• Korean Journal of Computational Design and Engineering
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• v.18 no.5
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• pp.359-366
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• 2013

In the lower arm design process, a tolerance optimization of the variance of design variables should be preceded before manufacturing process, since it is very cost-effective compared to a strict management of tolerance of products. In this study, a design of experiment (DOE) based on response surface model (RSM) was carried out to find optimized design variables of the lower arm, which can meet a given requirement of probability constraint for the process capability index (Cpk) of the weight and maximum stress. Then, the design space was explored by using the central composite design method, in which the 2nd order Taylor expansion was applied to predict a standard deviation of the responses. The optimal solutions satisfying the probability constraint of the Cpk were found by considering both of the mean value and the standard deviation of the design variables.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.136-144
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• 2006

Aluminum engine piston is manufactured by thixoforging according to forming variables. It is very important to find effects of forming variables on final products in thixoferging. In order to find the effects, however, many researchers and industrial technicians have depended upon too many types of experiments. In this study, the process parameters which have influences on thixofurging process of aluminum automotive engine piston are found by a statistical method and the correlation equations between the process parameters and quality of product are approximated through the surface response analysis. Forming variables such as initial solid fraction, die temperature, and compression holding time are considered fur manufacturing aluminum engine piston by thixofurging. Hardness and microstructure are inspected so that optimal forming condition is found by the statistical approach.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.13-25
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• 2021

The article presents the results of how employee's hierarchical job roles differently recognize a SM(smart manufacturing) and evaluate comprehensively on the SM employees training. The research was focus on small and medium size manufacturing corporation in Banwol·Siwha industrial complex, where is carried out Smart Complex National Policy. The Results from 205 participants working for a manufacturing firms in the Banwol·Siwha industrial complex. The results of study show that managers (vs workers) group is higher recognition of smart manufacturing and more intention to participate a SM employee training and utilize a SM equipments for test a manufacturing process. and these variables were mediated by SM cognition. These results will help SM manpower training center strategically design their training programs to maximize the training effectiveness.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.205-210
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• 2007

The integration method of binary and real encoding in genetic algorithm is proposed to deal with design variables of various types in gear drive design. The method is applied to optimum design of multi-stage gear drive. Integer and Discrete type design variables represent the number of teeth and module, and continuous type design variables represent face width, helix angle and addendum modification factor etc. The proposed genetic algorithm is applied for the gear ratio optimization and the volume optimization(minimization) of multi-stage geared motor which is used in field. In result, the proposed design optimization method shows an effectiveness in optimum design process and the new design has a better results compared with the existing design.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.243-246
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• 2003

Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields Classifying a group into subgroups is one of the most important subjects in data mining Tree-based methods, known as decision trees, provide an efficient way to finding classification models. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variables should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present several methods for measuring the node impurity, which are applicable to data sets with multiple target variables. For illustrations, numerical examples are given with discussion.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.06b
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• pp.28-42
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• 1998

Spinning is one of the incremental forming process by the rotating mandrel and forming roller, and has been applied to manufacturing the wheel disc of automobile to simplify the manufacturing process and to improve the mechanical properties of product. In the proesent study the process variables have been extracted and considered to decide the specification of the spinning machine. The maximum values of working load and power have been evaluated and the blank size has been disigned. The shape and dimensionof forming roller have been designed and the process condition such a s rotational velocity of mandrel and the feedrate of roller have been decided.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.113-118
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• 2017

In this paper, we propose a design procedure for determining the gate position robust to changes and inherent fluctuations in the process conditions during injection molding. To evaluate the robustness of the gate position, the signal-to-noise ratio is used, and noise conditions are implemented using orthogonal arrays, where the process variables are considered as noise factors and possible process fluctuations are set as the levels of the noise factors. To show the usefulness of the proposed robust design procedure, we apply it to a computer CPU baseplate. As a result, it is shown that a robust gate position can be determined that reduces the average warpage deflection by 2.4% and 1.7%, and the variance by 3.4% and 5.1%, compared to the two initial gate positions.

• The Journal of Bigdata
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• v.3 no.1
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• pp.95-103
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• 2018

In recent years, many people in the manufacturing field have been making efforts to increase efficiency while analyzing manufacturing data generated in the process according to the development of ICT technology. In this study, we propose a data mining based manufacturing process using decision tree algorithm (CHAID) as part of a smart factory. We used 432 sensor data from actual manufacturing plant collected for about 5 months to find out the variables that show a significant difference between the stable process period with low defect rate and the unstable process period with high defect rate. We set the range of the stable value of the variable to determine whether the selected final variable actually has an effect on the defect rate improvement. In addition, we measured the effect of the defect rate improvement by adjusting the process set-point so that the sensor did not deviate from the stable value range in the 14 day process. Through this, we expect to be able to provide empirical guidelines to improve the defect rate by utilizing and analyzing the process sensor data generated in the manufacturing industry.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.11-18
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• 2016

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.7
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• pp.105-112
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• 2021

Reduction of weld distortions and increase in productivity are some of the major goals of the shipbuilding industry. To address these issues, many researchers have attempted to apply new welding processes. In the shipbuilding industry, steel is the candidate material of choice owing to its good weldability. However, conventional welding techniques are not feasible for avoiding welding problems. Tip-rotating arc welding is one of the high-efficiency welding process that has several advantages, such as high welding speed, high melting rate, low heat input, and less distortion. The present study investigates the influence of the welding variables on the weld characteristics of tip-rotating arc welding. Welding was performed using EH36 as the base metal and SM-70s as the filler metal, which are widely used in shipbuilding. Basic experiments were conducted to understand the effects of the major welding variables, such as welding and tip-rotating speeds. The distortion and mechanical properties of the optimal welding conditions were used to evaluate the tip-rotating arc welding performance. Consequently, the feasibility of the tip-rotating arc welding process for joining steel components was investigated, so that the optimized welding conditions could be applied directly to ship body welding to enhance the quality of the welded joints.