• Animal Bioscience
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• v.34 no.4
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• pp.471-481
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• 2021

Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2013-2024
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• 2006

This paper proposes a condition classification system using wavelet transform, feature evaluation and artificial neural networks to detect faulty products on the production line of reciprocating compressors for refrigerators. The stationary features of vibration signals are extracted from statistical cumulants of the discrete wavelet coefficients and root mean square values of band-pass frequencies. The neural networks are trained by the sample data, including healthy or faulty compressors. Based on training, the proposed system can be used on the automatic mass production line to classify product quality instead of people inspection. The validity of this system is demonstrated by the on-site test at LG Electronics, Inc. for reciprocating compressors. According to different products, this system after some modification may be useful to increase productivity in different types of production lines.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.188-204
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• 1994

Most of computer-aided process planning(CAPP) systems have been developed to automate the process planning function. In this paper, we describe an analytical model for a CAPP system in order to improve the performance of production system in flexible manufacturing systems(FMSs) for computer intergrated manufacturing(CIM) architecture. This paper proposes an optimal process planning that minimizes the load time by minimizing the cycle time and the number of workstations using Kang and Hahm's heuristic approach so as to improve the performance of production system under the batch production of discrete products. We also perform simulation using SIMAN language to campare the line utilization of each for various product types. The proposed algorithm can be implemented in existing FMSs for on-line control of product quantity using programmable logic controllers(PLC) and communication devices.

• Publications of The Korean Astronomical Society
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• v.13 no.1 s.14
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• pp.129-134
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• 1998

Observations of the J=1-0 transition line of HCN were made at the center of Comet C/1995 O1 (Hale-Bopp) from November, 1996 to April, 1997 with the 14-m radio telescope at the TRAO (Taeduk Radio Astronomical Observatory). From the obtained data, an HCN production rate at each observed date was derived. The rapid variation of the HCN production rate near the perihelion was detected, and it is thought to be caused by jet(s) from the nucleus. The correlation between the visual magnitude and the HCN production rate is found to be $Q_{HCN}=27.03-0.11(m_v-5log{\Delta})$.

• 한국생물공학회:학술대회논문집
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• 2000.11a
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• pp.398-401
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• 2000

The effect of volatile components on cell growth and polysaccharide production in suspension cultures of Aloe saponaria was investigated using an intelligent on-line gas control system which enabled to control the concentrations of oxygen, carbon dioxide and ethylene simultaneously. Aloe production was enhanced in the presence of exogenous ethylene in the concentration range of 5ppm and 15ppm. Maintaining high tension of carbon dioxide (5% v/v) was found to enhance polysaccharide production significantly.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.470-475
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• 2002

An alternative to traditional production planning and control systems such as MRP and JIT is the drum-buffer-rope (DBR). Using the DBR system, companies can achieve a large reduction of work-in-process (WIP) and finished-goods inventories (FGI). significant improvement in scheduling performance, and substantial earnings increase. The purpose of this paper is to analyze the effect of the DBR system in a serial production line. Using Markov process, we modeled a DBR system with three stages. For the model developed we analyze the system characteristics and then present an optimization model for system design. The system performance is also analyzed through sensitivity analysis.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.344-350
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• 2002

An alternative to traditional production planning and control systems such as MRP and JIT is the drum-buffer-rope(DBR). Using the DBR system, companies can achieve a large reduction of work-in-process (WIP) and finished-goods inventories (FGI), significant improvement in scheduling performance, and substantial earnings increase. The purpose of this paper is to analyze the effect of the DBR system in a serial production line. Using Markov process, we modeled a DBR system with three stages. For the model developed, we analyze the system characteristics and then present an optimization model for system design. The system performance is also analyzed through sensitivity analysis.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.4
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• pp.334-344
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• 2003

A mixture experiment is a special type of response surface experiment in which factors are the ingredients or components of a mixture, and the response is a function of the proportions of each ingredient. Evolutionary operation is useful to improve on-line full-scale manufacturing process by systematically changing the levels of the process variables without jeopardizing the product. This paper presents an evolutionary operation procedure with mixture variables for large-scale mixture production process which can be beneficial to practitioners who should improve on-line mixture quality while maintaining the production amount of the mixture product.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.28-29
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• 2015

The tire production facility is a large-scale construction with the complexity of a manufacturing process. The process utilities should be wide-ranging as an effective arrangement of them is highly important. All the necessary information should be clarified together with the manufacturer at the basic planning stage, and this design should be developed to comply with the local culture and regulations. It is important to carry out more advanced engineering in terms of process, cost and quality, even if it is difficult to standardize due to the cultural and geographical conditions and regulations. The key point is to reflect all the given conditions and make a clear design during the design stage, to eliminate the problems after the construction has begun. Another key point is the delivery system, which must be totally managed from the initial design stage until the construction stage by proven companies. Flexibility, quick action, and single responsibility will be the fundamental features in all the steps of the project.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.102-109
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• 2018

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.