• 산업경영시스템학회지
• /
• 제42권3호
• /
• pp.25-38
• /
• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• 열처리공학회지
• /
• 제23권3호
• /
• pp.150-155
• /
• 2010

Generally, plasma nitriding process has composed with a nitriding layer within glow discharge region occurred by energy exchange. The dissociations of nitrogen molecules are very difficult to make neutral atoms or ionic nitrogen species via glow discharge area. However, the captured electrons in which a double-folded screen with same potential cathode can stimulate and come out some single atoms or activated ionic species. It was showed an important thing that is called "hat is a dominant component in this nitriding process?" in plasma nitriding process and it can take an effective species for without compound layer. During a plasma nitriding process, it was able to estimate with analyzing and identification by optical emission spectroscopy (OES) study. And then we can make comparative studies on the nitrogen transfer with plasma nitriding and ATONA process using plasma diagnosis and metallurgical observation. From these observations, we can understand role of active species of nitrogen, like N, $N^+$, ${N_2}^+$, ${N_2}^*$ and $NH_x$-radical, in bulk plasma of each process. And the same time, during DC plasma nitriding and other processes, the species of FeN atom or any ionic nitride species were not detected by OES analyzing.

• 한국빅데이터학회지
• /
• 제3권2호
• /
• pp.11-18
• /
• 2018

본 연구는 빅데이터 품질 진단의 핵심 요소인 도메인 기반 품질 진단을 위한 도메인 자동 판별에 관한 연구다. 빅데이터의 가치와 활용도의 증가와 4차 산업혁명의 대두로, 법률, 의료, 금융 등 IT와 융합된 다양한 분야에서 빅데이터를 활용하여 새로운 가치를 창출하려는 노력을 진행중이다. 하지만, 신뢰도가 낮은 데이터에 기반한 분석은 과정과 결과 모두에서 치명적인 문제를 발생하며, 분석 결과에 따른 판단 또한 신뢰하기 어려워 진다. 이처럼 신뢰도가 높은 데이터의 필요성 또한 증가하였지만, 데이터의 품질 확보에 대한 연구와 그에 대한 결과는 미비하다. 본 연구는 데이터 품질 향상을 위한 진단 평가의 핵심적 요소인 도메인 기반 품질 진단에서, 수작업으로 진행되었던 도메인 판별 작업을 머신러닝을 이용하여 자동화 함으로써, 작업시간을 단축하는 것을 목표로 한다. 데이터 베이스에 저장된, 도메인이 판별되어 있는 데이터의 특성에 관한 정보들을 추출하여 변수화하고, 이를 머신러닝을 이용하여 도메인 판별을 자동화 한다. 이를 빅데이터 품질 진단에 활용하고, 품질 향상에 기여하도록 한다.

• 한국산학기술학회논문지
• /
• 제10권11호
• /
• pp.3200-3206
• /
• 2009

본 논문은 현행 국내 우편기계 유지보수 체계의 문제점을 기술하고 이에 대한 개선 방안으로 현 우편기계 유지보수 방식과 다른 방식에 대해 경제성 및 효율성 측면에서 AHP 방식에 근거하여 조사한 결과를 제시하였다. 아울러 현 우편기계 유지보수 방식에서 정의되지 않은 예방 및 고장 수리에 대한 표준 절차와 우편기계 유지보수 이력관리 및 정보 공유 체계를 위한 유지보수 기술 지원 센터 운영 모델을 제시하였다. 제안된 우편기계 유지보수 방법은 우편기계 유지보수의 안전성과 효율성에 기여할 수 있다.

• 한국산학기술학회논문지
• /
• 제17권4호
• /
• pp.743-751
• /
• 2016

공동주택 유지관리 업무를 효율적으로 진행하기 위해서는 사후보전인 유지관리업무에서 벗어나 예방 차원의 관리체계로의 전환이 요구된다. 이를 위해서는 시설물의 점검 진단 교체 등의 일련의 작업을 시스템화 하는 것이 필요하며, 이보다 앞서 유지관리 업무의 표준화가 선행되어야 할 것이다. 따라서 본 연구에서는 현행 공공임대주택 유지관리 업무의 문제점을 분석하고 체계적인 관리를 위해서 전문가와의 1:1면담을 통해 입주자, 관리사무소, 본사의 업무체계로 구분하고 BPMN(Business Process Modeling Notation) 방식을 이용하여 일반관리 시설물관리 수선 및 보수 장기수선 업무 프로세스로 구분하여 제시하였다. 본 연구에서 제시한 표준업무체계는 공동주택 관리 시 업무의 효율성 제고를 통해 생산성 향상을 도모하고 지속적인 데이터 관리를 기반으로 공정성 및 투명성을 제공할 수 있을 것으로 기대한다. 또한 공동주택 유지관리 비용 및 진단조치 관리를 위한 시스템 개발 시 기초 자료로 활용될 수 있을 것이라 판단된다. 향후 더욱 더 객관적이고 표준화된 업무체계를 제시하기 위해서는 현장적용 후 입주자, 관리사무소, 본사 의견 및 업무 흐름에 따라 생산성 데이터 분석을 통해 추가적인 개선작업이 진행되어야 할 것이다.

