Recently, considerable attention has been given to nickel-based superalloys used in additive manufacturing. However, additive manufacturing is limited by a slow build rate in obtaining optimal densities. In this study, optimal volumetric energy density (VED) was calculated using optimal process parameters of IN718 provided by additive manufacturing of laser powder-bed fusion. The laser power and scan speed were controlled using the same ratio to maintain the optimal VED and achieve a fast build rate. Cube samples were manufactured using seven process parameters, including an optimal process parameter. Analysis was conducted based on changes in density and melt-pool morphology. At a low laser power and scan speed, the energy applied to the powder bed was proportional to and not . At a high laser power and scan speed, a curved track was formed due to Plateau-Rayleigh instability. However, a wide melt-pool shape and continuous track were formed, which did not significantly affect the density. We were able to verify the validity of the VED formula and succeeded in achieving a 75% higher build rate than that of the optimal parameter, with a slight decrease in density and hardness.

SiC-based composite materials with light weight, high durability, and high-temperature stability have been actively studied for use in aerospace and defense applications. Moreover, environmental barrier coating (EBC) technologies using oxide-based ceramic materials have been studied to prevent chemical deterioration at a high temperature of 1300℃ or higher. In this study, an ytterbium silicate material, which has recently been actively studied as an environmental barrier coating because of its high-temperature chemical stability, is fabricated on a sintered SiC substrate. Yb2O3 and SiO2 are used as the raw starting materials to form ytterbium disilicate (Yb2Si2O7). Suspension plasma spraying is applied as the coating method. The effect of the mixing method on the particle size and distribution, which affect the coating formation behavior, is investigated using a scanning electron microscope (SEM), an energy dispersive spectrometer (EDS), and X-ray diffraction (XRD) analysis. It is found that the originally designed compounds are not effectively formed because of the refinement and vaporization of the raw material particles, i.e., SiO2, and the formation of a porous coating structure. By changing the coating parameters such as the deposition distance, it is found that a denser coating structure can be formed at a closer deposition distance.

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.1)

This research focused on deciding optimal manufacturing WIP (Work-In-Process) limit for a small production system. Reducing WIP leads to stable capacity, better manufacturing flow and decrease inventory. WIP is the one of the important issue, since it can affect manufacturing area, like productivity and line efficiency and bottlenecks in manufacturing process. Several approaches implemented in this research. First, two strategies applied to decide WIP limit. One is roulette wheel selection and the other one is elite strategy. Second, for each strategy, JIT (Just In Time), CONWIP (Constant WIP), Gated Max WIP System and CWIPL (Critical WIP Loops) system applied to find a best material flow mechanism. Therefore, pull control system is preferred to control production line efficiently. In the production line, the WIP limit has been decided based on mathematical models or expert’s decision. However, due to the complexity of the process or increase of the variables, it is difficult to obtain optimal WIP limit. To obtain an optimal WIP limit, GA applied in each material control system. When evaluating the performance of the result, fitness function is used by reflecting WIP parameter. Elite strategy showed better performance than roulette wheel selection when evaluating fitness value. Elite strategy reach to the optimal WIP limit faster than roulette wheel selection and generation time is short. For this reason, this study proposes a fast and reliable method for determining the WIP level by applying genetic algorithm to pull system based production process. This research showed that this method could be applied to a more complex production system.

쇤베르크(A. Schönberg, 1874-1951)의 《다섯 개의 오케스트라 소품》(Op. 16, 1909) 가운데 제3번 <색깔>(Farben )로 시작되어 1960년대 리게티(G. Ligeti, 1923-2006)의 《아트모스페레》(Atmosphères , 1961)를 통해 음악 구성의 매개변수(Parameter)로 등장한 ‘음색’(Klangfarbe)은 19세기까지 음악 이론의 연구 대상이 아니었다. 역사적으로 음높이 그리고 음가와 분리할 수 없는 부수적인 소재였던 ‘음색’에 대한 많은 연구가 1960년대 등장한 ‘음색작곡’(Klangfarbenkomposition)을 대상으로 하고 있다. 그러나 본 연구에서는 역사적으로 ‘음색’이 결코 부수적인 음악 요소가 아니었음을 이론적으로 명료하게 설명할 수는 없지만, ‘음색’이라는 관점으로 음악을 관찰하여 18-19세기 작곡가들이 이 매개변수를어떻게 다루었는지, 그 비중의 정도 그리고 음색과 다른 음악 매개변수와의 관계성 변화를 우선적으로 살펴보았다. 특히 음과 관계된, 선율, 화성 조성과의 관계 속에서 음색 그리고 리듬과 음색의 관계를 관현악법을 통해 확인하는 작업을 포함한 제1장은 20세기 ‘음색’의 주요 매개변수로의 자리매김의 역사적 과정을 설명한다. 제2장에서는 음의 연속을 통해 얻어진 ‘선율’을 대신하는 ‘음색 선율’ 또는 ‘주제’를 대신하는‘음색 주제’를 넘어 ‘음색’ 그 자체가 형식을 이루는 과정을 20세기 전후 창작된 작품분석으로 확인시켜준다. 또한 작품분석은 ‘음색’이 주요 음악적 매개변수로 자리매김 하는 과정이 ‘악기고유 정체성 해체’에 종착점을 두었다는 결론을 이끌 수 있게 하였다. 그 방법에 있어서는‘음고’와의 관계를 유지하면서 구체화 한 음색작곡과 악기의 특수주법과 연결된 음색작곡이라는 두 가지 방법으로 분류할 수 있었고, 그 분류는 ‘쇤베르크/드뷔시-리게티-배음렬음악 작곡가들’ 그리고 ‘베베른-케이지/펜데레츠키-카겔’에 이른다.

In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.

In this study, cation and anion exchange process for performance evaluation was conducted. A pilot plant for the ultrpure water production was installed with the capacity of 25 m3/d. The various production rate and regeneration of ion exchange rate were tested to investigate the design parameters. The test resulst was applied to calculate the operating costs. Changing the flow rate of the ion exchange capacity of the reproduction reviewed the cation exchange process as opposed to the design value is 120 to 164% efficiency , whereas both anion exchange process is 82 to 124% efficiency, respectively. This results can be applied for more large scale plant if the scale up parameters are consdiered. The ion exchange capacity of the application in accordance with the design value characteristic upon application equipment is expected to be needed. In this study, the performance of cation and anion exchange resin process was evaluated with pilot plant(25m3/d). The ion exchange capacity along with space velocity and regeneration volume was evaluated. In results, the operation results was compared with design parameters.

A study to analyze and solve problems of a stone surface process experiment has presented in this paper. We have taken Taguchi's parameter design approach, specifically orthogonal array, and determined the optimal levels of the selected variables through analysis of the experimental results using S/N ratio.