• Title/Summary/Keyword: Production efficiency

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Economic Analysis and Comparison between Low-Power and High-Power SOEC Systems (저출력 및 고출력 SOEC 시스템의 경제성 분석 비교)

  • TUANANH BUI;YOUNG SANG KIM;DONG KEUN LEE;KOOK YOUNG AHN;YONGGYUN BAE;SANG MIN LEE
    • Transactions of the Korean hydrogen and new energy society
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    • v.33 no.6
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    • pp.707-714
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    • 2022
  • Hydrogen production using solid oxide electrolysis cells (SOEC) is a promising technology because of its efficiency, cleanness, and scalability. Especially, high-power SOEC system has received a lot of attention from researchers. This study compared and analyzed the low-power and high-power SOEC system in term of economic. By using revenue requirement method, levelized cost of hydrogen (LCOH) was calculated for comparison. In addition, the sensitivity analysis was performed to determine the dependence of hydrogen cost on input variables. The results indicated that high-power SOEC system is superior to a low-power SOEC system. In the capital cost, the stack cost is dominant in both systems, but the electricity cost is the most contributed factor to the hydrogen cost. If the high-power SOEC system combines with a nuclear power plant, the hydrogen cost can reach 3.65 $/kg when the electricity cost is 3.28 ¢/kWh and the stack cost is assumed to be 574 $/kW.

Injection Process Yield Improvement Methodology Based on eXplainable Artificial Intelligence (XAI) Algorithm (XAI(eXplainable Artificial Intelligence) 알고리즘 기반 사출 공정 수율 개선 방법론)

  • Ji-Soo Hong;Yong-Min Hong;Seung-Yong Oh;Tae-Ho Kang;Hyeon-Jeong Lee;Sung-Woo Kang
    • Journal of Korean Society for Quality Management
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    • v.51 no.1
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    • pp.55-65
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    • 2023
  • Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

Assessment of population structure and genetic diversity of German Angora rabbit through pedigree analysis

  • Abdul Rahim;K. S. Rajaravindra;Om Hari Chaturvedi;S. R. Sharma
    • Animal Bioscience
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    • v.36 no.5
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    • pp.692-703
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    • 2023
  • Objective: The main goals of this investigation were to i) assess the population structure and genetic diversity and ii) determine the efficiency of the ongoing breeding program in a closed flock of Angora rabbits through pedigree analysis. Methods: The pedigree records of 6,145 animals, born between 1996 to 2020 at NTRS, ICAR-CSWRI, Garsa were analyzed using ENDOG version 4.8 software package. The genealogical information, genetic conservation index and parameters based on gene origin probabilities were estimated. Results: Analysis revealed that, 99.09% of the kits had both parents recorded in the whole dataset. The completeness levels for the whole pedigree were 99.12%, 97.12%, 90.66%, 82.49%, and 74.11% for the 1st, 2nd, 3rd, 4th, and 5th generations, respectively, reflecting well-maintained pedigree records. The maximum inbreeding, average inbreeding and relatedness were 36.96%, 8.07%, and 15.82%, respectively. The mean maximum, mean equivalent and mean completed generations were 10.28, 7.91, and 5.51 with 0.85%, 1.19%, and 1.85% increase in inbreeding, respectively. The effective population size estimated from maximum, equivalent and complete generations were 58.50, 27.05, and 42.08, respectively. Only 1.51% of total mating was highly inbred. The effective population size computed via the individual increase in inbreeding was 42.83. The effective numbers of founders (fe), ancestors (fa), founder genomes (fg) and non-founder genomes (fng) were 18, 16, 6.22, and 9.50, respectively. The fe/fa ratio was 1.12, indicating occasional bottlenecks had occurred in the population. The six most influential ancestors explained 50% of genes contributed to the gene pool. The average generation interval was 1.51 years and was longer for the sire-offspring pathway. The population lost 8% genetic diversity over time, however, considerable genetic variability still existed in the closed Angora population. Conclusion: This study provides important and practical insights to manage and maintain the genetic variability within the individual flock and the entire population.

