• The Journal of Economics, Marketing and Management
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• v.8 no.3
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• pp.23-36
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• 2020

Purpose: The purpose of this study is to identify the strategic direction of organizations and their employees to efficiently utilize smart factories and enhance business performance among Korean manufacturing companies. Research design, data, and methodology: We derived a structured research model to check the mediated effect of utilization of smart factory between the characteristics of smart factory and the innovation activities. Results: Quality characteristics of smart factory and Innovation activities were all found to have a statistically significant effect on utilization of smart factory, utilization of smart factory was found to have a statistically significant effect on the business performance. And it has been shown that the utilization of smart factory is partially mediated relative to the quality characteristics of smart factory and business performance and relative to innovation activities and business performance. Conclusions: Smart factory builders can reflect the areas that affect utilization of the smart factory in their strategies by considering the quality characteristics of the smart factory and innovation Activities. Therefore, smart factory builders can identify the quality characteristics of smart factory and reflect them in the process and analyze active utilize measures through the innovative activities of the employees of the organization, thereby influencing business performance.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.228-238
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• 2009

This paper first presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first involves a number of location known retailers choosing one factory to supply their demands from a number of factories whose locations are to be determined. The goal is to minimize the transportation and manufacturing cost to satisfy the demands. The problem is then augmented into the second problem, where the procurement cost of the raw materials from a chosen material supplier (from a number of suppliers) is considered for each factory. Economic beneficial is taken into account in the cost evaluation. Therefore, the partner selections will influence the cost of the supply chain significantly. To solve these problems, an agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM consecutively and alternatively enable and disable the advancement of agent gaming and the evolution of genetic computation. Computation results on solving a number of examples by the AGGAHM were compared with those from methods of a general genetic algorithm and a mutual frozen genetic algorithm. Results showed that the AGGAHM outperforms the methods solely using genetic algorithms. In addition, various parameter settings are tested and discussed to facilitate the supply chain designs.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.6
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• pp.139-146
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• 2019

The modular building system is a type of prefabricated construction method, and is an industrialized building system that transports, assembles, and completes a three-dimensional module manufactured in a factory to the site. The economics of a modular building system where 50 to 80% of the entire process takes place in a modular factory is dominated by productivity of the factory manufacturing process. Since the building of the module is finished by the combination of unit parts produced by each material, it is necessary to manage the process in each module unit. However, currently marketed process control programs do not reflect the features of these modular methods. In this paper, we introduce Modular Factory Design software(MFD 2019) that can make modular unit production plan which reflects production base(modular factory) and production target(application and number of modular units). In order to verify software compatibility and reliability, two production plans with different production methods were formulated and simulated.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.148-156
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• 2014

Generally, over 95% of manufacturing cost is determined in the design and manufacturing preparation step, especially a great part of productivity is determined in the manufacturing preparation step. In order to improve the manufacturing competitiveness, we have to verify the problems that can be occurred in the production step and remove the unnecessary factors in the manufacturing preparation step. Thus, manufacturing industries are adopting digital manufacturing system based on modeling & simulation. In this paper, we introduce e-FEED system (electronic based Front End Engineering and Design) that is the integrated design and analysis system for optimized manufacturing line development based on simulation automation and explain the work process (Design, Analysis and Optimization) about manufacturing line development using e-FEED system. Also, the effect is described through the real implementation cases.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.229-237
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• 2017

Presented in this paper is a case study of constructing a smart factory for aircraft parts. The construction procedure involves four phases. First of all, its management goals are set, and layout design and simulation are carried out in the conceptual design phase. In the detail design phase, operating scenarios for each module are written out, and probable risks are analyzed by expert groups, and then requirements for developing equipments and subsystems are determined with consideration for element technologies and their integration schemes into the smart factory. In the fabrication and installation phase, system development, equipment fabrication and installation are proceeded in a separate manner, and then integrated together subsequently. In the operation and improvement phase, the factory is stabilized, sophisticated and improved constantly during real operation.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.109-115
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• 2019

Smart Factory is a part of and a key point of the 4th industrial revolution. It performs optimization from the whole viewpoint, using comprehensive data of the post-process data by utilizing various sensors, controllers, and mobile devices beyond the existing factory automation level. In this paper, we design and implement an IoT platform that can detect the safety factors of the workers, the environmental factors of the factory, and real time monitoring at the control center, among the fields to implement smart factory. To accomplish this, we construct a monitoring device that provides sensor information control, server transmission of sensor information, and visualization of collected information. By using this system, it is possible to maintain the temperature and humidity for the optimum working environment in the factory. and also, By using the beacon, it is possible to measure the working time of the worker and trace the position.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.191-194
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• 2003

Product factory is a real-time financial product design system for the Internet customers. Recently, as the number of the Internet customers increases, the importance of the product factory becomes more emphasized. However, there is not much research performed regarding its definition, properties, requirements, nor implementation. In this research, we make a clear definition of product factory, and analyze the requirements of the system from the perspectives of functions and services, and we propose an architecture that reflects the analyzed requirements. In additions, we implemented a prototypical system based on the proposed architecture to prove the usefulness of this research.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.12-18
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• 2017

This study presents a plant concept design for a smart factory which is mainly targeted to machine airplane parts. The plant layout is based on the TOC-DBR approach together with autonomous distributed factory control considered, while discrete event simulation is also performed in order to validate its layout. The resulting layout and its procedure turn out to be quite a useful guideline in realizing those smart factories especially for machining-oriented manufacturing industries.