This study develops a model to determine the input rate of the chemical for coagulation and flocculation process (i.e. coagulant) at industrial water treatment plant, based on real-world data. To detect outliers among the collected data, a two-phase algorithm with standardization transformation and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is applied. In addition, both of the missing data and outliers are revised with linear interpolation. To determine the coagulant rate, various kinds of machine learning models are tested as well as linear regression. Among them, the random forest model with min-max scaled data provides the best performance, whose MSE, MAPE, R2 and CVRMSE are 1.136, 0.111, 0.912, and 18.704, respectively. This study demonstrates the practical applicability of machine learning based chemical input decision model, which can lead to a smart management and response systems for clean and safe water treatment plant.

N-doped Na2Ti6O13@TiO2 (denoted as N-NTO@TiO2) composites are successfully synthesized using a simple two-step process: 1) ball-milling of TiO2 with Na2CO3 followed by heat treatment at 900oC; 2) mixing of the prepared Na2Ti6O13 with titanium isopropoxide and calcining with urea at 500oC. The prepared composites are characterized using XRD, SEM, TEM, FTIR, and BET. The N-NTO@TiO2 composites exhibit well-defined crystalline and anatase TiO2 with exposed {101} facets on the external surface. Moreover, dopant N atoms are uniformly distributed over a relatively large area in the lattice of the composites. Under visible light irradiation, ~51% of the aqueous methylene blue is photodegraded by N-NTO@TiO2 composites, which is higher than the values shown by other samples because of the coupling effects of the hybridization of NTO and TiO2, N-doping, and presence of anatase TiO2 with exposed {101} facets.

Many manufacturers applying third party logistics (3PLs) have some challenges to increase their logistics efficiency. This study introduces an effort to estimate the weight of the delivery trucks provided by 3PL providers, which allows the manufacturer to package and load products in trailers in advance to reduce delivery time. The accuracy of the weigh estimation is more important due to the total weight regulation. This study uses not only the data from the company but also many general prediction variables such as weather, oil prices and population of destinations. In addition, operational statistics variables are developed to indicate the availabilities of the trucks in a specific weight category for each 3PL provider. The prediction model using XGBoost regressor and permutation feature importance method provides highly acceptable performance with MAPE of 2.785% and shows the effectiveness of the developed operational statistics variables.

To meet rapidly changing market demands, manufacturers strive to increase both of productivity and diversity at the same time. As a part of those effort, they are applying flexible manufacturing systems that produce multiple types and/or options of products at a single production line. This paper studies such flexible manufacturing system with multiple types of products, multiple Bernoulli reliability machines and dedicated buffers between them for each of product types. As one of the prevalent control policies, priority based policy is applied at each machines to select the product to be processed. To analyze such system and its performance measures exactly, Markov chain models are applied. Because it is too complex to define all relative transient and its probabilities for each state, an algorithm to update transient state probability are introduced. Based on the steady state probability, some performance measures such as production rate, WIP-based measures, blocking probability and starvation probability are derived. Some system properties are also addressed. There is a property of non-conservation of flow, which means the product ratio at the input flow is not conserved at the succeeding flows. In addition, it is also found that increased buffer capacity does not guarantee improved production rate in this system.

This research examines deep learning based image recognition models for beef sirloin classification. The sirloin of beef can be classified as the upper sirloin, the lower sirloin, and the ribeye, whereas during the distribution process they are often simply unified into the sirloin region. In this work, for detailed classification of beef sirloin regions we develop a model that can learn image information in a reasonable computation time using the MobileNet algorithm. In addition, to increase the accuracy of the model we introduce data augmentation methods as well, which amplifies the image data collected during the distribution process. This data augmentation enables to consider a larger size of training data set by which the accuracy of the model can be significantly improved. The data generated during the data proliferation process was tested using the MobileNet algorithm, where the test data set was obtained from the distribution processes in the real-world practice. Through the computational experiences we confirm that the accuracy of the suggested model is up to 83%. We expect that the classification model of this study can contribute to providing a more accurate and detailed information exchange between suppliers and consumers during the distribution process of beef sirloin.

Many small and medium-sized manufacturing companies process various product types to respond different customer orders in a single production line. To improve their productivity, they often apply batch processing while considering various product types, constraints on batch sizes and setups, and due date of each order. This study introduces a batch scheduling heuristic for a production line with multiple product types and different due dates of each order. As the process times vary due to the different batch sizes and product types, a recursive equation is developed based on a flow line model to obtain the upper bound on the completion times with less computational complexity than full computation. The batch scheduling algorithm combines and schedules the orders with same product types into a batch to improve productivity, but within the constraints to match the due dates of the orders. The algorithm incorporates simple and intuitive principles for the purpose of being applied to small and medium companies. To test the algorithm, two case studies are introduced; a high pressure coolant (HPC) manufacturing line and a press process at a plate-type heat exchanger manufacturer. From the case studies, the developed algorithm provides significant improvements in setup frequency and thus convenience of workers and productivity, without violating due dates of each order.

