• 한국생물공학회:학술대회논문집
• /
• 2003.04a
• /
• pp.153-156
• /
• 2003

The MRS medium is widely used as an optimized medium for the growth of Lactobacillus spp. and also used for the growth of Leuconostoc spp. Leuconostoc mesenteroides shows quite different physicochemical properties compared to Lactobacilli spp. and it is one of the major strain of kimchi fermenting microorganisms with its usefulness in our traditional foods and availability in biotechnology in the future, specifically tailor-made medium is necessary for the growth of Leuconostoc mesenteroides. Sequential experimental designs (Plackett-Burman, fractional factorial, steepest ascent, central composite design and response surface methodology) were introduced to optimize and improve the Leuconostoc medium. Fifteen medium ingredients were investigated and fructose, sodium acetate and ammonium citrate were determined to give a critical and positive effect for cell-growth. The yield of biomass using the optimal medium was improved more than that of the MRS medium and the result of fed-batch culture showed the capability of the improvement in cell mass similar to the E.coli system.

• 유체기계공업학회:학술대회논문집
• /
• 2006.08a
• /
• pp.367-370
• /
• 2006

Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2004.04a
• /
• pp.513-516
• /
• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables while meeting production schedule. Evolutionary operation was developed using two or three process variables for process operators who are not good at statistics. Recently, when a product is developed, it is very important for the engineers to make the production line stable as soon as possible. And there are many causes which have influences to the product performance. This paper presents an evolutionary operation procedure with many process variables using saturated two level fractional factorial designs including Plackett-Burman design.

• The Korean Journal of Applied Statistics
• /
• v.18 no.3
• /
• pp.617-625
• /
• 2005

We usually use orthogonal designs-orthogonal array of strength 2 as orthogonal arrays. It was shown that fractional factorial plaits represented by orthogonal arrays of strength 3 are universally optimal under the additive motels that includes the mean, all main effects and all two-factor interactions. Therefore, we need the measure for evaluating the orthogonal array of strength 3. We can extend this measure as the measure for evaluating the orthogonal array of strength t($\ge$ 2).

• The Korean Journal of Applied Statistics
• /
• v.15 no.2
• /
• pp.395-403
• /
• 2002

In the third phase of the response surface methods, the first-order model is assumed and the curvature of the response surface is checked with a fractional factorial design augmented by centre runs. We further assume that a true model is a quadratic polynomial. To choose an optimal design, Box and Draper(1959) suggested the use of an average mean squared error (AMSE), an average of MSE of y(x) over the region of interest R. The AMSE can be partitioned into the average prediction variance (APV) and average squared bias (ASB). Since AMSE is a function of design moments, region moments and a standardized vector of parameters, it is not possible to select the design that minimizes AMSE. As a practical alternative, Box and Draper(1959) proposed minimum bias design which minimize ASB and showed that factorial design points are shrunk toward the origin for a minimum bias design. In this paper we propose a robust AMSE design which maximizes the minimum efficiency of the design with respect to a standardized vector of parameters.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.05a
• /
• pp.983-989
• /
• 2005

Secondary batteries with high performance are essential in widespread use of modern portable devices such as cellular phones and laptop computers. High energy density, long cycle life, and safety are some of important requirements for secondary battery. To achieve such characteristics, a mixing proportion of electrolyte solution ingredients in the battery should be carefully chosen. In this paper, using statistical design of mixture experiments (DOME), we attempt to find an optimum condition of designing the secondary battery. DOME has a distinct feature in that the experimental region is represented by simplex, rather than hypercube, because the sum of blend proportions should be unity. Several designs based upon this point have been proposed for mixture experiments. Among them, an extreme vertices design is employed in this paper because there are a couple of blend constraints to be considered. In order to investigate how the mixing proportion interacts with other manufacturing factors, a fractional factorial design is also included across the extreme vertices design. As a result, we find that the blend proportion of solution ingredients has a significant effect on battery performances. By simultaneously optimizing two battery capacities, this paper proposes an optimum blend proportion according to process factor settings.

• IE interfaces
• /
• v.18 no.4
• /
• pp.402-411
• /
• 2005

Secondary batteries with high performance are essential in widespread use of modern portable devices such as cellular phones and laptop computers. High energy density, long cycle life, and safety are some of important requirements for secondary battery. To achieve such characteristics, a mixing proportion of electrolyte solution ingredients in the battery should be carefully chosen. In this paper, using statistical design of mixture experiments (DOME), we attempt to find an optimum condition of designing the secondary battery. DOME has a distinct feature in that the experimental region is represented by simplex, rather than hypercube, because the sum of blend proportions should be unity. Several designs based upon this point have been proposed for mixture experiments. Among them, an extreme vertices design is employed in this paper because there are a couple of blend constraints to be considered. In order to investigate how the mixing proportion interacts with other manufacturing factors, a fractional factorial design is also included across the extreme vertices design. As a result, we find that the blend proportion of solution ingredients has a significant effect on battery performances. By simultaneously optimizing two battery capacities, this paper proposes an optimum blend proportion according to process factor settings.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.34 no.1
• /
• pp.60-73
• /
• 1989

