• 소성∙가공
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• 제15권1호
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• pp.82-88
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• 2006

In this paper, the web-based monitoring system is developed for the effective process monitoring of mold manufacturing using web. In developed system, the cutting force for monitoring the manufacturing condition is measured using hall-sensor that is low cost and useful to be installed in a machine tool indirectly. Specially, the current of main spindle in a machine tool is converted into cutting force by various experiments. For effective web-based monitoring, the program which runs in the local computer of client is made to exchange message between a server and a client by making of ActiveX control and the result of manufacturing is shown on web-browser by Ch language. The developed system in this study is the foundation of establishing E-manufacturing in mold factory.

• 전자통신동향분석
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• 제38권6호
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• pp.75-83
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• 2023

Smart manufacturing in Industry 4.0 is developing toward autonomous manufacturing as a last-mile technology. We investigate development trends in manufacturing innovation technologies, review major industrial intelligence projects currently carried out at ETRI, and infer directions of future technology developments.

• 과학기술학연구
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• 제18권2호
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• pp.269-306
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• 2018

포항시는 철강업 등의 일부 제조업에 영향을 크게 받는 우리나라의 대표적인 기업도시이다. 이러한 대기업 중심 기업도시의 모델은 우리나라 제조업 발전의 중요한 바로미터가 되어 왔다. 하지만 최근 경기침체와 위기가 확대되고 있는 상황에서 제조 한계 극복의 방안으로 논의되고 있는 보급 상황과 방향에 대한 포항 차원의 논의를 진행해 보고자 한다. 본 연구를 통해 첫째 현재의 스마트 공장 구축의 현황과 포항지역의 산업적 여건 그리고 추진 분야에 대한 검토 두 번째, 지역 기업들의 설문 자료를 통해 산업구조 고도화와 효율성을 위한 함의점과 차세대 생산혁명에 대비한 지역차원의 준비와 산업적 측면에서의 변화를 준비하고자 한다. 이러한 현황 분석과 기업 조사를 통해 다음과 같은 포항 지역 스마트공장 지원의 정책 대안을 새롭게 제시하고자 한다. 첫째, 포항시가 경북도 등 광역지자체와 협력하여 지역 특화형 스마트공장 지원 플랜을 구축할 필요가 있다. 둘째, 포항시 기업협의체, 업종별 협동조합 등 기업 중간조직이 업종별 특성에 맞는 스마트공장을 업계 자발적으로 개발하고 이를 보급하는 방식으로 전환할 필요가 있다. 셋째, 스마트공장 보급에서 가장 중요한 행위자는 스마트공장 IT 솔루션 공급사로 지역 중소기업간 연계 및 협력 강화가 중요하다. 현재의 포항 지역의 산업특성상 대기업과의 협력을 통한 공급가치사슬을 고려한 스마트공장 지원 프로그램의 마련이 구체화되어야 한다.

• 산업공학
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• 제10권3호
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• pp.145-153
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• 1997

This paper deals with constructing a scheduling system for a mold manufacturing factory. The scheduling system is composed of 4 submodules such as pre-processor, neural network training, neural networks and simulation. Pre-processor analyzes the condition of workshop and generates input data to neural networks. Network training module is performed by using the condition of workshop, performance measures, and dispatching rules. Neural networks module presents the most optimized dispatching rule, based on previous training data according to the current condition of workshop. Simulation module predicts the earliest completion date of a mold by forward scheduling with the presented dispatching rules, and suggests a possible issue date of a material by backward tracking. The system developed shows a great potential when applied in real mold factory for automotive parts.

• 한국산업융합학회 논문집
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• 제22권5호
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• pp.561-573
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• 2019

This study proposes a new approach to implement smart factory based on robot monitoring system for a small and medium sized enterprise. The simulator includes the forward kinematics and inverse kinematics analyzes of articulated robots. We also modeled the dynamics of the robot and made it possible to simulate it in the program. We studied the interface between the user and the monitoring programming system using the GUI environment of Windows OS, and it is configured to select the appropriate trajectory planning and control method. The reliability of simulator is illustrated by simulation test.

• 한국산업융합학회 논문집
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• 제21권6호
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• pp.369-378
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• 2018

This study proposes a new approach to real time implimemtation of shape recognition technology of die casting and forging parts based on robot vision for smart factory. The proposed shape recognition and inspection technology for forging and die casting parts is very useful for manufacturing process automatiom and smart factory including external form's automatic inspection of machanical or electronic panrs for the precision verification. The reliabiblity of proposed technology Ihas been illustrated through experiments.

