• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권9호
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• pp.393-402
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• 2015

데이터 시각화 기술은 다양한 데이터와 그 분석 결과를 쉽게 이해할 수 있도록 도와줌으로써 제조현장과 같은 실제 산업현장에서도 그 유용성이 기대되고 있다. 제조현장에서 발생하는 대량의 데이터는 제조 기술의 표준화를 위한 기반 데이터가 될 수 있으며 제조공정의 개선을 위하여 매우 중요한 역할을 수행할 수 있다. 본 논문에서는 실험계획법과 데이터 분석 기반의 제조공정 최적화를 위한 정보 시각화 방법을 제안한다. 데이터 분석 결과의 정보 시각화를 통하여 작업 현장에 이해하기 쉬운 분석 결과를 제공함으로써 다양한 불량원인을 감소시키고 제조공정을 개선시킬 수 있다.

• 대한산업공학회지
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• 제38권2호
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• pp.98-106
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• 2012

The current market preassure of least environmental effects of products needs companies to consider whole life cycle of their products during their design phase. To support the integrated and collaborative development of the products, this paper proposed product data model for extended Product Data Managemen (PDM) that can support integrated design of product, manufacturing process, and customer services, based on the consistent and comprehensive PDM databases. The product data model enables design, manufacturing, and service engineers to express their products and services efficiently, with sharing consistent product data, engineering changes, and both economical and environmental evaluations on their design alternatives. The product data model was implemented with a prototype PDM system, and validated through an example product. The result shows that the PDM based on the proposed product data model can support the integrated design for products, manufacturing process, and customer services, and provide an environment of collaborative product development for design, manufacturing and service engineers.

• 한국CDE학회논문집
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• 제19권4호
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• pp.434-442
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• 2014

Most manufacturing enterprises create CAD data as a result of the product/part design process; however, the CAD data is being utilized only for production activities. Besides the processes directly related to manufacturing such as design and production, the CAD data is an important resource that can be used in variety of services (e.g., catalog production and production manuals) for manufacturing enterprises. This study proposes a software platform that can support a wide range of services for manufacturing companies in an efficient and productive way. The software platform was designed based on the functions identified by requirement analysis. The platform consists of four layers: data model layer to manage relevant data; library layer and common function layer to configure services; and application layer to install and run the software. Finally, this study evaluates the validity of the proposed platform architecture by applying it to the digital catalog system.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2002년도 금형가공 심포지엄
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• pp.26-33
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• 2002

Die Factory follows typical order adaptive manufacturing, and delaying delivery affects directly product development of customer, Manufacturing Management System is tried to comply with the appointed date of delivery. It acquires running signal from NC milling, calculates manufacturing results, and offers the basic data to manage the operation ratio. Thus it offers Production data necessary to accomplish the objective of progress improvement for Unmanned Manufacturing. Manufacturing Management System runs on Web Environment, and is composed of electronic work order, operation ratio data acquisition and totaling module.

• 한국시뮬레이션학회논문지
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• 제14권2호
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• pp.15-24
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• 2005

The goal of a distributed simulation such as battle field simulation is to combine all kinds of simulations in the same synthetic environment and to make people interact at the same time. It is a key issue to share the same synthetic environment among simulations. To support reusability and affordability in the modeling and simulation area, DMSO(Defense Modeling and Simulation Office) of USA developed concepts such as HLA(High Level Architecture) and SEDRIS (Synthetic Environmental Data Representation and Interchange Specification). In the industrial simulation area, the digital manufacturing is the main stream. To reduce cost and to reuse simulation environment, the standardization becomes the focus of digital manufacturing. This study proposes to use SEDRIS to improve interoperability of manufacturing data. The simulation data of DELMIA, which is a leading commercial digital manufacturing solution, is mapped and translated into the SEDRIS transmittal format. Mapping of the manufacturing simulation data and the synthetic environment are implemented and verified through experiments.

