• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.9-13
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• 2013

Lapping is a very complicated and random process resulting from the variation of abrasive grains in its sizes and shapes and from the numerous factors having an effect on the process quality. This paper presents a study of a $2^4$ full factorial experimental design and analysis to optimize surface quality in lapping operation. The optimization of the factors to obtain minimum surface roughness was carried out by incorporating effect plots, main effect plots, interaction plots, analysis of variance(ANOVA), surface plots, and contour plots. The statistical design experiments, designed to reduce the total number of experiments required, indicated that, within the selected conditions, all the parameters influenced at a significance level of 5%. In addition, some of the possible interactions between these parameters also influenced the lapping process, especially those that were of third order. A regression model was suggested and fitted the experimental data very well.

• Tribology and Lubricants
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• v.24 no.6
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• pp.308-314
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• 2008

The thermal stress have an effect on the frictional factor such as applied load, sliding speed, sliding distance and number of ventilated disk hole. However, it is difficult to know the mutual relation of these factors on thermal stress of motorcycle break disk. For this, temperature of motorcycle break disk is measured using a disk-on-pad type friction tester with full factorial design containing above 4 elements. and the thermal stress analysis of it was carried out using with ANSYS workbench. From this study, the result was shown that the regression equation which have a trust rate of 95% for thermal stress presumption of motorcycle break disk with frictional factor was composed. It is possible to apply for another automobile parts.

• 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 information and communication convergence engineering
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• v.3 no.4
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• pp.191-194
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• 2005

SU-8 is a epoxy based photoresist designed for MEMS applications, where a thick, chemically and thermally stable image are desired. However SU-8 has proven to be very sensitive to variation in processing variables and hence difficult to use in the fabrication of useful structures. In this paper, negative SU-8 photoresist processed has been characterized in terms of delamination, based on a full factorial designed experiment. Employing the design of experiment (DOE), a process parameter is established, and analyzing of full factorial design is generated to investigate degree of delamination associated with three process parameters: post exposure bake (PEB) temperature, PEB time, and exposure energy. These results identify acceptable ranges of the three process variables to avoid delamination of SU-8 film, which in turn might lead to potential defects in MEMS device fabrication.

• 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.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels 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 in less than 40 experiments.

• Food Engineering Progress
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• v.15 no.2
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• pp.97-115
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• 2011

A review about the application of response surface methodology in the optimization of food technology is presented. The theoretical principles of response surface methodology and steps for its application are described. The response surface methodologies : three-level full factorial, central composite, Box-Behnken, and Doehlert designs are compared in terms of characteristics and efficiency. Furthermore, recent references of their uses in food technology are presented. A comparison between the response surface designs (three-level full factorial, central composite, Box-Behnken and Doehlert design) has demonstrated that the Box-Behnken and Doehlert designs are slightly more efficient than the central composite design but much more efficient than the three-level full factorial designs.

• Journal of Life Science
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• v.33 no.3
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• pp.268-276
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• 2023

This study was conducted to optimize the formulation conditions of the immediate-release layer of carvedilol in the development of a two-layer tablet formulation for carvedilol and ivabradine. Using a 2⁴+3 full-factorial design of experiments, excipients (microcrystalline cellulose, citric acid, and crospovidone) of the carvedilol immediate-release layer (wet granulation part) and process parameters for the tablet compression process (main compression) were optimized, and seven types of each dependent variable (assay, content uniformity, hardness, friability, disintegration, and dissolution [pH 1.2 and 6.8]) were evaluated using design expert software. The analysis of variance results confirmed that the main compression has a significant effect on hardness, friability, and disintegration time and that microcrystalline cellulose has a major effect on friability and dissolution. In addition, it was confirmed that citric acid has a significant effect on friability. Crospovidone affects friability and dissolution. According to the design space from the design of the experiment results, the optimized range is microcrystalline cellulose (~18.0-32.0 mg), citric acid (~0.5-12 mg), and main compression (~615-837 kgf). Consequently, this study confirmed the availability of manufacturing the carvedilol immediate-release layer in which all risk factors evaluated in the initial risk assessment are removed.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.483-495
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• 2007

In a general fractional factorial design, the n-levels of a factor are coded by the $n^{th}$ roots of the unity. Pistone and Rogantin (2007) gave a full generalization to mixed-level designs of the theory of the polynomial indicator function using this device. This article discusses the optimal blocking scheme for nonregular designs. According to hierarchical principle, the minimum aberration (MA) has been used as an important criterion for selecting blocked regular fractional factorial designs. MA criterion is mainly based on the defining contrast groups, which only exist for regular designs but not for nonregular designs. Recently, Cheng et al. (2004) adapted the generalized (G)-MA criterion discussed by Tang and Deng (1999) in studying $2^p$ optimal blocking scheme for nonregular factorial designs. The approach is based on the method of replacement by assigning $2^p$ blocks the distinct level combinations in the column with different blocks. However, when blocking level is not a power of two, we have no clue yet in any sense. As an example, suppose we experiment during 3 days for 12-run Plackett-Burman design. How can we arrange the 12-runs into the three blocks? To solve the problem, we apply G-MA criterion to nonregular mixed-level blocked scheme via the mixed-level indicator function and give an answer for the question.

• Environmental Engineering Research
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• v.23 no.1
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• pp.36-45
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• 2018

The phosphogypsum (PG) is a byproduct of the phosphate fertilizers manufacture. The world production estimated to 200 million tons per year induces environmental threats and storage problems, which requires strict policies to limit pollution and encourage its valorization. This paper presents a purification process of the crude PG including treatment with a diluted sulfuric acid, floatation, filtration and washing. The purified PG is used to produce plaster. The process optimization was conducted using a full factorial design. The significant factors considered in the experimental study are temperature ($X_1$), volume of sulfuric acid solution ($X_2$) and PG quantity ($X_3$). The main effects and interaction effects of these factors on the responses of the % $P_2O_5$, % F, Total Organic Carbon (TOC) ($mg{\cdot}kg^{-1}$) and pH were analyzed. The optimum conditions for $X_1$, $X_2$ and $X_3$ were found to be $60^{\circ}C$, 3 L and 1 kg, respectively and the optimized pH values was found to be 6.2. Under these conditions, 60% of $P_2O_5$, 95% of Fluorine and 98% of TOC were removed from PG. The predicted values were found approximately the same as the experimental ones. The plaster produced with purified PG was found to have similar properties to that produced from natural gypsum.