• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.29-38
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• 2018

Through process quality information, the time required for process quality analysis has been drastically shortened, the process defect rate has been reduced, and the manufacturing lead time has been shortened and the on-time delivery rate has been improved. Therefore, The purpose of this study is to develop a quality information analysis system model that effectively shortens the time required for process quality analysis in automobile safety belt parts manufacturing process. As a result of experiments on communication operation between manufacturing execution system (MES) quality server, injection machine control computer, injection machine programmable logic controller (PLC) and terminal, in analyzing quality information, the conventional handwriting input method took an average of 20 minutes, but the new multi-network method took about 2 minutes on average. In addition, the process defect rate was reduced by 13% and the manufacturing lead time was shortened from 28 hours to 20 hours. The delivery compliance rate improved from 96 to 99%.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.45-55
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• 1986

A method for forming production cells in cellular manufacturing systems is presented. The basic approach is based on part-machine group formation by using relationship matrix calculated from the original part-machine matrix. The cases of exceptional elements and bottleneck machines are discussed. The proposed method can work with any starting form of part-machine matrix and provides the same solution regardless of the changes of starting form of part-machine matrix for any given problem.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.123-130
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• 1992

The group formation problem of the machine and part in Flexible Manufacturing System (FMS) is a very important issue in planning stage of FMS. This paper discusses the problem of machine-part group formation. The purpose of the study is to develop a heuristic algorithm, which can handle more realistic machine-part group formation problem by considering manufacturing factors. A new similarity coeffecient has been developed to solve more realistic machine-part group formation problem. For the purpose of illustations, a numerical example is presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.109-114
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• 1997

As CNC machine tool is one of core elements of manufacturing system, it is much important that it remains without troubleshoots. As a virtual machine is a recent alternative using IT for optimal utilization of CNC machine tool, it is a computer model that represents a CNC machine tool. But a virtual machine is still conceptual. So, in this paper, it is proposed that a virtual machine be a realistic model in the fault diagnosis module. For this purpose, the fault diagnosis system of machine tool using CORBA and fault diagnosis expert system has been implemented. Using this system, we have expections to diagnose exactly and prompty without the restriction of time or location, to reduce MTTR(Mean Time To Repair) and finally to increase the availability of manufacturing system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.7-14
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• 2015

The machine tools builders are trying to improve the efficiency and performance of the machine tools. The electro-mechanical driven broaching machine has many advantages such as lower noisy operating, higher energy efficiency, and smaller space of installation. This paper presents the structural and mechanical development of an electro-mechanical driven broaching machine that is replaced for traditional hydraulic one. The servo motor, ball screw and roller linear guide are used instead of hydraulic cylinder and translation frictional sliding guides. The simulation method based on FEM was applied to analyze the stress, deformation of the machine for static analysis. The dynamic analysis was carried out for verifying and assessing the mechanical behavior of the developed broaching machine. This work helps broaching machine developer make a better product at the early design stage with lower cost and development time.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.4
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• pp.41-47
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• 2009

This research deals with evaluation of machining accuracy for Parallel Kinematic Machine Tool(PKMT) applied parallel type robot system with high precision and stiffness. For this purpose, machine simulation is carried out to foreknow collision and interference between workpiece and tool. Furthermore, on the basis of machine simulation data, PKMT is manufactured. Machining accuracy such as cylindricity straightness, squareness, parallelism circularity, concentricity pitch error and yaw error, is measured by using coordinate measuring machine. Test piece for evaluation of machining accuracy is designed and manufactured under the standard of ISO 10791-7.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.87-93
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• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• 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.