• 한국산업융합학회 논문집
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• 제24권4_1호
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• pp.397-409
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• 2021

This study proposes a new approach to implimentation of robust control and torque control response analysis based on monitoring simulator for smart factory. According to the physical properties of a flexible manipulator, a two time-scale approach, namely, singular perturbation ap proach, is further utilized for thorough analysis and general controller design. It is shown that asymptotic motional tracking can be effectively achieved, whereas the force regulation errors can be made arbitrarily small. For demonstration of the proposed technology performance, experiments of a eight joint flexible manipulator are performed for the proposed control method, and the reliability of proposed control results are illustrated based on monitoring simulator.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.65-72
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• 2022

With the mark of the fourth industrial revolution, the smart factory is evolving into a new future manufacturing plant. As a human-machine-interactive tool, augmented reality (AR) helps workers acquire the proficiency needed in smart factories. The valuable data displayed on the AR device must be delivered intuitively to users. Current AR applications used in smart factories lack user movement calibration, and visual fiducial markers for position correction are detected only nearby. This paper demonstrates a marker-based object detection using perspective projection to adjust augmented content while maintaining the user's original perspective with displacement. A new angle, location, and scaling values for the AR content can be calculated by comparing equivalent marker positions in two images. Two experiments were conducted to verify the implementation of the algorithm and its practicality in the smart factory. The markers were well-detected in both experiments, and the applicability in smart factories was verified by presenting appropriate displacement values for AR contents according to various movements.

• 한국의류산업학회지
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• 제22권5호
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• pp.660-675
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• 2020

Since Industry 4.0, there is a growing interest in smart manufacturing across all industries. However, there are few studies on this topic in the garment industry despite the growing interest in implementing smart manufacturing. This paper presents the feasibility and essential considerations for implementing smart manufacturing in the garment industry. A systematic review analysis was conducted. Studies on garment manufacturing and smart manufacturing were searched separately in the Scopus database. Key technologies for each manufacturing were derived by keyword analysis. Studies on key technologies in each manufacturing were selected; in addition, bibliographic analysis and cluster analysis were conducted to understand the progress of technological development in the garment industry. In garment manufacturing, technology studies are rare as well as locally biased. In addition, there are technological gaps compared to other manufacturing. However, smart manufacturing studies are still in their infancy and the direction of garment manufacturing studies are toward smart manufacturing. More studies are needed to apply the key technologies of smart manufacturing to garment manufacturing. In this case, the progress of technology development, the difference in the industrial environment, and the level of implementation should be considered. Human components should be integrated into smart manufacturing systems in a labor-intensive garment manufacturing process.

• Asian Journal of Atmospheric Environment
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• 제11권2호
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• pp.122-130
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• 2017

The main purpose of the study was to clarify the properties of individual particles collected at each behavior space of a factory worker. The samplings of size-segregated ($PM_{2.1-1.1}$ and $PM_{4.7-3.3}$) indoor particles were conducted at three different behavior spaces of a factory worker who is engaged in an auto parts manufacturing plant (i.e., his home, his work place in factory, and his favorite restaurant). Elemental specification (i.e., relative elemental content and distribution in and/or on individual particles) was performed by a micro-PIXE system. Every element detected from the coarse particulate matters of home was classified into three groups, i.e., a group of high net-counts (Na, Al, and Si), a group of intermediate net-counts (Mg, S, Cl, K, and Ca), and a group of minor trace elements (P, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pb). The results of EF for $PM_{4.7-3.3}$ in home indicated that several heavy metals were generated from the sources within the house itself. An exceptional feature shown in the individual particles in workplace is that Cr, Mn, and Co were clearly detected in both fine and coarse particles. Cluster analysis suggested that the individual coarse particles ($PM_{4.7-3.3}$) collected at the indoor of factory were chemically heterogeneous and they modified with sea-salt, mineral, and artificially derived elements. The principal components in individual coarse particles collected at restaurant were sea-salt and mineral without mixing with harmful trace elements like chromium and manganese. Compared to the indoor fine particles of home and restaurant, many elements, especially, Cl, Na, Cr, Mn, Pb, and Zn showed overwhelmingly high net-counts in those of factory.