• Animal Bioscience
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• 제37권4_spc호
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• pp.786-793
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• 2024

Latin America is a culturally, geographically, politically, and economically diverse region. Agriculture in Latin America is marked by a remarkable diversity of production systems, reflecting various agroecological zones, farm sizes, and technological levels. In the last decade, the swine industry increased by 30.6%, emerging as a great contributor to food security and economic development in Latin America. Brazil and Mexico dominate the pig production landscape, together accounting for 70% of sow inventory in the region. The swine industry in Latin America is predominantly comprised of small and medium-sized farms, however, in the past 30 years, the number of pig producers in Brazil dropped by 78%, whereas pork production increased by 326%. Similar to the global pork industry, the growing demand for pork, driven by population growth and changing dietary habits, presents an opportunity for the industry with an expected growth of 16% over the next decade. The export prospects are promising, however subject to potential disruptions from global market conditions and shifts in trade policies. Among the challenges faced by the swine industry, disease outbreaks, particularly African Swine Fever (ASF), present significant threats, necessitating enhanced biosecurity and surveillance systems. In 2023, ASF was reported to the Dominican Republic and Haiti, Porcine Reproductive and Respiratory Syndrome (PRRS) in Mexico, Costa Rica, the Dominican Republic, Colombia, and Venezuela, and Porcine Epidemic Diarrhea (PED) in Mexico, Peru, the Dominican Republic, Colombia, and Ecuador. Additionally, feed costs, supply chain disruptions, and energy expenses have affected mainly the smaller and less efficient producers. The swine industry is also transitioning towards more sustainable and environmentally friendly practices, including efficient feed usage, and precision farming. Ensuring long-term success in the swine industry in Latin America requires a holistic approach that prioritizes sustainability, animal welfare, and consumer preferences, ultimately positioning the industry to thrive in the evolving global market.

• 자원환경지질
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• 제41권2호
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• pp.253-265
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• 2008

지속가능한 자원관리모형(SRM)구축은 탈물질화 및 환경과 경제의 디커플링을 이루기 위한 핵심적 요소로 여겨지고 있다. 본 연구에서는 세계 각국의 지속가능한 자원관리 정책 및 연구방향을 살펴보고, decoupling factor를 이용하여 국내제조업의 경제활동과 에너지소비간의 디커플링현상을 살펴보았다. 마지막으로 이를 바탕으로 국내 실정에 맞는 SRM모형구축과 전략을 제시하였다. 자원관리 시스템은 수요전망, 물질흐름분석과 가치사슬분석, 시장구조분석 등의 분석과 조사 등을 바탕으로 구축된다. 이러한 분석들을 통해 환경적 문제 해결, 재활용시장관리방안 및 시장의 구조적 문제점 도출, 필요 재활용기술 도출, 1차자원과 2차자원의 최적 공급비율 등의 Hot-spot 도출 및 해결방안모색이 가능하다. 또한 지속가능한 자원 관리시스템과 국가단위, 권역단위의 물질흐름분석을 유기적으로 연계하고, 효과적인 이의 운영을 위해서는 국가차원의 법제화와 뒷받침이 이뤄져야 할 것이다.

• 한국산업융합학회 논문집
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• 제25권6_2호
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• pp.1097-1102
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• 2022

With the continuous development of the current industry, the current global environment is in a very serious situation, with resource supply and demand dependent on imports and huge costs for waste disposal due to the depletion of resources and mass generation of industrial waste. Its limitations have already been revealed in many fields, and the importance of re-manufacturing is drawing attention as a countermeasure to these problems. Re-manufacturing aims to recover products that are in the aging and disposal stages, recover to performance close to new products, and re-commercialize them. Among them, most of the machine tools are made of materials such as steel and cast iron with large structures, and raw materials are widely used when producing new products. In addition, since a lot of carbon is generated due to production, it is an object that can obtain a great re-manufacturing effect. Planner millers belonging to large machine tools are one of the machine tool equipment that can greatly reduce resources and energy through re-manufacturing because the structure is very large and the casting is several to tens of tons. Through this machine tool, performance tests and results are derived on the development of re-manufacturing source technology and domestic servo motor and CNC control device.

