Selecting Cutting Data Tests for Cutting Data Modeling Using the Colding Tool Life Model
Autor: | Sören Hägglund, Volodymyr Bushlya, Daniel Johansson, Jan-Eric Ståhl, Ville Akujärvi |
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Rok vydání: | 2018 |
Předmět: |
Production Engineering
Human Work Science and Ergonomics 0209 industrial biotechnology Turning Depth of cut Work (physics) Single parameter 02 engineering and technology Tool Life Chip Data modeling Colding Equation Data set Taylor 020303 mechanical engineering & transports 020901 industrial engineering & automation Data point 0203 mechanical engineering General Earth and Planetary Sciences Errors-in-variables models Algorithm Cutting data General Environmental Science Mathematics |
Zdroj: | Procedia CIRP Procedia CIRP; 72, pp 197-201 (2018) |
ISSN: | 2212-8271 |
DOI: | 10.1016/j.procir.2018.03.035 |
Popis: | 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. (Less) |
Databáze: | OpenAIRE |
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