Extraction of flank wear growth models that correlates cutting edge integrity of ball nose end mills while machining titanium
| Autor: | Lim Beng Siong, K. Ramesh |
|---|---|
| Přispěvatelé: | Department of Chemical Engineering, Faculty of Engineering and the Built Environment |
| Rok vydání: | 2010 |
| Předmět: |
Titanium
Engineering Precision engineering business.industry Mechanical Engineering Ball nose end mill Titanium alloy Mechanical engineering Machining Industrial and Manufacturing Engineering Tool geometry Computer Science Applications Specific strength Rake angle Control and Systems Engineering Ball (bearing) End mill business Software Surface integrity |
| Zdroj: | The International Journal of Advanced Manufacturing Technology |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s00170-010-2753-9 |
| Popis: | The application of titanium alloys are increasingly seen at aerospace, marine, bio-medical and precision engineering due to its high strength to weight ratio and high temperature properties. However, while machining the titanium alloys using solid carbide tools, even with jet infusion of coolant lower tool life was vividly seen. The high temperatures generated at the tool–work interface causes adhesion of work-material on the cutting edges; hence, shorter tool life was reported. To reduce the high tool–work interface temperature positive rake angle, higher primary relief and higher secondary relief were configured on the ball nose end-mill cutting edges. However, after an initial working period, the growth of flank wear facilitates higher cutting forces followed by work-material adhesion on the cutting edges. Therefore, it is important to blend the strength, sharpness and surface integrity on the cutting edges so that the ball nose end mill would demonstrate an extended tool-life. Presently, validation of tool geometry is very tedious as it requires extensive machining experiments. This paper illustrates a new feature-based ball-nose-end-mill–work interface model with correlations to the material removal mechanisms by which the tool geometry optimization becomes easier. The data are further deployed to develop a multi-sensory feature extraction/correlation model to predict the performance using wavelet analysis and Wagner Ville distribution. Conclusively, this method enables to evaluate the different ball nose end mill geometry and reduces the product development cycle time. |
| Databáze: | OpenAIRE |
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