Selecting Cutting Data Tests for Cutting Data Modeling Using the Colding Tool Life Model

An analysis on selecting cutting speed, cutting feed and depth of cut when collecting data for the Colding Tool Life Model based on Woxen's Equivalent Chip Thickness was performed to achieve the lowest possible model error. All possible combinations of a large data set were evaluated with regard to model error. This work shows that an increase of ratio between the highest and lowest cutting speed, feed, depth of cut and tool life within the five included tool life tests increases the likelihood of an accurate model. Further, to ensure an accurate model, it is not enough to have a large ratio of one single parameter, but a large ratio in all parameters is needed. The paper also presents a suggestion on how to select the cutting data points, derived from the best performing tool life models. It is concluded that one should aim to have one pair of cutting data points with equal equivalent chip thickness while varying cutting speed and three more test points with different equivalent chip thickness. 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.