• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.616-619
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• 2004

The term 'cost reduction' often carries a negative image in a sense of sacrifice of other management elements such as qualify, safety, client satisfaction, etc. However creative cost reduction approaches can achieve not only cost reduction itself but also value for money. The objective of this paper is to identify and discuss major characteristics of creative cost reduction strategies from best practice cases of Constructing Excellence.

• Journal of the Korea Institute of Building Construction
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• v.5 no.4 s.18
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• pp.4-10
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• 2005

• 월간 기계설비
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• s.258
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• pp.46-48
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• 2012

국토해양부는 지난해 12월 23일 권도엽 국토해양부장관 주재로 제3차 건설산업공생발전위원회 회의를 개최했다. 건설산업공생발전위원회는 지난해 10월 출범 이후 그동안 3차례의 본 위원회와 11차례의 실무위원회를 개최하여 ${\bigtriangleup}$건설산업 이미지 제고 ${\bigtriangleup}$건설산업 참여주체간 공생발전 정착 ${\bigtriangleup}$건설산업의 경쟁력 제고 및 미래시장 창출 등을 위한 다양한 과제들을 발굴하여 검토해 왔다. 이번 회의에서는 이들 과제 중에서 중요성, 시급성, 파급효과, 이해관계자 간 합의도출 가능성 등을 종합적으로 고려하여 우선적으로 추진이 필요한 과제들을 선정하여 조속히 추진해 나가기로 했다.

• 월간 기계설비
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• no.8 s.193
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• pp.40-50
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• 2006

하자발생은 막대한 보수비용과 함께 기업의 이미지와 신뢰성을 실추시키는 한 요인이다. 따라서 설비건설업계는 가급적이면 하자발생을 억제할 수 있는 공법개발과 함께 정밀한 시공으로 하자 발생율을 최대한 줄이기에 역정을 두고 있다. (주)우원(대표 김영호, 임종태)은 그동안 공동주택에서 발생한 하자사례를 모아 분석한 자료를 내놓았다. 이 자료를 토대로 유의하여 시공한다면 하자발생을 최대한 줄일 수 있을 것으로 보여진다.

• 월간 기계설비
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• s.240
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• pp.50-64
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• 2010

'그린'은 미래를 이끌어갈 신성장동력 즉, 향후 녹색성장을 주도할 핵심이다. 국내 주요 건설사들 역시 탄소저감기술 '그린'에 대한 영역확보와 시장선점에 사활을 걸면서 그린 기술을 접목한 첨단주택을 발빠르게 선보이고 있으며 특성화를 통해 브랜드의 친환경적 이미지를 높이고 있다. 정부도 저탄소 녹색성장을 추진하면서 '그린홈 보급사업'에 적극 나서고 있다. 바야흐로 친환경 녹색성장 시대에 접어든 것이다. 본지는 주택시장을 중심으로 빠르게 보급되고 있는 '그린홈'에 대해 알아본다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.171-172
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• 2023

본 연구는 건설현장 관리자를 대상으로 중대재해처벌법 인식이 건설업체의 경영성과에 미치는 영향을 실증적으로 확인하는 것이다. 최근의 사회적 이슈가 되는 중대재해처벌법이 건설회사 이미지 실추, 경제적 손실 등의 간접적인 손실뿐만 아니라, 최고경영자에게 직접적인 영향을 미친다. 또한 건설업체에서 중대재해 발생시에는 중대재해처벌법에 의하여 최고경영자의 구속등으로 기업의 업무연속성에 영향을 미치는 사회재난이다. 건설현장을 운영하는 기업의 사업주에게 중대재해로부터 실질적인 대처방안이 필요하며, 대안으로 건설현장 관리자의 중대재해처벌법의 위험성에 대하여 인식을 강조하여, 건설현장에서의 관리자가 주체가 되어 중대재해를 예방하고, 기업의 연속성을 확보하는 것이 필요하다.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.2
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• pp.177-184
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• 2017

Many ground subsidence accidents have happened in Korea. The accident was caused by the subsidence and leakage of the deteriorated sewage pipe. This study aims to establish the empirical data of the ground penetration radar(GPR) detection for ground subsidence. A test bed was also manufactured for the same purpose. The GPR detection variables are embedment depth and horizontal distance of embedded cast iron pipe and expanded polystyrene(EPS). From the detection results, the EPS embedded by a depth of 1.5m was difficult for detection. The EPS closely embedded to the cast iron pipe within a 0.5m distance had a very strong cast iron pipe signal. Therefore, the detection was impossible. This study developed an image processing program, called the GPR image processing program(GPRiPP), to process the GPR detection results. Its major function is the gain function, which amplifies the wiggle wave signal. Compared to the existing programs, the GPRiPP is capable of showing a similar image processing performance.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.4
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• pp.593-599
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• 2022

In this study, a crack monitoring system capable of detecting cracks based on image processing techniques was developed to effectively check cracks, which are the main damage of concrete structures, and a program capable of imaging and analyzing cracks was developed using machine vision. This system provides objective and quantitative data by replacing the appearance inspection that checks cracks with the naked eye. The verification of the development system was applied to the construction site of a self-healing concrete water tank to monitor the crack and the amount of change in the crack width according to age. In the case of crack width detected by image analysis, the difference from the measured value using a digital microscope was up to 0.036 mm, and the crack healing effect of self-healing concrete could be confirmed through the reduction of crack width.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.58-67
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• 2024

In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.