• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.47-54
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• 2008

Hard turning process can be defined as a single-point machining process carried out on "hard" materials. The process is intended to replace or limit traditional grinding operations that are expensive, environmentally unfriendly, and inflexible. The purpose of this study is to achieve a systematic understanding of machining characteristics and the effects of machining parameters on cutting force, tool wear shape and chip formation by the outer cutting of a kind of wear resistant tungsten carbide V30. Hard turning experiments were carried out on this alloy using the PCD (Poly Crystalline Diamond), cBN (cubic Boron Nitride) and PcBN (Polycrystalline cubic Boron Nitride) cutting tools. The PcBN and the usual cBN tools were used to be compare with the PCD tool and the dry turning was carried out. The PcBN is attractive as the tool material which replaces the PCD. The tool wear width and cutting force were measured, and the worn tool and chip were observed. The difference of the tool wear mechanism among the three tool materials was investigated.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.162-176
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• 2007

Machine Learning (ML) has become very popular within Data Mining (KDD) and Artificial Intelligence (AI) research and their applications. In the ML and KDD contexts, two main approaches can be used for inducing a Bayesian Network (BN) from data, namely, Conditional Independence (CI) and the Heuristic Search (HS). When a BN is induced for classification purposes (Bayesian Classifier - BC), it is possible to impose some specific constraints aiming at increasing the computational efficiency. In this paper a new CI based approach to induce BCs from data is proposed and two algorithms are presented. Such approach is based on the Markov Blanket concept in order to impose some constraints and optimize the traditional PC learning algorithm. Experiments performed with the ALARM, as well as other six UCI and three artificial domains revealed that the proposed approach tends to execute fewer comparison tests than the traditional PC. The experiments also show that the proposed algorithms produce competitive classification rates when compared with both, PC and Naive Bayes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.248-248
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• 2004

초경합금재 (cemented carbides)는 WC(텅스텐 카바이드, 탄화텅스텐)과 Co(코발트)를 주성분으로 한 복합재료로서 저온경도와 고온경도가 뛰어 나며, 압축강도와 강성이 높은 것 등, 제반 물리적 성질이 안정되어 있다 이와 같은 우수한 특징을 이용하여, 초경합금재는 다양한 분야에 이용되고 있는데, 크게 나누어 절삭 공구용으로 뿐만 아니라 IT 관련, 환경 관련 산업용, 광산용 공구, 건설 공구, 철강의 압연 롤러 등의 내마멸, 내충격용 재료에도 많이 사용된다. 이들 가운데, 내마멸, 내충격용으로 사용되는 것은 절삭 공구용 초경합금재에 비해 결합제인 코발트를 많이 함유하며 경질 성분의 텅스텐 카바이드의 입자 지름도 거칠고 크다.(중략)

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.74-81
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• 2003

This paper describes that the micro-cutting of WC-Co using PCD (Polycrystalline Diamond) and PcBN (Polycrystalline Cubic Boron Nitride) cutting tools are performed with SEM(Scanning Electron Microscope) direct observation method. The purpose of this study is to present reasonable cutting conditions to obtain precise finished surface and machining efficiency. Summary of the results are shown below: (1) The thrust cutting forces tend to increase more than the principal forces as the depth of cut and the cuttlllg speed are increased preferably on orthogonal microcutting. (2) The tool wear in the flank face was formed larger than that in the rake face on orthogonal micro cutting. (3) The wear appearance for PCD tools is abraded by hard WC particles of the work materials, which lead diamond grain to be detached from the bond.