• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.1020-1027
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• 2015

The combined effect of tumbling marination methods (vacuum continuous tumbling marination, CT; vacuum intermittent tumbling marination, IT) and effective tumbling time (4, 6, 8, and 10 h) on the water status and protein properties of prepared pork chops was investigated. Results showed that regardless of tumbling time, CT method significantly decreased the muscle fiber diameter (MD) and significantly increased the total moisture content, product yield, salt soluble proteins (SSP) solubility, immobilized water component (p<0.05) compared with IT method. With the effective tumbling time increased from 4 h to 10 h, the fat content and the MD were significantly decreased (p<0.05), whereas the SSP solubility of prepared pork chops increased firstly and then decreased. Besides, an interactive effect between CT method and effective tumbling time was also observed for the chemical composition and proportion of immobilized water (p<0.05). These results demonstrated that CT method of 8 h was the most beneficial for improving the muscle structure and water distribution status, increasing the water-binding capacity and accelerating the marinade efficiency of pork chops; and thus, it should be chosen as the most optimal treatment method for the processing production of prepared pork chops.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.3
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• pp.124-132
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• 2010

In spite of the global importance of primary production of phytoplankton, some primary production data in Korean coastal waters still need to be better processed. The daily rates of water column primary production is generally estimated by integrating the primary production per unit volume over time and depth, but efforts for time integration algorithm have been conducted insufficiently. In this study a mathematical equation evaluating daily primary production integrated over time of a day is proposed and the effectiveness of the model is tested on Saemangeum Lake. The daily primary productions computed with the proposed equation were nearly the same with the results numerically integrated by substituting solar irradiance data. It was suggested that better estimation of primary production would be obtained by using monthly or weekly means of solar irradiance rather than more variable daily data. Because of the vertically heterogenous distribution of phytoplankton, it's hard to integrate the equation over depth to give the daily rates of primary production per unit area of water surface. However, the problem would be solved if, after the vertical distribution of phytoplankton was classified into several patterns and reduced to mathematical formula, every composite function of time integrated equation and chlorophyll distribution equation was integrated successfully.

• International Journal of Human Ecology
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• v.6 no.1
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• pp.17-28
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• 2005

This study examines factors determining contemporary Chinese households' food away from home (FAFH) expenditures using Becker's household production theory. Data came from the 2000 urban household survey in Guangdong Province, collected by National Bureau of Statistics (NBS) of China. It was revealed that the contemporary urban Chinese wives also substitute their household work by time-saving product, FAFH, as Becker's household production theory postulated. This suggests the important role of time-value (opportunity cost) in determining household FAFH expenditure across the cultures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.69-78
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• 2002

The basic purpose of the JIT(Just In Time) production system is to increase profits by reducing costs-that is, by completely eliminating waste such as excessive stocks or workforce. To achieve cost reduction, Production must promptly and flexibly adapt to changes in market demand without having wasteful slacks. :iuch an ideal is accomplished by the concept of JIT, producing the necessary items in the necessary quantities at the necessary time. The JIT production system is supported by the following: reduction of setup time, smoothing of production, standardization of jobs, improvement activities, design of machine layout, Kanban system, autonomation etc. This study examined the present state of the domestic JIT production system and introduced the empirical case of JIT application a small and medium manufacturing company. A synthetic resins manufacturing company applied JIT principles to its processes and achieved the great performance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.92-93
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• 2014

Green Frame is a method for Rahmen structure construction composed of composite PC members. The composite PC members of Green Frame which are based on in-situ production can reduce the construction cost and are more likely to secure quality when compared to production in factories. Previous studies developed forms for in-situ production of Green Frame composite PC members and proposed algorithms to arrange them on site. However, it requires not only their arrangement, but also calculation of an accurate production period to produce the required PC members in a limited space and supply them in a timely manner. In particular, it is necessary to clearly define the properties of detailed processes for in-situ production of PC members and to calculate the time required for respective process. To do so, this study is a basic research on calculating the time for in-situ production using a linear scheduling method.

• Advances in Energy Research
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• v.2 no.1
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• pp.1-9
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• 2014

The green microalgae Chlamydomonas reinhardtti is well-known specie in the terms of $H_2$ production by photo fermentation and has been studying for a long time. Although the $H_2$ production yield is promising; there are some bottlenecks to enhance the yield and efficiency to focus on a well-designed, sustainable production and also scaling up for further studies. D1 protein of photosystem II (PSII) plays an important role in photosystem damage repair and related to $H_2$ production. Because Chlamydomonas is the model algae and the genetic basis is well-studied; metabolic engineering tools are intended to use for enhanced production. Mutations are focused on D1 protein which aims long-lasting hydrogen production by blocking the PSII repair system thus $O_2$ sensitive hydrogenases catalysis hydrogen production for a longer period of time under anaerobic and sulfur deprived conditions. Chlamydomonas CC124 as control strain and D1 mutant strains(D240, D239-40 and D240-41)are cultured photomixotrophically at $80{\mu}mol\;photons\;m^{-2}s^{-1}$, by two sides. Cells are grown in TAP medium as aerobic stage for culture growth; in logarithmic phase cells are transferred from aerobic to an anaerobic and sulfur deprived TAP- S medium and 12 mg/L initial chlorophyll content for $H_2$ production which is monitored by the water columns and later detected by Gas Chromatography. Total produced hydrogen was $82{\pm}10$, $180{\pm}20$, $196{\pm}20$, $290{\pm}30mL$ for CC124, D240, D239-40, D240-41, respectively. $H_2$ production rates for mutant strains was $1.3{\pm}0.5mL/L.h$ meanwhile CC124 showed 2-3 fold lower rate as $0.57{\pm}0.2mL/L.h$. Hydrogen production period was $5{\pm}2days$ for CC124 and mutants showed a longer production time for $9{\pm}2days$. It is seen from the results that $H_2$ productions for mutant strains have a significant effect in terms of productivity, yield and production time.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.318-323
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• 1992

The improvement of the production capability of multi PCB assembly line can not be simply done by improving the capacities of each assembly robot cells but must be done by controlling the production line effectively with the line host computer which controls over the whole assembly line. A real time production control, a real time model change and a real time trouble shooting compose the specific concepts of this technique. In this paper, we present and analyze the definition and application method of real time assembly concept. The meaning of real time model change, troubles and error sooting and its algorithm will be introduced. Also, the function of the host computer which is in charge of all of many different tasks mentioned above and the method are presented. The improvement of the productivity is mainly focused on the efficiency of multi-PCB production control. The importance of this aspect is gradually increasing, which we have presented the analysis and the solution.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.93-100
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• 2017

In this paper, we propose a methodology of using time-lag, make it serve the sound field, in order to smoothen the music production and reduce conflicts. The importance of music production in today's music industry chain is becoming more and more apparent. In the process of music production, the creators pay more attention to the design and adjustment of virtual sound field, especially the late mixing and production. In the process, as a commonly used tool for the adjustment of sound field, "time-lapse" plays a decisive role.