• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.250-250
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• 2004

자동차의 시동을 걸기 위해서는 맨 처음 엔진을 강제로 가동시키는 기계장치가 있어야 하며, 이를 시동모터라 한다. 시동모터는 모터부와 그 부속장치 그리고 발생된 힘을 엔진으로 전달하는 동력전달 기구로 구성되어 있다. 동력전달기구는 플라이 휠이라는 부품을 크랭크 축 끝단에 장착한 후 그 원주상에 링 기어를 만들고, 시동모터의 축에 피니언이라는 작은 기어를 맞물리게 하여 시동 키를 돌리면 이 기어가 회전되는 원리를 이용하고 있다. 피니언 기어는 작고 반대로 플라이 휠에 장착되어 있는 링 기어는 크기 때문에 일정한 기어비가 형성되어 큰 부하의 엔진회전이 가능하다.(중략)

• Journal of IKEEE
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• v.23 no.1
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• pp.224-229
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• 2019

Seat of automobile is required to support the comfort to driver and passenger during the driving. The control method of the seat position is changed from manual type to power type, which means using the motor to increase the comfort of the driver. By using the motor, several problems, such as vibration, noise, and over-current, appeared. These problems can be reduced through the control of seat motor. In this study, a control technology of four control variables, which determine profile of the input voltage applying to the seat motor, is proposed to generate the current profile having soft-start and soft-stop. The current flowing through the coil by input voltage is described by mathematical modeling of power seat. It is confirmed that optimized current profile having soft-start and soft-stop can be generated from simulation using the mathematical model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.197-197
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• 2003

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.85-91
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• 2021

In our daily life, artificial intelligence performs simple and complicated tasks like us, including operating mobile phones and working at homes and workplaces. Artificial intelligence is used in industrial technology for diagnosing various types of equipment using the machine learning technology. This study presents a fault mode effect analysis (FMEA) of start motors using machine learning and big data. Through multiple data collection, we observed that the primary failure of the start motor was caused by the melting of the magnetic switch inside the start motor causing it to fail. Long-short-term memory (LSTM) was used to diagnose the condition of the magnetic locations, and synthetic data were generated using the synthetic minority oversampling technique (SMOTE). This technique has the advantage of increasing the data accuracy. LSTM can also predict a start motor failure.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.381-392
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• 2020

The necessity and the importance of the remanufacturing are increasing day by day along with environmental problems. Many studies are being conducted on remanufacturing, but the research for cleaning is much lacking. This study aims to evaluate the effective cleaning method for remanufacturing of start motors, one of the automobile parts. The cleaning process consists of oil stain removal, drying and rust removal processes. In this study, the two processes were conducted except for the drying process which has little influence on cleaning. The methodology for cleaning agent selection, degreasing and rust removal process was presented. For each methodology, five analysis factors were calculated by two-way comparison according to the process, and the values were evaluated quantitatively by substituting them into the evaluation table. In the selection of cleaning agent, neutral system, ultrasonic cleaning in degreasing, and grinding in rust removal were selected as the best cleaning methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.276-282
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• 2006

PID controller has been widely used in industry. Because it has a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and a robustness to system parameters variation and different velocity command. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Korean Society of Safety
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• v.34 no.5
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• pp.55-62
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• 2019

In this paper, we introduce a case of a fire accident during parking of a large truck that is repeatedly occurring. The shape and location of the combustion and electrical singularity commonly found in other vehicle fire accidents could limit the starter motor as the ignition section. In addition, it was possible to confirm the electrical melting singularity that could act as a cause of ignition between the start motor B terminal and the start motor enclosure. By combining the above investigations and investigations, it was possible to estimate the electric fire expressed from insulation breaking of the starter motor B terminal, and by using the renewable starter motor comparison product mounted on the fire vehicle, an experiment was performed to reproduce the ignition process from the starter motor under specific conditions. So. It is hoped that this will raise awareness about vehicle fires, which can lead to large fires or casualties, share the risks of using starter motors for regeneration, and help in the rapid and accurate investigation of similar vehicle fires in the future.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.