form manufacture master pattern in Rapid Prototyping-RP through design program, processes to manufacture prototype using Vacuum Casting. In Rapid Prototyping-RP, there is an en-or by shrinkage of resin and, in Vacuum Casting, there is an error by shrinkage of silicon. To select condition which shrinkage become the minimum of each process, manufactured prototype after using Full Factorial Design of Design of Experiments, We could confirm shrinkage using reverse engineering and that result came into effect ANOVA 2-way. We applied errors of each process to master pattern, and then presented the method to improve flood control precision of prototype of Vacuum Casting.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.4
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• pp.47-53
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• 2007

A bearing is one of core parts in automobile. Rubber seal of the bearing is important to improve performance of bearing, formed by hot-press die of rubber seal for the intricate shape. In this study, formed tools are used to machine die of bearing rubber seal and the machining operation is classified into the several process of high precision. Design of experiments is used to optimize selection of the formed tools for the efficient machining of the hot-press die. The cutting force, tool wear and tool life are determined to characteristics. And, the clearance angle, the rake angle and the length cutting edge are considered as the major factors. Experiments are repeated to use one-way factorial design, and tool life is predicted by regression model.

• KSBB Journal
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• v.17 no.3
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• pp.228-234
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• 2002

Acetobacter xylinum KJ1 efficiently producing bacterial cellulose(BC) In shaking culture was isolated from a rotten grape. The strain was used to investigate optimum operating conditions for increasing BC production and factorial design model was employed for the optimization. The results of experiments were statistically analyzed by SAS program. Reciprocal effects of each factors(carbon source concentration, shaking speeds(rpm), oxygen pressure, and CSL concentration) and culture condition of BC production were examined by getting regression equation of the dependent variable. Comparisons between experimental results and predicted results about BC concentration were done in total 24 experiments by combination of each factors using SAS program, and the correlation coefficients of BC concentration and BC yield were 0.91 and 0.81, respectively. The agitated cultures were peformed in various operation conditions of factors which affected considerably to BC production in jar fermentor. The results showed that BC concentration was 11.67 g/L in 80 hours cultivation under the condition of carbon source concentration : shaking speeds(rpm) : oxygen pressure : CSL concentration : 4% : 460 rpm : 0.28 : 6%. On the other hand BC yield was 0.42 g/g in 80 hours cultivation under the condition of carbon source concentration : shaking speeds(rpm) : oxygen pressure : CSL concentration : 4% : 564 rpm : 0.21 : 2%. The BC production could be enhanced up to more than 2.4 times by factorial design. The result of a verifying experiment under the optimal conditions determined by the factorial design to the BC production showed that the model was appropriate by obtaining BC concentration of 11.47 g/L in the optimum condition.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.7
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• pp.88-96
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• 2002

High-speed machining is one of the most effective technologies 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 and spindle revolution are control factors. The effect of the control factors on machining accuracy is investigated using two-way factorial design.