In this work, TiO2 3D nanostructures (TF30) were prepared via a facile wet chemical process using ammonium hexafluorotitanate. The synthesized 3D TiO2 nanostructures exhibited well-defined crystalline and hierarchical structures assembled from TiO2 nanorods with different thicknesses and diameters, which comprised numerous small beads. Moreover, the maximum specific surface area of TiO2 3D nanostructures was observed to be 191 m2g-1, with concentration of F ions on the surface being 2 at%. The TiO2 3D nanostructures were tested as photocatalysts under UV irradiation using Rhodamine B solution in order to determine their photocatalytic performance. The TiO2 3D nanostructures showed a higher photocatalytic activity than that of the other TiO2 samples, which was likely associated with the combined effects of a high crystallinity, unique features of the hierarchical structure, a high specific surface area, and the advantage of adsorbing F ions.

A facile one-pot wet chemical process to prepare pure anatase TiO2 hollow structures using ammonium hexafluorotitanate as a precursor is developed. By defining the formic acid ratio, we fabricate TiO2 hollow structures containing fluorine on the surface. The TiO2 hollow sphere is composed of an anatase phase containing fluorine by various analytical techniques. A possible formation mechanism for the obtained hollow samples by self-transformation and Ostwald ripening is proposed. The TiO2 hollow structures containing fluorine exhibits 1.2 - 2.7 times higher performance than their counterparts in photocatalytic activity. The enhanced photocatalytic activity of the TiO2 hollow structures is attributed to the combined effects of high crystallinity, specific surface area (62 m2g-1), and the advantage of surface fluorine ions (at 8%) having strong electron-withdrawing ability of the surface ≡ Ti-F groups reduces the recombination of photogenerated electrons and holes.

F-containing TiO2 nanopowders are synthesized using simple wet processes (precipitation-based and hydrothermal) from ammonium hexafluorotitanate (AHFT, (NH4)2TiF6) as a precursor to apply as a photocatalyst for the degradation of rhodamine B (RhB). The surface properties of the prepared samples are evaluated using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), field-emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM). The results confirm that the synthesized anatase TiO2 has sphere-like shapes, with numerous small nanoparticles containing fluorine on the surface. The photocatalytic activity of F-containing TiO2 compared with F-free TiO2 is characterized by measuring the degradation of RhB using a xenon lamp. The photocatalytic degradation of F-containing TiO2 exhibits improved photocatalytic activity, based on the positive effects of adsorbed F ions on the surface.

We report a method for preparing rare earth oxides (RexOy) from the recycling process for spent Ni-metal hydride (Ni-MH) batteries. This process first involves a leaching of spent Ni-MH powders with sulfuric acid at 90℃, resulting in rare earth precipitates (i.e., NaRE(SO4)2·H2O, RE = La, Ce, Nd), which are converted into rare earth oxides via two different approaches: i) simple heat treatment in air, and ii) metathesis reaction with NaOH at 70℃. Not only the morphological features but also the crystallographic structures of all products are systematically investigated using field-emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD); their thermal behaviors are also analyzed. In particular, XRD results show that some of the rare earth precipitates are converted into oxide form (such as La2O3, Ce2O3, and Nd2O3) with heat treatment at 1200℃; however, secondary peaks are also observed. On the other hand, rare earth oxides, RExOy can be successfully obtained after metathesis of rare earth precipitates, followed by heat treatment at 1000℃ in air, along with a change of crystallographic structures, i.e., NaRE(SO4)2·H2O → RE(OH)3 → RExOy.

