• Journal of Microbiology and Biotechnology
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• v.16 no.9
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• pp.1410-1415
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• 2006

Media components, including date juice, sodium acetate, peptone, and $K_{2}HPO_4$, which were screened by Plackett-Burman fractional factorial design, were optimized for lactic acid production from date juice using the response surface method (RSM). Sodium acetate, peptone (p<0.0001), and $K_{2}HPO_4$ (p=0.0029) were highly significant in influencing the lactic acid production. Close correlationship between predicted and experimental values was observed. When the optimum values of the parameters obtained through RSM (25.0 g/l date sugar, 15.0 g/l sodium acetate, 19.1 g/l peptone, and 4.7 g/l $K_{2}HPO_4$) were applied, lactic acid production (22.7 g/l) increased by 50.33%, compared with unoptimized media (15.1 g/l). The subsequent validation experiments confirmed the validity of the statistical model.

• Textile Coloration and Finishing
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• v.20 no.2
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• pp.19-28
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• 2008

The objective of this study was to apply the statistical technique known as design of experiments to optimize the % exhaustion variables for phthalocyanine dyeing of nylon fiber. In this study, a three-factor Central Composite Rotatable Design (CCRD) was used to establish the optimum conditions for the phthalocyanine reactive dyeing of nylon fiber. Temperature, pH and liquor ratio were considered as the variable of interest. Acidic solution with higher temperature and lower liquor ratio were found to be suitable conditions for higher % exhaustion. These three variables were used as independent variables, whose effects on % exhaustion were evaluated. Significant polynomial regression models describing the changes on % exhaustion and % fixation with respect to independent variables were established with coefficient of determination, R2, greater than 0.90. Close agreement between experimental and predicted yields was obtained. Optimum conditions were obtained using surface plots and Monte Carlo simulation techniques where maximum dyeing efficiency is achieved. The significant level of both the main effects and interaction was observed by analysis of variance (ANOVA) approach. Based on the statistical analysis, the results have provided much valuable information on the relationship between response variables and independent variables. This study demonstrates that the CCRD could be efficiently applied for the empirical modeling of % exhaustion and % fixation in dyeing. It also shows that it is an economical way of obtaining the maximum amount of information in a short period of time with least number of experiments.

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.26-28
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• 2007

This research is concerned with a study of failure strength evaluation on heat element gap at resistance welding. The failure strength of resistance welded joint is changed by welding factor like as current(power level), welding time(total energy), pressure etc. and another heat element factor like as number of element line, element gap etc. Tensile-shear tests were carried out with the single-lap specimen using polypropylene(PP). The failure mechanism and optimization of gap was discussed in order to explain the tensile-shear strength evaluation on heat element gap at resistance welding. Orthogonal array was used by fractional factorial design for efficient experiments.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.1079-1092
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• 2020

A parametric study of several parameters relevant to design safety on the spent nuclear fuel (SNF) rod response under a drop accident is presented. In the view of the complexity of interactions between the independent safety-related parameters, a factorial design of experiment is employed as an efficient method to investigate the main effects and the interactions between them. A detailed single full-length fuel rod is used with consideration of post-irradiated fuel conditions under horizontal and vertical free-drops onto an unyielding surface using finite-element analysis. Critical drop heights and critical g-loads that yield the threshold plastic strain in the cladding are numerically estimated to evaluate the fuel rod structural resistance to impact load. The combinatory effects of four uncertain parameters (pellet-cladding interfacial bonding, material properties, spacer grid stiffness, rod internal pressure) and the interactions between them on the fuel rod response are investigated. The principal finding of this research showed that the effects of above-mentioned parameters on the load-carrying capacity of fuel rod are significantly different. This study could help to prioritize the importance of data in managing and studying the structural integrity of the SNF.