Two field experiments were carried out to assess the applicability of a central composite design (CCD) in determining optimum culture condition of an early rice cultivar, Unbongbyeo in southern Korea. A central composite design with two replicates was applied to five levels of five factors such as the number of hills per 3.3m2, the number of seedlings per hill, the levels of nitrogen, the transplanting date and the seedling age (Experiment 1). The levels of planting density were ranged from 30 hills to 150 hills per 3.3m2 ; the number of seedlings per hill from 1 seedling to 9 seedlings per hill; the levels of nitrogen application from 1 kg/l0a to 21 kg/l0a; the transplanting date from June 15 to July 5; the seedling age from 25 days to 45 days. A fractional factorial design was applied to three levels of five factors tested in CCD (Experiment 2). Yield per hill and per unit area were examined and the results obtained from both experiments were compared. The benefits from the central composite design were discussed. Maximum yield of brown rice per unit area was obtained at the combination of the central levels of one of five factors when the other four factors were fixed at central point. Furthermore, brown rice yield per unit area affected by interaction of two factors was maximized at the central point when the remain three factors being fixed at the central level. The responses of five factors to brown rice yield per hill and unit area were found to be a saddle point in both designs. Actual values of the stationary points were 107 hills per 3.3 m2, 4 seedlings per hill, 10 kg nitrogen per l0a, transplanting date of rice on June 26 and 33 days of seedling age in the central composite design. Brown rice yield per unit area at the stationary points were estimated 439 kg/l0a in the central composite design and 442 kg/l0a in the fractional factorial design. Considering the number of experimental treatment combinations, the central composite design was rather convenient in reducing the number of treatment combinations for similar information. It was more convenient for an experimenter to present the results from the central composite design than those from the fractional factorial design. Considering the optimum yields of brown rice per unit area at the stationary points being verified as saddle points in both designs. inter-heterogeneity of each of the factors should be avoided in setting up factors in pursuit of inducing unidirectional response of the factors to yield. Even though both the lower and higher levels in the central composite design being beyond the region of an experimenter's interest. they were considered highly valued in interpretation of the results. Conclusively. the central composite design was found to be more beneficial to optimize culture condition of paddy rice even with several levels of various factors were involved.

• Food Science of Animal Resources
• /
• v.30 no.1
• /
• pp.66-72
• /
• 2010

Pediococcus pentosaceus SA131 was isolated from jeotgal, is the bacteriocin producer against bovine mastitis pathogens, Streptococcus uberis E290, Enterococcus gallinarum E362, and Staphylococcus epidermidis ATCC 12228. The medium composition for pediocin SA131 production by P. pentosaceus SA131 was optimized using response surface methodology. Component of medium was studied as carbon source (glucose, fructose, lactose, glycerol, sucrose, maltose, and mannitol), nitrogen source (beef extract, yeast extract, peptone, malt extract, and tryptone), mineral and surfactant ($MgSO_4$, $KH_2PO_4$, $(NH_4)_2SO_4$, $MnSO_4$, NaCl, sodium acetate, and Tween 80). Through one factor-at-a-time experiment, glucose, fructose, yeast extract, malt extract, NaCl, $MgSO_4$, and Tween 80 were determined as the good ingredient. The effects of major factors for pediocin SA131 production were investigated by two-level fractional factorial designs (FFD). By a $2^4$ FFD, fructose, yeast extract, and $MnSO_4$ were found to be the important factors for the bacteriocin production. Subsequently, a $2^3$ central composite design (CCD) was adopted to derive a statistical model for optimizing the composition of the fermentation medium. The estimated optimum composition for the production of pediocin SA131 by P. pentosaceus SA131 was as follows; 0.13% fructose, 1% glucose, 1.8% yeast extract, 2.58% $MnSO_4$, 0.2% NaCl, and 0.2% Tween 80. The pediocin production under optimized medium was increased to 1,000 AU/mL, compared to the 400 AU/mL in MRS medium.

• Transactions on Electrical and Electronic Materials
• /
• v.12 no.2
• /
• pp.56-59
• /
• 2011

The characterization of the chemical mechanical polishing (CMP) process for undensified phophosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been used by experimenters to understand the relationship between the input variables and responses of interest in a simple and efficient way, and it typically is beneficial for determining the appropriatesize of experiments with multiple process variables and making statistical inferences for the responses of interest. The equipment controllable parameters used to operate the machine consist of the down force of the wafer carrier, pressure on the back side wafer, table and spindle speeds (SS), slurry flow (SF) rate, pad condition, etc. None of these are independent ofeach other and, thus, the interaction between the parameters also needs to be understoodfor improved process characterization in CMP. In this study, we selected the five controllable equipment parameters the most recommendedby process engineers, viz. the down force (DF), back pressure (BP), table speed (TS), SS, and SF, for the characterization of the CMP process with respect to the material removal rate and film uniformity in percentage terms. The polished material is undensified PSG which is widely used for the plananization of multi-layered metal interconnects. By statistical modeling and the analysis of the metrology data acquired from a series of $2^{5-1}$ fractional factorial designs with two center points, we showed that the DF, BP and TS have the greatest effect on both the removal rate and film uniformity, as expected. It is revealed that the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that process control based on a better understanding of the process is the key to success in current semiconductor manufacturing, in which the size of the wafer is approaching 300 mm and is scheduled to continuously increase up to 450 mm in or slightly after 2012.