• Bulletin of the Society of Naval Architects of Korea
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• v.32 no.1
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• pp.36-39
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• 1995

본고에서는 고속선의 항행 안전성과 관련된 공통의 문제로서 파랑중 조종성능에 관해서 언급하 고자 한다. 파랑중 조종성능이 문제시되는 것은 선박이 추파(following seas) 또는 추사 파(quartering seas)를 받으면서 고속으로 항해할 때이다. 보통의 속도 범위에서 운항되는 일반 선박중에서도 컨테이너선, 어선 등과 같이 비교적 속력이 빠른 선박은 추사파중에서 선수 동 요가 크게 일어나며, 보침을 위한 조타량이 커짐과 동시에 힁동요가 심하게 일어나는 것으로 알려져 있다. 이러한 불안정 현상은 정도의 차이는 있을지언정 고속선에서도 마찬가지 경향을 보이고 있다. 파랑중 조종성능을 요약하면 추파 또는 추사파중에서의 복원성과 보침성 문제에 귀착된다, 추사파중에서의 복원성 문제는 선체 중심이 파정에 위치할 때 복원력 저하로써 설명될 수 있으며, 이러한 현상은 파장과 선체 길이가 거의 같고 선속이 파속과 거의 같은 조건하에서 일어난다고 알려져 있다. 이러한 조건을 만족하는 선속은 Froude수 0.4 정도로서 고속선의 운항 범위에 미달되는 속도이다. 추사파중에서의 보침성 문제는 브로칭(broaching-to) 현상으로써 설명될 수 있으며, 브로칭 현상은 파장이 선체 길이의 2배 정도이고, 선속과 파속이 거의 같은 조건하에서 일어난다고 알려져 있다. 이러한 조건을 만족하는 선속은 Froude수 0.56 정도로서 고속선의 운항 범위와 일치하는 속도이다. 따라서 본고에서는 고속선을 대상으로 하기 때문에 복원성 문제는 다루지 아니하고 브로칭 현상에 관해서만 간략히 기술하기로 한다.

• IE interfaces
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• v.15 no.1
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• pp.64-72
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• 2002

Broaching machine is widely used for machining inner shaped slots in the work-pieces, and provides vertical motion (usually hydraulically powered) between tool and work-piece. In this study, we modelled the tool life process and investigated economic tool life of broaching machine. Tool life process is divided into wear-process and succeeding failure process. Wear process is defined as machining wear and failure process as 'chipping' occurred by random shock. We modelled wear process as linear regression function for products amounts and assumed failure process as Poisson process. Economic tool life is defined as the number of lots which minimizes average tool related cost per lot and analyzed by using age replacement policy technique. As tool-related cost factors, we consider tool replacement cost, tool maintenance cost and quality costs of products. The results of this study can be applied to analyze life process of general machining tools.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.518-525
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• 2019

Recently, the Sub-Committee on SDC (Ship Design and Construction) of IMO have discussed actively the technical issues associated with the second-generation intact stability criteria of ships. Generally, second generation intact stability criteria refer to vulnerability five modes ship stability which occurs when the ship navigating in rough seas. As waves passes the ship, dynamic roll motion phenomenon will affect ship stability that may lead to capsizing. Multi-tiered approach for second generation of intact stability criteria of IMO instruments covers apply for all ships. Each ship is checked for vulnerability to pure loss of stability, parametric roll, and broaching/surf-riding phenomena using L1(level 1) vulnerability criteria. If a possible vulnerability is detected, then the L2(level 2) criteria is used, followed by direct stability assessment, if necessary. In this study, we propose a new method to verify the criteria of the surf-riding/broaching mode of small ships. In case, L1 vulnerability criteria is not satisfied based on the relatively simple calculation using the Froude number, we presented the calculation code for the L2 criteria considering the hydrodynamics in waves to perform the more complicated calculation. Then the vulnerability criteria were reviewed based on the data for a given ship. The value of C, which is the probability of the vulnerability criteria for surf-riding/broaching, was calculated. The criteria value C is considered in new approach method using the Froude-Krylov force and the diffraction force. The result shows lower values when considering both the Froude-rylov force and the diffraction force than with only the Froude-Krylov force was considered. This difference means that when dynamic roll motion of ship, more exact wave force needs considered for second generation intact stability criteria This result will contribute to basic ship design process according to the IMO Second-Generation Intact Stability Criteria.

• Tribology and Lubricants
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• v.34 no.6
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• pp.262-269
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• 2018

In this work the friction and wear characteristics of the gray cast iron surface processed by broaching method, which is widely used in the machinery industry, were investigated. The broaching process is mainly used for mass production because it has high dimensional accuracy and processing speed, but the defects on surface can be easily generated. In order to improve the tribological characteristics, the approach was to reduce the roughness and hardness of the surface by adding a machining process to the broaching specimen. The secondary machining process using abrasive grains produces low roughness and hardness than broaching because it has high tool accuracy and removes the work hardened surface. The friction coefficient and the wear rate were assessed using a reciprocating-type tribotester to analyze the effects of surface finishing on the tribological properties. The friction tests were conducted under dry and lubricated conditions. The test results showed that the reduction of surface roughness and hardness through secondary machining process in lubricated condition improved the friction and wear characteristics. The reason why the same results did not appear in a dry condition was that wear occurred more rapidly than in lubricated condition. Thus, the positive effect of roughness and hardness of the surface obtained through the secondary machining process was not observed.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.737-745
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• 2008

Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.