• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.345-346
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• 2006

In the future, a machine will be more improved in the form of advanced concept with collaborative ability in M2M(Machine to Machine, Mobile to Machine) environment for u-Manufacturing system. This paper tried to standardize M2M and design advanced concept machine. The M2M is front-end system for implementing autonomous ubiquitous environment. The advanced machine in M2M will be a collaborative machine with knowledge-evolutionary ability such as u-Machine(Ubiquitous machine), Vortal(Vertical Portal) machine and P2P(Peer to Peer) machine. Such advanced concept machines will be the key subject for M2M cooperation.

• Journal of Powder Materials
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• v.26 no.6
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• pp.528-538
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• 2019

The transition from "More-of-Less" markets (economies of scale) to "Less-of-More" markets (economies of scope) is supported by advances of disruptive manufacturing and reconfigurable-supply-chain management technologies. With the prevalence of cyber-physical manufacturing systems, additive manufacturing technology is of great impact on industry, the economy, and society. Traditionally, backbone structures are built via bottom-up manufacturing with either pre-fabricated building blocks such as bricks or with layer-by-layer concrete casting such as climbing form-work casting. In both cases, the design selection is limited by form-work design and cost. Accordingly, the tool-less building of architecture with high design freedom is attractive. In the present study, we review the technological trends of additive manufacturing for construction-scale additive manufacturing in particular. The rapid tooling of patterns or molds and rapid manufacturing of construction parts or whole structures is extensively explored through uncertainties from technology. The future regulation still has drawbacks in the adoption of additive manufacturing in construction industries.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.647-664
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• 2022

Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.93-96
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• 2002

The manufacturing paradigm has shifted dramatically over the past decade from “push” or mass production mode to “pull” or customer-driven, order-based manufacturing mode, as multitudes of customers now demand mass customization of configurable products. As a means to achieve such rapidly responsive manufacturing system, Advanced Planning System (APS) has become an essential software tool for achieving modern “build-to-order” and “configure-to-order” manufacturing environment. APS enables manufacturers to respond to variety of customer demands In real time by instantly configuring manufacturing processes based on specifications described in each purchase orders and providing capable-to-promise information directly to customer by performing rapid “what-if” manufacturing simulated scenarios. This paper discusses the working of such system as well as the business processes that incorporate such systems to enable efficient “build-to-order” environment.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.34-35
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• 2006

The development of Micro MIM as a new manufacturing process for metallic micro parts made of advanced functional materials has been the subject of considerable research over the last years. This paper addresses important quality aspects on processing of new materials by Micro-MIM. Three examples of new functional materials that can be processed are reviewed in this paper. The first example is two-component-Micro-MIM to obtain multi-functional devices. A micro positioning encoder consisting of a magnetic / non-magnetic material combination is presented. The second issue is series production of the replicate of the smallest human bone in the ear (stapes) from Titanium as an example of medical application. Quality assurance and reproducibility in terms of injection moulding parameters are addressed. In the third part, first results on the processing of the shape memory alloy NiTi by Micro-MIM are presented. Potential applications include biocompatible devices and transportation, for example automotive and aerospace. Processing routes and initial microstructures obtained are discussed.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.141-159
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• 2016

Bearing joint dynamic parameter identification is crucial in modeling the high speed spindles for machining centers used to predict the stability and natural frequencies of high speed spindles. In this paper, a hybrid method is proposed to identify the dynamic stiffness of bearing joint for the high speed spindles. The hybrid method refers to the analytical approach and experimental method. The support stiffness of spindle shaft can be obtained by adopting receptance coupling substructure analysis method, which consists of series connected bearing and joint stiffness. The bearing stiffness is calculated based on the Hertz contact theory. According to the proposed series stiffness equation, the stiffness of bearing joint can be separated from the composite stiffness. Then, one can obtain the bearing joint stiffness fitting formulas and its variation law under different preload. An experimental set-up with variable preload spindle is developed and the experiment is provided for the validation of presented bearing joint stiffness identification method. The results show that the bearing joint significantly cuts down the support stiffness of the spindles, which can seriously affects the dynamic characteristic of the high speed spindles.

• Journal of Powder Materials
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• v.28 no.2
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• pp.91-96
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• 2021

Rare earth magnets with excellent magnetic properties are indispensable in the electric device, wind turbine, and e-mobility industries. The demand for the development of eco-friendly recycling techniques has increased to realize sustainable green technology, and the supply of rare earth resources, which are critical for the production of permanent magnets, are limited. Liquid metal extraction (LME), which is a type of pyrometallurgical recycling, is known to selectively extract the metal forms of rare earth elements. Although several studies have been carried out on the formation of intermetallic compounds and oxides, the effect of oxide formation on the extraction efficiency in the LME process remains unknown. In this study, microstructural and phase analyses are conducted to confirm the oxidation behavior of magnets pulverized by a jaw crusher. The LME process is performed with pulverized scrap, and extraction percentages are calculated to confirm the effect of the oxide phases on the extraction of Dy during the reaction. During the L ME process, Nd is completely extracted after 6 h, while Dy remains as Dy₂Fe₁₇ and Dy-oxide. Because the decomposition rate of Dy₂Fe₁₇ is faster than the reduction rate of Dy-oxide, the importance of controlling Dy-oxide on Dy extraction is confirmed.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.601-601
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• 2006

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.103-103
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• 2006

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.187-190
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• 2003

Many manufacturing companies consider the integrated and concurrent scheduling because they need the global optimization technology that could manufacture various products more responsive to customer needs. In this paper, we propose an advanced scheduling model to generate the schedules considering resource constraints and precedence constraints in make-to-order (MTO) manufacturing environments. Precedence of work- in-process(WIP) and resources constraints have recently emerged as one of the main constraints in advanced scheduling problems. The advanced scheduling problems is formulated as a multiobjective mathematical model for generating operation schedules which are obeyed resources constraints, alternative workstations of operations and the precedence constraints of WIP in MTO manufacturing. For effectively solving the advanced scheduling problem, the multi-objective hybrid genetic algorithm (m-hGA) is proposed in this paper. The m-hGA is to minimize the makespan, total flow time of order, and maximum tardiness for each order, simultaneously. The m-hGA approach with local search-based mutation through swap mutation is developed to solve the advanced scheduling problem. Numerical example is tested and presented for advanced scheduling problems with various orders to describe the performance of the proposed m-hGA.