• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.73-86
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• 2018

Most electric products produced during the manufacturing process are produced after design and mass production under a given control standard. In particular, the development phase should present the criteria for the production process by setting appropriate limits based on the performance being targeted. Even if the standard of performance is set considering the performance of the process, measuring the performance of the product after actual production results will cause nonconformities with the expected results. Among the performance of electrical products, Energy standards represented by energy consumption efficiency continue to be of importance, and are mandatory standards that correspond to national standards in most countries. Therefore, statistical quality control of these standards shall basically have a large number of test equipment for each product, ensure sufficient test time and continuous sampling of product samples. In the end, companies that produce and sell electric appliances are striving to control mass production at a great cost, but this is not acceptable. This study presents basic characteristics of the energy efficiency of electrical products and proposes and conducts a case study on statistical production control methods for performance variation across products under the standards about domestic and international regulations.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.453-456
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• 2022

The role of the power grid is to ensure stable power supply. It is necessary to take various measures to prepare for unstable situations without notice. After identifying the relationship between features through exploratory data analysis using weather data, a machine learning based energy production prediction model is modeled. In this study, the prediction reliability was increased by extracting the features that affect energy production prediction using principal component analysis and then applying it to the machine learning model. By using the proposed model to predict the production energy for a specific period and compare it with the actual production value at that time, the performance of the energy production prediction applying the principal component analysis was confirmed.

• Asian-Australasian Journal of Animal Sciences
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• v.3 no.3
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• pp.225-229
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• 1990

Sixteen mature sheep were fed chaffed orchardgrass hay once a day. Jaw movement of the sheep was recorded for 24 hours before slaughter. Four sheep were slaughtered either prior to eating, 2, 8 or 16 hours after the commencement of eating to measure digesta pool size and particle size distribution in the reticulo-rumen. Eating time was restricted to 120 minutes. Rumination time and actual chewing time during rumination increased with time after the meal. Mean dry matter (DM) pool size before and 2 hours after the meal were 1.36 and 2.45 times of DM intake, respectively. The proportion of large particle (>1.18 mm; LP) in the DM ingested during the meal was caculated to be about 70%. The mean DM and LP pool sizes per DM intake and the mean proportion of LP in the DM pool decreased with time after the meal. There were close negative relationships between either DM or LP pool sizes per DM intake and the chewing activities either expressed as time spent rumination, actual chewing time during rumination or total actual chewing time(total of eating time and actual chewing time during rumination). The difference between DM intake and LP pool size were assumed to be LP degradation in the present experiment, and correlated positively with the chewing activities. A large proportion of the digesta load was comprised of small particles, in excess of the daily intake.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.61-61
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• 2008

• Proceedings of the Korea Society of Costume Conference
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• 2004.10a
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• pp.114-115
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• 2004

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.157-167
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• 2023

As a new trend in the development of urban public spaces, the use of right-angle LED screens perfectly combines building facades with naked-eye 3D visual effects, providing designers with a brand-new creative platform. How to create a realistic naked-eye 3D effect on a right-angle LED screen and bring an immersive visual experience to the audience has become a question worth exploring. So far, production companies have yet to announce the relevant design ideas and complete production methods. In order to explore the production principle and production process of the naked-eye 3D effect of the right-angle LED screen, we summarize the basic production principle of the naked-eye 3D impact of the right-angle LED screen through case analysis. Based on understanding the production principle, the actual case production test was carried out, and a complete production process of the naked eye 3D visual effect of the right-angle led screen was tried to be provided by off-line rendering. For the problem of how to deal with image deformation, we provide two production methods: post-production software correction and UV mapping. Among them, the UV mapping method is more efficient and convenient. Referring to this paper can help designers quickly understand the production principle of the naked eye 3D effect of right-angle LED screens. The production process proposed in this paper can provide a reference for production method for related project producers.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.59-73
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• 2023

In the era of the 4th Industrial Revolution, manufacturing is the implementation of smart factories through digital transformation, and refers to consumer-centered intelligent factories that combine next-generation digital new technologies and manufacturing technologies beyond the existing factory automation level. In order to successfully settle such a smart factory, it is necessary to train professionals. However, education for smart factories is difficult to have actual field mechanical facilities or overall production processes. Therefore, there is a need for a system that can visualize and control the flow and process of logistics at the actual production site. In this paper, the logistics flow of the actual site was implemented as a small FMS, a physical system, and the production process was implemented as a digital system. In real-time synchronization of the physical system and the digital system, the location of AGV and materials, and the process state can be monitored to see the flow of logistics and process processes at the actual manufacturing site. The developed digital twin system can be used as an effective educational system for training manpower in smart factories.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.132-140
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• 2020

It is very important to use appropriate nutrition water for crop growth in hydroponic farming facilities. However, in many cases, the supply of nutrition water is not designed with a precise plan, but is performed in a conventional manner. We proposes a forecasting technique for nutrition water requirements based on a data analysis for optimal strawberry production. To do this, the proposed forecasting technique uses linear regression for correlating strawberry production, soil condition, and environmental parameters with nutrition water demand for the actual two-stage strawberry production soil. Also, it includes predicting the optimal amount of nutrition water requires according to the heterogeneous cultivation environment and variety by comparing the amount of nutrition water needed for the growth and production of different kinds of strawberries. We suggested study uses two types of section beds that are compared to find out the best section bed production of strawberry growth. The dataset includes 233 samples collected from a real strawberry greenhouse, and the four predicted variables consist of the total amounts of nutrition water, average temperature, humidity, and CO₂ in the greenhouse.