Material Life Cycle Assessments on Mg2NiHx-CaO Composites (Mg2NiHx-CaO 수소 저장 복합물질의 물질 전과정 평가)

  • HWANG, JUNE-HYEON;SHIN, HYO-WON;HONG, TAE-WHAN
    • Transactions of the Korean hydrogen and new energy society
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    • v.33 no.1
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    • pp.8-18
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    • 2022
  • With rapid industrialization and population growth, fossil fuel use has increased, which has a significant impact on the environment. Hydrogen does not cause contamination in the energy production process, so it seems to be a solution, but it is essential to find an appropriate storage method due to its low efficiency. In this study, Mg-based alloys capable of ensuring safety and high volume and hydrogen storage density per weight was studied, and Mg2NiHx synthesized with Ni capable of improving hydrogenation kinetics. In addition, in order to improve thermal stability, a hydrogen storage composite material synthesized with CaO was synthesized to analyze the change in hydrogenation reaction. In order to analyze the changes in the metallurgical properties of the materials through the process, XRD, SEM, BET, etc. were conducted, and hydrogenation behavior was confirmed by TGA and hydrogenation kinetics analysis. In addition, in order to evaluate the impact of the process on the environment, the environmental impact was evaluated through "Material Life Cycle Assessments" based on CML 2001 and EI99' methodologies, and compared and analyzed with previous studies. As a result, the synthesis of CaO caused additional power consumption, which had a significant impact on global warming, and further research is required to improve this.

Can Artificial Intelligence Boost Developing Electrocatalysts for Efficient Water Splitting to Produce Green Hydrogen?

  • Jaehyun Kim;Ho Won Jang
    • Korean Journal of Materials Research
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    • v.33 no.5
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    • pp.175-188
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    • 2023
  • Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

Analysis of UAV Photogrammetric Method for Generation of Terrain Model and Ortho Image (지형모델 및 정사영상 제작을 위한 무인항공측량 기술 분석)

  • Um, Dae Yong;Park, Joon Kyu
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.8
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    • pp.577-584
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    • 2016
  • UAV(Unmaned Aerial Vehicle), which is autonomous flight without pilots. Recently, UAV is being applied to various fields such as video recording, aerial photogrammetry. In particular, UAV is getting a lot of attention in the field of space-related information because of it's data acquisition speed and economic feasibility. But analytical study of an unmanned air-side technologies are lacking. In this study, the research of equipment for the unmanned aerial surveys and UAV technologies and trend analysis for generation of terrain model and ortho image effectively were performed. As a result, the ways to improve the utilization field of unmanned aerial surveying and processing of fixed-wing and rotary-wing unmanned aircraft. were suggested. If analytical research on generation of terrain models and ortho image will be performed, production efficiency of the geospatial information industry is expected to be significantly increased.

Recent advances on Oil-water Separation Technology (유수분리 기술의 최신 동향)

  • Hong Ryul Park;Woonbong Hwang;Dukhyun Choi
    • Composites Research
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    • v.36 no.2
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    • pp.69-79
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    • 2023
  • Oil-water separation is a critical process for several industrial applications, including oil production, wastewater treatment, food processing, and environmental area such as marine oil spills. The separation efficiency of oil-water mixtures can be influenced by various factors such as mixture composition, oil and water conditions, and the separation technology used. Over the years, various technologies have been developed to separate water and oil by physical, chemical and biological methods. This paper presents an overview of the various methods and technologies available for oil-water separation, including gravity separation, centrifugal separation, and separation using adsorbents, filters. The strengths and limitations of each method are discussed, along with recent research trends and future prospects. Furthermore, this paper aims to provide direction for future research and industrial application of sustainable and environmentally friendly oil-water separation technologies. In conclusion, we provide a comprehensive overview of recent oil-water separation technologies that will be beneficial to researchers and industrialists in the field of oil-water separation.

An Adaptive Tuned Heave Plate (ATHP) for suppressing heave motion of floating platforms