• 대한산업공학회지
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• 제17권2호
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• pp.115-129
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• 1991

An ecconomically competitive automated manufacturing system integrates the various control processes and data used in design, manufacturing, sale and service of products. CIM is a way to achieve such integration through computers and computational techniques in design, planning, and manufacturing. Developing effective CIM architectures is hampered by integration problems. The key to resolving these problems lies in a better understanding of manufacturing function and how it is related to other manufacturing functions. Integration of CIM environment requires coordinated solutions to data management problems for individual application system as well as for exchange of data between these applications. This requires a common framework for data management throughout the CIM environment. This paper discusses the design paradigm as a framework for this purpose. Designing an organizational structure to meet those goals involves 1) analyzing the functions through functional decomposition, 2) developing a data model to coordinate functions. As a result, we propose an object-oriented design methodology for manufacturing information system.

• Journal of Platform Technology
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• 제9권1호
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• pp.15-22
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• 2021

In a smart manufacturing environment, more and more devices are connected to the Internet so that a large volume of data can be obtained during all phases of the product life cycle. The large-scale industries, companies and organizations that have more operational units scattered among the various geographical locations face a huge resource consumption because of their unorganized structure of sharing resources among themselves that directly affects the supply chain of the corresponding concerns. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. The manufacturing units include machinery that may be situated in different geological areas and process instances that are executed from different machinery data should be constantly managed by the super admin to coordinate the manufacturing process in the large-scale industries these environments make the manufacturing process a tedious work to maintain the efficiency of the production unit. The data from all these instances should be monitored to maintain the integrity of the manufacturing service system, all these data are computed in the cloud environment which leads to the latency in the performance of the smart manufacturing service system. Instead, validating data from the external device, we propose to validate the data at the front-end of each device. The validation process can be automated by script validation and then the processed data will be sent to the cloud processing and storing unit. Along with the end-device data validation we will implement the APM(Asset Performance Management) to enhance the productive functionality of the manufacturers. The manufacturing service system will be chunked into modules based on the functionalities of the machines and process instances corresponding to the time schedules of the respective machines. On breaking the whole system into chunks of modules and further divisions as required we can reduce the data loss or data mismatch due to the processing of data from the instances that may be down for maintenance or malfunction ties of the machinery. This will help the admin to trace the individual domains of the smart manufacturing service system that needs attention for error recovery among the various process instances from different machines that operate on the various conditions. This helps in reducing the latency, which in turn increases the efficiency of the whole system

• International Journal of Quality Innovation
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• 제6권3호
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• pp.70-94
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• 2005

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work-order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the IC packaging industry, this work also proposes a WIP (i.e. work-in-process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

• 산업공학
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• 제9권3호
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• pp.225-235
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• 1996

The SECS Ⅰ and Ⅱ Protocol has been widely used for the TFT LCD and semiconductor industry. This paper shows how the SECS protocol is implemented for data communications between the Host (CAM) and the TFT LCD equipments. In addition, this study introduces a way to apply the SECS protocol to the manufacturing systems control. It provides better throughput in terms of production and faster control of the automated TFT LCD manufacturing system by way of shortcut and distribution of control and data communications. The SECS protocol is successfully used for the control of the real TFT LCD manufacturing system.

• 한국인터넷방송통신학회논문지
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• 제19권5호
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• pp.219-227
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• 2019

제조업의 생산 방법은 노동집약적인 방법에서 제조설비 중심의 기술집약적인 방법으로 변경되어가고 있다. 사람의 노동력을 제조설비가 대체하게 되면서 제조설비의 모니터링과 관리의 중요성이 강조되고 있다. 또한, 최근 빅데이터 기술은 한정된 데이터에서 새로운 가치를 찾아내는 중요한 기술로 등장하였다. 따라서 제조업의 변화는 기존 제조 공장에 사물인터넷(IoT), 정보통신기술, 센서 데이터, 빅데이터를 융합한 스마트팩토리의 필요성을 증대시켰다. 본 논문에서는 제조설비 데이터를 몽고DB에 실시간으로 분산 저장 및 처리하는 기술과 R 프로그래밍을 사용한 시각화를 통해 기존 국내 제조업 공장이 빅데이터 기반의 스마트팩토리가 되기 위한 전략을 제시하고자 한다.