• Transactions on Electrical and Electronic Materials
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• v.12 no.3
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• pp.115-118
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• 2011

Process characterization of the chemical mechanical polishing (CMP) process for undensified phosphosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been addressed to experimenters to understand the relationship between input variables and responses of interest in a simple and efficient way. It is typically beneficial for determining the adequate size of experiments with multiple process variables and making statistical inferences for the responses of interests. Equipment controllable parameters to operate the machine include the down force (DF) of the wafer carrier, pressure on the backside of the wafer, table and spindle speed (SS), slurry flow rate, and pad condition. None of them is independent; thus, the interaction between parameters also needs to be indicated to improve process characterization in CMP. In this paper, we have selected the five controllable equipment parameters, such as DF, back pressure (BP), table speed (TS), SS, and slurry flow (SF), most process engineers recommend to characterize the CMP process with respect to material removal rate (RR) and film uniformity as a percentage. The polished material is undensified PSG. PSG is widely used for the plananization in multi-layered metal interconnects. We identify the main effect of DF, BP, and TS on both RR and film uniformity, as expected, by the statistical modeling and analysis on the metrology data acquired from a series of $2^{5-1}$ fractional factorial design with two center points. This revealed the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that the process control based on better understanding of the process is the key to success in semiconductor manufacturing, typically when the wafer size reaches 300 mm and is continuously scheduled to expand up to 450 mm in or little after 2012.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.51-68
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• 2020

Purpose: The primary objective of this research is to develop the optimal operating conditions as well as their associated design spaces for a Cryogenic Submerged Arc Welding(SAW) process by improving its quality and productivity simultaneously. Methods: In order to investigate functional relationships among quality characteristics and their associated control factors of an SAW process, a stepwise design of experiment(DoE) method is proposed in this paper. Based on the DoE results, not only a multi-dimensional design space but also a safe operating space and normal acceptable range(NAR) by integrating statistical confidence intervals were demonstrated. In addition, the optimal operating conditions within the proposed NAR can be obtained by a robust optimal design method. Results: This study provides a customized stepwise DoE method (i.e., a sequential set of DoE such as a factorial design and a central composite design) for Cryogenic SAW process and its statistical analysis results. DoE results can then provide both the main and interaction effects of input control factors and the functional relationships between the input factors and their associated output responses. Maximizing both the product quality with high impact strength and the productivity with minimum processing times simultaneously in a case study, we proposed a design space which can provide both acceptable productivity and quality levels and NARs of input control factors. In order to confirm the optimal factor settings and the proposed NARs, validation experiments were performed. Conclusion: This research may provide significant contributions and applications to many SAW problems by preparing a standardization of the functional relationship between the input factors and their associated output response. Moreover, the proposed design space based on DoE and NAR methods can simultaneously consider a number of quality characteristics including tradeoff between productivity and quality levels.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.40-46
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• 1999

The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• The Journal of Information Systems
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• v.33 no.2
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• pp.219-236
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• 2024

Purpose The purpose of this study is to investigate the effect of micro and macro-influencers on consumer purchase intentions, specifically focusing on the role of the product's origin (domestic or foreign). The study will specifically analyze the markets of South Korea and Kyrgyzstan to understand how various types of influencers impact consumer behavior within these unique cultural and economic settings. Design/methodology/approach This study evaluates hypotheses using the factorial design method among social media users in South Korea and Kyrgyzstan. The experiments involve scenarios with eight different groups. The analytical research methodology used is analysis of variance (ANOVA). Findings The study findings confirmed that micro- and macro-influencers have varying effects on consumer behavior, which supports previous research. The inclusion of the product origin factor resulted in more accurate data. In both the South Korean and Kyrgyzstan markets, the findings indicated that micro- and macro-influencers have limited success in promoting local products. However, when it comes to promoting foreign products, there are notable differences in effectiveness between micro- and macro-influencers, with macro-influencers being more effective.

• Computers and Concrete
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• v.17 no.3
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• pp.323-336
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• 2016

Although the self-compacting concrete (SCC) offers several practical and economic benefits and quality improvement in concrete constructions, in comparison with conventionally vibrated concretes confronts with autogenously chemical and drying shrinkage which causes the formation of different cracks and creates different problems in concrete structures. Using different fibers in the mix design and implementation of fibrous concrete, the problem can be solved by connecting cracks and micro cracks together and postponing the propagation of them. In this study an experimental investigation using response surface methodology (RSM) based on full factorial design has been undertaken in order to model and evaluate the polypropylene fiber effect on the fibrous self-compacting concrete and curing time, fiber percentage and fiber amount have been considered as input variables. Compressive strength has been measured and calculated as the output response to achieve a mathematical relationship between input variables. To evaluate the proposed model analysis of variance at a confidence level of 95% has been applied and finally optimum compressive strength predicted. After analyzing the data, it was found that the presented mathematical model is in very good agreement with experimental results. The overall results of the experiments confirm the validity of the proposed model and this model can be used to predict the compressive strength of fibrous self-compacting concrete.