• 한국패류학회지
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• 제24권3호
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• pp.261-267
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• 2008

수온 및 염분에 따른 굴의 일반적인 대사경향을 알아보기 위하여 수온과 개체크기에 따른 산소소비율과 암모니아 질소 배설률을 측정하였으며, O:N원자비를 산출하였다. 산소소비율과 암모니아 질소배설률은 개체의 크기가 작을수록 높았으며, 수온증가에 따라 증가하였다. O:N 원자비는 일반해수에서 8-40의 범위에 있었으며, 수온 $25^{\circ}C$에서 O:N 원자비는 8로 감소하였는데, 이는 산란기에 주요 대사기질로서 단백질을 이용하며, 단백질의 요구가 큰 것으로 추정된다. 이 결과는 굴양식장의 지속적인 관리 및 적정 수용력 산정을 위한 기초자료로 활용이 가능하다.

• 한국해양공학회지
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• 제26권6호
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• pp.19-26
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• 2012

Recently the world has been suffering from difficulties related to the demand and supply of energy due to the democratic movements sweeping across the Middle East. Consequently, many have turned their attention to never-developed extreme regions such as the polar lands or deep sea, which contain many underground resources. This research investigated the strength and initial elastic modulus values of eternally frozen ground through a uniaxial compression test and indirect tensile test using frozen artificial soil specimens. To ensure accurate test results, a sandymud mixture of standard Jumunjin sand and kaolinite (20% in weight) was used for the specimens in these laboratory tests. Specimen were prepared by varying the water content ratio (7%, 15%, and 20%). Then, the variation in the strength value, depending on the water content, was observed. This research also established three kinds of environments under freezing temperatures of $-5^{\circ}C$, $-10^{\circ}C$, and $-15^{\circ}C$. Then, the variation in the strength value was observed, depending on the freezing environment. In addition, the tests divided the loading rate into 6 phases and observed the variation in the stress-strain ratio, depending on the loading rate. The test data showed that a lower freezing temperature resulted in a larger strength value. An increase in the ice content in the specimen with the increase in the water content ratio influenced the strength value of the specimen. A faster load rate had a greater influence on the uniaxial compression and indirect tensile strengths of a frozen specimen and produced a different strength engineering property through the initial tangential modulus of elasticity. Finally, the long-term strength under a constant water content ratio and freezing temperature was checked by producing stress-strain ratio curves depending on the loading rate.

• 한국해양공학회지
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• 제35권1호
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• pp.50-58
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• 2021

The demand for eco-friendly energy is expected to increase due to the recently strengthened environmental regulations. In particular, the flow inside the pipe used in a cargo handling system (CHS) or fuel gas supply system (FGSS) of hydrogen transport ships and hydrogen-powered ships exhibits a very complex pattern of multiphase-thermal flow, including the boiling phenomenon and high accuracy analysis is required concerning safety. In this study, a feasibility study applying the boiling model was conducted to analyze the multiphase-thermal flow in the pipe considering the phase change. Two types of boiling models were employed and compared to implement the subcooled boiling phenomenon in nucleate boiling numerically. One was the "Rohsenow boiling model", which is the most commonly used one among the VOF (Volume-of-Fluid) boiling models under the Eulerian-Eulerian framework. The other was the "wall boiling model", which is suitable for nucleate boiling among the Eulerian multiphase models. Moreover, a comparative study was conducted by combining the nucleate site density and bubble departure diameter model that could influence the accuracy of the wall boiling model. A comparison of the Rohsenow boiling and the wall boiling models showed that the wall boiling model relatively well represented the process of bubble formation and development, even though more computation time was consumed. Among the combination of models used in the wall boiling model, the simulation results were affected significantly by the bubble departure diameter model, which had a very close relationship with the grid size. The present results are expected to provide useful information for identifying the characteristics of various parameters of the boiling model used in CFD simulations of multiphase-thermalflow, including phase change and selecting the appropriate parameters.

