• 한국기계가공학회지
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• 제20권12호
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.33-40
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• 2013

Purpose: The goal of this study was to build an accurate digital factory that evaluates the performance of a factory using computer simulation. To achieve this goal, we evaluated the effect of worker-related variables on production in a simulation model using comparative analysis of two cases. Methods: The overall work process and worker-related variables were determined and used to build a simulation model. Siemens PLM Software's Plant Simulation was used to build a simulation model. Also, two simulation models were built, where the only difference was the use of the worker-related variable, and the total daily production analyzed and compared in terms of the individual process. Additionally, worker efficiency was evaluated based on worker analysis. Results: When the daily production of the two models were compared, a 0.16% error rate was observed for the model where the worker-related variables were applied and error rate was approximately 5.35% for the model where the worker-related variables were not applied. In addition, the production in the individual processes showed lower error rate in the model that included the worker-related variables than the model where the worker-related variables were not used. Also, among the total of 22 workers, only three workers satisfied the IFRS (International Financial Reporting Standards) suggested worker capacity rate (90%). Conclusions: In the daily total production and individual process production, the model that included the worker-related variables produced results that were closer to the real production values. This result indicates the importance of worker elements as input variables, in regards to building accurate simulation models. Also, as suggested in this study, the model that included the worker-related variables can be utilized to analyze in more detail actual production. The results from this study are expected to be utilized to improve the work process and worker efficiency.

• 한국건설관리학회논문집
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• 제6권3호
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• pp.61-71
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• 2005

외국인 근로자들은 90년대 들어 그 수가 급격히 증가하였고, 각종 제조업이나 3D업종에서 중요한 위치를 차지하게 되었다. 이러한 상황에서 정부는 산업기술 연수생이라는 제도를 통해서 편법적으로 외국인 근로자를 수입하는 정책을 유지해왔었다. 산업기술 연수생은 불분명한 신분을 가진 외국인 근로자들에 대한 차별과 인권 유린으로 수많은 사업장 이탈자를 만들었다. 2004년 8월에 도입된 '고용허가제'는 그 동안의 국내 외국인력 정책을 그 근본에서부터 바꿨다는 점에서 그 의의가 있다. 고용허가제의 도입은 제조업 및 서비스업 뿐만 아니 라 건설업에도 많은 영향을 미칠 것으로 기대된다. 이에 본 연구에서는 외국인 근로자와 고용허가제의 정보를 바탕으로 고용허가제가 건설현장에 미치는 인건비, 작업품질 및 태도, 노동력 수급, 의사소통에 대해 현장관리자와의 설문조사를 실시하였다. 도출된 현장관리자들의 인식을 통해 향후 건설업에서의 부작용을 제거하고 대응방안을 제시하고자 한다.

• 한국컴퓨터정보학회논문지
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• 제25권7호
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• pp.143-150
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• 2020

최근 모바일, 클라우드, 그리고 사물인터넷의 융합으로 다양한 스마트팩토리 서비스가 제공되고, 많은 기업에서도 관심을 가지고 있다. 그러나 대부분의 시스템은 근로자 관점에서 구현되지 않았기 때문에 근로자로부터 외면 받고 있다. 이에 본 논문은 스마트공장 서비스를 수요자들이 정의하여 사용할 수 있도록 서비스 제작을 현장 근로자가 직접할 수 있는 개발도구를 구현하였다. 서비스에 사용되는 제조데이터는 제조설비와 연결된 센서로부터 실시간으로 수집하여 스마트팩토리 플랫폼 내에 저장된다. 그리고 플랫폼에 저장된 제조데이터로부터 설비 모니터링, 공정상태분석, 설비 제어 등 다양한 스마트 공장 서비스를 근로자가 직접 드래그앤드롭 방식으로 매우 쉽게 만들 수 있다. 구현된 시스템은 특히 소규모 제조 기업에서 기업의 특정 목적에 맞게 수시로 서비스를 변경해야하는 환경에서 더욱더 큰 효과를 낼 것으로 예상된다. 또한, 현장 근로자의 스마트팩토리 운용 및 활용 능력 향상은 물론 중소기업의 스마트팩토리 인재 양성에 많은 도움이 될 것으로 기대된다.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 2004년도 추계학술대회
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• pp.11-11
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• 2004

