• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.12 no.6
• /
• pp.37-44
• /
• 2013

Friction stir welding (FSW) is a solid state joining technique that has expanded rapidly since its development in 1991 and has numerous applications in a wide variety of industries. This paper introduces the basic principles of friction stir welding (FSW) and presents a survey of the latest technologies and applications in the field. The basic principles that are discussed include the terminology, tool/workpiece processes, FSW merits and process variants. In particular, the process variants including the rotation speed and traveling speed are discussed, which include the defect-free zone in an oxygen free copper and Al alloy, respectively. Multiple aspects of the FSW machine are developed, including a horizontal 2D FSW machine and a hybrid complex FSW machine. The latest applications are introduced, with an emphasis on the recent advances in the aerospace, automotive, and IT display industries. Finally, the direction for future research and potential applications are examined.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.831-836
• /
• 2000

During machining, since more than 50% compliance of the cutting point in machine tool structures comes from headstocks, with the remainder coming from beds, slides and structural joints, the structural analysis of the headstock is very important to improve the static and dynamic performances. Especially, in case of machining hard and brittle materials such as glasses and ceramics with the grinding machine, the reinforced headstock with the high damping material is demanded. Since the fiber reinforced composite materials have excellent properties for structures, owing to its high specific modulus, high damping and low thermal expansion, it is expected that the dynamic and thermal characteristics of the headstock will be improved if they are employed as the materials fur headstock. In this paper, the design and the manufacturing methods as well as the static and dynamic characteristics of a steel-composite hybrid headstock were investigated analytically and experimentally to improve the performance of the grinding machine system.

• Asia pacific journal of information systems
• /
• v.10 no.1
• /
• pp.19-35
• /
• 2000

Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2006.05a
• /
• pp.77-88
• /
• 2006

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.385-390
• /
• 2000

This paper deals with the design and simulation of the hybrid power filter to compensate reactive power and harmonic components of nonlinear load. Control target is a 3-phase diode full bridge rectifier with L-R-C nonlinear load, this load is assumed adjustable speed driver(ASD). The hybrid filter consists of a shunt active filter, shunt passive filters and series inductors. Control algorithm is based on instantaneous power compensation theory proposed by H.Akagi and etc. The result from simulation shows the hybrid filter is superior than other filters on the point of compensation performance and low cost. The PSCAD/EMTDC 3.0 is used as simulation tools.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.5
• /
• pp.27-34
• /
• 2005

To accomplish various and complex tasks by intelligent robots, improvement is needed not only in mechanical system architecture but also in control system architecture. Hybrid control architecture has been suggested as a mutually complementing architecture of the weak points of a deliberative and a reactive control. This paper addresses a control architecture of robots, and a behavior representation methodology. The suggested control architecture consists of three layers of deliberative, sequencing, and reactive as hybrid control architecture. Multi-layer behavior model is employed to represent desired tasks. 3D simulation will be conducted to verify the applicability of suggested control architecture and behavior representation method.

• Korean Journal of Computational Design and Engineering
• /
• v.10 no.6
• /
• pp.421-431
• /
• 2005

This paper introduces a new approach for saving build time of hybrid rapid prototyping by decomposing a part into minimum number of layers. In the hybrid rapid prototyping, a part of a complicated shape is realized by adding layers of a simpler shape, each of which is obtained by machining a sheet of constant thickness from its top and bottom surfaces. Thus it is desired to decompose a given part into the minimum number of layers while guaranteeing each layer to be fabricated from the given sheets using a 3-axis milling machine. To satisfy these requirements, a concave edge-based algorithm is proposed to decompose a part into layers by considering the tool accessibility, the total number of layers, and the allowable sheet thickness.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.238-246
• /
• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.15 no.2
• /
• pp.38-45
• /
• 2016

Since a 5-axis machine tool has two rotary axes, it offers numerous advantages, such as flexible accessibility, longer tool life, better surface finish, and more accuracy. Moreover, it can conduct whole machining by rotating the rotary feed axes while setting the fixture at once without re-fixing in contrast to conventional 3-axis machining. However, it is difficult to produce complicated products that have a hollow shape. In contrast, 3D printing can produce an object with a complicated hollow shape easily and rapidly. However, because of layer thickness and shrinkage, its surface finish and dimensional accuracy are not adequate. Therefore, this study proposes hybrid technology by integrating the advantages of these two manufacturing processes. 3D printing was used as the additive manufacturing rapidly in the whole body, and 5-axis machining was used as the subtractive manufacturing accurately in the joining and driving places. The reliability of the proposed technology was verified through a comparison with conventional technology in the aspects of processing time, surface roughness. and dimensional accuracy.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.18 no.1
• /
• pp.59-67
• /
• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.