• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.39-54
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• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.100-105
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• 2003

With the recent development of machining technology, high speed machining process is widely used for-the mold and difficult-to -cut-materials machining since it allows achieving high productivity and surface quality. However, during the high speed machining process, high cutting speed and feed rate can cause abrupt tool life decrease due to rapid rising of the cutting tool temperature. Such situation may cause increase of machining cost. Thus, in this study, developed optimization algorithm is applied to determine optimal machining variables for multiple high speed machining. The R-T characteristic curve for machining economics problems with a linear-lorarithmic tool life model is determined by applying sensitivity analysis. finally, a series of high speed machining experiments are performed to determine the desired optimal machining variables, and the results are analyzed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.11
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• pp.89-95
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• 2019

In this research, the effect of roughing on tool load through bottom-up machining is investigated through actual machining. Generally, through the use of high-speed machining technology, machining methods, such as general roughing, operate by deepening the cutting depth for as long as the tool is able to withstand it, giving a slower feed rate, less cutting depth, and faster feed. However, when the cutting depth is deep, there is a problem in that the stepped shape of the cutting area is increased (e.g., by the shaking of the tool or the chipping load). However, if the cutting is performed less, the cutting time becomes relatively long. To compensate for these drawbacks and extend the service life of the tool, economic efficiency needs to be secured.