• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.41-47
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• 2012

Railroad rolling stock has long service life and a lot of maintenance cost running on rail by wear and vibration. And it is very important to get optimization of maintenance. This paper want to analyze rolling stock maintenance situation of KORAIL and find out its improvement methods. Especially, the purpose of this paper is to adopt the most effective maintenance period and methods to daily inspection which needs many maintenance manpower in rolling stock. Rolling stock has self-diagnosis function using computer system and the quality of rolling stock has much improved these days but current daily inspection repeat for short period routinely and it is very ineffective. Therefore, the paper adopt improved daily inspection period reflecting the characteristics of rolling stock, and want to secure reliability of rolling stock and minimize maintenance cost.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1642-1649
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• 2010

At present, KORAIL is in the middle of renovating. All steps exert great effort at cost reduction and a profit improvement. Especially to improve maintenance method and inspection period at the rolling-stock division lots of research is under progress. Daily inspection of rolling stocks is to operate the rolling stock normally. Daily inspection items are driving control device, coupling device, brake system, water system and air conditioning system, electrical system etc. Half of the maintenance manpower are inputted at daily inspection. Strengthens the quality and optimize the proportion of daily inspection are urgent problem. Daily inspection period extension aim is as follows. KTX from 3,500km to 5,000km, passenger car from 1st to 3,500km, new style electric locomotive from 2nd to 5,000km, the diesel locomotive is 2,800km from 1,200km. In this paper, the optimal daily inspection period and methods are considered including expected problem and counter measures.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1025-1027
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• 2022

도시화가 급속도로 진행됨에 따라서 일상생활에서 생활폐기물의 관리와 처리에 대한 문제가 심각해지고 있다. 이 문제를 해결하고자 어플리케이션을 통해 생활폐기물 처리를 쉽게 할 수 있는 시스템을 제안한다. '싹처리'는 편리성, 정확성, 확장성, 수익성을 가지고 (중)대형 생활 폐기물 처리하는 딥러닝 어플리케이션이다. 어플리케이션 내의 저장된 딥러닝 과정으로 학습되어진 생활폐기물 분류 모델을 통해 폐기물 사진을 자동 인식하는 과정으로 누구나 쉽게 폐기물 배출을 신청할 수 있다. 정확한 딥러닝 알고리즘과 전이학습, 데이터 검수 등을 통해 높은 성능의 사물 자동 인식을 할 수 있다. 이 시스템을 통해 임산부, 장애인, 독거노인 등의 사회적 약자는 불필요한 과정 없이 손쉽게 폐기물을 처리할 수 있고, 더 나아가 중고시장의 활성화에 기여할 수 있는 가치가 있다.