• IE interfaces
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• v.18 no.3
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• pp.247-252
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• 2005

In the automated production environment in the present days, the minimization of manual operation becomes a very important factor in increasing the efficiency of the production system. The exit burr produced through the milling operation on the edge of workpiece usually requires manual deburring process to enhance the level of precision of the resulting product. So far, researchers have developed various methods to understand the formation of exit burr in cutting process. One method to analytically identify the formation of exit burr was to use the geometrical information of CAD and CAM data used in automated machining. This method, in turn, generated the information resulting from the analysis such as burr type, cutting region, and exit angle. Up to now, the geometrical data were restricted to the single feature and single path. In this paper, a method to deal with the complicated geometric features such as line segment, arc, hole, and spline will be presented and validated using the field data. This method also deals with the complex workpiece shape which is a combination of multiple features. As for the cutting path, multiple tool path is analyzed in order to simulate the real cutting process. All this analysis is combined into a Windows based software and real data are used to validate the program in the conclusion.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of Sensor Science and Technology
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• v.9 no.5
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• pp.373-379
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• 2000

In this paper, an estimation system of vehicle position and orientation on magnetic lane, which is a parameter of the steering controller for automated lane following is described. To verify that the magnetic dipole model could be applied to a magnetic unit paved in roadway, the analysis of the model is compared with the data of 3-axis magnetic field measured experimentally. The sensor location could be estimated by analysis of the model based on experimental data. For the magnetic lane model merged magnetic unit, the relation of sensor location and magnetic field is acquired experimentally. The proposed estimation of vehicle position and orientation is adopted to automated lane following by computer simulation.

• Journal of Welding and Joining
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• v.14 no.4
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• pp.33-42
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• 1996

In recent years there has been a significant growth in the use of the automated and/or robotic welding system, carried out as a means of improving productivity and quality, reducing product costs and removing the operator from tedious and potentially hazardous environments. One of the major difficulties with the automated and/or robotic welding process is the inherent lack of mathematical models for determination of suitable welding process parameters. Partial-penetration, single-pass bead-on-plate welds were fabricated in 12mm AS 1204 mild steel flats employing five different welding process parameters. The experimental results were used to develop three empirical equations: curvilinear; polynomial; and linear equations. The results were also employed to find the best mathematical equation under weld bend width to assist in the process control algorithms for the Gas Metal Arc Welding(GMAW) process and to correlate welding process parameters with weld bead width of bead-on-plates deposited. With the help of a standard statistical package program. SAS, multipe regression analysis was undertaken for investigating and modeling the GMAW process, and significance test techniques were applied for the interpretation of the experimental data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.987-992
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• 2005

Manufacturing companies should perform process planning and its evaluation concurrently with new product developments so that they can be highly competitive in the modern market. Process planners should make decisions in the manner of concurrent and collaborative engineering in order to reduce the manufacturing preparation time and cost when developing new products. Automated generation of analysis models from the integrated database, which contains process and material information, reduces time to prepare analyses and makes the models reliable. In this research, we developed a web-based system for concurrent and collaborative system for production flow analysis, using web, database, and simulation technology. An integrated database is designed to automatically generate analysis models from process and material plans without reworking the data. This system enables process planners to evaluate their decision fast and share their opinions with others easily. With this system, it is possible to save time and cost for assembly process and material planning, and reliability of process plans can be improved

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.107-118
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• 2002

This paper deals with an automated computer-aided process planning and die design system by which designer can determine operation sequences even if they have a little experience in process planning and die design of quasi-axisymmetric cold forging product by cold former working. The approach to the system is based on knowledge-based rules and a process knowledge base consisting of design rules is built. Knowledge for the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for the AutoCAD using a personal computer. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. The system is composed of three main modules and five sub-modules. The process planning and die design module considers several factors, such as the complexities of preform geometry, punch and die profiles, specifications of available cold farmer, and the availability of standard parts. As the system using 2D geometry recognition is integrated with the technology of process planning, die design, and CAE analysis, the standardization of die parts for wheel bolt requiring cold forging process is possible. The developed system makes it possible to design and manufacture quasi-axisymmetric cold forging product more efficiently.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.944-949
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• 2012

As modern power systems become large and complicated, the automated voltage and reactive power control system is required in most developed countries due to the recent amazing progress of computer net works and information thechnology. So far the voltage control has been depend on human operator in korean power system. This paper presents an intelligent voltage control system based on sensitivity analysis and artificial intelligence technology. Detailed state space modeling technique is discussed and a new performance index is proposed to speed up the searching performance of the expert system. As the searching strategy is very important factor of the speed of expert system the least first search algorithm is applied using this performance index. The intelligent voltage control system is applied to the Jeju power system. As a result, case studies showed a promissing application of the intelligent voltage control system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2535-2544
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• 2009

The brain-wave research provides relatively various information for brain condition in safety. The counselor or measuree will must easily reduce user TCO about the series of process for the measurement, analysis, and management of brain-wave, and can access to the desired information in real time. While the traditional method for brain-wave process was processed manually by the judgment of a specialist. In this paper the developed system is smart brain-wave care system based on optimizing and combining the 3-Tier client/server by IT with brain-wave technology including BQT. This system was developed in the real-time service with a completely automated process by the conveniently web interface. Our system currently gave a service at the field, and the collected data on DB were provided to researchers for the use of clinical research.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.24-26
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• 2005

At present, KS-1000 which is one of a commercial measurement instrument for motor fault diagnosis has been used in industrial field. The measurement system of KS-1000 is composed of three part : harmonic acquisition, signal processing by KS-1000 algorithm, diagnosis for motor fault. First of all, voltage signal taken from harmonic sensor is analysed for frequency by KS-1000 algorithm. Then, based on the result values of analysis skilled expert makes a judgment about whether motor system is the abnormality or degradation state. But the expert system such a motor fault diagnosis is very difficult to bring the expectable results by mathematical modeling due to the complexity of judgment process. In this reason, we propose an automation system using fuzzy model based on genetic algorithm(GA) that builded a qualitative model of a system without priori knowledge about a system provided numerical input output data.