• Current Optics and Photonics
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• v.8 no.1
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• pp.45-55
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• 2024

A fiber spool with ultra-low vibration sensitivity has been demonstrated for the ultra-narrow-linewidth fiber-stabilized laser by the multi-object orthogonal experimental design method, which can achieve the optimization object and analysis of influence levels without extensive computation. According to a test of 4 levels and 4 factors, an L₁₆ (4⁴) orthogonal table is established to design orthogonal experiments. The vibration sensitivities along the axial and radial directions and the normalized sums of the vibration sensitivities are determined as single objects and comprehensive objects, respectively. We adopt the range analysis of object values to obtain the influence levels of the four design parameters on the single objects and the comprehensive object. The optimal parameter combinations are determined by both methods of comprehensive balance and evaluation. Based on the corresponding fractional frequency stability of ultra-narrow-linewidth fiber-stabilized lasers, we obtain the final optimal parameter combination A3B1C2D1, which can achieve the fiber spool with vibration sensitivities of 10^-12/g magnitude. This work is the first time to use an orthogonal experimental design method to optimize the vibration sensitivities of fiber spools, providing an approach to design the fiber spool with ultra-low vibration sensitivity.

• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.277-299
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• 2002

Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.177-183
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• 2015

Incremental sheet metal forming is a manufacturing process to produce thin parts using sheet metals by a series of small incremental deformation. The process rarely needs dedicated dies and molds, thus, preparation time for the process is relatively short as to be compared to conventional metal forming. Spring back in sheet metal working is very common, which causes critical errors in dimensions. Incremental sheet metal forming is not fully investigated yet. Hence, incremental sheet metal forming frequently produces inaccurate parts. This paper proposes a method to minimize dimensional errors to improve shape accuracy of products manufactured by incremental forming. This study conducts experiments using an exclusive incremental forming machine and the material for these experiments are sheets of aluminum AL1015. This research defines a process parameter and selects a few factors for the experiments. The parameters employed in this paper are tool feed rate, tool diameter, step depth, material thickness, forming method, dies applied, and tool path method. In addition, their levels for each factor are determined. The plan of the experiments is designed using orthogonal array $L_8$ ($2^7$) which requires minimum number of experiments. Based on the measurements, dimensional errors are collected both on the tool contacted surfaces and on the non-contacted surfaces. The distances between the formed surfaces and the CAD models are scanned and recorded using a commercial software product. These collected data are statistically analyzed and ANOVAs (analysis of variances) are drawn up. From the ANOVAs, this paper concludes that the process parameters of tool diameter, forming depth, and forming method are the significant factors to reduce the errors on the tool contacted surface. On the other hand, the experimental factors of forming method and dies applied are the significant factors on the non-contacted surface. However, the negative forming method always produces better accuracy than the positive forming method.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.695-706
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• 1999

When fractional factorial experiments contain some infeasible treatment combinations called debarred combinations we should construct experimental designs so that those debarred combinations are to be excluded by selecting defining contrasts appropriately. By applying Franklin(1995)'s procedure for selecting defining contrasts to Cheng and Li(1993)'s method this paper presents a method of selecting defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.347-352
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• 2009

Nonnegative matrix factorization (NMF) is a popular method for multivariate analysis of nonnegative data, the goal of which is decompose a data matrix into a product of two factor matrices with all entries in factor matrices restricted to be nonnegative. NMF was shown to be useful in a task of clustering (especially document clustering). In this paper we present an algorithm for orthogonal nonnegative matrix factorization, where an orthogonality constraint is imposed on the nonnegative decomposition of a term-document matrix. We develop multiplicative updates directly from true gradient on Stiefel manifold, whereas existing algorithms consider additive orthogonality constraints. Experiments on several different document data sets show our orthogonal NMF algorithms perform better in a task of clustering, compared to the standard NMF and an existing orthogonal NMF.