The 4th industrial revolution is in its progressive form, and its effects are already being revealed throughout society. It has led to a variety of new technologies including artificial intelligence (AI), big data, Internet of Things (IoT), robotics, cyber-physical systems, biotechnology, 3D printers, drones, and Uber. The winds of this revolution are expected to bring many changes to the manufacturing industry. The low-growth global economy and a decline in productivity are prompting a 4th industrial revolution centered on Europe’s Germany, as it needed new growth engines. In Korea, manufacturing industries focused on labor and capital were the center of the industry. The goal was to pursue the first and second industrial revolution led by the developed countries, and to achieve what is called the “Miracle of the Han River”, “The Four Dragons for Asia”, and “The East Asian Miracle”. However, unlike the past, the 4th industrial revolution is not expected to bring about theoretical but substantial changes. The preparations and research into the 4th industrial revolution may seem to be ahead of the major countries, but unfortunately it is far behind the major ones. The United States, China, Germany and Japan are in the process of reorganizing the society, culture and economy in relation to the 4th industrial revolution. Korea`s economy, however, is showing a decline in the growth rate, with the exception of technical hardware and equipment and telecommunications. The 4th industrial revolution is an industry that requires highly specialized knowledge, information, and technology, and if it fails to respond to rapidly evolving technological changes and trends, it is bound to be relegated to the government's position. For small and medium sized manufacturers in particular, the longer the preparation is delayed due to poor environment, structural backwardness, lack of core competencies, and lack of innovation, the more likely they will adjust to social and technological changes caused by the 4th industrial revolution. Accordingly, it is necessary to enhance the importance of preparation for the 4th Industrial Revolution and to take strategic approaches to enhance the sophistication of technologies and the autonomy of small and medium sized manufacturing companies. In this study, we intend to study the manufacturing-ready effects of manufacturing industries based on the level of perception of the company’s 4th industrial revolution. For this purpose, 122 small and medium manufacturing companies were surveyed on the 4th industrial revolution. The survey was conducted for about four months from December 1, 2017 to March 31, 2018. In the case of small and medium sized manufacturing companies, a hypothesis was established on how the perception and preparation of the industrial revolution affects the direct preparation of the 4th industrial revolution. Three assumptions were presented depending on the level of perception of the 4th industrial revolution and the data were drawn from the questionnaire. When comparing the data to the hypothesis, small and medium manufacturing companies should be able to determine the level of interest they have in the 4th Industrial Revolution, and if they are not prepared to do so, they should be able to invest in a certain extent.

지난 20여년 동안 글로벌화의 진전으로 중소기업의 해외진출의 중요성이 높아지면서 중소기업의 국제 화에 관한 연구관심이 지속적으로 증가되고 있다. 여기에는 수출관련 연구, 국제화 결정요인 연구, 국제화 과정 연구, 그리고 국제화 성과에 관한 연구 등이 있다. 이 가운데 중소기업의 국제화 결정요인에 관한 연구가 중심적 위치를 차지하고 있다. 나아가, 중소기업의 국제화가 경영성과와 어떤 관계를 가지는가에 관한 연구관심 역시 크게 확산되고 있다. 한편, 최근 10여년 동안 중앙정부는 혁신적인 기술이나 상품 혹 은 경영기술의 개발 또는 도입을 통해 수익을 창출하는 혁신형 중소기업을 적극적으로 육성해 오고 있다. 혁신형 중소기업의 경우 차별화된 기술역량을 바탕으로 국제화를 전향적으로 추구할 가능성이 높으므로 이들 기업에 관한 국제화 결정요인에 관한 실증연구가 필요하다. 이에 본 연구에서는 혁신형 중소기업의 국제화 결정요인을 실증적으로 규명하고자 하였다. 구체적으로 는 혁신형 중소기업의 기업가정신, 기술역량, 그리고 국내시장 환경이 국제화에 어떤 영향을 미치는지를 알아보고자 한다. 나아가 혁신형 중소기업의 국제화가 성과에는 어떤 효과를 가지는지를 규명하고자 한다. 233개 혁신형 중소기업으로부터 설문자료를 수집하여 분석한 결과 혁신형 중소기업의 기업가정신, 기 술역량, 그리고 국내시장환경 모두 국제화에 긍정적으로 유의한 효과를 가지는 것으로 나타났다. 그러나 혁신형 중소기업의 국제화는 순이익증가율에는 긍정적인 영향을 미치는 것으로 나타났으나, 영업이익율 에는 유의한 영향을 미치지 못하는 것으로 나타났다. 이와 같은 연구결과를 바탕으로 이론적 및 실무적 시사점들을 제시하였다. 나아가 본 연구의 한계점 및 향후 연구방향에 대해서도 논의하였다.

In this study, TiO2 powders are synthesized from ammonium hexafluoride titanate (AHFT, (NH4)2TiF6) as a precursor by heat treatment. First, we evaluate the physical properties of AHFT using X-ray diffraction (XRD), particle size analysis (PSA), thermogravimetric analysis (TGA), and field-emission scanning electron microscopy (FESEM). Then, to prepare the TiO2 powders, is heat-treated at 300-1300oC for 1 h. The ratio of anatase to rutile phase in TiO2 is estimated by XRD. The anatase phase forms at 500oC and phase transformation to the rutile phase occurs at 1200oC. Increase in the particle size is observed upon increasing the reaction temperature, and the phase ratio of the rutile phase is determined from a comparison with the calculated XRD data. Thus, we show that anatase and rutile TiO2 powders could be synthesized using AHFT as a raw material, and the obtained data are utilized for developing a new process for producing high-quality TiO2 powder.

