• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.294-299
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• 2009

Micro end-milling has been becoming an important machining process to manufacture a number of small products such as micro-devices, bio-chips, micro-patterns and so on. Many related researches have given grand effects to micro end-milling phenomenon, for example, micro end-milling mechanism, cutting force modeling and machinability. This paper strongly concerned actual problem, micro tool deflection, which causes excessive machining errors on the workpiece. Machining error were predicted and measured through a series of test micro cutting and analysis of their SEM images and FEM analysis. Experiments are carried out to validate the approaches.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.105-106
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.775-776
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• 2007

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.261-269
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• 2009

Micro end-milling process is applied to fabricate precision mechanical parts cost-effectively. It is a complex and time-consuming job to select optimal process conditions with high productivity and quality. To improve the productivity and quality of precision mechanical parts, micro end-mill wear and cutting force characteristics should be studied carefully. In this paper, high speed machining experiments are studied to construct the optimum process design as well as the mathematical modeling of tool wear and cutting force related to cutting parameters in micro ball end-milling processes. Cutting force and wear characteristics under various cutting conditions are investigated through the condition monitoring system and the design of experiment. In order to construct the cutting database, mathematical models for the flank wear and cutting force gradient are derived from the response surface method. Optimal milling conditions are extracted from the developed experimental models.

• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.3
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• pp.1-6
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• 2018

Micro prism pattern is applying in order to get increase of luminance, control the light, and so forth especially in optics and display industry. Most patterns are fabricated by lithography, planning, and EDM, but they have limitations on the productivity or the unit cost of produce. However, ultra precision mold is one of the processes able to replace it, and assure high productivity required by industries. In this investigation, micro prismatic end-milling is suggested in order to fabricate the pattern effectively. Micro prism pattern having $100{\mu}m$ of pitch and height was machined on STD-11. After machining, the flank and boundary wear on micro end mill were measured and analyzed, as well as burr formation and dimensional accuracy of fabricated pattern were evaluated. Thus the optimal cutting conditions were derived.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.77-83
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• 2007

The study on damaged layer is necessary for machinability improvement in micro machining. The damaged layer in metal cutting is derived from plastic deformation and transformation of metal structure. The damaged layer affects micro mold life and micro machine parts. In this study, the damaged layer of micro machined surface of copper is evaluated according to various machining condition. The damaged layer structure and metallurgical characteristics are measured by optical microscope, and evaluated by cutting forces and surface roughness. The scale of this damaged layer depends on cutting process parameters and machining environments. By experimental results, depth of damaged layer was increased with increasing of cutting depth, also the damaged layer is less occurred in down-milling compared to up-milling during micro endmilling operation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.598-603
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• 2005

Recently, the advanced industries using micro parts are rapidly growing. The appearance of ultra-precision feed mechanism and the development of control system make it possible to process parts in sub millimeter scale by mechanical methods. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. So, micro stairs have been trying to cut by using high revolution air turbine spindle and micro-endmill, and studying for magnitude of cutting force. This investigation deals removal characteristics of burr generated by micro endmilling process. Also, decreasing of burr is significant problem in making smooth and precise parts in micro endmilling. In micro endmilling, the material removal rate(MRR) and cutting forces are very small. This paper presents an investigation on the machining characteristics for micro stairs by using ultrahigh-speed air turbine spindle in machining.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.209-210
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• 2010

• Design & Manufacturing
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• v.17 no.4
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• pp.24-32
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• 2023

In this study, we introduce research aimed at minimizing machining errors without compromising productivity by compensating for the machining errors caused by tool deformation. Our approach experimentally establishes the direct correlation between cutting depth and machining error, and creates predictive models using mathematical functions. This method allows for the prediction of compensated cutting depths to obtain the desired cutting profiles, thereby maximizing the compensation of machining errors in the cutting process.