• Journal of Plant Biotechnology
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• v.2 no.3
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• pp.157-163
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• 2000

Optimization of chemicals in the large scale sea water medium and inoculum for biomass and natural colourants production in the marine cyanobacteria, Phomidium tenue BDU 46241 (phycoerythrin producer) and P.valderianum BDU 30501 (phycocyanin producer) was carried out by experiments in L8 orthogonal array. Mathematical analysis revealed the significance of these factors. The factor(s) that critically control the yield varied with the organism and the end-product further, the desirable level of these factors between the normal and a higher level tested was identified and improved media were evolved. In both cyanobacteria, higher level of $K_2$$HPO_4$, $NaNO_3$ and inoculum with normal level of ferric ammonium citrate was found to be desirable for biomass production and additionally, higher level of $MgSO_4$ for pigment production. The level of other factors varied with the organism and the end-product. Confirmation experiments showed that the clues obtained based on mathematical experimentation are valid. In P.tenue, the medium optimized for biomass production increased the yield of biomass by 495% and the medium optimized for phycoerythrin production increased the yield of biomass by 408% with 30% increase in phycoerythrin content of the biomass. Similarly in P.valderianum, the medium optimized for biomass production increased the yield of biomass by 224% and the medium optimized for phycocyanin production increased the yield of biomass by 143% with 44% increase in phycocyanin content of the biomass.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.4
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• pp.10-15
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• 2013

For design optimization, engineers should require the accurate information of design space and then explore the design space and carry out optimization. Recently, the total design framework, based on design of experiments and optimization, is widely used in industry areas to explore the design space above all. For optimizing turbofan engine design point, the response surface model is constructed by using the 7 level orthogonal array which satisfies the statistical uniformity and orthogonality and gets the dense design space information. The multi-objective genetic algorithm is used to find the optimal solution within the given constraints for finding global optimal one in response surface model. The optimal solution from response surface model is verified with GasTurb simulation result.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.84-90
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• 2022

The purpose of the cover housing component of a car door is to protect the terminals of the plug housing that connects the electric control unit on the door side to the car body. Therefore, for a smooth assembly with the plug housing and to prevent contaminants from penetrating into the gaps that occur after assembly, the warpage of the cover housing should be minimized. In this study, to minimize the warpage of the cover housing, optimization was performed for design factors related to the mold and processes based on the injection molding simulation. These design factors include gate location, gate diameter, injection time, resin temperature, mold temperature, and packing pressure. To optimize the design factors, Taguchi's approach to the design of experiments was adopted. The optimal combination of the design factors and levels that minimize warpage was predicted through L₁₈-orthogonal array experiments and main effects analysis. Moreover, the warpage under the optimal design was estimated by the additive model, and it was confirmed through the simulation experiment that the estimated result was quite consistent with the experimental result. Additionally, it was found that the warpage under the optimal design was significantly improved compared to both the warpage under the initial design and the best warpage among the orthogonal array experimental results, which numerically decreased by 36.9% and 23.4%, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1718-1729
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• 1997

This paper describes motion errors due to acceleration and deceleration types of servo motors in NC machine tools. Motion errors are composed of two components : one is due to transient response of a servomechanism and the other comes from gain mismatching of positioning servo motors. It deals with circular interpolation to identify motion errors by using Interface card. Also in order to minimize motion errors, this study presents an effective method to optimize parameters which are connected with motion errors. The proposed method is based upon a second order polynomial regression model and it includes an orthogonal array method to make the effective results of experiments. The validity and reliability of the study were verified on a vertical machining center equipped with FANUC 0MC through a series of experiments and analysis.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.6
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• pp.1-9
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• 2011

In this study, the specifications of the components of the vent vale were optimally determined in order to enhance the performance of the vent valve. Design objective was to minimize fuel leakage while satisfying the design constraints on the performance indices. To obtain the optimum solution based on real experiments, several design techniques available in PIAnO, a commercial PIDO tool, were used. First, an orthogonal array was used to generate training design points and then real experiments were performed to measure the experimental data at the training design points. Next, Kriging metamodels for the objective function and design constraints were generated using the experimental data. Finally, a genetic algorithm was employed to obtain the optimization results using the Kriging models. Fuel leakage of the optimized vent valve was found to be reduced by 95.8% compared to that of the initial one while satisfying all the design constraints.