  • Ruisheng Ma;Kaiming Bi;Haoran Zuo
    • Smart Structures and Systems
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    • v.31 no.3
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    • pp.283-299
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    • 2023
  • Structural stability of floating platforms has long since been a crucial issue in the field of marine engineering. Excessive motions would not only deteriorate the operating conditions but also seriously impact the safety, service life, and production efficiency. In recent decades, several control devices have been proposed to reduce unwanted motions, and an attractive one is the tuned heave plate (THP). However, the THP system may reduce or even lose its effectiveness when it is mistuned due to the shift of dominant wave frequency. In the present study, a novel adaptive tuned heave plate (ATHP) is proposed based on inerter by adjusting its inertance, which allows to overcome the limitation of the conventional THP and realize adaptations to the dominant wave frequencies in real time. Specifically, the analytical model of a representative semisubmersible platform (SSP) equipped with an ATHP is created, and the equations of motion are formulated accordingly. Two optimization strategies (i.e., J1 and J2 optimizations) are developed to determine the optimum design parameters of ATHP. The control effectiveness of the optimized ATHP is then examined in the frequency domain by comparing to those without control and controlled by the conventional THP. Moreover, parametric analyses are systematically performed to evaluate the influences of the pre-specified frequency ratio, damping ratio, heave plate sizes, peak periods and wave heights on the performance of ATHP. Furthermore, a Simulink model is also developed to examine the control performance of ATHP in the time domain. It is demonstrated that the proposed ATHP could adaptively adjust the optimum inertance-to-mass ratio by tracking the dominant wave frequencies in real time, and the proposed system shows better control performance than the conventional THP.

Supplementation of guanidinoacetic acid and rumen-protected methionine increased growth performance and meat quality of Tan lambs

  • Zhang, Jian Hao;Li, Hai Hai;Zhang, Gui Jie;Zhang, Ying Hui;Liu, Bo;Huang, Shuai;Guyader, Jessie;Zhong, Rong Zhen
    • Animal Bioscience
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    • v.35 no.10
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    • pp.1556-1565
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    • 2022
  • Objective: Tan lambs (n = 36, 3 mo old, 19.1±0.53 kg) were used to assess effects of dietary guanidinoacetic acid (GAA) and rumen-protected methionine (RPM) on growth performance, carcass traits, meat quality, and serum parameters. Methods: Lambs were randomly assigned to three treatment groups, with 6 pens per group and 2 lambs per pen. Dietary treatments were: basal diet alone (I); basal diet supplemented with 0.08% GAA+0.06% RPM (II); and basal diet supplemented with 0.08% GAA+0.08% RPM (III). Diets were provided three times a day for 90 d. Intake per pen was recorded daily and individual lamb body weight (BW) was measured monthly. Carcass traits were measured after slaughter and meat quality at the end of the experiment, blood samples were taken on a subgroup of lambs for analysis of indicators mostly related to protein metabolism. Results: Final BW and average daily gain for the first and second month, and for the entire experiment were greater in Treatment II compared to Treatment I (p<0.05), whereas feed to gain ratio was lower (p<0.05). Treatment II had the optimal dressing percentage and net meat weight proportion, as well as crude protein and intramuscular fat concentrations in muscles. Treatment II improved meat quality, as indicated by the greater water holding capacity, pH after 45 min and 48 h, and lower shear force and cooking loss. Dietary supplementation of GAA and RPM also increased the meat color a* and b* values at 24 h. Finally, Treatment II increased total protein, and serum concentrations of albumin and creatinine, but decreased serum urea nitrogen concentrations, indicating improved protein efficiency. Conclusion: In this study, 0.08% GAA+0.06% RPM supplementation improved growth performance and meat quality of Tan lambs.

International Trade and Labor Demand of Korean Firms: Focusing on Heterogeneous Firm Productivity (수출입과 기업의 노동수요)

  • Eum, Jihyun;Park, Jinho;Choi, Moon Jung
    • Economic Analysis
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    • v.25 no.3
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    • pp.30-69
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    • 2019
  • This paper analyzes the effects of trade on demand for labor of trading firms in Korea. We apply system GMM methodology to estimate the effects of imports and exports on employment of Korean manufacturing firms using firm-level data from the Survey of Business Activities of Statistics Korea between 2006 and 2014. According to our estimated results, for firms with high-productivity, exports have a positive and significant effect on the labor demand, while other firms do not show any such significant effects. Furthermore, our results show that offshoring mitigates the positive effects of exports on employment, since tasks within the firms can be relocated abroad. On the other hand, an increase in imports reduces demand for labor because labor is replaced with low-priced imported inputs. Also, when firms partake in global outsourcing, the negative effects of imports are mitigated as those firms expand their production by enhancing their efficiency in the process of offshoring. Therefore, our results suggest that it is important to consider heterogeneous firm productivity as well as offshoring in analyzing the effect of trade on labor demand of firms.