크리깅 메타모델을 이용한 MQL 밀링공정의 소비전력 예측 연구

Abstract

Energy consumption reduction has become an important key word in manufacturing that can be achieved through the efficient and optimal use of raw materials and natural resources, and minimization of the harmful effects on nature or human society. The successful implementation of this concept can only be possible by considering a product's entire life cycle and even its disposal from the early design stage. To accomplish this idea with milling, minimum quantity lubrication (MQL) strategies and cutting conditions are analyzed through process modeling and experiments. In this study, a model to predict the cutting energy in the milling process is used to find the cutting conditions, which minimize the cutting energy through a Kriging meta-modeling process. The MQL scheme is developed first to reduce the amount of cutting oil and costs used in the cutting process, which is then employed for the entire modeling and experiments.

Energy consumption reduction has become an important key word in manufacturing that can be achieved through the efficient and optimal use of raw materials and natural resources, and minimization of the harmful effects on nature or human society. The successful implementation of this concept can only be possible by considering a product's entire life cycle and even its disposal from the early design stage. To accomplish this idea with milling, minimum quantity lubrication (MQL) strategies and cutting conditions are analyzed through process modeling and experiments. In this study, a model to predict the cutting energy in the milling process is used to find the cutting conditions, which minimize the cutting energy through a Kriging meta-modeling process. The MQL scheme is developed first to reduce the amount of cutting oil and costs used in the cutting process, which is then employed for the entire modeling and experiments.