• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.204-205
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• 2015

Demands for free-form buildings are on the rise, but such building designs require most cost and longer construction schedule, with less constructability due to challenges in construction member production and installation. FCP production technology has been developed using CNC machine in a bid to resolve the difficulties of member production. Exterior finishing panels of free-form building design must be divided in size and shape that can be produced by CNC machine. To solve this problem, constraints of CNC machine and correlations between CNC machine and panel need to be reviewed. Thus, the purpose of this study is to analyze decision factors on free-form concrete panel sizes produced by CNC machines. Through this study, FCP size can be optimized, which in turn can lead to improved FCP productivity and aesthetical quality of free-form building designs determined by the pattern of exterior finishing panels. CNC machine-enabled free-form concrete panel production technology will apply on site in the future, which will not only maximize the economic benefits of the technology but also support shorter construction schedule and better constructability.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.361-370
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• 2020

Automatic building material recognition has been a popular research interest over the past decade because it is useful for construction management and facility management. Currently, the extensively used methods for automatic material recognition are mainly based on 2D images. A terrestrial laser scanner (TLS) with a built-in camera can generate a set of coloured laser scan data that contains not only the visual features of building materials but also other attributes such as material reflectance and surface roughness. With more characteristics provided, laser scan data have the potential to improve the accuracy of building material recognition. Therefore, this research aims to develop a TLS-based building material recognition method by combining machine learning techniques. The developed method uses material reflectance, HSV colour values, and surface roughness as the features for material recognition. A database containing the laser scan data of common building materials was created and used for model training and validation with machine learning techniques. Different machine learning algorithms were compared, and the best algorithm showed an average recognition accuracy of 96.5%, which demonstrated the feasibility of the developed method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.153-154
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• 2012

The accuracy of cost estimation at an early stage in school building project is one of the critical factors for successful completion. So many method and techniques have developed that can estimate construction cost using limited information available in the early stage. Among the techniques, Support Vector Machine(SVM) has received attention in various field due to its excellent capacity for self-learning and generalization performance. Therefore, the purpose of this study is to verify the applicability of cost prediction model based on SVM in school building project at the early stage. Data used in this study are 139 school building cost constructed from 2004 to 2007 in Gyeonggi-Do. And prediction error rate of 7.48% in support vector machine is obtained. So the results showed applicability of using SVM model for predicting construction cost of school building projects.

• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.3
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• pp.46-54
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• 2012

The accuracy of cost estimation at an early stage in school building project is one of the critical factors for successful completion. So various of techniques are developed to predict the construction cost accurately and expeditely. Among the techniques, Support Vector Machine(SVM) has an excellent ability for generalization performance. Therefore, the purpose of this study is to construct the prediction model for construction cost of educational building project using support vector machine technique. And to verify the accuracy of prediction model for construction cost. The performance data used in this study are 217 school building project cost which have been completed from 2004 to 2007 in Gyeonggi-Do, Korea. The result shows that average error rate was 7.48% for SVM prediction model. So using SVM model on predicting construction cost of educational building project will be a considerably effective way at the early project stage.

• Journal of The Korean Digital Architecture Interior Association
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• v.4 no.1
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• pp.46-53
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• 2004

The interest about noise and vibration is increasing by a living level elevation recently. Particularly, the interest about the influence that vibration of machine has on the safety of building is rising. However, there are a lot of the cases that the influence of machine isn't considered in designing the factory buildings. The purpose of this study is to suggest the results of measuring that the influence of machine's vibration in A factory has on the building structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1516-1539
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• 2022

This article shows a set of physical information fusion IoT systems that we designed for smart buildings. Its essence is a computer system that combines physical quantities in buildings with quantitative analysis and control. In the part of the Internet of Things, its mechanism is controlled by a monitoring system based on sensor networks and computer-based algorithms. Based on the design idea of the agent, we have realized human-machine interaction (HMI) and machine-machine interaction (MMI). Among them, HMI is realized through human-machine interaction, while MMI is realized through embedded computing, sensors, controllers, and execution. Device and wireless communication network. This article mainly focuses on the function of wireless sensor networks and MMI in environmental monitoring. This function plays a fundamental role in building security, environmental control, HVAC, and other smart building control systems. The article not only discusses various network applications and their implementation based on agent design but also demonstrates our collaborative information fusion strategy. This strategy can provide a stable incentive method for the system through collaborative information fusion when the sensor system is unstable in the physical measurements, thereby preventing system jitter and unstable response caused by uncertain disturbances and environmental factors. This article also gives the results of the system test. The results show that through the CPS interaction of HMI and MMI, the intelligent building IoT system can achieve comprehensive monitoring, thereby providing support and expansion for advanced automation management.

• Journal of The Korean Digital Architecture Interior Association
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• v.3 no.1
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• pp.50-58
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• 2003

The interest about noise and vibration is increasing by a living level elevation recently. Particularly, the interest about the influence that vibration of machine has on the safety of building is rising. However, there are a lot of the cases that the influence of machine isn't considered in designing the factory buildings. The purpose of this study is to suggest the results of measuring that the influence of machine's vibration in A factory has on the building structure.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.138-139
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• 2015

Human productivity of Boring Machine for stack is provided but not its hourly workable quantity(Q-value) in the Equipment ownership cost and expenses section of the Poom-Same that is used for construction cost estimation of public sectors in Korea, which leads to less realistic and subjective estimation for the works. The optimized Q-value of the machine is proposed as a result of thorough investigation into many of its operations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.30-35
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• 2021

In this study, a machine simulation system was built using the actual scale of an AC-type 5-axis machine tool for mold surface machining that can be used in applications, such as, modeling and machine building, stroke, and collision detection. The validity of the 5-axis machine simulation system was verified by performing tool path generation, post-processing, machine simulation, prototype motion simulation, and an actual cutting experiment. This entire process was intended to activate the 5-axis machining in mold surface machining.

• Proceedings of the KAIS Fall Conference
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• 2001.11a
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• pp.104-106
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• 2001

This paper presents the usage of software package APM WinMachine for design of train car elements. APM software uses fur maximization of design productivity and efficiency in designing and evaluation machine elements and systems and CAD modeling. In process of machine designing needs make strength calculations of machine parts with complecated design. Will the help of APM software strength calculations can be done quickly. On the Demichovo machine-building plant with the use of APM software were made quickly and effectively strength calculations of the cradle of the suspension of air-conditioner of car train and the mounting brackets of a tank of train toilet.