• Asian-Australasian Journal of Animal Sciences
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• 제31권7호
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• pp.951-960
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• 2018

Hanwoo cattle are an important food source in Korea and their supply can have a major impact on meat availability for Korean consumers. The Hanwoo population was 1.8 million head in 2005 and gradually increased to 2.6 million in 2015. Per capita beef consumption has also increased, to 11.6 kg per year in 2015, and is expected to continue to increase. Because intramuscular fat percentage is a critical contributor to meat quality, Hanwoo cattle are fed a high-energy corn-based diet for long fattening periods. Long fed diet causes significant alterations in fat percentage in the loin muscle and other areas of the carcass. However, these long feeding periods increase feeding costs and beef prices. Recently, there has been increased Korean consumer demand for lean beef which has less fat, but is tender and priced more reasonably. These consumer demands on the Korean beef industry are driving differing beef production systems and also changes to the beef grading methodology. Korean government has made a significant investment to select bulls with favorable production traits using progeny testing. Progeny tested bull semen has been disseminated to all Hanwoo farmers. A beef traceability system has been employed for all cattle breeds in Korea since 2009. Hanwoo cattle are ear-marked with a 12-digit identification number from birth to slaughter. This number allows traceability of the management history of individual cattle, and also provides information to consumers. Traceability including management information such as herd, farm, year of birth, and carcass data can determine estimated breeding values of Hanwoo. For a sustainable Hanwoo industry, research scientists in Korea have attempted to develop feeds for efficient fattening periods and precision feeding systems based on genetic information for Hanwoo cattle. These initiatives aim to Korean consumer demands for beef and provide more precision management in beef production in Korea.

• Animal Bioscience
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• 제34권3_spc호
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• pp.354-362
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• 2021

Broiler chickens grow rapidly, and their nutrient requirements change daily. However, broilers are fed three to five diet phases, meaning nutrients are under or oversupplied throughout production. Increasing diet phases improves production efficiency as there is less time in the production cycle that nutrients are in under or over-supply. Nevertheless, the process of administering four or more diets is costly and often impractical. New technologies are now available to blend feed to match the daily nutrient requirements of broilers. Thus, the aim of this review is to evaluate previous studies measuring the impact of increasing feed phases on nutrient utilisation and growth performance, and review recent studies taking this concept to the extreme; precision nutrition - feeding a new diet for each day of the production cycle. This review will also discuss how modern precision feeding technologies have been utilised and the potential that new technologies may bring to the poultry industry. The development of a precision nutrition regime which targets daily requirements by blending dietary components on farm is anticipated to improve the efficiency of production, reduce production cost and therefore improve sustainability of the industry. There is also potential for precision feeding technology along with precision nutrition strategies to deliver a plethora of other management and economic benefits. These include increased fluidity to cope with sudden environmental or market changes, and the ability to alter diets on a farm by farm level in a large, integrated operation. Thus, the future possibilities and practical implications for such technologies to generate a paradigm shift in feed formulation within the poultry industry to meet the rising demand for animal protein is also discussed.

• 설비공학논문집
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• 제30권3호
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• pp.130-142
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• 2018

We use heat pumps with thermal storage system to reduce peak usage of electric power during winters and summers. A heat pump stores thermal energy in a thermal storage tank during the night, to meet load requirements during the day. This system stabilizes the supply and demand of electric power; moreover by utilizing the inexpensive midnight electric power, thus making it cost effective. In this study, we propose a system wherein the thermal storage tank and heat pump are modeled using the TRNSYS, whereas the control simulations are performed by (i) conventional control methods (i.e., thermal storage priority method and heat pump priority method); (ii) region control method, which operates at the optimal part load ratio of the heat pump; (iii) load response control method, which minimizes operating cost responding to load; and (iv) dynamic programming method, which runs the system by following the minimum cost path. We observed that the electricity cost using the region control method, load response control approach, and dynamic programing method was lower compared to using conventional control techniques. According to the annual simulation results, the electricity cost utilizing the load response control method is 43% and 4.4% lower than those obtained by the conventional techniques. We can note that the result related to the power cost was similar to that obtained by the dynamic programming method based on the load prediction. We can, therefore, conclude that the load response control method turned out to be more advantageous when compared to the conventional techniques regarding power consumption and electricity costs.

• 산업경영시스템학회지
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• 제44권4호
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.