Ni(OH)2 hollow spheres have been prepared by solvent displacement crystallization using a micro-injection device, and the effect of process parameters such as concentration and the relative ratio of the injection speed of the precursor solution, which is an aqueous solution of NiSO4·6H2O, to isopropyl alcohol of displacement solvent have been investigated. The crystal phases after NaOH treatment are in the β-phase for all process parameters. A higher concentration of NiSO4·6H2O aqueous solution is injected by a micro-injection device and bigger Ni(OH)2 hollow spheres with a narrower particle size distribution are formed. The crystallinity and hardness of the as-obtained powder are so poor that hydrothermal treatment of the as-obtained Ni(OH)2 at 120oC for 24 h in distilled water is performed in order to greatly improve the crystallinity. It is thought that a relative ratio of the injection speed of NiSO4·6H2O to that of isopropyl alcohol of at least more than 1 is preferable to synthesize Ni(OH)2 hollow spheres. It is confirmed that this solution- based process is very effective in synthesizing ceramic hollow spheres by simple adjustment of the process parameters such as the concentration and the injection speed.

본 연구는 농식품 부산물을 TMR 원료로 이용하여 사료비 절감 효과와 축산물 품질향상에 도움이 될 수 있도록 그 이용을 활성화하기 위한 농식품 부산물 발생현황조사 및 분석, TMR 이용 현황 및 문제점 조사, 사료이용 시 문제점 및 법률과 제도적 대안을 제시코자 수행하였으며 그 결과는 다음과 같다. 첫째, 폐기물관리법에서 관리되고 있는 유기성폐기물은 폐식용유 10,488톤, 동식물성잔재물 832,493톤, 동물사체 5,740톤, 동물성잔재물 1,171,892톤, 식물성잔재물 2,172,415톤, 왕겨와 미강 12,905톤 등 총 4,205,931톤이었으며 TMR 원료로 이용할 수 있는 식물성 잔재물과 왕겨 그리고 미강이 전체의 51.7%를 차지하였으며 발생지 별로는 전국 상위 10개 지자체에서 76~100% 발생되고 있어 이의 체계적 수급관리시스템이 필요하였다. 둘째, TMR 원료로 사용되는 10대 주요 농식품 부산물은 콩비지, 미강, 깻묵, 맥주박, 주정박, 맥강, 장유박, 감귤박, 버섯부산물 및 기타 식품부산물(빵, 국수, 과자 등)이었다. 셋째, 농가가 농식품 부산물을 이용하는데 가장 큰 애로사항은 농식품 부산물이 폐기물관리법에 의해 폐기물로 관리되고 있어 이를 사용하기 위해서는 재활용신고나 재활용시설설치 등 법률적 의무가 있어 사료이용 활성화를 위해 폐기물 지위 종료제와 같은 제도 개선과 전국적으로 10여 개의 공적 유통센터 설립이 필요한 것으로 사료되었다.

Leaching of MOCVD dust in the LED industry is an essential stage for hydro-metallurgical recovery of pure Ga and In. To recover Ga and In, the leaching behavior of MOCVD scrap of an LED, which contains significant amounts of Ga, In, Al and Fe in various phases, has been investigated. The leaching process must be performed effectively to maximize recovery of Ga and In metals using the most efficient lixiviant. Crystalline structure and metallic composition of the raw MOCVD dust were analyzed prior to digestion. Subsequently, various mineral acids were tested to comprehensively study and optimize the leaching parameters such as acidity, pulp density, temperature and time. The most effective leaching of Ga and In was observed for a boiling 4 M HCl solution vigorously stirred at 400 rpm. Phase transformation of GaN into gallium oxide by heat treatment also improved the leaching efficiency of Ga. Subsequently high purity Ga and In can be recovered by series of hydro processes.

Nowadays, research and development on quantum dot have been intensively and comprehensively pursued worldwide in proportion to concurrent breakthrough in the field of nanotechnology. At present, quantum dot technology forms the main interdisciplinary basis of energy, biological and photoelectric devices. More specifically, quantum dot semiconductor is quite noteworthy for its sub-micro size and possibility of photonic frequency modulation capability by controlling its size, which has not been possible with conventionally fabricated bulk or thin film devices. This could lead to realization of novel high performance devices. To further understand related background knowledge of semiconductor quantum dot at somewhat extensive level, a review paper is presently drafted to introduce basics of (semiconductor) quantum dot, its properties, applications, and present and future market trend and prospect.