• 한국산업보건학회지
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• 제1권2호
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• pp.144-153
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• 1991

This study was conducted to evaluate worker exposure to airborne asbestos fibers by industry, and to evaluate polarized-light microscopy for determining airborne asbestos fibers. A total of 11 plants including asbestos textile, brake-lining manufacturing, slate manufacturing, and automobile maintenance shops were investigated. Rsults of the study are summarized as follows. 1. Worker exposure levels to airborne asbestos fibers were the highest in asbestos textile industry, followed by brake-lining manufacturing, slate manufacturing, and automobile maintenance shops, in order. In asbestos textile industry, large variation of asbestos levels was found by plants. The worst plant indicated airborne fiber concentrations in excess of 10 fibers/cc, however, the best plant showed concentrations within 0.50 fibers/cc. 2. Characterization of airborne fibers by industry indicated that fibers from asbestos textile industry were the longest with the largest aspect ratio. Fibers from automobile maintenance shops were the shortest with the smallest aspect ratio. Based on characteristics of fibers and the highest levels of concentrations, it is concluded that workers in the asbestos textile industry are exposed to the highest risk of producing asbestosis, lung cancer, and mesothelioma. 3. Result s obtained using polarized-light microscopy were $43.7{\pm}12.3%$ of the results obtained using phase contrast microscopy. This may be resulted from the worse resolution of polarized-light microscopy than that of phase contrast microscopy. Based on the results, it is recommended that polarized-light microscopy be used for mainly bulk sample analyses and further study be performed to improve the method for determining airborne samples. However, polarized-light microscopy can be used for determining thick fibers.

• 대한안전경영과학회지
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• 제9권6호
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• pp.123-135
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• 2007

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

• 디지털융복합연구
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• 제13권1호
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• pp.375-382
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• 2015

본 연구는 직종별 문제음주 관련 요인을 확인하고자 시도되었다. 본 연구는 2012년 1월부터 12월까지 수집된 국민건강영양조사 자료를 이용하여 분석하였다. 전체 대상자 중 본 연구의 목적에 따라 사무직 391명, 생산직 707명, 서비스직 309명을 최종 대상자로 선정하였다. 자료는 Rao-Scott 카이제곱 검정과 로지스틱 회귀분석으로 분석하였다. 알코올사용장애 선별검사 도구를 이용하여 8점 이상을 문제음주군, 8점 미만은 정상음주군으로 분류하여 분석한 결과 문제음주율은 사무직이 45.1%, 생산직 39.1%, 서비스직 42.3%로 나타났으나 직종간 통계적으로 유의한 차이는 없었다. 문제음주 관련 요인은 직종에 따라 차이가 있었는데 사무직은 흡연만이 관련 요인으로 확인되었으며 흡연자의 문제음주 위험이 4.44배 높았다. 생산직은 배우자가 있는 경우 문제음주 위험이 0.46배 낮고 흡연자는 4.07배 높았다. 서비스직은 20대에 비해 60대 이상의 문제음주 위험이 0.02배 낮은 반면 흡연자는 11.17배 높게 나타났다. 본 연구는 직종별 문제음주 관련 요인의 차이를 확인하였으며 향후 본 결과가 음주 중재프로그램 개발에 의미있게 활용될 수 있을 것이라 생각한다.

• 대한임베디드공학회논문지
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• 제18권6호
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2004년도 제5회 정기학술발표대회 논문집
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• pp.592-595
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• 2004

외국인 노동자들은 90년대 들어 그 수가 급격히 증가하였고, 각종 제조업이나 3D업종에서 중요한 위치를 차지하게 되었다. 이번에 새로 도입된 `고용허가제`는 그 동안의 국내 외국인력 정책을 그 근본에서부터 바꾼 것이라는데 그 의의를 찾을 수 있다. 외국인 근로자와 고용허가제의 정보를 바탕으로 공용허가제가 건설현장에 미칠 영향요소에 대해 설문조사를 실시하였다. 도출된 현장관리자들의 인식을 통해 향후 건설업체에서의 부작용을 제거하여 외국인 근로자 활용에 필요한 연구 방향을 제시할 것이다.