• International conference on construction engineering and project management
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• 2017.10a
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• pp.242-244
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• 2017

Excavation for construction is implemented in natural geographical terrain using a variety of construction equipment. Therefore, 3D excavation simulation requires integration of geographical and equipment modeling. This paper proposes a technique that integrates geographical and equipment modeling for 3D simulations of construction excavation. The geographical model uses a digital map to show ground surface changes during excavation and the equipment model shows equipment movement and placement. This combination produced a state of the art 3D simulation environment that can be used for machine guidance. An equipment operator can use the 3D excavation simulation to help construction equipment operators with decisions during excavation work and consequently improve productivity.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.61-67
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• 2007

The construction machine is the composite machine assembled by about 30,000 parts. Excavator, one kind of a construction machine, plays the leading role for export of construction equipment. It is generally impossible to produce all of the items within one company. Especially the supply of hydraulic control valves, one of the core part of the construction equipment, depends on the import heavily. So it is important to make an efficient production plan of hydraulic control valves in the company. The most important thing for the production scheduling of a hydraulic control valve is to make production schedule keeping the start date for assembly line for an excavator and to make minimization of the stock level. The production plan of hydraulic control valve includes the decision of the quantity supplied by subcontractor. This paper presents a scheme for a scheduling system of the hydraulic control valve considering the schedule of the assembly line for excavator production. This paper provides a methodology, which can make a plan of supply and production and generate a detailed schedule for daily production.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• Journal of Drive and Control
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• v.17 no.3
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• pp.1-8
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• 2020

Recently, a special purpose machine with two manipulators and quadruped crawler system has been developed for rapid life-saving and initial restoration work at disaster sites. This special purpose machine provides the driver with various environmental recognition functions for accurate and rapid task determination. In particular, the human detection technology assists the driver in poor working conditions such as low-light, dust, water vapor, fog, rain, etc. to prevent secondary human accidents when moving and working. In this study, a human detection module is developed to be mounted on a special purpose machine. A thermal sensor and CCD camera were used to detect victims and nearby workers in response to the difficult environmental conditions present at disaster sites. The performance of various AI-based life detection algorithm were verified and then applied to the task of detecting various objects with different postures and exposure conditions. In addition, image visibility improvement technology was applied to further improve the accuracy of human detection.

• Journal of Drive and Control
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• v.17 no.1
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• pp.37-43
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• 2020

An intelligent excavator can be divided into Machine Guidance (MG), semi-automatic, and unmanned by technology. The MG technology excavator is equipped with a tilt sensor on each link of the excavator and a GPS is installed on the excavator body to inform the user of the position of the excavator bucket end. Machine control (MC) technology that assists the user's work can be divided into semi-automatic and fully automatic technology. The semi-automatic MC equipment has already been commercialized by Komatsu and Caterpillar. The MC excavator is equipped with an electro-hydraulic system, sensors and controllers to control the excavator bucket end according to the user's needs. In this study, the semi-automated excavator modified based on manual excavator, is equipped with an electro-hydraulic system, a controller system, multi-sensors and a control algorithm is developed to assist in excavation work such as leveling and grading. By applying the developed technology, it was possible to confirm productivity improvement compared to manual digging and leveling work. In the future, further research to improve the accuracy of the hydraulic precision control and collaborative work with heterogeneous construction equipment such as dump truck and automated collaboration tasks technology could be developed.

• Journal of Drive and Control
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• v.17 no.3
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• pp.9-14
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• 2020

A special purpose machine with two manipulators and quadruped crawler system is being developed to work at disaster sites where it is intended to quickly respond in the initial stages after the event. In this study, a terrain recognition module is developed so that the above special purpose machine can quickly obtain ground information to help choose its path while recognizing objects in its way, this is intended to enhance the remote driver's limited situational awareness. Terrain recognition modules were developed for two tasks (real-time path guidance, precision terrain measurements). The real-time path guidance analyzes terrain and obstacles while moving, while the precision terrain measurement feature provides more accurate terrain information by precisely measuring the ground in front of the vehicle while stationary. In this study, an air-cooled sensor protection module was developed so that the terrain recognition module can continue its vital tasks in the event of exposure to foreign substances, including scattered dust, mist and rainfall, as well as high temperatures.

