• Journal of the Korean Society of Industry Convergence
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• v.4 no.3
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• pp.281-287
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• 2001

Traditional job shop scheduling is supposed that machine has a fixed processing job type. But actually the machine has a highly utilization or long processing time is occurred delay. Therefore product system is difficult to respond quickly to the change of products or loads or machine failure etc. Here we use flexible job shop which is supposed that a machine has several jobs by tool change. The heuristic for the flexible job shop scheduling has to solve two problems. One is a routing problem which is determine a machine to process job. The other is sequencing problem which is determine processing sequence. The approach to solve two problems arc a hierarchical approach which is determined routing and then schedule, and a concurrence approach which is solved concurrently two problems by considering routing when it is scheduled. In this study, we simulate for flexibility efficiency fo flexible job shop scheduling with machine failure using hierarchical approach.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.4
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• pp.147-153
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• 2012

The demands of the large scale machine tools, for instance, such as planomiller, turning machine, boring machine, NC machine, have been gradually increased in recent years. As the performances of machine tools and/or cutting tools are advanced, it is possible to perform high-speed and high-precision cutting works. The effective treatment of wet chip, which is discharged from cutting works, becomes very important problems. Therefore, this study is forced on the design of large scale machine tools using CATIA V5R18 and analysis of cutter, which is considered as essential equipment in large scale machine tools, using MSC.Nastran & MSC.Patran. Especially, the relations between tolerated load of cutter, driving horse power and rpm of driving shaft in chip processing system are investigated through analysis. As the results, the reliability of design could be improved by evaluating simulated numerical values, it showed that tolerated loads of supported part and edged part of cutter are 87,000N and 14,450N, respectively.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.953-954
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• 2006

Ti-Cu-Ni-Sn quaternary amorphous alloys of $Ti_{50}Cu_{32}Ni_{15}Sn_3$, $Ti_{50}Cu_{25}Ni_{20}Sn_5$, and $Ti_{50}Cu_{23}Ni_{20}Sn_7$ composition were prepared by mechanical alloying in a planetary high-energy ball-mill (AGO-2). The amorphization of all three alloys was found to set in after milling at 300rpm speed for 2h. A complete amorphization was observed for $Ti_{50}Cu_{32}Ni_{15}Sn_3$ and $Ti_{50}Cu_{25}Ni_{20}Sn_5$ after 30h and 20h of milling, respectively. Differential scanning calorimetry analyses revealed that the thermal stability increased in the order of $Ti_{50}Cu_{32}Ni_{15}Sn_3$, $Ti_{50}Cu_{25}Ni_{20}Sn_5$, and $Ti_{50}Cu_{23}Ni_{20}Sn_7$.

• Journal of Powder Materials
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• v.17 no.1
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• pp.7-12
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• 2010

In this work, effect of various process-control agents (PCAs) on the mechanical alloying of amorphous alloy of $Al_{85}Y_8Ni_5Co_2$ has been investigated. The dependence of the particle shape, size and crystallization behavior of the amorphous alloy powders on the type of PCAs and their concentrations was investigated by using X-ray diffraction, field-emission scanning electron microscopy and differential scanning calorimetry. It was found that the additive of toluene could affect positively the amorphization and thermally induced crystallization processes, as well as the size refinement, morphology and particle-size distribution of as-milled powders in comparison with alloy obtained without PCA.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.678-683
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• 2010

The drum cam with rotational follower is used to apply the ATC and index table of machine tools and it has the merit of minimizing the backlash. In general, to machine the drum cam with rotational follower, 5-axis CNC machine must be used and its kinematic principle must be included in modeling on CAM. So, the commercialized CAM software can't be applied to this machining of drum cam. Though some special software for machining drum cam was developed, it could be applied to special 5-axis CNC machine tools and the finish machining module was not applied. To solve this problem, this study includes the induction of the post processing algorithm for the rough machining of drum cam on several 5-axis CNC machine tools, type AC, AB and Be. The finish machining software will be treated in next study. A sample drum cam was machined on 5-axis CNC machine tool of AC type. The designed geometric profile of drum cam consist to the measured profile after machining well. This post processing algorithm for rough machining of the drum cam was clearly verified.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.291-295
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• 1997

본 논문은 복합 단위 정보를 이용하여 모호성을 감소시키고 자연스러운 대역어 정보를 제공할 수 있는 차트파서를 기술한다. 복합 단위 정보를 사용하는 파싱은 태깅과 구문 분석 과정 사이에서 여러 단어들을 하나의 단위로 만들어서 형태론적/구문적 모호성과 파스 트리의 수를 감소시킨다. 우리는 Bottom-up 차트 파싱을 사용하는데, 이는 모호성 있는 태깅 결과가 많을수록 파스 트리의 생성 시간과 수의 증가를 초래하므로 복합 단위를 사용하여 파서에 대한 입력 단어의 수 및 모호성을 감소시켜 안정적인 파싱 결과를 얻을 수 있게 한다. 실험 결과는 복합 단위 정보를 사용한 차트 파싱이 차트들의 크기와 파스 트리의 수를 50%까지 감소시킴을 보여준다.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2003.10a
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• pp.90-90
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• 2003

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.117-122
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• 2002

Electrical discharge machining uses thermal energy from electrical discharge, while wire electrical discharge machining (WEDM) technology is widely used in conductive material machining. This paper proposes a method for evaluating the characteristics of wires in WEDM. In order to evaluate the wire processing performance, processing speed and roughness, straightness, corner processing have been assessed with precision experiment equipment and image processing including Laplacian filtering with various threshold levels.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1001-1007
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• 2020

In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.