• IE interfaces
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• v.20 no.3
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• pp.277-287
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• 2007

Semiconductor manufacturing is one of the most complex and capital-intensive processes composed of several hundreds of operations. In today’s competitive business environments, it is more important than ever before to manage manufacturing process effectively to achieve better performances in terms of customer satisfaction and productivity than those of competitors. So, many semiconductor manufacturing companies implement advanced planning and scheduling (APS) system as a management tool for the complex semiconductor manufacturing process. In this study, we explain roles of production planning and scheduling in semiconductor manufacturing and principal factors that make the production planning and scheduling more difficult. We describe the APS system implementation project at Korean semiconductor manufacturing company in terms of key issues with realistic samples.

• 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 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 the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.39-47
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• 2015

Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today's manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.55-61
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• 2014

Recently, the manufacturing system is being changed in a mass customization and small quantity batch production. MES is a powerful production management tool supporting production optimization from the process initiation to the final shipment. It is a production management system which plans and executes based on the production data in the shop floor. This study deployed the utilization of production data and web HMI system to process real-time production data through the collection with the shop floor. The developed system was applied to the equipment operating time and other production data could be processed with the real-time. The proposed system and web HMI can be applied for various production systems by using different logic.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.517-521
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• 2016

General industrial robots are difficult to use for precision assembly because they are operated based on position control. Their position accuracy is also usually higher than the assembly clearance (several tens of ${\mu}m$). In previous researches, force control was suggested as a robotic assembly solution. However, this method is difficult to apply in reality because of speed and cost problems. The RCC provides high speed, but applications are limited because the compliance is fixed, and it cannot detect an assembly condition during a task. A variable passive compliance device (VPCD) was developed herein. The VPCD can detect the assembly condition during tasks. This device can provide proper compliance for successful assembly tasks. The pneumatic system and the Stewart platform with an LVDT sensor were applied for measuring the displacement and variable compliance, respectively. The concept design and analysis were conducted to prove the effectiveness of the developed VPCD.

• Journal of Powder Materials
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• v.27 no.5
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• pp.420-428
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• 2020

Additive manufacturing technology is recognized as an optimal technology for mass-customized distributed production because it can yield products with high design freedom by applying an automated production system. However, the introduction of novel technologies to the additive manufacturing industry is generally delayed, and technology uncertainty has been pointed out as one of the main causes. This paper presents the results of the research and analysis of current standardization trends that are related to additive manufacturing by examining the hierarchical structure of the quality system along with the various industry and evaluation standards. Consequently, it was confirmed that the currently unfolding standardization does not sufficiently reflect the characteristics of additive manufacturing technology, and rather can become a barrier to entry for market participants or an element that suppresses the lateral shearing ability of additive manufacturing technology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.151-161
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• 1999

For many decades, Deterministic DCF approach has been widely used to evaluate investment opportunities. Under new manufacturing conditions involving uncertainty and risk, the DCF approach is not appropriate. In DCF, Risk is incorporated in two ways: certainty equivalent method, risk adjusted discount rate. This paper proposes a determination method of the Risk Adjusted Discount Rate for economically decision making advanced manufacturing technologies. Conventional DCF techniques typically use discount rate which do not consider the difference in risk of differential investment options and periods. Due to their relative efficiency, advanced manufacturing technologies have different degree of risk. The risk differential of investments is included using $\beta$ coefficient of capital asset pricing model. The comparison between existing and proposed method investigated. The DCF model using proposed risk adjusted discount rate enable more reasonable evaluation of advanced manufacturing technologies.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.69-78
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• 2001

This paper presents a process and operation planning system and an NC code post-processor for effective machining of press dies for production of cars. Based on the machining feature, major parts of press dies are categorized into 15 groups and a standard process plan is defined for each group. The standard process plan consists of a series of processes where a process is defined as a group of operations that can be done with one setup. Details such as cutting tools, cutting conditions, and tool paths are decided at the operation planning stage. At the final stage of process and operation planning, the NC code post-processor adjusts feedrates along the tool path to reduce machining time while maintaining the quality. The adjustment rule is selected based on the machining load estimated by virtual machining.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.800-807
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• 2003

Decomposition of tasks in the ordinary manufacturing systems is usually based on the predefined goal of the system. To achieve the high-level-goals (e.g., factory goal or company goal), several sub-goals should be achieved in advance. However, goals can change along with the current status of the system and the external environmental situations. Thus, a manufacturing system should support the goal-formations which can be bearable these changes for efficient and effective operations. Therefore, it IS necessary to develop a systematic methodology for the goal-formations in a manufacturing system. Especially, the formation and/or change of goals in real-time should be possible for distributed and dynamic systems including the fractal manufacturing system (FrMS). In this paper, a threefold methodology is proposed for the goal-formation process (GFP) in the FrMS; 1) a goal­generating process (GGP) to make and propagate fuzzy goals, 2) a goal-harmonizing process (GHP) to eliminate or reduce conflicts and interferences of goals by using a mobile agent- based negotiation scheme, and 3) a goal-balancing process (GBP) to make a compromise between goals by using quantifiable indicators of the manufacturing system.