• 제어로봇시스템학회논문지
• /
• 제22권4호
• /
• pp.276-280
• /
• 2016

Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $T^2$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.

• 반도체디스플레이기술학회지
• /
• 제22권4호
• /
• pp.113-118
• /
• 2023

Maintenance of semiconductor equipment processes is crucial for the continuous growth of the semiconductor market. The process must always be upheld in optimal condition to ensure a smooth supply of numerous parts. Additionally, it is imperative to monitor the status of the robots that play a central role in the process. Just as many senses of organs judge a person's body condition, robots also have numerous sensors that play a role, and like human joints, they can detect the condition first in the joints, which are the driving parts of the robot. Therefore, a normal state test bed and an abnormal state test bed using an aging reducer were constructed by simulating the joint, which is the driving part of the robot. Various sensors such as vibration, torque, encoder, and temperature were attached to accurately diagnose the robot's failure, and the test bed was built with an integrated system to collect and control data simultaneously in real-time. After configuring the user screen and building a database based on the collected data, the characteristic values of normal and abnormal data were analyzed, and machine learning was performed using the KNN (K-Nearest Neighbors) machine learning algorithm. This approach yielded an impressive 94% accuracy in failure diagnosis, underscoring the reliability of both the test bed and the data it produced.

• 한국전자통신학회논문지
• /
• 제15권2호
• /
• pp.307-312
• /
• 2020

본 논문에서는 산업 현장에서 효율적인 전동기 제어를 수행하도록 전동기 보호 릴레이, 스마트 회로 차단기 및 가변 속도 드라이브 등의 스마트 전동기 장치를 하나의 통합 모듈로 대체한 지능형 전동기 제어 시스템을 제안하였다. 제안된 지능형 전동기 제어 시스템은 CIP(Common Industrial Protocol)기반의 네트워크를 통하여 지능형 전동기 제어 시스템에 연결된 각각의 전동기 또는 부하에 대한 중요 데이터를 쉽게 모니터링할 수 있으므로 언제나 정확한 프로세스 제어가 가능하고, 고장 정보 및 기록에 실시간으로 액세스하여 진단을 간소화하며, 장비 가동 중단 시간을 최소화할 수 있다.

• 한국CDE학회논문집
• /
• 제17권4호
• /
• pp.274-281
• /
• 2012

This paper proposed a control simulation method for design and verification of the transport system in an automobile assembly line based on digital manufacturing system. The design of the transport system involves two major activities: mechanical design (device specification) and electrical design (device behavior and system control). Conventionally, the simulation and emulation system of the transport system focuses on the abstract level, which mainly deals with design verification, alternative comparison, and system diagnosis. Although it can provide overall system visibility in monitoring how well it works in the process and view, its simulation models are not sufficiently realistic to be used for a detailed design or for implementation purposes. In this paper, a digital simulation model for a transport system in an automotive assembly line is constructed by adapting a digital manufacturing methodology. We use the concept of the "Virtual Probe", which transport a carrier instead of the belt of the conveyor. In conclusion, the proposed method is valuable in the process of test run in the shop floor. This method would reduce the time and effort for validating the manufacturing system and improve the productivity and integrity of the control program.

• 반도체디스플레이기술학회지
• /
• 제18권4호
• /
• pp.92-95
• /
• 2019

Automation control and the data for control of industrial equipment for the diagnosis and prediction is a key to success in the 4th industrial revolution. It increases process efficiency and productivity through data collection, realtime monitoring, and the data analysis. However, university and research environment are still suffering from logging the data in manual way, and we occasionally loss the equipment data logging due to the lack of automatic data logging system. State variable presents the current condition of the equipment operation which is closely related to process result, and it is valuable to monitor and analyze the data for the equipment health monitoring. In this paper, we demonstrate the collection of equipment state variable data via programmable logic controller (PLC) and the visualization of the collected data over the Web access supervisory control and data acquisition (SCADA). Test vehicle for the implementation of the suggested SCADA system is a relay switched physical vapor deposition system in the university environment.