• Title/Summary/Keyword: 마이크로 홈가공

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Tool Condition Monitoring using AE Signal in Micro Endmilling (마이크로 엔드밀링에서 AE 신호를 이용한 공구상태 감시)

  • Kang Ik Soo;Jeong Yun Sik;Kwon Dong Hee;Kim Jeon Ha;Kim Jeong Suk;Ahn Jung Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.1 s.178
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    • pp.64-71
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    • 2006
  • Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmill is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for condition monitoring is presented. Also, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by the fuzzy C-means algorithm.

Condition Monitoring of Micro Endmill using C-means Algorithm (C-means 알고리즘을 이용한 마이크로 엔드밀의 상태 감시)

  • Kwon Dong-Hee;Jeong Yun-Shick;Kang Ik-Soo;Kim Jeon-Ha;Kim Jeong-Suk
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2005.05a
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    • pp.162-167
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    • 2005
  • Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

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A Study on the Truing of Diamond Wheel for Micro V-shaped Groove Grinding (마이크로 V홈 연삭가공을 위한 다이아몬드숫돌의 V형상 트루잉에 관한 연구)

  • Lee, Joo-Sang
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.9 s.174
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    • pp.27-33
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    • 2005
  • This study deals with the truing of diamond wheel fur the manufacture of micro v-shaped grooves with fine sharp edges in the grinding. Fine micro v-shaped grooves are key components to fabricate LGP(light guide plate), optical fiber connector and so on. Conventional v-shaped groove methods such as etching and lithography are difficult to make grooves with accuracy and cutting by lathe is difficult to select target materials. Therefore, as a preliminary stage to developing the grinding technology that will be expected fabrications for micro 3-dimensional structure of high effectivity and accuracy and freed up the restrictions of machinability to the materials for micro v-shaped grooves, truing is carried out with resin bond diamond wheel and electroforming diamond wheel using a cup-type truer. From the experimental results, it is found that the effects according to working direction of the cup-type truer and the restrainable methods of plastic deformation that is generated at wheel edge are examined. As a result, fine micro v-shaped diamond wheel was obtained, which are applicable to micro grinding for optical devices.