• Journal of KIBIM
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• v.8 no.1
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• pp.24-32
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• 2018

A construction machine guidance system is an assistance system that helps construction equipment operators dig grounds during excavation work at a construction site. This system has long been applied in the overseas countries of the United States, Japan and Europe. However, the system has not been paid much attention in Korea. The objective of this paper is to present a business model for adopting construction machine guidance systems in Korea and evaluate the effectiveness of applying the system to excavation work. The business model in this study shows a new process of applying construction machine guidance system, business stakeholders and revenues, and suggests the benefits to the business stakeholders. A field test of the construction machine guidance system proves that the system can be applied as a tool that can improve the productivity of excavation work. This productivity improvement consequently demonstrates that the business model in this study is a prospective challenge in improving the effectiveness of excavation work at the construction site.

• Journal of Drive and Control
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• v.21 no.1
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• pp.31-37
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• 2024

In this study, to prevent accidents in underground facilities during excavation, we developed a Lv.3 automated control system that can be configured as an electronic control system without changing the existing hydraulic system in a general excavator and utilized digital map information of underground facilities. We aimed to develop a strategy to prevent accidents caused by operator error. To implement this, a real-time excavator bucket end position recognition and control system was developed through angle measurement of the boom, arm, and bucket using an electronic joystick, RTK-GPS, and angle sensors. In addition, excavators are large, machine-based equipment, and it is difficult to control overshoot due to inertia with feedback control using position recognition information of the bucket tip. Therefore, feed-forward control is used to calculate the moving speed of the bucket tip in real-time to determine the target position. We developed a technology that can converge and verified the performance of the developed system through actual vehicle installation and field tests.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.219-225
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• 2013

State transportation agencies utilize fleets of heavy equipment to construct and maintain roadways. Equipment cost models can be developed to forecast economic life, which is the point at which the average unit cost to date reaches a minimum. A calculated economic life and cost models can be used to quantify the impacts of management strategies applied to a fleet. The purpose of this research was to develop an accurate method of quantifying the results of management strategies applied to a fleet of heavy construction equipment. The strategies evaluated are related to the annual usage of the fleet and the size of the fleet. More specifically the methodology is used to adjust the economic model to consider a limit to the annual decline in machine usage and a reduction in the number of machines in the fleet. When limiting annual machine usage, a specified rate is applied to the usage of the fleet, while total usage is held constant. This causes aging at a modified rate. A reduction in fleet size also causes a change to the usage of a fleet as the fleet must use fewer machines to produce the same total usage.

• Korean Journal of Construction Engineering and Management
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• v.21 no.1
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• pp.78-86
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• 2020

Dozer is an expensive construction equipment and has a significant performance impact on earthwork performance. A machine guidance system has been applied to dozer equipment as a solution that can improve the performance. The system can provide earthwork-related information to equipment operators so that earthworks can be carried out with minimum support from surveyors. Construction Equipment Machine guidance has the function of supporting earthwork according to an earthwork plan by providing excavation-related information to machine operators. The objective of this study is to evaluate the performance improvement of a machine guidance system for an dozer earthwork operation, and to compare the machine guidance method with the traditional method. The performance has been evaluated in two folds: 1) productivity and 2) accuracy. The productivity shows the quantity of earthwork for a given unit time. The accuracy shows the deviation of grading level from the designed level on the construction drawing for earthwork. The machine guidance system has been applied to a testing bed in a construction site. Data comparison analysis showed that the earth earthwork had 46.59% improvement in productivity as well as 46.96% improvement in accuracy, and is expected to provide a tool for applying smart constrction to the earthwork operation.